Autonomous Vehicle Pullover Planning Under Changing Ambient Conditions
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Solution Overview
Problem
Autonomous vehicles face challenges in dynamically determining suitable stopping locations, especially in cluttered urban environments where ambient conditions can change rapidly, such as traffic density, obstacles, and ground hazards, which existing systems struggle to address effectively.
Innovation Solution
The implementation of a perception system with sensors and a motion control system that assesses ambient conditions against stopping rules to determine if a desired stopping location is feasible, and if not, identifies and selects an alternate stopping location based on cost analysis, ensuring safe and efficient operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the AV selects a stop location based on initial navigation, then the pickup or drop-off operation can be performed, but ambient conditions may change rapidly making the location physically impossible or impractical
Solution Approach 1:
The system performs preliminary detection of ambient conditions before finalizing the stop location. Sensors detect traffic density, flow rate, and other environmental factors in advance, allowing the system to pre-assess whether a selected stop location remains viable and to make adjustments before the vehicle arrives
Solution Approach 2:
The system continuously monitors ambient conditions and uses this feedback to dynamically adjust the stop location. By comparing real-time sensor data against stopping rules and thresholds, the system can determine when conditions have changed sufficiently to warrant selecting an alternate location
2Reliability
If the AV continuously monitors ambient conditions to ensure safety, then safety is improved, but computational complexity increases significantly
Solution Approach 1:
The system monitors changes in ambient condition parameters such as traffic density and flow rate. By detecting when these parameters exceed predefined thresholds or change beyond acceptable ranges, the system can trigger stop location adjustments without continuously re-evaluating all possible locations, thus reducing computational burden while maintaining safety
Solution Approach 2:
The system applies stopping rules and threshold comparisons selectively rather than exhaustively analyzing every possible stop location. It focuses monitoring on key ambient conditions and only performs full re-evaluation when necessary, balancing safety requirements with computational efficiency
3Productivity
If the AV selects a stop location without considering traffic density and flow rate, then the stopping decision is simpler, but the road capacity may be exceeded causing traffic congestion
Solution Approach 1:
The system calculates traffic density and flow rate thresholds based on road capacity parameters. By comparing actual ambient conditions against these predetermined thresholds, the system can make informed stopping decisions that maintain traffic flow efficiency without requiring complex real-time optimization of traffic patterns
Data Source
AI summary
This document describes methods and systems for enabling an autonomous vehicle (AV) to determine a path to a stopping location. The AV will determine a desired stop location (DSL) that is associated with a service request. The AV's motion control system will move the AV along a path to the DSL. While moving along the path, the AV's perception system will detect ambient conditions near the DSL. The ambient conditions will be parameters associated with a stopping rule. The AV will apply the stopping rule to the ambient conditions to determine whether the stopping rule permits the AV to stop at the DSL. If the stopping rule permits the AV to stop at the DSL, the motion control system will move the AV to, and stop at, the DSL. Otherwise, the motion control system will not stop the AV at the DSL.