Assessing the Effectiveness of In-Vehicle Highway Back-of-Queue Alerting System

This paper proposes an in-vehicle back-of-queue alerting system that is able to issue alerting messages to drivers on highways approaching traffic queues. A prototype system was implemented to deliver the in-vehicle alerting messages to drivers via an Android-based smartphone app. To assess its effectiveness, a set of test scenarios were designed and implemented on a state-of-the-art driving simulator. Subjects were recruited and their testing data was collected under two driver states (normal and distracted) and three alert types (no alerts, roadside alerts, and in-vehicle auditory alerts). The effectiveness was evaluated using three parameters of interest: 1) the minimum Time-to-Collision (mTTC), 2) the maximum deceleration, and 3) the maximum lateral acceleration. Statistical models were utilized to examine the usefulness and benefits of each alerting type. The results show that the in-vehicle auditory alert is the most effective way for delivering alerting messages to drivers. More specifically, it significantly increases the mTTC (30% longer than that of 'no warning') and decreases the maximum lateral acceleration (60% less than that of 'no warning'), which provides drivers with more reaction time and improves driving stability of their vehicles. The effects of driver distraction significantly decrease the efficiency of roadside traffic sign alert. More specifically, when the driver is distracted, the roadside traffic sign alert performs significantly worse in terms of mTTC compared with that of normal driving. This highlights the importance of the in-vehicle auditory alert when the driver is distracted.

• Record URL:
  https://annualmeeting.mytrb.org/OnlineProgram/Details/15765
• Supplemental Notes:
  • This paper was sponsored by TRB committee ACH40 Standing Committee on Human Factors of Infrastructure Design and Operations.
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Shen, Dan
  • Zhang, Zhengming
  • Ruan, Keyu
  • Tian, Renran
  • Li, Lingxi
  • Li, Feng
  • Chen, Yaobin
  • Sturdevant, Jim
  • Cox, Ed
• Conference:
  • Transportation Research Board 100th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2021-1-5 to 2021-1-29
• Date: 2021

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References; Tables;
• Pagination: 18p

Subject/Index Terms

• TRT Terms: Audible warning devices in vehicles; Crash avoidance systems; Distraction; Distress alerting systems; Driver support systems; Mobile applications; Reaction time; Smartphones
• Subject Areas: Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

• Accession Number: 01764182
• Record Type: Publication
• Report/Paper Numbers: TRBAM-21-03879
• Files: TRIS, TRB, ATRI
• Created Date: Feb 4 2021 11:00AM