Impacts of information quantity and display formats on driving behaviors in a connected vehicle environment

Wenjing Zhao; Siyuan Gong; Dezong Zhao; Fenglin Liu; N N Sze; Mohammed Quddus; Helai Huang; Xiangmo Zhao

doi:10.1016/j.aap.2024.107621

Impacts of information quantity and display formats on driving behaviors in a connected vehicle environment

Accid Anal Prev. 2024 May 9:203:107621. doi: 10.1016/j.aap.2024.107621. Online ahead of print.

Authors

Wenjing Zhao¹, Siyuan Gong², Dezong Zhao³, Fenglin Liu⁴, N N Sze⁵, Mohammed Quddus⁶, Helai Huang⁷, Xiangmo Zhao⁴

Affiliations

¹ School of Information Engineering, Chang'an University, Xi'an 710064, China; Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, China.
² School of Information Engineering, Chang'an University, Xi'an 710064, China. Electronic address: sgong@chd.edu.cn.
³ James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK.
⁴ School of Information Engineering, Chang'an University, Xi'an 710064, China.
⁵ Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, China.
⁶ Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK.
⁷ School of Traffic and Transportation Engineering, Central South University, Changsha 410000, China.

PMID: 38729056
DOI: 10.1016/j.aap.2024.107621

Abstract

The emerging connected vehicle (CV) technologies facilitate the development of integrated advanced driver assistance systems (ADASs), with which various functions are coordinated in a comprehensive framework. However, challenges arise in enabling drivers to perceive important information with minimal distractions when multiple messages are simultaneously provided by integrated ADASs. To this end, this study introduces three types of human-machine interfaces (HMIs) for an integrated ADAS: 1) three messages using a visual display only, 2) four messages using a visual display only, and 3) three messages using visual plus auditory displays. Meanwhile, the differences in driving performance across three HMI types are examined to investigate the impacts of information quantity and display formats on driving behaviors. Additionally, variations in drivers' responses to the three HMI types are examined. Driving behaviors of 51 drivers with respect to three HMI types are investigated in eight field testing scenarios. These scenarios include warnings for rear-end collision, lateral collision, forward collision, lane-change, and curve speed, as well as notifications for emergency events downstream, the specified speed limit, and car-following behaviors. Results indicate that, compared to a visual display only, presenting three messages through visual and auditory displays enhances driving performance in four typical scenarios. Compared to the presentation of three messages, a visual display offering four messages improves driving performance in rear-end collision warning scenarios but diminishes the performance in lane-change scenarios. Additionally, the relationship between information quantity and display formats shown on HMIs and driving performance can be moderated by drivers' gender, occupation, driving experience, annual driving distance, and safety attitudes. Findings are indicative to designers in automotive industries in developing HMIs for future CVs.

Keywords: Advanced driver assistance systems; Connected vehicles; Driving performance; Field tests; Human-machine interfaces.