A Fuzzy Full Velocity Difference Model Based on Driver’s Perception Characteristics

The perception characteristics of drivers greatly vary with the status of traffic flow. To designate the vehicle trajectory more accurately, a driver’s perception headway coefficient is introduced, and a fuzzy full velocity difference (FVD) model is proposed in this paper. Consistent with the contro...

Full description

Saved in:
Bibliographic Details
Published in:Mathematical problems in engineering 2022-09, Vol.2022, p.1-10
Main Authors: An, Shu-Ke, Xu, Liang-Jie, Liu, Gang, Shi, Ze Yu
Format: Article
Language:English
Subjects:
Car following
Control methods
Control theory
Flow stability
Fuzzy control
Fuzzy sets
Genetic algorithms
Headways
Mathematical problems
Perception
Traffic congestion
Traffic flow
Vehicles
Velocity
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The perception characteristics of drivers greatly vary with the status of traffic flow. To designate the vehicle trajectory more accurately, a driver’s perception headway coefficient is introduced, and a fuzzy full velocity difference (FVD) model is proposed in this paper. Consistent with the control theory, the stability conditions of the improved model are derived. Through the fuzzy control method, the input and output items of the control rule are constructed, respectively. The genetic algorithm is operated to calibrate the model parameters of timid and aggressive drivers. Eventually, the effectiveness of the model is verified by simulations. The research results show that, with the decrease of driver’s perception headway coefficient, the stability range of the traffic flow gradually increases, which is beneficial. Additionally, the average root means square percentage errors (RMSPE) values of the full velocity difference (FVD) model, the intelligent driver model (IDM), and the proposed model are, respectively, 0.312, 0.308, and 0.213. Compared with IDM and FVD models, the proposed model can accurately describe the local velocity variations and determine the car-following behavior of the human driving vehicle better.
ISSN:1024-123X
1563-5147
DOI:10.1155/2022/7626095