AP
A.J. Pauwels
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Safety of Automated Driving in Mixed-Traffic Urban Areas
Considering Vulnerable Road Users and Network Efficiency
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.
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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.