This overview of connected vehicle (CV) pilot studies, test beds, and deployments in the United States was derived from a research project conducted by the SMARTER Center in partnership with the Maryland State Highway Administration. It outlines the leading CV deployment studies taking place across the country, in addition to exemplary case studies and informational resources on CV components like On-Board Units and CAVe-In-a-Box Systems. Use the Table of Contents below to navigate the page.
Table of Contents
What Are Connected Vehicles?
The four main CV applications
Connected Vehicles (CVs) use advanced sensors, software, and communication technologies to interact with their surroundings and reduce dependence on human drivers. These vehicles are equipped with Vehicle-to-Everything (V2X) communication capabilities, enabling them to exchange information with other vehicles, infrastructure, and pedestrians through an integrated network. The benefits of CVs include reduced traffic congestion and accident rates, enhanced fuel efficiency, and improved mobility for all road users, including pedestrians, bicyclists, children, the elderly, and individuals with disabilities.
V2X communication encompasses four essential applications:
- Vehicle-to-Vehicle (V2V) – Direct communication between automobiles, sharing critical information such as speed, location, and direction to enable collision avoidance and adaptive cruise control.
- Vehicle-to-Infrastructure (V2I) – Data-sharing between vehicles and road infrastructure, including traffic signals and construction zones, enabling smoother traffic flow and real-time hazard alerts.
- Vehicle-to-Pedestrian (V2P) – Communication that connects vehicles with pedestrians and cyclists to prevent accidents and enhance safety.
- Vehicle-to-Network (V2N) – Links vehicles to broader networks, providing access to real-time traffic data, weather updates, and route optimization.
Communication technologies like Dedicated Short Range Communication (DSRC) and Cellular Vehicle-to-Everything (C-V2X) are being tested in multiple projects across the Unites States. While DSRC remains predominant, C-V2X adoption is growing due to its potential for wider applications and integration with existing cellular networks. Research has demonstrated the effectiveness of cooperative lane change maneuvers using CV platforms and hardware-in-the-loop (HIL) testing for applications like Cooperative Adaptive Cruise Control (CACC), which combines physical test vehicles with virtual models to evaluate system performance.
CV Pilots and Testbeds
CV deployments span urban, suburban, and rural areas, highlighting the adaptability of these technologies across diverse environments. Projects in urban areas typically focus on traffic congestion reduction and crash safety, whereas rural deployments emphasize incident detection and response. Each deployment demonstrates unique operational and technological characteristics—for example, Arizona projects focus on transit signal priority and emergency vehicle preemption, while California initiatives demonstrate multi-modal intelligent traffic signal systems.
Successful CV projects involve collaboration among DOTs, academic institutions, and private companies. These partnerships enable knowledge sharing and resource pooling, augmenting the overall impact of projects. These institutional arrangements also introduce collective challenges, however, from interoperability issues to regulatory and funding limitations.
The establishment of CV testbeds is essential for advancing traffic safety and efficiency in real-world environments. These testbeds serve as controlled settings where CV technologies can be rigorously tested and refined before widespread deployment, enabling researchers to evaluate how V2V and V2I communications interact with existing transportation systems and providing valuable data on effectiveness. CV testbeds are particularly pivotal in addressing traffic safety goals for pedestrians, bicyclists, children, the elderly, and individuals with disabilities, as V2X communication networks enhance situational awareness for both vehicles and other road users—for instance, enabling CVs to receive real-time information about pedestrians on crosswalks and take proactive collision avoidance measures. This controlled experimentation is vital for understanding how Connected and Automated Vehicles (CAVs) can reduce traffic congestion, improve traffic flow, and enhance overall roadway safety, with data collected from testbeds informing the design of safer infrastructure, optimal traffic signal timings, and adaptive traffic management strategies that create safer roadways for CVs, automated vehicles, and human-driven vehicles alike.
Connected Vehicle Testbeds in the US
Planned and operational CV deployment locations in the US
Table of Contents
1. University of Alabama, Center for Advanced Vehicle Technologies & Alabama DOT
2. Arizona Connected Vehicle Testbed (Anthem)
3. Delaware CV Project (DelDOT SPaT Challenge Deployment)
4. Gainesville SPaT Deployment
5. Osceola County CV Signal Project
8. Tallahassee US90 SPaT Challenge Deployment
9. Tampa Hillsborough Expressway Authority (THEA) Connected Vehicle Deployment
10. City of Atlanta Smart Corridor Demonstration Project
13. Marietta GA Emergency Vehicle Signal Preemption
14. North Fulton Community Improvement District
15. Ala Moana Boulevard/Nimitz Highway Corridor Project (Honolulu DOT), Hawaii
16. Montgomery and Prince George Counties Connected Vehicle Pilots
17. MDOT US-1 Innovative Technology Corridor, SPaT Challenge, TIM, MD 214 VRU Deployments
18. Montgomery County (MCDOT) CV Pilot
19. Morgan State University CAV Testbed, Baltimore, Maryland
20. Ann Arbor Connected Vehicle Test Environment (AACVTE)
21. Road Commission for Oakland County DSRC
22. The Michigan DOT Wayne County Project
23. North Carolina DOT (NCDOT) Projects and Testbed
24. Dover SPaT Challenge (New Hampshire DOT)
26. Nevada DOT DSRC and Las Vegas SPaT Corridor
27. New York City Connected Vehicle Pilot Project Deployment
31. Tennessee DOT (SPaT Challenge Project and CV Projects)
32. Utah Transit Authority (UTA) DSRC Traffic Signal Pilot Project
33. Washington State Transit Insurance Pool (WSTIP) Safety-Collision Warning Pilot Project
35. Nevada DOT DSRC for Rural ITS (Washoe County)
36. California CV Testbed, Palo Alto
37. I-85/”The Ray” CV Testbed, Georgia
38. Idaho CV Testbed (The Ada County Highway District)
39. American Center for Mobility (Willow Run)
40. I-75 Connected Work Zone (Oakland County)
41. Macomb County Dept. Roads DSRC Deployment (MDOT/SMART Pilot)
42. Michigan DOT Wayne County Project
44. Southeast Michigan Testbed
45. Ohio Turnpike & Infrastructure Commission DSRC Projects
46. NW US33 Smart Mobility Corridor
47. Wyoming CV Project Deployment
49. Indiana CV Testbed (Indiana DOT SPaT Deployment – Greenwood)
50. Michigan Safety Pilot Model Deployment
51. Utah Salt Lake Valley Snowplow Preemption
52. Virginia Smart Roads CV Testbeds
53. Michigan, American Center for Mobility (Willow Run)
55. Minnesota Roadway Safety Institute Connected Vehicle Testbed
1. University of Alabama, Center for Advanced Vehicle Technologies & Alabama DOT
The CV testbed in Alabama, situated in Tuscaloosa, is a collaborative initiative spearheaded by the University of Alabama’s Center for Advanced Vehicle Technologies and the Alabama Department of Transportation (ALDOT). This testbed is a sophisticated infrastructure system featuring 85 RSUs strategically deployed at various intersections. These RSUs utilize DSRC technology to broadcast Signal Phase and Timing (SPaT) information. The deployment of this testbed aims to enhance the efficiency and safety of urban traffic management by leveraging real-time data to optimize traffic flow and reduce congestion.
The primary motivation behind the implementation of the Alabama CV testbed was to address growing traffic congestion and safety concerns in urban areas. With the increasing number of vehicles on the road, the need for smarter traffic management solutions became evident. The integration of DSRC-based communication through RSUs allows for real-time monitoring and management of traffic, which can significantly reduce delays and improve the overall traffic flow. The Alabama CV testbed has been the site of numerous research projects and initiatives aimed at advancing CV technology. One key project involves the testing and validation of SPaT broadcasts to improve signalized intersection efficiency. By using real-time SPaT data, V2V and V2P communication, it is possible to enhance safety for all road users. Another significant project focuses on implementing and analyzing cooperative adaptive cruise control (CACC) systems, which allow vehicles to maintain safe following distances and respond more quickly to changes in traffic flow. Additionally, the testbed supports initiatives that explore the integration of CV technology with automated driving systems, examining how these technologies can work together to further enhance safety and efficiency on the roads in Alabama. It is also worth mentioning that the University of Alabama Center for Advanced Vehicle Technologies implemented Advanced Driver Assistance Systems (ADAS) and other automated technologies to address safety concerns associated with large transit buses, such as blind spots and pedestrian detection.
2. Arizona Connected Vehicle Testbed (Anthem)
The Maricopa County Department of Transportation (MCDOT) Implemented Testbed in Anthem, Arizona
The Arizona CV testbed in Anthem spans 5.5 miles along West Daisy Mountain Drive, equipped with Roadside Units (RSUs) at 11 intersections utilizing Dedicated Short-Range Communication (DSRC) technology. This setup facilitates V2I communication, enabling vehicles to exchange real-time data with traffic signals and roadway infrastructure. The testbed provides a controlled environment for piloting CV applications focused on enhancing traffic management and safety through innovations such as transit signal priority and emergency vehicle preemption.
The Arizona CV testbed was developed to explore and demonstrate the practical benefits of CV technologies in improving traffic efficiency and safety. By enabling real-time communication between vehicles and traffic signals, the testbed aims to reduce delays for public transit vehicles, improving the reliability and attractiveness of public transportation. The emergency vehicle preemption feature allows emergency responders to receive priority at intersections, reducing response times and enhancing public safety. Several projects conducted on the testbed have tested and refined these technologies. Pilot studies on transit signal priority have shown potential to reduce bus travel times and improve schedule adherence, benefiting both transit agencies and passengers. The testbed has also demonstrated the capability to effectively clear intersections for emergency vehicles, minimizing potential conflicts with other road users.
Additionally, the Loop 101 Mobility project along the Loop 101 freeway in the Greater Phoenix area represents another significant CAV testbed initiative. This project, developed by the Arizona Department of Transportation (ADOT) and the Maricopa Association of Governments (MAG), aims to enhance traffic management and safety on one of the region’s busiest freeways. The testbed incorporates advanced communication technologies including DSRC and cellular-based vehicle-to-everything (C-V2X) communication, enabling vehicles to communicate with each other and roadside infrastructure for real-time data exchange.
The Loop 101 Mobility project explores how CAV technologies can reduce traffic congestion, improve safety, and enhance freeway operations efficiency. Through V2V and V2I communication, the project provides drivers with critical information about traffic conditions, upcoming hazards, and optimal speeds. As a testing ground for scalable technologies, the project contributes real-world data and insights to the development of smarter, more adaptive traffic management systems across Arizona’s transportation network.
