Abstract-We address the problem of cooperative conflict resolution for multi-vehicle motion planning in mixed-traffic scenarios, where automated and manually-driven vehicles coexist. We propose a novel solution based on reachability analysis, which provides the drivable area of each collaborative traffic participant. Overlapping drivable areas are redistributed so that each traffic participant receives an individual area for motion planning. We do not stipulate a specific method for predicting the future motion of non-communicating traffic participants. Furthermore, uncertainties in the initial states of the cooperative vehicles, e.g. due to sensor noise, can be easily integrated. A byproduct of our approach is that collaborative groups can be automatically found by identifying conflicting drivable areas; if no conflict exists, collaboration becomes unnecessary. We demonstrate the redistribution of drivable areas with two numerical examples. Collaborative motion planning of various automated road vehicles is clearly superior in terms of achievable safety and comfort compared to computing individual motion plans. This is because individual motion planning is a special case of collaborative planning when vehicles are not communicating. Many promising approaches for multi-vehicle motion planning have been developed; however, dealing with mixed-traffic situations and uncertainty is still an open research topic. We propose a unified approach for cooperative conflict resolution based on the computation of drivable areas where automated and manually-driven vehicles share the road. We first review literature concerning specific applications like intersection management and merging; after, we discuss priority-based, market-based, and reservation-based approaches. Much work on cooperative motion planning has been devoted to road intersections, since these are hotspots for traffic accidents. Collision avoidance at intersections using V2V-communication for cooperation is investigated in [1] under the consideration of model uncertainty and communication delays. Colombo et al. [2] solve scheduling problems to ensure safety during intersection passages. Another line of research is the design of cooperative lanechanging and merging strategies. In [3] , it is discussed how V2V-communication can be utilized for cooperative decision making: a distributed receding horizon control framework is set up to solve tasks of platooning and cooperative merging. Further lane-changing and merging control algorithms for platoons of vehicles are developed in [4], [5] .
Manzinger and Althof REF develop an algorithm for cooperative collision avoidance by redistributing drivable regions fairly among the cooperating vehicles.
Negotiation of drivable areas of cooperative vehicles for conflict resolution
2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)
2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)
Engineering Computer Science