Abstract
Currently, most traffic control methods at intersections rely on the control of signal lights. However, most signal lights operate in the traditional fixed timing mode, which cannot adjust the timing based on the time-varying traffic flow. To solve the problem, this paper constructs a signal timing control model to optimize road capacity, delay time and the number of stops at the intersections, under the following constraints: cycle time, effective green light time and the maximum number of vehicles in each direction of intersection. To solve the model, the standard dragonfly algorithm (DA) was improved by a hybrid mutation operator, which ensures the diversity of solution set. The proposed model and algorithm were compared with the Webster model through simulations in an actual scene and on a virtual platform. The comparison fully proves the advantages of our model and algorithm.
Highlights
In recent years, traffic overload has become a thorny problem in urban road system
Mou: Intersection Traffic Control Based on Multi-objective Optimization first optimization model for signal timing at intersections
Under the constraints of phase saturation, effective green light time and total signal cycle time, Lin et al [22] proposed a nonlinear function model of signal timing for a single intersection in urban area, in an attempt to minimize the mean delay time and the number of stops; the proposed model was separately solved by the traditional genetic algorithm (GA) and GA-based simulated annealing (SA) algorithm; the results show that the two algorithms can effectively shorten the vehicle delay
Summary
Traffic overload has become a thorny problem in urban road system. The problem can be partly attributed to the increase of motor vehicles and the lag of infrastructure. Most of the efficient signal control models are improved versions of classical methods, such as Transport Road Research Laboratory (TRRL) method, the Highway Capacity Manual (HCM) method and the Australian Road Research Board (ARRB) method [3]–[5]. These methods provide a good theoretical basis for analyzing the relationship between signal timing and the indices of intersection performance. Compared with the existing research, this paper proposed a multi-objective programming dynamic timing model based on accurate traffic flow prediction, and intelligent algorithm was used to solve it. The proposed algorithm in this paper can well realize the collision avoidance between vehicles at signal less intersections
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