3. Delaware CV Project (DelDOT SPaT Challenge Deployment)
The Delaware Department of Transportation (DelDOT) has deployed the SPaT Challenge project in Smyrna, Delaware, including 11 signalized intersections along US 13 equipped with RSUs utilizing DSRC technology to broadcast SPaT information. The SPaT Challenge aims to enhance traffic safety and efficiency by enabling vehicles to receive real-time information about traffic signal statuses, allowing seamless exchange of information between infrastructure and vehicles. This project is part of the nationwide SPaT Challenge, which aims to deploy SPaT broadcasts at over 20,000 signalized intersections across the United States by 2025.
The DelDOT SPaT Challenge Deployment addresses the need to improve traffic safety and operational efficiency on key Delaware corridors. As traffic volumes increase, ensuring efficient and safe intersection operation has become a priority for DelDOT. By deploying RSUs that broadcast SPaT information, the project enables real-time communication between vehicles and infrastructure, allowing for more informed driving decisions. This capability is expected to reduce traffic crashes caused by sudden stops or signal violations. The testbed also supports the broader goal of integrating CV technologies into the state’s transportation infrastructure, preparing for future advancements in autonomous and semi-autonomous vehicle technologies.
Several research projects and initiatives using the Delaware CV testbed have advanced CV technologies and improved transportation safety and efficiency. Primary projects include evaluating SPaT data effectiveness in reducing traffic delays and enhancing safety at signalized intersections. One significant initiative focuses on developing and testing applications that use SPaT data to provide advanced warnings about impending red light changes and red-light running incidents. The testbed is also studying CV technology’s potential benefits in supporting emergency vehicle preemption, allowing emergency responders to navigate intersections more efficiently and safely.
4. Gainesville SPaT Deployment
The Gainesville SPaT Deployment covers 27 signals across four corridors in Gainesville, Florida. The project involves installing RSUs on these signals and OBUs on various vehicles, including emergency vehicles, transit buses, and research vehicles (CVs). Designed to improve travel time reliability, safety, throughput, and traveler information, the project also includes deploying and testing smartphone-based applications for pedestrian and bicyclist safety to enhance overall mobility in the area.
5. Osceola County CV Signal Project
The Osceola County CV Signal Project incorporates Dedicated Short-Range Communications (DSRC) technology to facilitate real-time data exchange between Roadside Units (RSUs) and equipped vehicles. The deployed RSUs transmit Signal Phase and Timing (SPaT) data, Basic Safety Messages (BSMs), and other required information to improve vehicle-to-infrastructure communication. Osceola County, supported by the FHWA, tested CV technology by installing RSUs at two intersections: Osceola Parkway/Orange Blossom Trail (span wire) and Orange Blossom Trail/Poinciana (mast arm).
RSU communications enable vehicles to process precise signal timings, lane geometry, and potential safety hazards. The system architecture integrates advanced processing algorithms at the intersection level and enables collection and analysis of high-resolution traffic data to inform adaptive traffic signal control and optimize safety-critical applications. The RSUs support low-latency communication necessary for timely relay of warnings, such as red-light violations and pedestrian crossings, contributing significantly to crash avoidance scenarios.
The project methodology emphasizes rigorous field testing under real-world traffic conditions to assess DSRC reliability and scalability for CV applications. Data collected from this project models intersection performance, assesses network-level impacts, and refines deployment strategies for future CV infrastructure. The testbed also supports interoperability testing, ensuring RSUs and Onboard Units (OBUs) from different manufacturers meet industry standards such as SAE J2735 for message formatting and IEEE 802.11p for DSRC communication.
6. Pinellas County SPaT
The Pinellas County SPaT project covers 23 traffic signals along a portion of the US 19 corridor in Pinellas County, Florida, involving the installation of RSUs at these intersections. The project aims to broadcast SPaT information to improve traffic signal coordination and efficiency along the US 19 corridor while enhancing traffic flow and safety through better signal management.
7. Seminole County SR 434
The Seminole County SR 434 project deploys CV technology with Signal Performance Metrics (SPM) along SR 434 from McCulloch Road to E Mitchell Hammock Road. The deployment includes RSUs at six intersections and OBUs. The project’s key goal is to implement and assess CV technology applications such as SPaT, Transit Signal Priority, and preemption while enhancing traffic signal performance and improving transit operations along the SR 434 corridor.
8. Tallahassee US90 SPaT Challenge Deployment
US 90 Signal Phase and Timing Tallahassee
The Tallahassee US90 SPaT Challenge Deployment is situated along US-90 Mahan Drive in Tallahassee, Florida, including RSUs at 22 signalized intersections and OBUs inside vehicles. The primary objective is to evaluate the operational and safety benefits of SPaT applications along this arterial corridor. The project tests SPaT technology effectiveness in diverse terrain characterized by hilly and forested environments. The short-term goal verifies the technology’s functionality in these conditions, while the long-term goal focuses on assessing efficiency and safety improvements provided by DSRC for road users along signalized corridors. Figure 4 illustrates plans for 22 signalized intersections equipped with DSRC along US 90 Mahan Drive.
9. Tampa Hillsborough Expressway Authority (THEA) Connected Vehicle Deployment
CV Pilot Deployment in Downtown Tampa
The Tampa Hillsborough Expressway Authority (THEA) CV Deployment involves installing 1,000 enhanced rearview mirrors, 47 RSUs, 10 bus OBUs, and 8 streetcar OBUs. The deployment concentrates on areas around reversible express lanes and major arterials in downtown Tampa. This project aims to alleviate congestion, improve safety during peak commuting hours, and enhance traffic flow while reducing crashes, improving transit trip times, and minimizing greenhouse gas emissions through advanced CV technologies. Figure 5 shows the CV pilot deployment in downtown Tampa.
10. City of Atlanta Smart Corridor Demonstration Project
The City of Atlanta is implementing a Smart Corridor Demonstration Project along North Avenue, stretching from the Georgia Tech Campus to Ponce City Market. This project involves upgrading 20 intersections with advanced CV technology as part of the Renew Atlanta program, in collaboration with partners including AT&T Smart Cities, the Georgia Institute of Technology, and the Georgia Department of Transportation. The project features a self-driving vehicle demonstration to evaluate and improve driving conditions on one of Atlanta’s busiest corridors. By integrating DSRC and C-V2X technologies, the project facilitates emergency vehicle preemption, transit signal priority, and other smart traffic management solutions while serving as a platform to test and demonstrate autonomous vehicle capabilities in an urban environment.
11. Georgia DOT SPaT Project
The Georgia Department of Transportation’s SPaT Project in Atlanta includes installing SPaT technology at 54 intersections and 12 freeway locations. This project uses DSRC technology to broadcast SPaT messages and receive Basic Safety Messages (BSMs), providing real-time traffic signal information to CVs along critical corridors like SR 141, SR 8, and I-75/85 in downtown Atlanta. The project enables smoother traffic flow, reduces congestion, and improves safety at intersections by minimizing conflicts and optimizing signal timings based on real-time traffic conditions.
12. iATL CV2X Project
The infrastructure-Automotive Technology Laboratory (iATL) CV2X project in Alpharetta, Georgia leverages C-V2X technology. The Federal Communications Commission (FCC) has issued an experimental license for this deployment, which operates within a five-mile radius of the iATL. The project includes installing 55 RSUs to test various safety applications in real-world traffic scenarios. The iATL CV2X project aims to test and develop safety applications for CVs by using C-V2X technology to enhance V2I and V2V communications. This testbed provides valuable insights into how CV technologies can improve road safety and traffic management.
13. Marietta GA Emergency Vehicle Signal Preemption
In Marietta, Georgia, an innovative project has installed traffic preemption software on emergency response vehicles, including those operated by the Marietta Fire Department. This system ensures that first responders receive green lights at pre-cleared intersections, enhancing response times and safety for both responders and the public. The project covers a 24-square-mile area, with RSUs installed at 120 intersections to facilitate these operations. The primary goal is to improve the efficiency and safety of emergency response operations. By providing priority green lights for emergency vehicles, the project reduces response times and minimizes the risk of collisions at intersections.
14. North Fulton Community Improvement District
The North Fulton Community Improvement District (NFCID) project in Fulton County, Georgia, focuses on connecting 44 intersections with CV technology. This project, in partnership with Applied Information Inc., implements Glance ‘hybrid’ three-way CV technologies across the region. Using 4G LTE, DSRC, and C-V2X technologies enables green light priority for emergency vehicles and transit buses, as well as enhanced communication through the TravelSafely app. The NFCID project seeks to improve traffic management and safety in the North Fulton area. By providing priority signaling for emergency and transit vehicles, the project reduces response times and improves transit reliability. The integration of multiple communication technologies provides robust and adaptable infrastructure capable of supporting various safety and mobility applications.
15. Ala Moana Boulevard/Nimitz Highway Corridor Project (Honolulu DOT), Hawaii
The Nimitz Corridor Project in Honolulu, Hawaii aims to improve traffic safety and efficiency across a critical transportation route. This project deploys RSUs at 16 traffic signals along the Nimitz Corridor utilizing C-V2X communication technology. The deployment supports advanced traffic management and safety features including Red Light Violation Warning, Pedestrian and Cyclist Collision Warnings, Emergency Vehicle Preemption, Transit Signal Priority, Traffic Queue Warning, and SPaT information. The TravelSafely smartphone app is integrated to provide real-time traffic updates and safety alerts to drivers and pedestrians.
The project facilitates communication between vehicles, infrastructure, and pedestrians, enabling timely warnings and signal adjustments. The red-light violation warning system prevents crashes from signal violations, while pedestrian and cyclist collision warnings provide critical alerts to both drivers and non-motorized road users. Emergency vehicle preemption ensures efficient intersection navigation for emergency vehicles, and transit signal priority improves public transit reliability. The Nimitz Corridor Project is expected to yield valuable data on C-V2X technology effectiveness in real-world traffic scenarios, with research focusing on assessing improvements in traffic safety, collision rate reductions, and overall traffic flow efficiency.
16. Montgomery and Prince George Counties Connected Vehicle Pilots
The Montgomery and Prince George Counties CV Pilots demonstrate a comprehensive effort to advance CV technology across a broad geographic area. This testbed involves installing over 30 RSUs at various intersections within the two Maryland counties. The pilot program utilizes both DSRC and C-V2X technologies to support a range of CV applications including broadcasting SPaT messages, intersection map data (MAP), pedestrian warnings, emergency vehicle preemption, and traveler information messages.
The primary goal is to enhance traffic management and safety by providing real-time information to drivers and other road users. By broadcasting SPaT messages and intersection map data, the project improves traffic signal coordination, facilitates better driver decision-making, and enhances overall traffic flow. Pedestrian warning systems increase safety at intersections by alerting drivers to pedestrian presence. The operational phase reflects a significant commitment to integrating advanced communication technologies into urban and suburban transportation systems. Data collected from this testbed will contribute to developing best practices for deploying CV technologies and improving traffic management and safety.
