applied sciences  
A Multi-Agent Driving-Simulation Approach for Characterizing Hazardous Vehicle Interactions between Autonomous Vehicles and Manual Vehicles  
[PERSON]\({}^{\copyright}\), [PERSON], [PERSON],*, [PERSON] and [PERSON]  
Department of Smart City Engineering, Hanyang University Erica Campus, 55 Hanyangdaehak-ro, Sangnok-gu, Ansan 15588, Gyeonggi-do, Republic of Korea; [EMAIL_ADDRESS] Department of Road and Traffic Research, Korea Institute of Civil Engineering and Building Technology, (Daehwa-Dong) 283, Goyangdae-ro, Isanaseo-gu, Goyang 10223, Gyeonggi-do, Republic of Korea; [EMAIL_ADDRESS] Department of Transportation and Logistics Engineering, Hanyang University Erica Campus, 55 Hanyangdaehak-ro, Sangnok-gu, Ansan 15588, Gyeonggi-do, Republic of Korea Department of Highway & Transportation Research, Korea Institute of Civil Engineering and Building Technology, (Daehwa-Dong) 283, Goyangdae-ro, Isanaseo-gu, Goyang 10223, Gyeonggi-do, Republic of Korea; [EMAIL_ADDRESS] (J.P.); [EMAIL_ADDRESS] (D.Y.) Correspondence: [EMAIL_ADDRESS]; Tel.: +82-31-400-5158  
Footnote 14:  
car-following behavior between an AV and MV is of keen interest for evaluating the risk of rear-end crashes. The change in road alignments, including horizontal and vertical curves, is a significant factor affecting driving behavior [4; 5]. Vehicles traveling in a section where the road-alignment changes are required to adjust the acceleration and operate the steering wheel. In this case, the driver's improper decision making could lead to hazardous situations, leading to a greater crash potential. AVs driven by machines in support of sensor-based awareness of the surrounding environment will have significantly different driving behaviors from MVs driven by humans with various uncertainties. It is, therefore, important to understand the characteristics of a mixed car-following pair, which consists of an MV following an AV or an AV following an MV. An emerging question is 'What road conditions would make the mixed car-following situations hazardous?' This question motivates our study. The existing road conditions are devised to ensure the safety of the MV. However, vehicle interactions between AVs and MVs need to be evaluated to identify which geometric conditions are vulnerable in terms of mixed traffic safety. A hypothesis established in this study is that the different interactions observed for each driving pair of AVs and MVs would lead to different road conditions that are vulnerable to safety.  
This study proposes a methodology to evaluate the driving safety of mixed car-following situations between AVs and MVs on freeways, which is fundamental to fully exploiting the benefit of crash prevention using AVs. The proposed methodology can be applied to identify hazardous road-alignment conditions for mixed car-following pairs. A multi-agent driving-simulation (MADS) technique, which is able to synchronize the space and time domains on the road by connecting two driving simulators, is conducted to evaluate driving safety. MADS experiments allow for effectively observing the interactions that occur when the subject vehicle follows the preceding vehicle. This study defined a driving simulator as an agent. The SCANeRTM STUDIO program is used to simulate the road network and the maneuvering of the AV. Driving information for each vehicle is collected with driving experiments on AV pairs, mixed pairs, and MV pairs. A total of three safety indicators, including acceleration noise (AN), standard deviation of lane position (Std.LP), and average headways (Avg.HW), are used to identify the vehicle interaction of mixed car-following situations in terms of traffic safety. The evaluation results allow for identifying road-alignment conditions where mixed car-following pairs would experience relatively more hazardous situations.