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One of the main challenges in developing autonomous transport systems basedon connected and automated vehicles is the comprehension and understanding ofthe environment around each vehicle. In many situations, the understanding islimited to the information gathered by the sensors mounted on the ego-vehicle,and it might be severely affected by occlusion caused by other vehicles orfixed obstacles along the road. Situational awareness is the ability toperceive and comprehend a traffic situation and to predict the intent ofvehicles and road users in the surrounding of the ego-vehicle. The mainobjective of this paper is to propose a framework for how to automaticallyincrease the situational awareness for an automatic bus in a realistic scenariowhen a pedestrian behind a parked truck might decide to walk across the road.Depending on the ego-vehicle's ability to fuse information from sensors inother vehicles or in the infrastructure, shared situational awareness isdeveloped using a set-based estimation technique that provides robustguarantees for the location of the pedestrian. A two-level information fusionarchitecture is adopted, where sensor measurements are fused locally, and thenthe corresponding estimates are shared between vehicles and units in theinfrastructure. Thanks to the provided safety guarantees, it is possible toappropriately adjust the ego-vehicle speed to maintain a proper safety margin.It is also argued that the framework is suitable for handling sensor failuresand false detections in a systematic way. Three scenarios of growinginformation complexity are considered throughout the study. Simulations showhow the increased situational awareness allows the ego-vehicle to maintain areasonable speed without sacrificing safety.

Set-Membership Estimation in Shared Situational Awareness for Automated Vehicles in Occluded Scenarios