TRB Pubsindex
Text Size:

Title:

Empirical Identification and Quantification of Driver Anticipation Factor in Car-Following Behavior Modeling

Accession Number:

01476991

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

Abstract:

In car-following behavior modeling, the anticipation factor represents the situation that drivers change the speed based on their predicted traffic condition, rather than the current condition. While current models address the anticipation factor as a constant, it is actually a dynamic variable in reality. This paper presents a new car-following model that incorporates the anticipation factor as a variable. The data from a field experiment reveal that the anticipation factor is a function of the drivers’ choice of braking process and the application of the advanced driving assistance system. The observed anticipation factor values are compared with the theoretical boundary, which is obtained from a linear stability analysis for the new car-following model. The comparison results show that the observed values are in the stable region, which indicates the modeling effort is consistent with the field observation. The new car-following model, in conjunction with the observed anticipation factor, is utilized in several simulation experiments in order to identify the influence of the anticipation factor on traffic flow. It is found that when the anticipation factor takes into effect on more drivers, it is easier for the traffic flow to recover to stability from local disturbances. The new car-following model is helpful for microscopic traffic simulation models and applications of Intelligent Transportation System (ITS).

Supplemental Notes:

This paper was sponsored by TRB committee AND20 User Information Systems.

Monograph Accession #:

01470560

Report/Paper Numbers:

13-2360

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Hao, Liu
Wei, Heng
Yao, Zhuo
Ai, Qingyi
Li, Bin

Pagination:

18p

Publication Date:

2013

Conference:

Transportation Research Board 92nd Annual Meeting

Location: Washington DC, United States
Date: 2013-1-13 to 2013-1-17
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Subject Areas:

Data and Information Technology; Highways; Operations and Traffic Management; I70: Traffic and Transport; I71: Traffic Theory

Source Data:

Transportation Research Board Annual Meeting 2013 Paper #13-2360

Files:

TRIS, TRB, ATRI

Created Date:

Feb 5 2013 12:31PM