Cooperative Driving Control With Preference-Based Route Negotiation
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Solution Overview
Problem
Current vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) communication systems lack personalized decision-making capabilities tailored to the preferences of vehicle occupants, compromising safety and comfort in cooperative driving scenarios.
Innovation Solution
A cooperative driving system that integrates a long-time scale framework using cloud-based servers and digital twins to adjust decisions based on occupant preferences, combined with a short-time scale framework for real-time road-segment-level decisions through V2X communication, allowing vehicles to negotiate and maneuver based on shared operating parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If V2V/V2X communication systems are used for cooperative driving, then vehicles can share information and maneuver safely with respect to one another, but the systems lack personalized decision-making capabilities tailored to occupant preferences
Solution Approach 1:
The system segments decision-making into two levels: (1) road-segment-level decisions for specific maneuvers negotiated in real-time between vehicles, and (2) route-level decisions that incorporate occupant preferences. This segmentation allows simultaneous achievement of safety through real-time negotiation and personalization through preference-based route selection.
Solution Approach 2:
The system performs preliminary action by determining occupant preferences in advance and using digital twins to pre-negotiate route-level decisions. This allows the system to prepare personalized routes before actual driving scenarios arise, enabling both safety and personalization without real-time delays.
2Ease of operation
If real-time negotiation between vehicles is performed for road-segment-level decisions, then smooth interactions and optimal route choices are achieved, but communication overhead and negotiation time increase
Solution Approach 1:
The system performs preliminary route-level negotiations using digital twins before actual driving scenarios arise. By pre-negotiating routes based on occupant preferences and sharing them among vehicles, the system reduces real-time negotiation overhead while maintaining smooth interactions during actual maneuvers.
Solution Approach 2:
The system introduces digital twins as intermediaries that represent vehicles in negotiations. These digital twins handle the complex negotiation process, allowing real vehicles to execute pre-determined routes with minimal real-time communication, thus reducing negotiation time while maintaining smooth interactions.
3Adaptability or versatility
If cloud-based servers and digital twins are used for long-time scale framework, then personalized decisions based on occupant preferences are achieved, but system complexity and computational requirements increase
Solution Approach 1:
The system uses digital twins as intermediaries that encapsulate occupant preferences and vehicle characteristics. These digital twins simplify interactions with cloud-based servers by pre-processing preference data and presenting standardized negotiation requests, thereby reducing system complexity while maintaining personalization capabilities.
Solution Approach 2:
The system creates simplified copies (digital twins) of vehicles and their occupants' preferences. These digital twins handle complex preference modeling and negotiation tasks, allowing the actual vehicle systems to remain simpler while still achieving personalized decision-making through the twin-based framework.
Data Source
AI summary
A cooperative driving system includes a processor and a memory having one or more modules. The modules cause the processor to determine a route that includes a road segment to a destination for an ego vehicle based on (1) an ego vehicle operating parameter that has information regarding a preferred operation of an ego vehicle by an occupant, and (2) a location of a like vehicle with respect to the ego vehicle when the ego vehicle is traveling on at least a portion of the route. The one or more modules also cause the processor to determine a road-segment-level decision for the ego vehicle for the road segment based on the ego vehicle operating parameter, communicate with the like vehicle near the road segment to negotiate the road-segment-level decision to generate a negotiated road-segment-level decision, and maneuver the ego vehicle inside the road segment using the negotiated road-segment-level decision.