Issue Date: 2016-05-17
Overview: Connected vehicles have the potential to significantly improve the safety and mobility of vehicles in our transportation network. Vehicle-to-vehicle communications are the foundation of connected vehicle safety applications. Vehicle-to-infrastructure communications provide the foundation for infrastructure based safety and mobility applications. One of the areas that can be significantly improved using vehicle to infrastructure communications is the operation of traffic signals. In a connected vehicle environment, the traffic signals can be aware of each connected vehicle that is approaching an intersection – the signal can know the mode of the vehicle, the approach lane, and the approach speed of the vehicle. Intelligent signal control algorithms can use this information to determine the best allocation of green time to achieve an operating objective – such as minimizing delay or ensuring platoon progression along an arterial. Special modes of vehicles – including emergency vehicles, transit, and freight trucks can request traffic signal priority to reduce their delay so that the system can achieve a modal based operating objective - such as reducing transit delay or providing smooth flow for freight trucks. Pedestrian and bicycles can be included in the intelligence through the use of nomadic devices, such as smartphones.
The Multi Modal Intelligent Traffic Signal System (MMITSS) has been developed through a Transportation Pooled Fund project to realize the vision of an intelligent traffic signal system in a connected vehicle environment. MMITSS was designed to consider new information available from connected vehicles, the concept of an operating policy or modal based objective, and to provide a priority based traffic control framework.
MMITSS has been implemented and field tested in the Arizona Connected Vehicle Test Bed and the California Connected Vehicle Test Bed. This seminar will present the intelligent traffic signal control principles and multimodal priority strategies used in MMITSS and results from each of the test sites.
Larry Head, University of Arizona
Kun Zhou, California PATH Program, University of California Berkeley
Wei-Bin Zhang, California PATH Program, University of California Berkeley
Event Type: Webinar
Content Type: Presentation