17. MDOT US-1 Innovative Technology Corridor, SPaT Challenge, TIM, MD 214 VRU Deployments
This pioneering project advances traffic management and efficiency along Route 1 (US-1) in Howard County, MD, deploying SPaT systems at 20 signalized intersections from Montgomery Road to Route 175. The primary objective is to enhance traffic signal coordination, optimize traffic flow, and reduce congestion along this key transportation corridor. Advanced communication technologies ensure accurate SPaT information broadcast to approaching vehicles, providing drivers with timely signal phase updates to inform travel speed and timing decisions. The project aims to minimize stop-and-go driving, reduce travel times, and lower fuel consumption. An additional 19 RSUs installed from MD 32 south to I-195 north provide origin-destination data and traveler information messages on congestion, incidents, and weather. The operational project provides valuable insights into SPaT system effectiveness and their impact on traffic management and safety.
MDOT also operates a VRU pilot deployment in Prince George’s County covering pedestrian detection and alerts at MD 214 (Central Avenue) and Addison Road.
18. Montgomery County (MCDOT) CV Pilot
Montgomery County CV Pilot demonstrates a comprehensive effort to integrate CV-capable technology within Montgomery County’s standard infrastructure. This testbed includes 10 RSUs at signalized intersections along MD 124 (Quince Orchard Rd) and MD 28 (Darnestown Rd). MCDOT uses 3 OBUs utilizing DSRC technology to test and verify a range of CV applications including broadcasting SPaT messages and BSMs, while also supporting TIMs, TSP/Preemption, and detection.
The primary goal is to provide an environment for testing CV applications incorporated into existing, standard traffic signal infrastructure. By broadcasting SPaT messages, the project improves traffic signal coordination, facilitates better driver decision-making, and enhances overall traffic flow. Data collected from this testbed contributes to developing best practices for deploying CV technologies and improving traffic management and safety.
19. Morgan State University CAV Testbed, Baltimore, Maryland
The Morgan State University Connected and Automated Vehicle (CAV) Testbed in Baltimore, MD, is a state-of-the-art research facility for CAV technologies. Equipped with two RSUs, two OBUs, two LiDAR sensors, and four CCTV cameras operating under C-V2X technology, the testbed focuses on enhancing traffic safety, particularly for VRUs, at two signalized intersections: Cold Spring Lane–Hillen Road and East 33rd–Hillen Road. Smart signal controllers broadcast real-time SPaT, MAP, and TIM messages, enabling advanced traffic management and safety research.
Key studies include statistical analysis of vehicle conflicts using LiDAR, evaluation of Post Encroachment Time (PET) thresholds for vehicle-pedestrian interactions, and mitigation strategies for jaywalking and vehicle-bicyclist conflicts. The testbed supports research on traffic signal failures, smart green time allocation, and sensor performance under varying conditions, providing insights into traffic flow and safety enhancements. Future research will explore pre-emption systems for emergency vehicles, dynamic safety messaging, and Time-to-Collision (TTC) analysis for V2V, V2P, and V2B conflicts. Additionally, the testbed will develop real-time warning devices to alert drivers and VRUs to potential conflicts, advancing CAV technologies and ensuring safer, more efficient intersections.
20. Ann Arbor Connected Vehicle Test Environment (AACVTE)
The Ann Arbor CV Test Environment (AACVTE) is a pioneering project managed by the University of Michigan Transportation Research Institute (UMTRI). This testbed covers a 27-square-mile area in Ann Arbor and has transitioned from a research-oriented deployment to an operational environment aimed at assessing CV safety technologies’ effectiveness in reducing crashes. The testbed includes 25 RSUs and 2,500 OBUs, making it one of the most extensive CV environments in the world. Research conducted on this platform has provided valuable data on the performance and reliability of DSRC-based safety applications, contributing to the development of national standards for CV technology. The AACVTE is a critical stepping stone toward achieving the USDOT’s vision of nationwide CV and infrastructure deployment.
21. Road Commission for Oakland County DSRC
The Road Commission for Oakland County (RCOC) prioritizes safety and oversees approximately 900 square miles of land, including maintenance of 1,400 traffic signals. As part of its commitment to improving transportation, RCOC is planning to update and expand its systems with roadside units capable of communicating with connected vehicles. In 2018, RCOC partnered with Oakland County to launch the Connected Vehicle Task Force, a pilot program aimed at testing CV infrastructure and developing a sustainable CV business model. The initiative, led by P3 Mobility, operates as a public-private partnership leveraging expertise and resources from both sectors. While the project’s scope is still being refined, it marks a significant step toward integrating CV technology to enhance traffic safety and efficiency in Oakland County.
22. The Michigan DOT Wayne County Project
This project in Wayne County, Michigan, is a notable initiative focusing on CV technology, involving deployment of 12 RSUs and 250 OBUs using DSRC technology. The primary objective is to document lessons learned, assess benefits, and evaluate potential business models for future CV deployments. By analyzing operational data and outcomes, Michigan DOT aims to refine its approach to CV technologies and explore sustainable models for broader implementation across the state. This project is an important step toward understanding the practical implications of DSRC-based systems and their potential to improve traffic safety and efficiency in urban environments.
23. North Carolina DOT (NCDOT) Projects and Testbed
The NCDOT DSRC project, part of the AASHTO SPaT Challenge, involves deploying DSRC technology at 20 intersections across the NC55 corridor and High House Road in Cary, NC. This deployment includes 16 RSUs strategically placed to manage traffic control functions such as signal preemption for emergency vehicles, transit signal priority, and broadcasting SPaT information. Utilizing DSRC technology, the project enhances traffic management, improves safety, and supports efficient vehicle and transit movement. The project addresses traffic congestion and improves safety at key intersections by providing real-time information on traffic signal phases and timing. Key achievements include evaluating DSRC technology’s impact on traffic management and safety, assessing SPaT broadcasting effectiveness in reducing delays and improving traffic signal coordination, and analyzing benefits of signal preemption and transit priority systems.
Additionally, the NCDOT Multimodal Connected Vehicle Pilot (MMCVP) at North Carolina State University in Raleigh is creating a connected vehicle system to evaluate CV technology’s effects on driver and pedestrian safety. Although still in planning stages, the pilot aims to develop and test integrated CV systems that enhance safety and mobility for various transportation modes, including vehicles, pedestrians, and cyclists. The project seeks to understand how CV technologies can improve safety and efficiency across multiple transportation modes, with planned research studies evaluating how CV systems enhance pedestrian safety, improve traffic flow, and support multimodal transportation strategies.
24. Dover SPaT Challenge (New Hampshire DOT)
The New Hampshire DOT SPaT Challenge Deployment in Dover represents a significant advancement in evaluating CV technologies. This testbed includes sophisticated equipment such as traffic controllers, DSRC, RSUs, OBUs, a V2I Hub, traffic servers, and LTE Radios. The core aim is to compare the performance of DSRC and 4G LTE communication technologies in transmitting SPaT and other critical data. The testbed provides valuable insights into their respective strengths—DSRC’s low latency and high reliability versus 4G LTE’s broader coverage and higher data throughput. DSRC’s reliability and low latency are crucial for safety-critical applications, while 4G LTE offers extensive coverage and high data rates advantageous for broader, non-critical applications.
The deployment has supported several research projects, including one major project assessing the latency and reliability of SPaT data transmission using both DSRC and 4G LTE in various traffic conditions. Another key project explores integrating a V2I Hub and Traffic Server to manage and process data from these communication technologies, aiming to optimize the delivery and accuracy of traffic information.
25. New Jersey CV Testbed
The Integrated Connected Urban Corridor in New Jersey (ICUC NJ) Initiative is a pioneering project designed to enhance urban mobility and environmental monitoring in Newark, New Jersey. This testbed features eight RSUs equipped with DSRC technology and air pollution sensors, strategically placed at key Newark intersections to collect and transmit real-time traffic data. The implementation addresses Newark’s need to manage high traffic volumes and improve air quality. As a major urban center experiencing significant congestion and increased vehicle emissions, Newark benefits from DSRC-equipped RSUs that enable real-time vehicle-infrastructure communication, providing drivers with critical information about traffic conditions and potential hazards. The ICUC NJ Initiative supports various projects and research efforts focused on advancing CV technologies and improving urban traffic management.
The Route US 322 and US 40/322 Adaptive Traffic Signal (ATS) Project focuses on a 10.8-mile highway stretch within Atlantic County, deploying Adaptive Traffic Systems at five intersections along Route US 322 and twenty-two intersections along US 40/322, parallel to the Atlantic City Expressway. It features new fiber optic communications, mid-block system detectors, four camera surveillance systems, and upgraded signal controllers for adaptive operations. This project marks NJDOT’s first deployment of CV RSUs. The fiber optic cables support real-time data exchange, with all devices integrated into virtual servers to optimize traffic flow, reduce congestion, and improve safety in Pleasantville and the Townships of Hamilton and Egg Harbor.
Additionally, the Route 40, CR 606 to Atlantic Avenue Interchange, and Route 50 ATS project enhances traffic management and safety in Atlantic City and Hamilton Township. Covering Route 40 from milepost 45.89 to 47.84 and 62.98 to 64.32, plus Route 50 from milepost 18.62 to 21.60, it involves installing ATS and ITS infrastructure at 15 intersections. Key components include new signal controllers, cabinets, image detectors, Camera Surveillance Systems, RSUs, and midblock detectors providing real-time traffic data and monitoring. The integration of fiber optic and ISP communication ensures robust data exchange and coordination among traffic control systems.
26. Nevada DOT DSRC and Las Vegas SPaT Corridor
The Las Vegas SPaT corridor on Fremont Street in Las Vegas, Nevada spans five critical intersections: Las Vegas Boulevard/Fremont, Fremont/6th, Fremont/7th, Fremont/8th, and Carson/7th. The testbed is equipped with RSUs utilizing DSRC technology capable of broadcasting real-time SPaT and map information. This infrastructure supports various CAV applications by providing precise signal phase and timing data, along with detailed mapping information. The testbed enhances traffic flow, reduces congestion, and improves overall safety and efficiency of urban mobility in one of Las Vegas’s busiest areas.
The implementation was motivated by the need to improve traffic management and safety in downtown Las Vegas’s urban environment. This area experiences significant pedestrian and vehicle traffic, making it ideal for testing and refining CV technologies. The testbed enables timely SPaT information broadcasting, helping drivers and autonomous vehicles anticipate signal changes and make informed decisions, reducing crash likelihood and improving traffic efficiency. One key project uses real-time SPaT broadcasts to CVs to optimize speed and reduce idling time, leading to lower emissions and improved fuel efficiency. Another significant initiative tests SPaT data integration with autonomous vehicle systems, enabling more reliable and efficient autonomous driving in complex urban environments.
