Signal Parameters Estimation and Optimization Using Mobile Navigation Data

Luxi Dong,Jiyuan Tan,Meijie Jia,Xiaoming Liu,Xiangda Wei

doi:10.1155/2020/8898938

Abstract

In the management and evaluation of traffic network, signal parameters are important for monitoring and evaluating the operation state and the traffic capacity of intersection. However, a wide range of real-time signal timing schemes lacks a clear and effective method. In this paper, we propose the signal parameter calculation method based on mobile navigation data. Then, the possibility of crossing intersection passing time of the stop line is studied. The time differences between passing times of different cycles are distributed periodically that several peaks appear cycle by cycle. The relationship between sampling rate and relative error is discussed. Combined with the distribution peak normality test, the appropriate distribution peak is selected through the actual case. The cycle lengths and effective red time parameters are calculated and compared with the known signal parameters. The result demonstrates the proposed method has high accuracy and provides data support for the research of the traffic management.

Highlights

We propose the signal parameter calculation method based on mobile navigation data. en, the possibility of crossing intersection passing time of the stop line is studied. e time differences between passing times of different cycles are distributed periodically that several peaks appear cycle by cycle. e relationship between sampling rate and relative
T Why do we choose mobile navigation data to estimate the signal timing? First of all, the timing parameters of most intersections cannot be obtained directly, which need to be acquired by the system
According to continuous time series of traffic flow for signal timing estimation in Ban’s research, it needs to observe the effective trajectory of continuous cycles

Summary

Introduction

T Why do we choose mobile navigation data to estimate the signal timing? First of all, the timing parameters of most intersections cannot be obtained directly, which need to be acquired by the system. E advantages of high precision and coverage method of the start and end of a period and the effective green and red time is estimated based on the delayed model [3]. According to continuous time series of traffic flow for signal timing estimation in Ban’s research, it needs to observe the effective trajectory of continuous cycles. Hao et al [2] pro- clustering algorithm was used to further separate the traffic posed a method to estimate the timing of the signal based on flow time series. Axer et al [16] studied the periodicity of the vehicle trajectory in the fixed signal timing and estimated the cycle start time by calculating.

Data Description

D Figure 2

Conclusion