Lane Change Assistance Using TTC, TIV, and Minimum Jerk Paths
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Solution Overview
Problem
Current lane change assistance systems lack the capability to accurately determine the probability of collision with target vehicles on a target lane during a lane change and safely execute the maneuver.
Innovation Solution
A lane change assistance system that includes sensors to detect vehicle speeds and distances, a controller to calculate an expected lane change time based on time to collision (TTC) and inter-vehicular time (TIV), and generates a lane change path using a minimum jerk trajectory and dynamic equation of motion to ensure safe lateral and longitudinal movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the lane change assistance system uses basic collision detection, then the system complexity is low, but the accuracy of determining collision probability with target vehicles is insufficient
Solution Approach 1:
The system segments the assessment of collision probability into multiple independent components: TTC calculation for longitudinal safety, TIV calculation for lateral safety, and target vehicle behavior prediction. Each component processes specific sensing data separately and contributes to the overall collision probability assessment, improving accuracy without requiring a completely complex unified system.
Solution Approach 2:
The system performs preliminary calculations of TTC and TIV values before executing the lane change maneuver. By pre-assessing the safety margins and predicting target vehicle behaviors in advance, the system determines collision probability proactively, allowing for more accurate decision-making before the actual lane change occurs.
2Manufacturing precision
If the system calculates detailed expected lane change time using minimum jerk trajectory, then the lane change path accuracy is improved, but the calculation time and processing complexity increase
Solution Approach 1:
The system applies minimum jerk trajectory optimization selectively to the lateral motion profile during lane changing, while using simpler constant acceleration models for longitudinal motion. This partial application of complex optimization only where necessary (lateral direction) reduces overall calculation time while maintaining sufficient path accuracy for the critical lateral maneuver.
Solution Approach 2:
The system changes the complexity of motion model parameters based on the specific maneuver phase: using detailed minimum jerk trajectory parameters for lateral motion during active lane changing, and simpler constant velocity/acceleration parameters for longitudinal motion and pre/post-lane-change phases, optimizing the balance between accuracy and computational efficiency.
Data Source
AI summary
A lane change assistance system includes: at least one sensor that detects sensing information including a first vehicle speed of a host vehicle, a second vehicle speed of a surrounding vehicle around the host vehicle, and a distance between the host vehicle and the surrounding vehicle; a lane change controller that identifies a lane change possible condition based on the sensing information, calculates an expected lane change time, and generates a lane change path for the expected lane change time; a steering device that controls lateral movement of the host vehicle based on the lane change path; and an acceleration and deceleration device that controls longitudinal movement of the host vehicle based on the lane change path.