Arterial Velocity Planning based on Traffic Signal Information under Light Traffic Conditions

被引:0
|
作者
Mandava, Sindhura [1 ]
Boriboonsomsin, Kanok [2 ]
Barth, Matthew [1 ]
机构
[1] Univ Calif Riverside, Dept Elect Engn, Riverside, CA 92507 USA
[2] Univ Calif Riverside, Ctr Environm Res & Technol, Coll Engn, Riverside, CA 92507 USA
关键词
traffic signal; speed; algorithm; energy; emissions;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Vehicle fuel consumption and emissions are directly related to the acceleration/deceleration patterns and the idling period. In order to reduce emissions and improve fuel economy, sharp acceleration/deceleration and idling should be avoided as much as possible. Unlike on freeways, traffic on signalized corridors suffers from increased fuel consumption and emissions due to idling and acceleration/deceleration maneuvers at traffic signals. By taking advantage of the recent developments in communication technology between vehicles and roadside infrastructure, it is possible for vehicles to receive the signal phase and timing information well in advance of approaching a signalized intersection. Based on this traffic signal information, we have developed arterial velocity planning algorithms that give dynamic speed advice to the driver so that the probability of having a green light is maximized when approaching signalized intersections. The algorithms are aimed at minimizing the acceleration/deceleration rates while ensuring that the vehicle never exceeds the speed limit, and that it will pass through intersections without coming to a stop. Using a stochastic simulation technique, the algorithms are used to generate sample vehicle velocity profiles along a 10-intersection signalized corridor. The resulting vehicle fuel consumption and emissions from these velocity profiles are calculated using a modal emissions model, and then compared with those from a typical velocity profile of vehicles without velocity planning. The energy/emission savings for vehicles with velocity planning are found to be 12-14%.
引用
收藏
页码:160 / +
页数:2
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