27. New York City Connected Vehicle Pilot Project Deployment
The New York City CV Pilot Project is a large-scale initiative aimed at improving traveler safety and mobility through advanced CV technologies. This project covers Midtown Manhattan, Central Brooklyn, and a four-mile stretch of the FDR Drive in Manhattan, with 204 intersections equipped with V2V and V2I capabilities. The project facilitates communication between vehicles and traffic infrastructure to optimize traffic flow and enhance safety.
Designed to address traffic safety issues in New York City’s densely populated urban environment, the deployment tests and implements key applications including Emergency Electronic Brake Lights, Forward Crash Warning, Intersection Movement Assist, Blind Spot Warning, Lane Change Warning, and Red-Light Violation Warning. These applications use DSRC to provide real-time alerts to drivers, helping them avoid collisions and navigate traffic more efficiently. The project also includes pedestrian safety measures such as the Pedestrian in Signalized Crosswalk Warning and Mobile Accessible Pedestrian Signal System, vital for protecting VRUs.
28. PennDOT Ross Township Testbed
The PennDOT Ross Township Testbed focuses on deploying adaptive traffic signal controls and DSRC technology along the McKnight Road corridor in Pittsburgh, Pennsylvania. Funded by a Federal Highway Administration (FHWA) grant, this testbed aims to improve traffic management and safety along a critical transportation corridor. The implementation enhances traffic flow and safety through adaptive signal controls and DSRC technology deployment, addressing the need for advanced traffic management solutions in a high-traffic area. Projects include installing adaptive traffic signal systems and DSRC units along McKnight Road, with research focusing on evaluating these technologies’ effectiveness in optimizing traffic flow and improving safety.
29. PennDOT SPaT Deployments
The PennDOT SPaT deployments project includes installations along routes 19 and 228 in Cranberry Township and the Baum Centre Avenue corridor in Pittsburgh, Pennsylvania. This project features 11 RSUs at intersections utilizing DSRC technology to enhance traffic management and safety. The deployments improve traffic safety and mobility through real-time SPaT information dissemination. The project aims to develop the transportation workforce, foster partnerships, and strengthen economic collaboration by leveraging CV technology. Research focuses on the impact of real-time traffic signal information on safety and traffic flow.
30. SmartPGH Project
The SmartPGH project in Pittsburgh, Pennsylvania implements transit signal priority across the city’s “Smart Spine” corridors, expanding the network of connected, real-time adaptive signal controllers to enhance transit operations. The initiative includes converting nearly 40,000 streetlights to LED technology equipped with traffic detection and air quality sensors. SmartPGH improves transit efficiency and reduces delays through advanced signal priority systems, while the LED conversion provides energy savings, enhanced traffic detection, and environmental monitoring capabilities. The project encompasses real-time adaptive signal control systems, smart LED streetlight deployment, and integrated traffic detection and air quality sensor networks throughout Pittsburgh’s transit corridors.
31. Tennessee DOT (SPaT Challenge Project and CV Projects)
The Tennessee Department of Transportation (TDOT) participated in the SPaT Challenge, focusing on enhancing traffic signal systems to improve road safety. The CV testbed was established along Cumberland Avenue in Knoxville, Tennessee, featuring 17 RSUs strategically installed at intersections. These RSUs utilize DSRC technology to broadcast SPaT information to CVs, creating a more responsive traffic environment. This initiative supports efficient vehicle flow and reduces emissions by minimizing idling times at traffic signals while providing a platform for CV technology research and development. Primary research focuses on assessing SPaT data effectiveness in reducing crash rates at high-risk intersections.
The Metro Nashville 2020 Advanced Transportation and Congestion Management Technologies Deployment (ATCMTD) project modernizes Nashville’s transportation infrastructure to enhance safety, reduce congestion, and improve urban mobility efficiency. This planned deployment implements CV technologies across the metropolitan area, facilitating real-time data exchange between vehicles, infrastructure, and traffic management centers. The project aligns with federal ATCMTD program goals, demonstrating CV technology efficacy in reducing urban traffic problems and supporting efficient transportation solutions.
TDOT’s I-24 Corridor Nashville project is a large-scale CV deployment planned along the I-24 corridor between Nashville and Murfreesboro, Tennessee. This initiative enhances traffic management, improves safety, and reduces congestion along one of the state’s busiest highway segments. The project optimizes traffic flow using CV data to dynamically adjust traffic signal timing, manage lane use, and provide speed harmonization. Key goals include reducing crashes caused by sudden stops or traffic bottlenecks. By enhancing situational awareness and enabling proactive traffic management strategies, the project aims to reduce crash rates, improve emergency response times, and create a safer, more efficient travel environment.
32. Utah Transit Authority (UTA) DSRC Traffic Signal Pilot Project
The Utah Transit Authority (UTA) DSRC Traffic Signal Pilot Project aims to improve bus schedule reliability and reduce delays along Redwood Road, a major Salt Lake City area thoroughfare. This project utilizes DSRC technology enabling UTA buses to communicate directly with traffic signals at 24 intersections along the route, facilitating dynamic traffic signal adjustments that prioritize transit vehicles and help keep buses on schedule.
The primary motivation is to enhance public transit operations efficiency in a region experiencing significant growth and congestion. Prioritizing buses at intersections reduces time spent idling at red lights, encouraging higher ridership and reducing overall vehicles on the road, thus reducing emissions and improving air quality. The project provides valuable insights into CV technology deployment and interoperability by testing hardware from multiple vendors for compatibility and performance across different DSRC platforms. The project’s success may lead to expanding DSRC applications across Utah, including integrating additional transit routes and potentially deploying other CV technologies such as V2I communications for passenger cars.
33. Washington State Transit Insurance Pool (WSTIP) Safety-Collision Warning Pilot Project
The Washington State Transit Insurance Pool (WSTIP) Safety-Collision Warning Pilot Project enhances bus safety through advanced technology. This project equips 38 buses with 152 cameras (four per bus) and leverages internet connectivity to test and analyze a collision avoidance system. The primary objective is assessing the system’s effectiveness in reducing frequency and severity of transit bus collisions.
The pilot addresses the increasing need for advanced safety measures in public transportation. Multiple cameras on each bus enable comprehensive coverage of vehicle surroundings, allowing the system to detect potential hazards and provide timely driver warnings. Data gathered evaluates the system’s impact on collision rates and driver performance.
34. Wisconsin CV Testbed
The Connected Park Street Corridor project in Madison, Wisconsin represents a pioneering effort to integrate CV technology into a major urban thoroughfare. Spanning 20 to 30 signalized intersections along Park Street, this operational testbed enhances traffic management and safety through advanced V2I communications. By equipping intersections with sensors and communication technologies, the project enables real-time data exchange between vehicles and traffic signals, allowing dynamic signal timing adjustments based on current traffic conditions to optimize flow and reduce congestion. The testbed facilitates valuable data collection on traffic patterns, vehicle interactions, and system performance.
The primary motivation is addressing increasing traffic congestion and safety concerns from urban growth. Park Street, a critical transportation link connecting neighborhoods and business districts, experiences significant traffic volumes leading to delays and crashes. Key studies evaluate adaptive signal control system effectiveness, which adjusts signal timings based on real-time traffic data to reduce delays and improve intersection performance. The testbed also focuses on transmitting basic safety messages to CVs, including critical information about speed, location, and heading.
35. Nevada DOT DSRC for Rural ITS (Washoe County)
The Nevada Department of Transportation (NDOT) DSRC for Rural ITS (Washoe County) testbed enhances safety and efficiency along the I-580 corridor between Reno and Carson City. This 32-mile pilot corridor features 18 DSRC locations as a crucial component of the Nevada Integrated Mobile Observations (NIMO) project. The testbed utilizes advanced communication and sensing technologies including RSUs, CCTV cameras, radar, thermal/infrared sensors, LiDAR, and microwave sensors. This multimodal approach enables real-time monitoring and data collection, supporting traffic flow optimization and responses to dynamic road conditions such as construction, special events, and pedestrian and cyclist presence.
The primary objective is establishing a platform for CV applications compliant with the National Transportation Communications for Intelligent Transportation System Protocol (NTCIP). This initiative enhances rural ITS by leveraging a hybrid communication approach integrating DSRC with other technologies to create a robust, real-time information network.
36. California CV Testbed, Palo Alto
Map of the California CV Testbed in Palo Alto, CA
This testbed along Highway 82 (El Camino Real) in Palo Alto serves as a vital research and development site for CV technologies. The testbed features DSRC units across 11 intersections, evaluating the performance of a multi-modal Intelligent Transportation Systems (ITS) traffic signal system. The project recently transitioned to C-V2X technology across 16 intersections, demonstrating the Multi-Modal Intelligent Traffic Signal System (MMITSS). Key objectives include enhancing traffic signal control, providing signal priority for transit and freight, and promoting environmentally friendly driving practices. This operational testbed supports ongoing research into advanced traffic management solutions. Figure 6 illustrates the California CV testbed, Palo Alto.
37. I-85/"The Ray" CV Testbed, Georgia
The I-85/”The Ray” CV testbed spans 18 miles of Interstate 85 in Southern Georgia, deploying six RSUs along the highway to communicate with CVs. Equipped vehicles send data including speed, location, and operational information (such as windshield wiper use and hard braking) to a traffic management platform. The testbed enhances highway safety and efficiency using DSRC and C-V2X technologies to detect incidents immediately and warn drivers of potential hazards. This real-time data exchange significantly reduces secondary crash risk and improves traffic conditions by providing timely information to drivers and traffic managers.
38. Idaho CV Testbed (The Ada County Highway District)
The Ada County Highway District (ACHD) in Idaho has established a CV testbed to evaluate communications infrastructure and control technology effectiveness. Located in Ada County, this testbed deploys 20 RSUs and 20 OBUs utilizing DSRC technology. The primary objective is validating communication system readiness for real-world applications, focusing on improving traffic management and enhancing road safety. The ACHD testbed represents a crucial step in Idaho’s efforts to integrate advanced transportation technologies that interact seamlessly with CVs.
The implementation addresses Idaho’s high traffic fatality incidence and significant economic costs from motor vehicle crashes. In 2018, Idaho experienced 231 traffic fatalities, with a 10-year total of 2,131 fatalities. The annual economic cost of motor vehicle crashes is estimated at $886 million (based on 2010 data). By deploying CV technologies, Ada County Highway District aims to reduce traffic crash frequency and severity.
The testbed supports various projects and research initiatives advancing CV technology capabilities. One major project tests DSRC communication reliability and performance in different traffic scenarios, ensuring consistent and accurate information exchange between vehicles and infrastructure. The testbed assesses DSRC integration potential with traffic signal control systems to optimize signal timings, reduce congestion, and improve traffic flow. Additionally, it evaluates pedestrian safety enhancement applications, such as providing driver alerts when pedestrians are detected near crosswalks.
