Lane-Change Acceleration Control for Congested Autonomous Driving
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In congestion scenarios, driverless vehicles face challenges in finding suitable lane change opportunities due to surrounding vehicles' inability to cooperate and give way, leading to lane change failures.
Innovation Solution
A data processing method and apparatus that generates initial and updated predicted lane change accelerations based on driving parameters, determines target obstacle vehicles, and controls the vehicle to change lanes safely by considering the position relationship with these obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the driverless vehicle requires surrounding vehicles to cooperate and give way for lane change, then the lane change safety is improved, but the lane change success rate deteriorates in congestion scenarios
Solution Approach 1:
Instead of requiring surrounding vehicles to cooperate and give way for the driverless vehicle to change lanes, the system inverts the approach by having the driverless vehicle actively adjust its speed and trajectory to navigate around obstacles in the target lane. The vehicle calculates predicted positions of obstacle vehicles and determines appropriate acceleration or deceleration to create safe lane change opportunities without relying on other drivers' cooperation.
Solution Approach 2:
The system performs preliminary calculations of the driverless vehicle's predicted position during the lane change process and the predicted positions of obstacle vehicles in the target lane. By anticipating future positions and potential conflicts before the lane change is executed, the system can proactively adjust speed and timing to ensure safe lane changes even in congested conditions where surrounding vehicles cannot cooperate.
2Reliability
If the driverless vehicle waits for suitable lane change opportunities in congestion, then the collision risk is reduced, but the time consumption increases
Solution Approach 1:
The system dynamically adjusts the driverless vehicle's speed during the lane change process based on real-time calculations of predicted positions relative to obstacle vehicles. Rather than waiting passively for a suitable gap, the vehicle actively modifies its motion profile - accelerating or decelerating as needed - to create and exploit lane change opportunities, thereby reducing time loss while maintaining collision avoidance.
Solution Approach 2:
The system continuously monitors the positions of the driverless vehicle and obstacle vehicles, calculating predicted positions to determine whether a lane change can be safely executed. This feedback mechanism allows the vehicle to make real-time decisions about when to initiate or abort a lane change, optimizing the balance between collision avoidance and time efficiency by only attempting lane changes when predicted positions indicate safety.
Data Source
AI summary
This application provides a data processing method performed a computer device. The method includes: generating an initial predicted lane change acceleration corresponding to a target vehicle in a current lane; generating target predicted position information corresponding to the target vehicle according to a predicted lane change time duration taken for the target vehicle to change from the current lane to a target lane, the target lane being a lane to which the target vehicle is expected to change to; determining a target obstacle vehicle in the target lane and adjacent to the target vehicle according to the target predicted position information; determining, according to a predicted position relationship between the target obstacle vehicle and the target vehicle, a target predicted lane change acceleration; and controlling, according to the target predicted lane change acceleration, the target vehicle to change from the current lane to the target lane.