Incorporating human factors into LCM using fuzzy TCI model

作     者：Li, Linbo Li, Yang Ni, Daiheng 

作者机构：Tongji Univ Key Lab Rd & Traff Engn Minist Educ 4800 Caoan Rd Shanghai 201804 Peoples R China Univ Massachusetts Civil & Environm Engn Amherst MA 01003 USA 

出 版 物：《TRANSPORTMETRICA B-TRANSPORT DYNAMICS》 (运输研究B：传输动力学)

年 卷 期：2021年第9卷第1期

页      面：198-218页

核心收录：

学科分类：08[工学] 0823[工学-交通运输工程] 

基　　金：National Key Research and Development Program of China [2018YFE0102800] 

主　　题：Car-following model human factors task capability interface model fuzzy logic algorithm 

摘      要：Incorporation of Human Factors (HF) into the mathematical car-following (CF) models has always been the research hotspot. Ignorance of such inclusion would inevitably hinder us from acquiring a comprehensive understanding of traffic flow phenomena. This paper proposed a novel CF model in order to bridge three existing research gaps: the demand for more inclusion of HF into the Longitudinal Control Model (LCM);the requirement for a more desirable underlying CF model for the Task Capability Interface (TCI) model;the ignorance of the fuzziness of human brains when modeling Task Difficulty (TD). Specifically, in order to imitate driver s natural or subjective uncertainty and ambiguity of his TD, the fuzzy logic approach is introduced, and the TD is then incorporated into the LCM. Thereafter, both numerical simulation and field-data validation have been performed. Results indicate that our proposed model is more capable of accommodating HF and exhibits better performance than its predecessor.