Abstract
In this paper, we state a combining programming approach to optimize traffic signal control problem. The objective of the model is to minimize the total queue length with weight factors at the end of each phase. Then, modified Twin Gaussian Process (MTGP) is employed to predict the arrival rates for the traffic signal control problem. For achieving automatic control of the traffic signal, an intelligent control method of the traffic signal is proposed in view of the combining method, that is to say, the combining method of MTGP and LP, called MTGPLP, is embraced in the intelligent control system. Furthermore, some numerical experiments are proposed to test the validity of the model and the MTGPLP approach. In particular, the results of numerical experiments show that the model is effective with different arrival rates, departure rates, and weight factors and the combining method is successful.
Highlights
Research Article MTGPLP Approach for Traffic Signal Intelligent ControlReceived 7 May 2020; Revised 14 July 2020; Accepted 17 July 2020; Published 17 August 2020
E characteristic of the fixed systems is to build the signal scheduling based on the periodic prearranged time
Mathematical Problems in Engineering coordinated adaptive traffic systems, which have been broadly utilized to compute the division time, offsets, and periodic time being in line with present traffic light cycle length prerequisite, was proposed by Lowrie [8] firstly. e split cycle offset optimization technique (SCOOT) was utilized to deal with the traffic signal control problems by Bretherton and Browen [9], Bretherton [10], and Sharma and Gidde [11]. e likelihood methods that were stated by Wey [12] and Clempner and Poznyak [13] were employed to cope with the traffic light planning problems
Summary
Received 7 May 2020; Revised 14 July 2020; Accepted 17 July 2020; Published 17 August 2020. We state a combining programming approach to optimize traffic signal control problem. Some intelligence approaches for coping with the multiple objective systems for traffic light control problems were introduced by Garcia-Nieto et al [25] and Li et al [26]. Friesz et al [28] and Liu and Smith [29] stated approaches to cope with traffic signal control problems in which the models contained 0-1 variables for controlling the traffic light. En, combining equations (1) and (2), the queue length in entrance lane i at the end of phase l during cycle k + 1 can be reformulated as follows: xi,l,k+1 maxmaxxi,l,k−1, 0 + λi,l,k+1yl,k+1 + dy.
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