Abstract: Traffic signs and markings are essential components of road infrastructure.Currently,the design of traffic signs and markings primarily meets the needs of human drivers,without considering the requirements of autonomous vehicles.This study proposes an evaluation framework based on human-machine mixed driving,used to assess the effectiveness of the physical characteristics of traffic signs and markings,and to analyze and compare the roles in driving tasks from the perspectives of human drivers and autonomous vehicles.This study selects accident-prone roads as the research objects.For human drivers,a subjective evaluation method is used to assess the physical characteristics of traffic signs and markings and the effectiveness of driving tasks.For autonomous driving,video recognition is used to evaluate the physical attributes of traffic signs and markings,and simulation methods are used to assess the impact of traffic sign and marking design on driving tasks.The results show that there are differences in the perception of traffic signs and markings between human drivers and autonomous vehicles.This finding emphasizes the need for future transportation infrastructure design to consider and understand different requirements.The optimization of traffic infrastructure should ensure that they can be accurately recognized and understood by autonomous vehicles.This study provides direction and guidance for the design and optimization of future TSM to meet the safety requirements and the needs of both human drivers and autonomous vehicles driving together.
Xuesong Wang*, Junyu Huo,Dingming Qin, Qian Liu. Evaluation of Traffic Signs and Markings Considering Human Driversand Automated Vehicles. Journal of Traffic and Transportation Engineering, 2024.