Auditory warning of speeding behaviour is considered to be one of the most effective methods developed to reduce the accidents involving commercial passenger vehicles. Facing a complex, mixed traffic condition and a lot of risky driving behaviours in China, commercial passenger vehicles need an effective speeding warning system to reduce the high accident rate. Although many automobile manufacturers have installed the speeding warning systems on their vehicles, the styles of these auditory speeding warning systems are different, and few studies has been found to investigate the effectiveness of the auditory speeding warning systems for commercial passenger vehicles. Therefore this study is intent to fill such a gap to evaluate the effectiveness of three different sound-based speeding warning styles. In this study, thirty drivers qualified for driving the commercial passenger vehicles are recruited and then asked to drive for four 80-km field trips on an expressway in Wuhan, China. Driving behaviour is logged by a monitoring system and is monitored by two observers during these trips. Study results showed that ‘beep warning’ is most effective and ‘break-sound warning’ is the least. Basically, the results of this study could provide a good reference for development of future voice-based speed warning systems in China.
Evaluation of the effectiveness of auditory speeding warnings for commercial passenger vehicles –a field study in Wuhan, China
IET Intelligent Transport Systems ; 9 , 4 ; 467-476
2015-05-01
10 pages
Article (Journal)
Electronic Resource
English
automobile manufacturers , Wuhan , future voice-based speed warning systems , risky driving behaviours , commercial passenger vehicles , China , auditory speeding warning systems , sound-based speeding warning styles , alarm systems , speech-based user interfaces , break-sound warning , human computer interaction , auditory speeding warning effectiveness evaluation , behavioural sciences computing , speeding behaviour , high accident rate reduction , traffic engineering computing , speech processing , mixed traffic condition , beep warning
Metadata by IET is licensed under CC BY 3.0
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