An Autonomous Driving Model Integrated with BEV-V2X Perception, Fusion Prediction of Motion and Occupancy, and Driving Planning, in Complex Traffic Intersections
The comprehensiveness of vehicle-to-everything (V2X) recognition enriches and holistically shapes the global Birds-Eye-View (BEV) perception, incorporating rich semantics and integrating driving scene information, thereby serving features of vehicle state prediction, decision-making and driving plan...
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Zusammenfassung: | The comprehensiveness of vehicle-to-everything (V2X) recognition enriches and
holistically shapes the global Birds-Eye-View (BEV) perception, incorporating
rich semantics and integrating driving scene information, thereby serving
features of vehicle state prediction, decision-making and driving planning.
Utilizing V2X message sets to form BEV map proves to be an effective perception
method for connected and automated vehicles (CAVs). Specifically, Map Msg.
(MAP), Signal Phase And Timing (SPAT) and Roadside Information (RSI)
contributes to the achievement of road connectivity, synchronized traffic
signal navigation and obstacle warning. Moreover, harnessing time-sequential
Basic Safety Msg. (BSM) data from multiple vehicles allows for the real-time
perception and future state prediction. Therefore, this paper develops a
comprehensive autonomous driving model that relies on BEV-V2X perception,
Interacting Multiple model Unscented Kalman Filter (IMM-UKF)-based fusion
prediction, and deep reinforcement learning (DRL)-based decision making and
planning. We integrated them into a DRL environment to develop an optimal set
of unified driving behaviors that encompass obstacle avoidance, lane changes,
overtaking, turning maneuver, and synchronized traffic signal navigation.
Consequently, a complex traffic intersection scenario was simulated, and the
well-trained model was applied for driving planning. The observed driving
behavior closely resembled that of an experienced driver, exhibiting
anticipatory actions and revealing notable operational highlights of driving
policy. |
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DOI: | 10.48550/arxiv.2312.05104 |