39. American Center for Mobility (Willow Run)
The American Center for Mobility (ACM) at Willow Run, Ypsilanti Township, is a 500-acre testing facility dedicated to developing and testing CAVs in Michigan. This testbed is equipped with RSUs, OBUs, and self-driving cars, offering various testing environments including urban, rural, and off-road scenarios. The facility plays a vital role in advancing mobility technologies by providing a controlled environment where automotive manufacturers, technology companies, and research institutions can test and refine their systems. The ACM focuses particularly on V2X communications, emphasizing DSRC technologies. Research conducted at this facility has been instrumental in advancing autonomous driving technologies and understanding the complexities of integrating CAVs into existing transportation networks.
40. I-75 Connected Work Zone (Oakland County)
The I-75 Connected Work Zone project in Oakland County, Michigan represents a collaboration between MDOT and 3M aimed at enhancing work zone safety through CV technologies. Spanning three miles, this project integrates advanced all-weather lane markings, retroreflective signs, and DSRC devices to improve V2I communication. The project includes CCTV cameras, vehicle detectors, and Dynamic Message Signs (DMS) placed at every mile, alongside Environmental Sensor Stations monitoring weather conditions. These components work together to automatically detect crashes, notify motorists of travel times, traffic queues, and adverse conditions, and provide critical safety alerts such as curve speed and bridge deck warnings. Research focuses on evaluating these systems’ effectiveness in real-time incident detection and response.
41. Macomb County Dept. Roads DSRC Deployment (MDOT/SMART Pilot)
The Macomb County Department of Roads, in collaboration with MDOT and SMART, has launched a comprehensive three-year DSRC deployment across the county. This project involves installing 750 RSUs at signalized intersections, along with Wi-Fi vehicle detectors, to enhance vehicle-infrastructure communication. The primary objective is broadcasting SPaT information to CVs, improving traffic flow and safety at intersections. Data collected from these RSUs is vital for ongoing research, particularly understanding real-time SPaT information’s impact on reducing intersection-related crashes and optimizing traffic management. Studies have explored the potential for reducing delays and improving safety, especially in high-traffic urban areas. This project stands out due to its scale and comprehensive data generation, with significant implications for future city-wide CV technology deployments.
42. Michigan DOT Wayne County Project
The Michigan DOT Wayne County Project in Wayne County, Michigan is a notable initiative focusing on CV technology, involving deployment of 12 RSUs and 250 OBUs using DSRC technology. The primary objective is documenting lessons learned, assessing benefits, and evaluating potential business models for future CV deployments. By analyzing operational data and outcomes, Michigan DOT aims to refine its CV technology approach and explore sustainable models for broader statewide implementation. This project represents an important step toward understanding practical implications of DSRC-based systems and their potential to improve traffic safety and efficiency in urban environments.
43. US Army Tank Automotive Research, Development & Engineering Center (TARDEC) "Planet M Initiative"
The US Army’s TARDEC “Planet M Initiative” is a pioneering project testing and developing CV technologies along 21 miles of I-69 in St. Clair and Lapeer Counties, Michigan. Supported by the Michigan Department of Transportation (MDOT), which installed roadside infrastructure to facilitate testing, the initiative employs DSRC systems integrated with six RSUs providing crucial safety warnings including curve speed warnings, lane closure alerts, speed recommendations, and disabled vehicle warnings. This project advances military and civilian CV technology applications by leveraging real-world conditions to test and refine V2I communication systems. Research focuses on evaluating these warning systems’ effectiveness in enhancing driver safety and operational efficiency.
44. Southeast Michigan Testbed
The Southeast Michigan testbed is a comprehensive CV test environment integrating several existing infrastructure assets across the Ann Arbor area and broader Southeast Michigan region. This project connects various RSU deployments along major corridors such as I-96 and I-696, enabling testing and implementation of advanced CV applications. Key features include dynamic speed harmonization, incident scene work zone alerts, eco-friendly approaches and departures at signalized intersections, and motorist advisories. The testbed supports extensive research on these applications’ efficacy in real-world scenarios, with particular emphasis on improving safety and reducing environmental impacts. The Southeast Michigan testbed serves as an efficient platform for advancing CV technology, providing valuable insights into operational benefits and challenges associated with large-scale deployments.
45. Ohio Turnpike & Infrastructure Commission DSRC Projects
The Ohio Turnpike & Infrastructure Commission project involves deploying DSRC technology along a 50-mile section of the Ohio Turnpike. This project includes 15 RSUs and aims to evaluate DSRC effectiveness in enhancing vehicle-infrastructure communication. The initiative is part of a broader effort to improve road safety and traffic management through CV technologies, providing real-time information to drivers, reducing traffic congestion, and enhancing overall turnpike efficiency.
46. NW US33 Smart Mobility Corridor
The NW US33 Smart Mobility Corridor is a CAV testbed in Ohio utilizing DSRC technology along 35 miles of the US 33 corridor from Dublin to Marysville. With 800-1000 OBUs and 27 RSUs, this corridor enhances travel time reliability and accommodates increased traffic volumes. The project supports CAV technology development and testing by optimizing travel lanes and decreasing crash risk. The operational corridor serves as a live test environment for various research initiatives focused on improving traffic management and safety.
47. Wyoming CV Project Deployment
A map of the Wyoming I-80 CV Corridor
The Wyoming CV Project Deployment enhances transportation safety and efficiency along the Interstate 80 (I-80) corridor, a critical freight route spanning 402 miles between Wyoming Department of Transportation’s Maintenance Districts 1 and 3. Conducted to address commercial vehicle operators’ needs who frequently navigate this highway stretch, the project’s main objectives are reducing adverse weather-related incidents and mitigating incident-related delays common in this region. The testbed integrates advanced CV technologies with the state’s Traffic Management Center (TMC), enabling real-time monitoring and management of traffic conditions.
Focusing on commercial vehicle operators particularly vulnerable to weather-related incidents, the project enhances road safety and operational efficiency. The testbed is equipped with 75 RSUs and 450 OBUs utilizing DSRC technology. This extensive deployment enables collection and dissemination of critical real-time information including weather alerts, road conditions, and traffic incidents directly to drivers, helping them make informed decisions.
Numerous projects within the Wyoming CV testbed evaluate CV technology effectiveness in reducing weather-related crashes and improving traffic management. One key project uses DSRC-enabled devices to transmit real-time weather data such as visibility and road surface conditions to commercial and passenger vehicles, enhancing driver awareness and enabling proactive responses to changing conditions. Another significant initiative integrates CV data with Wyoming Department of Transportation’s Traffic Management Center. Figure 7 illustrates Wyoming’s CV testbed.
48. Florida Smart Work Zones
The Smart Work Zones Project in Florida provides advanced CV infrastructure to enhance traffic safety and management across six major state road corridors: US 1, Dixie Highway, Powerline Road, US 441, Hillsboro Boulevard, and Sample Road. The project deploys RSUs, CCTV cameras, and vehicle detectors equipped with DSRC technology to facilitate real-time V2I data exchange. This infrastructure delivers critical safety and operational information including real-time traffic conditions, queue warnings, and travel time estimates to drivers in work zones.
Using DSRC-enabled communication, the system provides low-latency alerts for incidents like traffic slowdowns or stoppages, ensuring enhanced situational awareness for drivers and reducing crash risk from sudden deceleration or erratic behavior in work zones. The project focuses on real-time decision-making tools including Traffic Queue Warning, Travel Time Advisory, and Alternate Route Advisory to mitigate congestion and improve traffic flow. These systems rely on V2I communication to alert drivers of potential delays and provide timely detour recommendations, reducing rear-end collision likelihood and improving overall road safety.
49. Indiana CV Testbed (Indiana DOT SPaT Deployment - Greenwood)
The Indiana Department of Transportation (INDOT) implemented a CV testbed known as the SPaT Deployment along US 31 in Greenwood, Indiana. This project includes installing SPaT capabilities at approximately six signalized intersections. The primary goal is enhancing traffic management and safety utilizing advanced communication technologies that enable real-time data exchange between traffic signals and CVs. This testbed forms part of Indiana’s broader strategy to modernize transportation infrastructure and prepare for increasing CAV technology integration.
The SPaT Deployment in Greenwood addresses the need to improve traffic efficiency and safety in one of the region’s major corridors. US 31 serves as a vital transportation route experiencing significant traffic volumes, leading to congestion and delays especially during peak hours. By deploying SPaT technology, INDOT aims to optimize signal timing and improve coordination across multiple intersections to reduce congestion and travel times.
Additionally, the Indiana CV Corridor Deployment Project is a significant initiative enhancing traffic safety and efficiency along Interstate 94 (I-94). Part of the national SPaT Challenge, this deployment involves installing 10 RSUs at key corridor intersections utilizing DSRC technology to broadcast SPaT information to CVs.
50. Michigan Safety Pilot Model Deployment
The MI Safety Pilot Model Deployment at US 23 and Plymouth Road, Ann Arbor, and Washtenaw Avenue, Michigan is a comprehensive CV testbed assessing operational readiness of DSRC-based safety applications. This testbed integrates 2,700 OBUs, 29 RSUs, and 12 Traffic Signal Controllers (TSCs), enabling extensive V2I data exchange between vehicles and infrastructure. The primary objective demonstrates DSRC technology capabilities and effectiveness in real-world environments, particularly improving traffic safety and reducing crash risks through communication-based interventions. The project utilizes DSRC technology facilitating various safety applications including forward collision warnings, intersection movement assistance, and emergency vehicle alerts. These applications improve situational awareness and provide real-time alerts, helping drivers make informed decisions to avoid crashes.
51. Utah Salt Lake Valley Snowplow Preemption
The Salt Lake Valley Snowplow Preemption project spans five corridors and 55 intersections, employing DSRC technology for traffic signal preemption specifically designed for snowplow vehicles. This system allows snowplows to preemptively change signal phases, ensuring plows can clear critical routes efficiently during snowstorms.
The UTA DSRC Traffic Signal Pilot Project optimizes traffic signal operations through V2I communication, primarily improving public transit efficiency and reliability. The system dynamically adjusts signal phases to prioritize buses, reducing delays and maintaining schedules. A key objective is enhancing transit operational efficiency in high-congestion areas, ensuring smoother traffic flow and reducing environmental impact from idling buses. The project also tests DSRC-based system scalability and interoperability, assessing multiple hardware vendor integration to ensure compatibility across different infrastructure and vehicle platforms.
