Comparison of safety and kinematic patterns of automated vehicles turning left in interaction with oncoming manually driven vehicles

• Published in: Transactions on transport sciences 2022-03, Vol.12 (3), p.55-66
• Main Authors: Junghans, Marek, Krauns, Florian, Sonka, Adrian, Böhm, Michael, Dotzauer, Mandy
• Format: Article
• Language: English
• Subjects: automated driving; conditionally tolerable left turn, trajectory data analysis; road user behaviour; traffic safety
• ISSN: 1802-9876; 1802-9876
• DOI: 10.5507/tots.2021.003

Highly and fully automated driving has been under development for the past two decades in order to increase comfort, efficiency, and traffic safety. Particularly in the latter domain, experts agree on automated driving, especially in case of automated vehicles (AV) with SAE level 4 or higher, having the most promising effects. Automated driving is expected to decrease the number of seriously injured or even killed road users to zero (Vision Zero). However, automated driving is still in an early stage of development and many AV tend to drive very carefully to avoid crashes. So, the goal is to make driving more efficient while maintaining the highest level of safety. In the project "Digitaler Knoten 4.0" cooperative automated driving was assessed regarding efficiency and safety aspects. One of the use cases investigated was turning left with oncoming traffic at an urban intersection as this situation represents one of the most complex situations in urban areas yielding to crashes with-in many cases-serious consequences for the involved road users. At the Application Platform Intelligent Mobility (AIM) Research Intersection in Braunschweig, Germany, an SAE level 3 AV was turning left interacting with oncoming manually driven vehicles (MV). The performance of the AV was compared to MV executing the same manoeuvre. The recorded video-based trajectories of the respective AV as well as MV were analysed regarding the influence of situational factors (e.g. position of the vehicle in the queue and gap acceptance) and kinematic factors (e.g. speed and acceleration) on traffic safety. The similarities and differences between this specific AV and MV were identified yielding insight for further developing algorithms for more efficient driving while maintaining the same traffic safety level. For instance, it appears that the AV shows a very conservative left turning behaviour leading to very safe PET distributions in comparison to left turning MV.