Signal Control And Energy-efficient Timetable Optimization For Tram Based On Passive Priority Strategy

In recent years,trams get fast development around the world because of their advantages of low investment,passenger comfort,energy saving and environment protection.Since most of the modern tram systems adopt semi-exclusive right-of-way,trams may experience delay due to red lights at signalized intersections,resulting in the increase of traction energy consumption and traveling time.Therefore,it is of practical significance and research value to reduce the traction energy consumption by avoid stops of trams at intersections as much as possible via signal control and schedule optimization.In this paper,we take modern trams which have semi-exclusive right-of-way as a research object.Firstly,the research on passive signal control has been launched and the signal timings at a series of intersections have been optimized.Secondly,based on the passive signal priority strategy,a bi-level optimization model on energy saving of tram timetable and tram control strategy has been established.The upper layer is to determine the optimal distribution of tram running time in each section for energy saving,while the lower layer is to optimize the tram energy-efficient driving strategy under a given scheme of running time in each section.On this basis,the stochastic optimization model of timetable is established considering the disturbance of dwell time which may cause stops of tram due to the red light at intersections,and the chaos genetic algorithm is designed to solve the problem.The main contents include:(1)Under the fixed green bandwidth of the tram,non-stop movements of trams at intersection are guaranteed,and a passive priority control model of tram is established whose objective is to maximize the green bandwidth of social vehicles.The model considers realistic constraints such as the consistency of social vehicle running speed in different sections,the effective bandwidth of social vehicles and the additional time of starting and stopping of trams.LINGO and VISSIM are used to solve and simulate the model respectively.The results show that the delay of the tram and social vehicle in this model is reduced by 13.14s/pcu and 2.22%compared with the TRAMBAND model respectively.Further analysis shows that the results of this model are superior to the TRAMBAND model in different headways,dwell times and vehicle volume at intersections.(2)On the basis of signal passive priority,the tram lines are divided into several sub-sections according to stations and intersections,and a bi-level optimization model jointly considering tram schedule and tram control strategy whose objective is to minimize the traction energy consumption of trams is established.The upper layer is to determine the optimal distribution of tram running time in each section for energy saving.Under a given scheme of running time in each section.,the lower layer is to minimize the traction energy consumption by searching different operating conditions of conversion points,using an energy-efficient control strategy of maximum traction-cruise-coasting-maximum braking.This model is to optimize the running time of each sections and avoid the stops of trams due to red lights at the intersection.The case study of a city in China shows that the model can reduce the traction energy consumption of 37.31%,compared with the existing method(determining the timetable according to the green center line)under the fixed total traveling time.Meanwhile,the actual total traveling time is reduced by 28.06%.(3)Changes in boarding and alighting of passengers will lead to changes in dwell time,resulting in influencing the effect of greenband.Therefore,in this paper,dwell time perturbation at stations is considered.A tram schedule and a bi-level stochastic optimization model are established with the objective of minimizing the weighted sum of expected traction energy and expected travel time.Chaos search of bi-level genetic algorithm is designed.The average number of stops of the tram at intersections with stochastic optimization model is 5.63%and 8.45%lower,compared with the coordinated operation optimization model irrespective of dwell time perturbation and the existing method whose timetable is determined by the center line of the green band,so that both traction energy consumption and travel time were reduced.