52. Virginia Smart Roads CV Testbeds
A map of VA Smart Roads CV Testbed
The Virginia Smart Roads CV Testbed, located on sections of major highways including Interstate 66, Interstate 495, US 29, and US 50, encompasses a controlled-access environment meeting Federal Highway Administration standards. With 49 RSUs employing DSRC technology, this facility provides robust infrastructure for real-time data exchange between vehicles and the surrounding environment. As urban areas expand, demand for more efficient and safer transportation systems becomes increasingly critical. The Virginia Department of Transportation (VDOT) established this testbed as a proving ground for new technologies that can alleviate these issues. Figure 8 illustrates the CV testbed locations.
The Virginia Smart Roads Testbed has hosted numerous projects advancing CAV technologies. Key research initiatives focus on testing V2I communication protocols enabling vehicles to interact with traffic signals, signage, and other roadside equipment. Studies evaluate DSRC technology effectiveness in various traffic scenarios including congestion management and incident response. Additionally, projects explore integrating CV data with advanced traffic management systems (ATMS) to optimize signal timings and enhance traffic flow coordination across multiple intersections.
53. Michigan, American Center for Mobility (Willow Run)
The American Center for Mobility (ACM) at Willow Run, Ypsilanti Township, is a 500-acre testing facility dedicated to developing and testing CAVs in Michigan. Equipped with RSUs, OBUs, and self-driving cars, the ACM offers various testing environments including urban, rural, and off-road scenarios. This facility plays a vital role in advancing mobility technologies by providing a controlled environment where automotive manufacturers, technology companies, and research institutions can test and refine their systems. The ACM focuses particularly on V2X communications, emphasizing DSRC technologies. Research conducted at this facility has been instrumental in advancing autonomous driving technologies and understanding the complexities of integrating CAVs into existing transportation networks.
54. Mcity Testbed
Mcity, located at the University of Michigan in Ann Arbor, is a 32-acre CAV testbed simulating urban and suburban driving environments. The facility features various testing scenarios including intersections, roundabouts, and pedestrian crossings, allowing comprehensive V2X technology testing. Mcity is equipped with RSUs, OBUs, and edge computing infrastructure supporting advanced research on transit signal priority, emergency vehicle preemption, dynamic signal optimization, and VRU notification. This testbed has been instrumental in advancing autonomous driving technology development and understanding CV-urban infrastructure interactions. Research conducted at Mcity has profoundly impacted the automotive industry, helping accelerate safe and efficient CAV system deployment.
55. Minnesota Roadway Safety Institute Connected Vehicle Testbed
The Roadway Safety Institute (RSI) CV Testbed is a permanent facility in Minnesota designed to advance CV technology development and testing. Located on a high-crash segment of Interstate 94 Westbound in Minneapolis between Hiawatha and Portland Avenues, this testbed provides a real-world environment for evaluating CV application effectiveness.
The RSI CV testbed addresses pressing safety concerns on Minnesota’s roadways, particularly high-crash segments like the designated I-94 portion. The testbed serves as a research and development hub where cutting-edge CV technologies are tested and refined. By simulating real-life traffic conditions, it provides invaluable data and insights into how vehicles with advanced communication systems interact with each other and road infrastructure.
Notable projects at the RSI testbed include testing V2I and V2V communication systems to improve traffic flow and reduce collision risks. The testbed is equipped with one RSU, one OBU, and seven radars utilizing DSRC technology, designed to implement and evaluate next-generation vehicle-based freeway safety applications. This integrated infrastructure establishes an efficient sensor communication network and data collection system, enabling real-time vehicle-infrastructure communication and facilitating critical safety information exchange including collision warnings and traffic condition alerts.
Case Studies in Connected Vehicle Testbed Deployment
Tampa Hillsborough Expressway Authority (THEA) Connected Vehicle Deployment, Florida
The Tampa Hillsborough Expressway Authority (THEA) CV Deployment improves traffic flow, safety, and environmental outcomes in downtown Tampa through installation of 1,000 advanced rearview mirrors, 47 RSUs, 10 bus OBUs, and 8 streetcar OBUs. The project concentrates on reversible express lanes and major downtown arterials where traffic peaks during rush hours. Using CV technology, the deployment reduces congestion, crashes, and transit times while lowering greenhouse gas emissions.
Located within Tampa’s Central Business District and along the Lee Roy Selmon Expressway, the testbed covers approximately ten CBD intersections and an expressway segment. This diverse environment of commuters, pedestrians, and transit systems provides ideal conditions for testing CV technologies under varied traffic and weather conditions. The infrastructure utilizes DSRC technology enabling seamless V2V and V2I communication, with integrated sensors collecting real-time traffic and environmental data. The comprehensive deployment includes nearly 1,000 equipped vehicles operating throughout the testbed area.
The testbed’s primary goals include reducing collision rates through real-time alerts for sudden braking, speed adjustments, and pedestrian crossings; mitigating congestion by offering rerouting options and precise travel time predictions; reducing emissions through smoother traffic flow; and collecting comprehensive data to assess CV technology operational effectiveness. Advanced communication systems provide dashboard alerts seconds before potential hazards, allowing drivers to adjust speed or change lanes to avoid crashes. CVs equipped with sensors share data enabling drivers to anticipate hidden pedestrians and cyclists.
For mobility improvements, vehicles continuously communicate with infrastructure and other vehicles, sharing information about travel speeds, delays, and lane closures. This interconnected system provides precise travel time predictions and suggests alternative routes during congestion. Environmental benefits result from maintained consistent speeds and reduced idle times, with smoother traffic patterns reducing fuel consumption and carbon emissions. The testbed provides critical environmental data supporting city planning for energy-efficient traffic management policies.
The comprehensive deployment assesses each application’s effectiveness including V2V collision alerts, V2I rerouting information, and traffic flow patterns. Performance data helps engineers and policymakers refine systems while addressing practical concerns about maintenance costs, alert effectiveness, and manufacturer compatibility. This knowledge base supports future intelligent transportation system deployment throughout Florida and nationwide.
Implementation Strategies
The THEA CV testbed integrates multiple operational strategies for Tampa’s Central Business District including rush hour collision avoidance, wrong-way entry prevention, traffic flow optimization, streetcar safety, pedestrian safety, and bus priority systems. The deployment features 1,000 enhanced rearview mirrors enabling V2V communication, 47 RSUs along major corridors and reversible express lanes, 10 bus OBUs, and 8 streetcar OBUs. These components relay critical data between vehicles and infrastructure including traffic signals and transit systems.
The infrastructure utilizes wireless modems at signalized intersections integrated with pre-existing fiber networks, creating a robust backhaul system supporting over-the-air updates. This interconnected system minimizes transit delays, enhances bus and streetcar operational efficiency, reduces congestion, and lowers greenhouse gas emissions through optimized traffic flow.
Achievements and Collaboration
The testbed has achieved significant milestones in urban mobility through V2X communication systems that improve real-time traffic management. Intelligent traffic signals facilitate vehicle-transit communication, reducing delays and travel times for public transportation while maintaining efficient flow for personal vehicles. Data-driven decision-making capabilities enable city planners and transportation officials to analyze traffic patterns more effectively.
The project demonstrates successful multi-stakeholder collaboration combining state and local agencies with private sector expertise. Key partners include City of Tampa, Hillsborough Area Regional Transit Authority, and University of South Florida’s Center for Urban Transportation Research, along with hardware and software providers. Hillsborough Community College Master Mechanic Program students installed onboard equipment in over 1,000 participant vehicles, providing educational opportunities while supporting project implementation. Performance evaluation led by CUTR focuses on safety, mobility, environmental impact, and agency efficiency metrics.
Extended cooperative agreements with major OEMs including Hyundai, Honda, and Toyota enable spectrum testing and ensure uninterrupted CV communication. These partnerships allow OEM vehicles to interact with existing pilot participants, demonstrating seamless integration of new technologies into the established network.
Future Research Priorities
Future studies will focus on enhancing V2X communication to ensure seamless real-time data transmission between vehicles, infrastructure, VRUs, and transit services. Research aims to reduce traffic conflicts, improve navigation, and create coordinated transportation ecosystems responsive to urban dynamics.
Public transportation integration studies will evaluate how CV-enabled buses and streetcars communicate with traffic signals for intersection priority, minimizing delays and encouraging ridership. Real-time transit schedule and location updates will enhance user experience and make public transport more attractive for Tampa commuters.
Safety improvement research will analyze crash patterns in high-risk areas including intersections and pedestrian zones, evaluating CV alert effectiveness in preventing collisions. Long-term studies will assess CV technology scalability, examining integration with existing transportation frameworks and adaptation to future technological advancements.
Stakeholder engagement remains critical, with collaboration between local communities, government agencies, and private sector partners ensuring outcomes align with public needs. Resident involvement in pilot programs and feedback mechanisms will assess system effectiveness and acceptance, fostering inclusive smart transportation development benefiting all users.
Published Research and Reports
The THEA CV testbed, part of USDOT’s Connected Vehicle Pilot Deployment Program, has generated extensive documentation through multiple evaluation reports and studies:
Key Reports:
- “Connected Vehicle Infrastructure: Deployment and Funding Overview” (Texas A&M Transportation Institute, January 2018) – Infrastructure requirements, funding strategies, RSU/OBU integration
- “Connected Vehicle Pilot Deployment Program Independent Evaluation: Tampa” (May 2018) – Deployment of 1,000+ equipped vehicles, real-time alert systems, V2X application testing
- “Connected Vehicle Pilots Phase 2 Interoperability Test Report” (November 2018) – DSRC deployment, Forward Collision Warning, Wrong-Way Entry notifications, SPaT integration
- “System Architecture Document – Tampa” (November 2018) – Technical specifications for V2I safety applications
- “Comprehensive Installation Plan – Tampa” (May 2018) – RSU Requirements Specification v4.0, procurement processes, detection technologies
- “Data Privacy Plan – Tampa” (February 2017) – PII protection policies, security framework, CIA triad implementation
- “System Requirements Specification – Tampa” (2020) – Operational modes, environmental considerations, durability standards
- “Financial & Institutional Assessment—Tampa” (July 2022) – Sustainability analysis, partnership structures, cost-benefit evaluation
Deployed Safety Applications
V2V Safety Applications:
- Emergency Electronic Brake Lights (EEBL)
- Forward Collision Warning (FCW)
- Intersection Movement Assist (IMA)
- Vehicle Turning Right in Front of Transit Vehicle (VTRFTV)
V2I Safety Applications:
- End of Ramp Deceleration Warning (ERDW)
- Pedestrian in Signalized Crosswalk (PED-X)
- Pedestrian Collision Warning (PCW)
- Pedestrian Transit Movement Warning (PTMW)
- Wrong Way Entry (WWE)
V2I Mobility Applications:
- Intelligent Traffic Signal System (I-SIG)
- Transit Signal Priority (TSP)
- Mobile Accessible Pedestrian Signal (PED-SIG)
Technical Architecture
The system architecture includes:
- 1,500 OBUs with Human Machine Interface, GPS, and DSRC antennas
- 84 additional OBUs using SiriusXM technology
- 41 RSUs with DSRC capabilities connected to Master Server
- Detection technologies: Radar, LiDAR, video systems
- Pedestrian applications via smartphone Wi-Fi connectivity
- Data management: Siemens SAP software for inventory tracking
Installation and Security Framework
Installation follows comprehensive site surveys assessing intersection geometry, electrical systems, and optimal RSU placement. The security framework employs three control types:
- Preventive controls: Inhibit harmful events
- Detective controls: Discover security incidents
- Corrective controls: Restore systems post-incident
Implementation approaches include administrative (policies/training), logical/technical (encryption/access controls), and physical measures (guards/locks).
