Bus Drivers’ Behavioral Intention to Comply with Real-Time Control Instructions: An Empirical Study from China

Author:

Chen Weiya12ORCID,Chen Ying12,Wang Yufen12,Fang Xiaoping12ORCID

Affiliation:

1. School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China

2. Rail Data Research and Application Key Laboratory of Hunan Province, Changsha 410075, China

Abstract

Developing intelligent bus control systems is crucial for fostering the sustainability of urban transportation. Control instructions are produced in real time by the bus control system; these are important technical commands to stabilize the order in which buses operate and improve service reliability. Understanding the behavioral intention of bus drivers to comply with these instructions will help improve the effectiveness of intelligent bus control system implementation. We have developed a psychological model that incorporates decomposed variables of the theory of planned behavior (TPB) and other influencing variables to explain the micromechanisms that determine bus drivers’ behavioral intention to comply with real-time control instructions during both peak and off-peak-hour scenarios. A total of 258 responses were obtained and verified for analysis. The results showed that the influential factors in the peak- and off-peak-hour scenarios were not identical. Female drivers had greater off-peak-hour behavior intention to comply than male drivers, and there were significant differences in peak-hour behavior intention among drivers of different ages. In both peak and off-peak-hour scenarios, perceived benefit positively and perceived risk negatively affected behavioral intention. Perceived controllability positively affected behavioral intention only during peak hours. Self-efficacy only negatively affected behavioral intention during off-peak hours. Three antecedent variables (i.e., trust, mental workload, and line infrastructure support) influenced drivers’ behavioral intentions indirectly via the decomposed variables of TPB. These results provide profound insights for the improvement and implementation of real-time control technology for bus services, thereby facilitating the development of smart and sustainable urban public transport systems.

Funder

Science and Technology Program of the Hunan Provincial Department of Transportation

Publisher

MDPI AG

Reference127 articles.

1. A predictive-control framework to address bus bunching;Andres;Transp. Res. Part B Methodol.,2017

2. Bunching and headway adherence approach to public transport with GPS;Byon;Int. J. Civ. Eng.,2018

3. Dynamic holding control to avoid bus bunching: A multi-agent deep reinforcement learning framework;Wang;Transp. Res. Part C Emerg. Technol.,2020

4. Reducing bunching with bus-to-bus cooperation;Daganzo;Transp. Res. Part B Methodol.,2011

5. Comparison of dynamic control strategies for transit operations;Giesen;Transp. Res. Part C Emerg. Technol.,2013

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3