Abstract
In this paper, we propose a consensus algorithm with input constraints for traffic light signals in transit signal priority (TSP). TSP ensures control strategy of traffic light signals can be adjusted and applied according to the real-time traffic status, and provides priority for buses. We give the convergence conditions of the consensus algorithms with and without input constraints in TSP respectively and analyze the convergence performance of them by using matrix theory and graph theory, and PTV-VISSIM is used to simulate the traffic accident probability of three cases at intersections. Simulation results are presented that a consensus is asymptotically reached for all weights of priority; the algorithm with input constraints is more suitable for TSP than the algorithm without input constraints, and the traffic accident rate is reduced.
Highlights
Transit signal priority (TSP) improves the operational efficiency of transportation and reduces overall delay at an intersection on a per-person basis
Simulation results show that, compared with the former two cases, the proposed algorithm with input constraints in TSP reduces the number of traffic accidents in the same grid, and plays an effective role in TSP
We focus on the TSP strategy consensus problem of the same grid in road networks
Summary
Transit signal priority (TSP) improves the operational efficiency of transportation and reduces overall delay at an intersection on a per-person basis. The strategies of TSP include passive priority strategy, active priority strategy and real-time strategy [3,4,5,6]. Passive priority [7,8] is a strategy of signal timing at an intersection based on historical data without the vehicle detector. Through the GPS(Global Positioning System)and AVL(Automatic Vehicle Location) and other advanced information detection devices to estimate the status of the road network and vehicles, real-time strategy [13,14] provides priority signal for buses by optimizing, adjusting the signal timing of the intersection or trunk according to the real-time traffic information.
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