In this paper, we study a theoretical traffic control problem with the consideration of vehicle-to-infrastructure communications. During the control process, vehicles approaching the intersection inform the control center their data, then the control center authorizes each vehicle a precise time to cross intersection by analyzing the received information. Our objective is to minimize the time of evacuating all autonomous vehicles at intersection and the key point is to decide an optimal vehicle passing order. An dynamic programming algorithm is proposed to solve this problem.

This paper addresses a vehicle sequencing problem for adjacent intersections under the framework of Autonomous Intersection Management (AIM). In the context of AIM, autonomous vehicles are considered to be independent individuals and the traffic control aims at deciding on an efficient vehicle passing sequence. Since there are considerable vehicle passing combinations, how to find an efficient vehicle passing sequence in a short time becomes a big challenge, especially for more than one intersection. In this paper, we present a technique for combining certain vehicles into some basic groups with reference to some properties discussed in our earlier works. A genetic algorithm based on these basic groups is designed to find an optimal or a near-optimal vehicle passing sequence for each intersection. Computational experiments verify that the proposed genetic algorithms can response quickly for several intersections. Simulations with continuous vehicles are carried out with application of the proposed algorithm or existing traffic control methods. The results show that the traffic condition can be significantly improved by our algorithm.

Purpose -This paper deals with real-time control of urban traffic with an emphasis on public transportation systems. The main objective is the regulation of traffic after the occurrence of disturbances. In a few words, the problem is to find a feasible schedule for some vehicles of some lines subject to certain constraints in order to design a decision support system (DSS) that detects, analyses and resolves disturbances. Design/methodology/approach -This work is achieved in cooperation with a public transport company called SEMURVAL. It consists of developing a DSS for the future transportation network of Valenciennes (city in the north of France). As a consequence, regulators of traffic have to treat a new lot of information and it becomes necessary to assist them in order to keep up with demands and to come up to passengers' expectations and hopes. Findings -From the case study finds that the solution proposed assures that arrival times of vehicles are more regular. Originality/value -The solution proposed presents a good combination of scheduling decisions permitting the good regulation of traffic.

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