|Table of Contents|

Analysis of vehicle following behavior and construction of model under mixed traffic flow in rainfall environment(PDF)

长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2024年3期
Page:
138-148
Research Field:
交通工程
Publishing date:

Info

Title:
Analysis of vehicle following behavior and construction of model under mixed traffic flow in rainfall environment
Author(s):
XING Guo-zheng1;  GAO Chao1; 2
(1. School of Highway, Chang'an University, Xi'an 710064, Shaanxi, China; 2. Key Laboratory of lntelligent Construction and Maintenance of CAAC, Xi'an 710064, Shaanxi, China)
Keywords:
traffic engineering;  highway;  car-following model;  optimal velocity model;  rainfall environment
PACS:
U491.112
DOI:
10.19721/j.cnki.1671-8879.2024.03.012
Abstract:
Aiming at the problem that lacks accurate car-following models in rainfall environments, a car-following model under various rainfall intensities was proposed. Firstly, the date of car-following and rainfall intensity were extracted from the cloud control platform database using Python program. The changing characteristics of car-following speed, acceleration, and headway distance, as well as their inter-relationships, were investigated under various rainfall intensities and traffic flow. The difference ofcar-following behavior between rainfall and normal weather was further explored. Subsequently, a method based on optimal velocity model was proposed to determine the safe distance and driver's desired speed under various rainfall intensities by considering the impacts of rainfall on the relative distance and relative speed between the leading and following vehicles. Then car-following model was created for various rainfall intensities, and the parameters of the new model were calibrated using genetic algorithms. Finally, the calibrated results were evaluated using cross-validation methods, and the error between the model output and actual values was calculated. The results show that speed and acceleration decrease to varying extents with increasing rainfall intensity. However, the variations in acceleration are more significant than those in speed, indicating a more accurate sensitivity of acceleration to rainfall. The headway distance is influenced by the leading vehicle's speed, which in turn controls the following vehicle's speed. Both the rainfall intensity and the speed range of the leading vehicle affect the headway distance, and the following speed of the following vehicle increases with the increase of headway. Model validation results indicate that the root mean square percentage error between the model outputs and collected values is no more than 0.5, demonstrating that the car-following behavior is accurately described by new car-following model considering rainfall intensity on highway.5 tabs, 6 figs, 26 refs.

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Last Update: 2024-05-01