Intersection Driving Assistance for Slip-Through Vehicle Prediction
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Solution Overview
Problem
When a host vehicle approaches an intersection, the possibility of a following vehicle slipping past another vehicle that has entered from a different route can hinder the host vehicle's progress, even if the initial vehicle does not obstruct the host vehicle's path, due to priority rules at intersections.
Innovation Solution
A driving assistance device with a controller that uses sensor data, map information, and communication units to predict whether a following vehicle can slip past the initial vehicle by calculating the minimum distance between the initial vehicle and the road edge or surrounding objects, determining if the following vehicle can pass through the gap and potentially interfere with the host vehicle's path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the host vehicle proceeds in the intersection when another vehicle enters from a different route, then the host vehicle's travel efficiency is improved, but the risk of collision with a following vehicle increases
Solution Approach 1:
The system performs preliminary detection of following vehicles and prediction of their slip-pasting behavior before the host vehicle enters the intersection. By calculating the minimum distance between the other vehicle and road edges, and comparing it with the following vehicle's dimensions, the system anticipates potential collisions and adjusts the host vehicle's trajectory in advance to avoid them.
2Reliability
If the host vehicle waits for potential following vehicles, then collision risk is reduced, but travel efficiency deteriorates
Solution Approach 1:
The system continuously monitors the positions and movements of other vehicles and following vehicles, updating the prediction of slip-pasting behavior in real-time. Based on this feedback, the host vehicle's trajectory is dynamically adjusted - proceeding when safe and waiting when necessary - thereby resolving the contradiction between caution and efficiency.
3Measurement precision
If the system detects and predicts following vehicle behavior, then judgment accuracy is improved, but computational complexity increases
Solution Approach 1:
The system extracts only the critical parameters needed for judgment - the minimum distance between the other vehicle and road edges, and the dimensions of the following vehicle. By focusing on these essential factors rather than processing all possible variables, the system achieves high judgment accuracy while keeping computational complexity manageable.
Data Source
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AI summary
A driving assistance method includes: detecting (S4) a first other vehicle (v1) entering an intersection on a first route (21) where a host vehicle (20) is traveling from a second route (21) different from the first route (21); predicting (S7) whether or not the first other vehicle (v1) will stop in the intersection, and predicting a stop position of the first other vehicle (v1) when the first other vehicle (v1) is predicted to stop in the intersection; calculating (S8) a minimum distance (d1) of a first gap between a vehicle body of the first other vehicle (v1) and a surrounding object around the first other vehicle (v1) or between the vehicle body of the first other vehicle (v1) and a road edge of a travel lane of the first other vehicle (v1) when the first other vehicle (v1) stops at the predicted stop position; and predicting (S9, S12, S18) according to the calculated minimum distance (d1) whether or not a second other vehicle (v2), which is a following vehicle behind the first other vehicle (v1), may slip through the first gap from behind the first other vehicle (v1).