A research of guidance signs adjustment based on naturalistic driving study data

Lei Li; Hao Li; Shiyin Li

doi:10.1117/12.3054832

20 December 2024 A research of guidance signs adjustment based on naturalistic driving study data

Lei Li, Hao Li, Shiyin Li

Author Affiliations +

Proceedings Volume 13421, Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024); 134211V (2024) https://doi.org/10.1117/12.3054832
Event: Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), 2024, Dalian, China

Abstract

This paper analyzed the naturalistic driving data of speed and eye movement from Xi'an to Yulin to explore the effectiveness of guidance signs at entrances and exits on expressway. Supporters of the natural driving that it is only unfamiliar with the road must to drive through this section of the road to complete their work due to official needs. The current analysis included 20 participants, all of them have work to travel between Xi'an and Yulin, aged among 30-40 who are more likely to using a high speed, and those who owned 3 years or less driving experience is 50%. Results show that when drivers enter or exit the ramp on expressway, the line of sight were focused on the front and the right side, therefore it was effective to set the guidance sign on the right and front side. Datas show that the suitable guidance signs ensuerance drivers to obtain road information accurately and in a timely manner, which is beneficial to drivers cut down frequently change lanes and reduce the risk of traffic. This study provides strong support for the effectiveness of guidance signs on expressway. Matlab 2020b is used to simulate and analyze the evolution model array constructed by driving speed, driving behavior and guidance signs.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lei Li, Hao Li, and Shiyin Li "A research of guidance signs adjustment based on naturalistic driving study data", Proc. SPIE 13421, Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), 134211V (20 December 2024); https://doi.org/10.1117/12.3054832

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