Autonomous Vehicle Trajectory Control in Multi-Lane Turns
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Solution Overview
Problem
Autonomous vehicles face challenges in safely navigating multi-lane turns due to the risk of being cut off or forced to adjust their trajectory by other vehicles, leading to uncomfortable and unsafe conditions for passengers, as they are programmed to follow a specific path within a lane.
Innovation Solution
The autonomous vehicle adjusts its trajectory based on its position relative to other vehicles, using historical data or the trajectory of preceding vehicles, to follow an alternate path that avoids collisions and maintains safety, while also staggering its position to increase visibility to surrounding drivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle follows a specific programmed path within a lane, then the vehicle maintains predictable behavior, but the vehicle risks being cut off or forced to make evasive maneuvers by other vehicles
Solution Approach 1:
The autonomous vehicle dynamically adjusts its trajectory during multi-lane turns based on real-time detection of surrounding vehicles. The system transitions from a static programmed path to a dynamic adaptive path, allowing the vehicle to modify its course to avoid collisions while maintaining safety. This is achieved through continuous monitoring of object positions and recalculating the trajectory to accommodate other vehicles' actions.
2Reliability
If the autonomous vehicle adjusts its trajectory to avoid other vehicles, then collision risk is reduced, but the vehicle's movements become less predictable to human drivers
Solution Approach 1:
The system uses feedback from sensors detecting other vehicles' positions and trajectories to adjust the autonomous vehicle's path. By continuously monitoring the environment and responding to detected objects, the vehicle can make safety adjustments while attempting to maintain natural driving patterns. The feedback loop allows the vehicle to balance safety requirements with predictable behavior.
3Adaptability or versatility
If the autonomous vehicle uses historical data to adjust trajectory, then the vehicle can anticipate typical driving patterns, but the system complexity increases
Solution Approach 1:
The system performs preliminary analysis of historical trajectory data to establish expected driving patterns before executing the turn. By pre-processing and storing typical vehicle behavior patterns, the system can quickly reference this information during actual driving situations without requiring complex real-time calculations. This reduces the processing burden during critical maneuver execution.
Data Source
AI summary
The technology relates controlling an autonomous vehicle through a multi-lane turn. In one example, data corresponding to a position of the autonomous vehicle in a lane of the multi-lane turn, a trajectory of the autonomous vehicle, and data corresponding to positions of objects in a vicinity of the autonomous vehicle may be received. A determination of whether the autonomous vehicle is positioned as a first vehicle in the lane or positioned behind another vehicle in the lane may be made based on a position of the autonomous vehicle in the lane relative to the positions of the objects. The trajectory of the autonomous vehicle through the lane may be adjusted based on whether the autonomous vehicle is positioned as a first vehicle in the lane or positioned behind another vehicle in the lane. The autonomous vehicle may be controlled based on the adjusted trajectory.