Partnerships and Collaboration
Key collaborators include:
- City of Tampa
- Hillsborough Area Regional Transit Authority (HART)
- University of South Florida’s Center for Urban Transportation Research (CUTR)
- Hillsborough Community College (student installation program)
- Technology vendors: Cohda Wireless, Siemens
- OEM partners: Hyundai, Honda, Toyota (spectrum testing)
Financial Sustainability Challenges
The 2022 evaluation revealed declining user willingness to pay for retrofitting:
- Initial surveys: Most willing to pay <$500
- Later surveys: Significant portion unwilling to pay anything
- Challenge: Demonstrating tangible benefits to sustain funding beyond pilot phase
- Goal: Seven-year operational sustainability without federal funding
Research Findings
According to Chowdhury et al.’s “Lessons Learned from the Real-World Deployment of a Connected Vehicle Testbed,” the deployment includes:
- 1,600 vehicles
- 10 buses
- 10 trolleys
- 500 pedestrians using smartphone apps
- 40 RSUs interconnected via DSRC
The testbed operates in three distinct modes (Normal, Degradation, Error) ensuring operational reliability while addressing challenges including smartphone GPS limitations and urban connectivity issues. Environmental considerations include lightning protection and device durability for Tampa’s extreme weather conditions.
Mcity Testbed, University of Michigan, Ann Arbor, Michigan
Mcity Architecture
Mcity is a 32-acre CAV testing facility located at the University of Michigan’s North Campus in Ann Arbor, designed to replicate real-world driving experiences in a controlled environment. The facility incorporates urban and suburban infrastructure elements typical of city areas, enabling evaluation of V2V, V2I, and V2P interactions under realistic but controlled conditions.
The facility features 16 acres of roads mimicking essential urban components including straight and curved roads, intersections, traffic lights, roundabouts, road signs, and varied road surfaces. This diverse infrastructure provides real-world context for testing V2X communications critical for CAV systems. The controlled environment allows researchers to test vehicle responses under conditions ranging from routine commuting to complex intersections and pedestrian crossings.
Mcity serves as a critical site for testing, assessing, and improving high-tech systems before deployment on public roads. The center enables detailed exploration of V2X communication possibilities while ensuring proper system operation under various circumstances including heavy traffic, severe weather conditions, and potential cyber-attacks. Through examination of equipment, sensor technologies, and data management practices, Mcity advances the safety and efficiency of connected vehicle systems.
The testbed’s infrastructure supports development of communication protocols, safety requirements, and intelligent infrastructure for autonomous and connected vehicles. Research activities include traffic management system development, safety analysis, and real-time data applications, establishing Mcity as a leader in intelligent transportation systems research. The controlled yet flexible environment enables examination and resolution of real-world transportation challenges while vehicles and infrastructure interact in predictable patterns.
Layout for the Mcity Facility
Physical Infrastructure
Mixed Road Design: Mcity features diverse road configurations including straight and curved roads, Léonard junctions, circles, and gyratories for testing vehicle control systems under varied conditions. A 1,000-foot stretch facilitates high-speed testing, while urban blocks enable V2I application testing and roundabouts simulate urban scenarios.
Traffic Signals and Smart Intersections: Intelligent signal controllers at intersections evaluate complex AV and Traffic Management Center algorithms, transmitting SPaT, MAP, and TIM messages.
Urban Elements: Simulated features include facades, pedestrian crossings, tree covers, garages, and ramps, adding visual and spatial complexity for testing first/last-mile logistics and ride-hailing scenarios while providing AVs with capabilities to handle real-world obstructions.
Data Capture and Control Systems
Data Collection Network: Integrated wireless systems, fiber optics, Ethernet, and real-time kinematic (RTK) positioning systems enable precise tracking of vehicle movement, speed, and interactions. RTK provides exact latitude and longitude data critical for vehicular activity assessment.
Augmented Reality Platform: Patent-pending AR system overlays virtual vehicles on real ones, enabling hybrid testing that minimizes physical resources while increasing test diversity. This platform safely conducts high-risk test scenarios by virtually recreating difficult situations.
Mcity Operating System: Mcity OS manages infrastructure and testing conditions, allowing researchers to modify vehicle settings and test parameters in real-time. The system enables quick data gathering, control, and nuanced analysis across diverse testing scenarios.
Components and operational schematics of the Mcity Facility
Communication Technologies
5G and DSRC: Fully connected 5G network combined with DSRC enables high-speed, low-latency V2X communication for applications requiring immediate action including pedestrian notifications, collision avoidance, and emergency vehicle prioritization.
V2I Integration: Testing capabilities for dynamic signal control, emergency vehicle preemption, and green wave systems enhance cooperative automation and intelligent transportation networks.
Standards Compliance: Communication protocols follow SAE J2735, SAE J2945, and IEEE 1609 standards for message structure, security, and interoperability, ensuring alignment with international CAV standards.
Collaborative Partnerships
Ann Arbor Connected Vehicle Test Environment (AACVTE): Partnership provides access to over 2,500 vehicles testing V2V applications including forward collision warnings and intersection movement assistance. Real-time data from AACVTE enriches research on red-light violations, curve speed warnings, and pedestrian detection.
American Center for Mobility (ACM): The 500-acre Ypsilanti facility complements Mcity’s urban focus with highway loops, curved tunnels, and high-speed testing areas, enabling comprehensive testing across urban and highway environments.
Safety and Efficiency Testing
Collision Avoidance: V2X communication and intelligent intersections thoroughly test collision avoidance systems, red-light violation warnings, and automated pedestrian detection using intelligent cameras and RSUs.
Dynamic Traffic Management: Testing includes green wave advisories, emergency preemption, and public transportation priority through dynamic signal optimization and real-time information transmission.
Real-Time Monitoring: Sophisticated data visualization tools enable live test scenario monitoring, allowing researchers to observe vehicle behavior in real-time and make rapid adjustments during time-critical situations.
Data Collection Devices
Connected Vehicle-Centric Interface Device (CV-CID): Interfaces with CV system components to acquire speed, location, and communication data from various sensors and vehicle modules.
Econolite CoProcessor: Collects, processes, and transmits data to improve vehicle-infrastructure interactions, assisting in traffic simulation and formulating control strategies for enhanced traffic and safety management.
Published Research
Key research contributions include:
- Traffic simulation models leveraging SimEvents for ITS capabilities
- Mcity OS development as cloud-based automated vehicle testing tool
- Motion sickness prevention technologies using preemption strategies
The integrated physical infrastructure and digital systems, combined with partnerships extending beyond test facilities, position Mcity as a significant contributor to intelligent transport systems development at local and global levels.
Remote Testing and Mcity 2.0
In 2022, Mcity received a $5.1 million National Science Foundation grant to develop “Mcity 2.0,” an advanced test environment combining physical testing with virtual reality simulation. This modification enables researchers nationwide to access Mcity facilities remotely without physical attendance, democratizing access to advanced testing infrastructure and making mobility research more equitable.
Collaborative Research Opportunities
Remote capabilities enable previously impossible collaborations. In November 2023, Purdue University researchers successfully tested path planning algorithms remotely using Mcity’s automated research vehicles. These partnerships allow institutions without testing infrastructure to evaluate technologies in real-world settings, accelerating CAV technology development.
Future Research Priorities
Cybersecurity in CAVs: Exploring vulnerabilities in connected vehicle protocols and developing countermeasures to mitigate risks.
Traffic Flow Optimization: Investigating collaborative autonomy and connected vehicle technologies for emissions reduction and traffic efficiency improvement.
Infrastructure Readiness: Evaluating existing infrastructure’s capability for mass CAV deployment and identifying enhancement requirements.
Policy and Standards Development: Contributing to federal regulations for CAV safety testing, addressing gaps in current frameworks.
Integrated Research Environment
Mcity’s technological infrastructure enables development and testing of safety and traffic control methods through comprehensive vehicle-infrastructure interaction using state-of-the-art intelligent transport systems. The facility advances practical transportation solutions by incorporating green driving and energy-efficient technologies in development processes, improving prospects for automated eco-friendly vehicles.
The center addresses cybersecurity concerns by studying V2X vulnerabilities and developing mitigation strategies for CVs and AVs. Through partnerships with the American Center for Mobility and Ann Arbor Connected Vehicle Test Environment, Mcity expands testing and data collection capabilities while creating systems that improve vehicle-to-vehicle interactions.
These collaborative efforts and advanced capabilities position Mcity to significantly advance connected and autonomous vehicle technologies, working toward safer and more efficient transportation systems.
CAV Testbed at Morgan State University in Baltimore, Maryland
Morgan State University’s CAV Testbed
The Morgan State University CAV Testbed in Baltimore, MD, serves as a research and development facility for CV technologies, equipped with two RSUs, two OBUs, two LiDAR sensors, and four CCTV cameras operating under C-V2X technology. The testbed focuses on improving road user safety, particularly for VRUs, at two signalized intersections: Cold Spring Lane–Hillen Road and East 33rd–Hillen Road.
Smart signal controllers at these intersections broadcast real-time SPaT messages, MAP data, and TIMs, providing a controlled environment for evaluating CV systems and their impact on traffic management and safety. The integration of LiDAR sensors and CCTV cameras enables comprehensive data collection on vehicle and VRU movements, while RSUs and OBUs facilitate vehicle-infrastructure communication for real-time updates and traffic signal coordination.
Since 2022, the testbed has supported extensive research into vehicle conflict analysis using LiDAR sensors, comparing detection accuracy with microsimulation tools like VISSIM and AIMSUN. Researchers have developed new Post Encroachment Time (PET) threshold classifications to assess vehicle-pedestrian interactions, improving conflict detection accuracy and pedestrian safety at signalized intersections. Statistical analyses of jaywalking incidents and vehicle-bicyclist conflicts have contributed to targeted safety measures for VRUs.
