Autonomous Vehicle Stop Request Handling With Dynamic Stop Selection
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Solution Overview
Problem
Autonomous vehicles (AVs) face challenges in efficiently responding to stop requests with varying degrees of urgency and identifying suitable stopping locations while navigating to a target location, especially when the initial target location becomes unavailable or inappropriate during trajectory execution.
Innovation Solution
The AV system evaluates features of the stop request, including urgency, environment, and map data to identify a target stopping place, continuously updates this location based on new data, and adapts the trajectory plan if the initial target becomes unsuitable, using proximity regions and quality determination processes to select appropriate stopping places.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the AV system continuously monitors and updates target location based on new data, then the reliability of stopping location selection is improved, but the computational complexity and processing time increase
Solution Approach 1:
The system pre-identifies multiple candidate stopping locations before the current target becomes unavailable. These candidate locations are evaluated and ready in advance, so when the current target location becomes unsuitable, the system can immediately switch to a pre-evaluated alternative without extensive real-time computation, thus maintaining reliability while reducing computational burden during critical moments.
Solution Approach 2:
The system dynamically adjusts the monitoring and reevaluation process based on the AV's current state and environmental conditions. Instead of continuous full reevaluation, the system triggers location reassessment only when necessary (e.g., when current target becomes unavailable or conditions change significantly), optimizing the balance between reliability and computational complexity through adaptive, event-driven updates.
2Adaptability or versatility
If the AV system identifies multiple candidate stopping locations and evaluates them, then the adaptability to changing conditions is improved, but the time required to select a target location increases
Solution Approach 1:
The system performs preliminary evaluation of multiple candidate stopping locations in advance, assessing their suitability based on current conditions. By pre-evaluating candidates and maintaining a ready list of alternatives with their quality metrics, the system reduces the time needed for decision-making when conditions change, as the candidates are already assessed and ranked.
Solution Approach 2:
Instead of evaluating all possible stopping locations exhaustively, the system focuses on evaluating a limited set of promising candidate locations that meet basic criteria. This partial evaluation approach identifies sufficient alternatives without the time cost of complete enumeration, achieving adaptability through selective assessment of the most relevant options.
3Productivity
If the AV system executes a trajectory plan to a target location, then the operational efficiency is improved, but the risk of reaching an unavailable or inappropriate location increases
Solution Approach 1:
The system continuously monitors the availability and suitability of the current target stopping location during trajectory execution. When the target becomes unavailable or inappropriate, the system receives feedback and automatically triggers a reevaluation process to select a new target location, ensuring the AV does not proceed to an unsuitable location while maintaining efficient operation through automated monitoring and adjustment.
Solution Approach 2:
The trajectory execution process is made dynamic with continuous verification of target location validity. The system adapts the execution plan in real-time based on environmental feedback, switching to alternative trajectories or reselecting targets when conditions change, thus maintaining both operational efficiency and reliability through flexible, condition-responsive execution.
Data Source
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AI summary
Among other things, a vehicle drives autonomously on a trajectory through a road network to a goal location based on an automatic process for planning the trajectory without human intervention; and an automatic process alters the planning of the trajectory to reach a target location based on a request received from an occupant of the vehicle to engage in a speedreducing maneuver.