Research
The deployment of a network of smart intersections in Ann Arbor, Michigan will accelerate the deployment of CAVs by building a connected vehicle-infrastructure foundation and deploying equipped vehicles and object detection sensors, demonstrating interoperability between CV2X and DSRC. Furthermore, the smart intersections will generate sensor data sharing messages (SDSMs) that will address the penetration issue. Finally, we will develop an Implementation Guide which includes all the tools a local jurisdiction needs to start down the road of building a self-sustainable CAV eco-system.
Testing and evaluation is a critical step in the development and deployment of the ADS. Current testing procedures designed for human-driven vehicles only regulate automobile safety-related components, systems, and design features. For an ADS, it is essential to evaluate the “intelligence” of the vehicle, which indicates whether an ADS can operate safely and efficiently without human intervention. This study focuses on developing new science and technologies in systematical generation of testing scenarios and platforms for efficient and accurate assessment an ADS under different Operational Design Domains (ODDs) in terms of both safety and mobility.
The traffic control system is experiencing dramatic changes with the emergence of connected and automated vehicle (CAV) technologies. The future traffic control systems should be able to perceive the traffic environment, communicate with all road users in real-time, and make intelligent decisions to management multi-modal traffic. However, there will be a long transition period from the state-of-practice to the next generation traffic control system in a fully CAV environment. Toward this end, we study various research topics along this transition path including trajectory-based signal operations, spatiotemporal intersection management, infrastructure adaptation and “signal-free” intersections
SMART Signal (Systematic Monitoring of Arterial Road Traffic Signals) simultaneously collects event-based high-resolution traffic data from multiple intersections and generates real-time signal performance measures, including arterial travel time, number of stops, queue length, intersection delay, and level of service.
Traffic engineers can use this information to improve traffic flow on roads controlled by traffic lights—reducing congestion and saving drivers both time and fuel. SMART Signal could also give drivers a more accurate prediction of travel times by accounting for time spent waiting at traffic lights.
The system is now deployed at more than 100 intersections on major arterial corridors in Minnesota and Pasadena, California.
The I-35W Mississippi River bridge was an eight-lane, steel truss arch bridge that carried Interstate 35W across the Saint Anthony Falls of the Mississippi River in Minneapolis, Minnesota, United States. During the evening rush hour on August 1, 2007, it suddenly collapsed, killing 13 people and injuring 145. Within a few days of the collapse, the Minnesota Department of Transportation (Mn/DOT) planned a replacement bridge, the 10-lane I-35W Saint Anthony Falls Bridge. Construction was completed rapidly, and it opened on September 18, 2008. Although the capacity of the new bridge is larger, the daily traffic volume drops, comparing to the old bridge. A serious of traffic behavioral study on the Effects of the I-35W Bridge Collapse were conducted including modeling the day-to-day traffic evolution process after an unexpected network disruption and bounded rationality and irreversible network change.