The facility has also been instrumental in exploring real-time traffic control during signal failures and smart green time allocation for optimized signal timing. Comparative analyses of LiDAR versus CCTV sensor accuracy under various weather conditions provide valuable insights into the reliability of different sensor technologies for traffic monitoring and delay time estimation.
Future research will focus on developing preemption systems for emergency vehicles and Morgan shuttles, integrating dynamic safety messages with real-time data from LiDAR sensors, RSUs, and OBUs to prioritize emergency passage through signalized intersections. Researchers will calculate Time-to-Collision for various conflict types using LiDAR data to measure potential severity and risk levels. Additionally, the development of real-time warning devices will alert both drivers and VRUs to imminent conflicts at testbed intersections, advancing CV technologies and improving traffic safety through innovative sensor applications and data-driven analyses.
Comparison of Mcity and Morgan State University CAV Testbeds
Mcity at the University of Michigan and Morgan State University’s Connected Vehicle testbed represent complementary approaches to advancing autonomous vehicle technologies, each addressing distinct aspects of CAV development through different methodologies.
Mcity encompasses a 32-acre controlled facility that replicates urban and suburban environments with various intersections, traffic signals, and building facades, enabling comprehensive CAV testing under diverse conditions. The facility’s recent $5.1 million NSF grant has enabled the integration of physical testing with virtual reality simulation, allowing researchers nationwide to conduct remote testing. This expansive controlled environment supports wide-ranging research including vehicle dynamics, sensor integration, cybersecurity, and policy development, with resources for large-scale testing and collaboration among industry partners and government agencies.
In contrast, Morgan State’s CAV testbed operates within Baltimore’s actual urban environment, focusing on real-world traffic conditions and interactions. The testbed features SMART Intersections equipped with LiDAR sensors, roadside units, and connected vehicle technology specifically targeting pedestrian and cyclist safety. This real-world deployment emphasizes pedestrian safety through intelligent safety warnings and traffic conflict assessment routines that foster more effective transportation systems.
The fundamental difference lies in their operational environments and research priorities. Mcity’s controlled setting enables testing of various scenarios including high-speed operations and complex geographical structures, supporting broad technological and policy development initiatives. Morgan State’s integration within Baltimore provides authentic urban challenges and immediate community engagement, enabling studies on societal impacts and community sentiment regarding CAV technologies, particularly focusing on underserved populations.
While Mcity pursues a comprehensive research strategy encompassing technology development, policy formation, and large-scale case studies from a more theoretical perspective, Morgan State addresses practical CAV implementation with emphasis on safety and effective integration into existing urban transportation networks. Morgan State’s location facilitates direct community participation in research, providing insights into how CAV technologies affect urban populations, while Mcity’s controlled environment and diverse partnerships focus more extensively on technological advancement and policy frameworks.
Together, these testbeds provide complementary contributions to CAV development—Mcity offering broad technological and policy advancement in a controlled setting, while Morgan State delivers practical insights into safety challenges within authentic urban environments. This dual approach ensures comprehensive advancement of CAV technologies addressing both theoretical possibilities and real-world implementation challenges.
Feature | Mcity (University of Michigan) | Morgan State University’s CAV Testbed |
Location | Ann Arbor, Michigan | Baltimore, Maryland |
Scale | 32-acre purpose-built facility simulating urban and suburban environments. | Integrated within actual urban intersections: Cold Spring Lane at Hillen Road and East 33rd Street at Hillen Road. |
Infrastructure | Diverse road types and intersections, traffic signals, signage, and building facades. Controlled environment for testing various scenarios. | It has two roadside units (RSUs), two Onboard Units (OBUs), two LiDAR sensors, and four CCTV cameras. It operates under Cellular Vehicle-to-Everything (C-V2X) technology. |
Technological Features | V2X and 5G wireless communication, augmented reality testing capabilities, and software-controlled infrastructure for dynamic testing scenarios. | Real-time Signal Phase and Timing (SPaT) messages, Intersection Map Data (MAP), and Traveler Information Messages (TIM). Focus on real-time data exchange and coordination. |
Research Focus | Broad spectrum, including vehicle dynamics, sensor integration, cybersecurity, and policy development. Large-scale testing and collaborations with industry partners and government agencies. | Emphasis on pedestrian and cyclist safety. Development of dynamic safety warnings and customized traffic conflict assessments. |
Community Engagement | Collaboration with various stakeholders, including industry partners and government agencies, focusing on technological advancements and policy development. | Direct integration within Baltimore City facilitates community involvement, allowing studies on public perception and societal impacts of CAV technologies. |
Unique Capabilities | Remote access for researchers nationwide through the Mcity 2.0 initiative. Integration of physical testing with virtual reality simulations. A comprehensive environment for diverse scenario testing. | It focuses on real-world traffic conditions and interactions. It is equipped with the SMART Intersection to enhance pedestrian and traffic safety. It utilizes LiDAR and connects vehicle technology for comprehensive data collection. |
The CAVe-in-a-Box System
The CAVe-in-a-Box, developed by FHWA, provides a comprehensive framework for connected vehicle deployments through an integrated system that facilitates both vehicle-to-vehicle and vehicle-to-infrastructure communication. This setup combines essential hardware components with open-source software tools to create a flexible testing and deployment environment for CV technologies.
Core System Components
- Traffic Signal Controller – Manages intersection operations and communicates with connected vehicles for optimized traffic flow
- Roadside Units (RSUs) – Transmit traffic conditions, hazard information, and signal phases to vehicles
- V2X Hub – Central communication node integrating DSRC and C-V2X technologies for data exchange
- Onboard Units (OBUs) – Enable vehicle-based V2X communication with RSUs and other vehicles
- Controller Area Network (CAN) – Coordinates electronic components within vehicles
- Wired Network Switch – Provides ethernet connectivity between system components
- Wi-Fi Router – Enables wireless communication for mobile devices and backup connectivity
- Power Supply – Ensures continuous operation of all system components
- Touchscreen Tablet/PC – Control interface for real-time monitoring and system management
Open-Source Tools
The CAVe-in-a-Box integrates several open-source platforms that enhance functionality and accessibility:
- CARMA – Platform for cooperative driving automation enabling vehicles to coordinate movements for optimized traffic flow
- Operational Data Environment (ODE) – Centralizes data gathering, processing, and analysis from CV installations
- Secure Data Commons (SDC) – Provides secure storage and exchange of collected data for research collaboration
V2X Hub Plugin Architecture
The V2X Hub supports multiple plugins enhancing V2I communication:
- Curve Speed Warning – Alerts drivers to reduce speed approaching curves
- Pedestrian Plugin – Detects and alerts drivers to pedestrian presence
- Preemption Plugin – Adjusts signals to prioritize emergency vehicles
- Dynamic Message Sign (DMS) – Displays real-time information via electronic signage
- MAP Plugin – Provides detailed intersection geometry data
- SPAT Plugin – Delivers signal phase and timing information
- Location and RTCM Plugins – Support precise positioning and correction data
Network Architecture
The network configuration demonstrates integrated communication between all components. Traffic signal controllers, RSUs, V2X hubs, and OBUs exchange data through both wired and wireless networks. The architecture ensures:
- Real-time traffic management capabilities
- Continuous safety alert transmission
- Seamless V2X communication protocols
- Scalable deployment from testing to full implementation
This modular design allows adaptation to various scenarios, from small-scale testing environments to comprehensive urban deployments, while maintaining consistent operational efficiency across connected and automated vehicle technologies.
Industry Applications of CAV Technologies
Several automotive manufacturers now integrate On-Board Units directly into their vehicles, enabling connected car technologies and V2X communication capabilities. These built-in systems represent a significant shift from aftermarket solutions toward factory-integrated connectivity.
General Motors – OnStar
General Motors leads the industry with OnStar, providing comprehensive connected services across Chevrolet, GMC, Cadillac, and Buick models. Starting with 2024 models, OnStar connectivity comes standard for three years, including remote vehicle commands, automatic crash response, and stolen vehicle recovery. The system integrates with Alexa and Google Assistant, while premium models like Cadillac Escalade and GMC Denali offer advanced features including Super Cruise and unlimited Wi-Fi streaming. By 2025, GM will introduce OnStar One Essentials, providing navigation and voice assistance at no additional cost for eight years. The built-in OBU enables Automatic Crash Response using integrated sensors, connecting drivers to trained advisors who can dispatch first responders and utilize Injury Severity Prediction technology.
European Manufacturers
BMW incorporates OBUs through ConnectedDrive across models including the 3 Series, 5 Series, X5, and i3. The system provides real-time traffic updates, remote diagnostics, and V2I communication, free for three years before requiring subscription renewal.
Mercedes-Benz models after 2024 feature V2X communication capabilities with availability varying by model and market. The company partners with Luminar for LiDAR integration in its Drive Pilot system, enabling Level 3 autonomous driving with enhanced environmental perception in challenging conditions.
Audi integrates OBUs through Audi connect, featuring permanently installed SIM cards for navigation, vehicle services, and smart road object connectivity, enabling traffic information and in-car internet access.
Volkswagen pioneered European V2X implementation with the 8th generation Golf, using Wi-Fi-based DSRC for vehicle, infrastructure, and pedestrian communication without cellular dependency. The ID. electric vehicle family includes online connectivity for over-the-air updates, traffic hazard alerts, and swarm-based semi-autonomous driving.
Volvo equips newer models like the EX90 with built-in OBUs for V2X communication, enabling V2V and infrastructure interaction. Google-integrated software provides continuous over-the-air updates and digital services supporting real-time safety data exchange.
Asian Manufacturers
Toyota deployed DSRC-based V2X systems in models like the 2022 Mirai, facilitating direct communication for safety warnings and traffic information without cellular networks. The company is transitioning toward C-V2X technologies combining short-range and long-range communication through 4G and 5G networks.
Hyundai includes advanced connected features in luxury models like Genesis and Equus (2023 onward), incorporating sophisticated telematics systems supporting various connected services.
Alternative Approaches
Tesla vehicles lack dedicated OBUs for standardized V2X communication despite extensive sensor suites and communication capabilities. Their systems focus on navigation, autopilot features, and Tesla-specific vehicle communication rather than industry-standard V2X protocols.
Ford offers FordPass Connect integrated within vehicle systems for remote access, navigation, and diagnostics, but does not provide dedicated OBUs for electronic toll collection, requiring regional-specific arrangements for toll payments.
Market Implications
The integration of built-in OBUs represents a fundamental shift in automotive connectivity, with manufacturers taking varied approaches based on regional requirements and technological strategies. European manufacturers generally emphasize DSRC-based V2X communication, while American manufacturers focus on proprietary connected services. Asian manufacturers are transitioning from DSRC to C-V2X technologies, reflecting the global evolution toward cellular-based vehicle communication. This diversity in implementation strategies highlights the ongoing standardization challenges facing the connected vehicle industry.