Autonomous Vehicle Merge Planning for Intersection Intent Prediction
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately determining the driving intentions of oncoming vehicles at intersections, leading to potential collisions due to misjudgment of traveling conditions.
Innovation Solution
A method and apparatus for planning autonomous vehicle travel that involves acquiring and analyzing traveling information of both the autonomous vehicle and obstacle vehicles, predicting the obstacle vehicle's driving intention, and planning a vehicle-converging strategy to avoid collisions by controlling the autonomous vehicle's speed and trajectory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the autonomous vehicle uses basic traveling information to control its movement, then the control system is simple, but the accuracy of predicting obstacle vehicle driving intention is insufficient leading to potential collisions
Solution Approach 1:
The planning system is segmented into multiple functional modules: traveling information acquisition module, convergence area determination module, time point prediction module, and strategy planning module. Each module handles a specific aspect of the planning process, allowing the system to achieve high prediction accuracy through specialized sub-functions while maintaining overall system manageability
Solution Approach 2:
The system performs preliminary actions by pre-determining the vehicle convergence area and predicting time points of convergence before actual vehicle interaction occurs. This advance planning allows the autonomous vehicle to prepare appropriate strategies (overtaking or yielding) in advance, improving response accuracy and reducing collision risks
2Reliability
If the autonomous vehicle accurately predicts convergence time points and controls speed precisely, then collision avoidance is improved, but the control system complexity increases
Solution Approach 1:
The control system dynamically adjusts the autonomous vehicle's speed based on real-time predictions of convergence time points and determined driving intentions. The system transitions between different control states (acceleration, deceleration, maintaining speed) according to the predicted scenario, achieving high reliability through adaptive control while managing complexity through state-based decision logic
Solution Approach 2:
The system continuously monitors actual vehicle positions and speeds, comparing them against predicted trajectories and time points. This feedback mechanism allows the system to verify prediction accuracy and adjust control strategies in real-time, improving collision avoidance reliability while using the feedback loop to manage control complexity through iterative refinement
Data Source
AI summary
The present application provides a method and apparatus for planning an autonomous vehicle, an electronic device and a storage medium, which relates to the field of autonomous driving. According to the technical solutions of the present application, time points of entering a vehicle-converging area can be accurately predicted according to traveling conditions of two parties, so that a driving behavior of the autonomous vehicle is controlled more accurately. The specific implementation is as follows: acquiring first traveling information of an autonomous vehicle; acquiring second traveling information of at least one obstacle vehicle; predicting a driving intention of the obstacle vehicle according to the acquired second traveling information of the obstacle vehicle; planning a vehicle-converging strategy for the autonomous vehicle according to the first traveling information and the driving intention of the obstacle vehicle; and controlling the autonomous vehicle to travel according to the vehicle-converging strategy.