Collaborative Trajectories Optimization for Tram and Connected Vehicles at Signalized Intersection - Weixi Lv; Jianwu Dang; Zhenhai Zhang; Yongzhi Min; Jing Zuo (Applied Sciences, 2023)
In order to alleviate the conflict at intersections in a networked environment between trams in a semi-exclusive right-of-way mode and social vehicles, the running characteristics of these trams and vehicles and their coupling characteristics with the intersection signal are analyzed. The positive and negative effects of the special priority signal on the intersection are considered, and a guidance optimization model that combines urban rails and roads is constructed. With the aim of creating an unplanned delay adjustment scenario for trams, an online collaborative optimization algorithm is proposed, which takes the energy consumption, passenger travel time and comfort of both trams and connected vehicles as optimization objectives in order to realize integrated adjustment of the running trajectories and signal timing, and the population is evolved by using an adaptive elitist genetic algorithm. The study is based on the actual traffic information and timing scheme of an intersection on the T1 line of the Sanya Tram. By comparing with conventional trajectories, the optimized trajectories reduce the total transit time by about 17.1%, the total energy consumption by about 34.7% and the passenger discomfort degree by about 27.8%. The contradiction of the right-of-way distribution at the intersection is alleviated, effectively safeguarding the interests of different users and enterprises. The experimental results show that the model has excellent applicability for different proportions of passenger numbers.