Effects of the Amount of Information from Navigation Voice Guidance on Driving Performance

Liping Yang, Xiaohua Zhao, Yang Bian (), Mengmeng Zhang and Yajuan Guo
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Liping Yang: School of Transportation and Logistics Engineering, Shandong Jiaotong University, 5001 Haitang Road, Changqing District, Jinan 250357, China
Xiaohua Zhao: Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China
Yang Bian: Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China
Mengmeng Zhang: School of Transportation and Logistics Engineering, Shandong Jiaotong University, 5001 Haitang Road, Changqing District, Jinan 250357, China
Yajuan Guo: School of Transportation and Logistics Engineering, Shandong Jiaotong University, 5001 Haitang Road, Changqing District, Jinan 250357, China

Sustainability, 2024, vol. 16, issue 14, 1-18

Abstract: Nowadays, navigation systems are widely used in public travel because they can instantly offer GPS-based route directions. Following the navigation prompt messages while driving is considered a secondary driving task, while vehicle control is regarded as a primary driving task. Navigation prompt messages with more information can deliver more cues to drivers, but they require a higher cognitive demand and vice versa. To systematically explore the effects of the amount of information from navigation voice prompts and further quantify the utility of voice prompts, four types of prompt messages with increasing amounts of information, denoted as a Single Message, Double Message, Triple Message, and Quadruple Message, were designed. A driving simulation experiment was conducted to obtain driving behavior data under different prompt messages. The one-way analysis of variance (ANOVA) and Kruskal–Wallis (KW) test were used to examine the differences in driving performance under the guidance of different prompt messages from multiple perspectives. Then, eight indicators were selected based on the functions of the navigation system and the driver’s response, and the grey near-optimal method was used to determine the utility of the four types of prompt messages. This study found that the four types of navigation prompt messages all began to take effect at about 200 m upstream of the stop bar. The differences between the four types of prompt messages were more significant in the zone from 100 m upstream and ended at 100 m downstream of the stop bar of the intersection. Drivers using Single and Double Messages exhibited more powerful deceleration than those using Triple and Quadruple Messages. The utility values of the four types of prompt messages increased with the increase in the amount of information. This study provides theoretical support for optimizing navigation information and lays a foundation for establishing navigation broadcast guidelines.

Keywords: navigation system; the amount of information from navigation voice; driving behavior and performance; grey near-optimal method; driving simulation technology (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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