Modeling Vehicle Speed Guidance at Signalized Intersections under IntelliDriverSM
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Most methods to forecast traffic flow arrivals in the adaptive control strategy assume that traffic flow speed is subject to uniform distribution.However,these methods have some disadvantages over efficiency and reliability.To deal with this,this paper uses real-time vehicle-to-vehicle and vehicle-to-road communications provided by IntellidriverSM to obtain minimum vehicle delay at intersections.Then,it proposes a vehicle speed guidance mechanism to model individual vehicles based on real-time signal state,queue length,vehicle location and acceleration.Using a simulation verification example at the intersection of Caoan Road and North Jiasong Road in Shanghai,this paper concludes that under heavy traffic flows,the model can efficiently reduce the average vehicle delay at intersections by 30%;it can decrease the average number of vehicle stops at intersections by 60%.Better results can be obtained for medium or low level of saturation.