Safety of Automated Driving in Mixed-Traffic Urban Areas
Considering Vulnerable Road Users and Network Efficiency
A.J. Pauwels (TU Delft - Mechanical Engineering)
F. Schulte – Mentor (TU Delft - Transport Engineering and Logistics)
Nadia Pourmohammad-Zia – Mentor (TU Delft - Transport Engineering and Logistics)
J.K. Moore – Graduation committee member (TU Delft - Biomechatronics & Human-Machine Control)
Rudy R. Negenborn – Graduation committee member (TU Delft - Transport Engineering and Logistics)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
The establishment of areas for safe automated driving in mixed-traffic settings is one major barrier in the development and adoption of Autonomous Vehicles (AVs). This work investigates safety in the interactions between AVs, human-driven vehicles, and vulnerable road users such as cyclists and pedestrians in a simulated urban environment in the Dutch city of Rotterdam. Proposing new junction and pedestrian models, virtual AVs with an occlusion aware driving system are deployed to deliver cargo autonomously. Assessing the impact of various measures, including V2V, V2I, V2X communications, infrastructure modifications, and driving behavior, we show that traffic safety and network efficiency can be achieved in a living lab setting for the considered case. Our findings further suggest that V2X gets implemented, new buildings are not placed close to intersections, and the speed limit of non-arterial roads is lowered.