Route Selection Minimizing Sun Backlight for Traffic Light Recognition
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Solution Overview
Problem
Level 4 automated driving systems face challenges in reliably recognizing traffic lights, especially due to backlighting from the sun, which can lead to incorrect decision-making regarding vehicle movement or stopping.
Innovation Solution
A travel route setting system that estimates passage times at stop lines, calculates the sun's position, and determines a backlight margin value based on the distance between traffic lights and the sun, using this information to select a route with minimal backlight interference, thereby reducing the risk of misrecognizing traffic lights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle travels through intersections during daytime, then the vehicle can reach the destination efficiently, but the traffic light recognition may fail due to backlighting from the sun
Solution Approach 1:
The system performs preliminary calculation of the sun's position and backlight margin values for all upcoming stop lines along each route before making the routing decision. This allows the system to anticipate and avoid backlighting conditions in advance, ensuring reliable traffic light recognition while maintaining travel efficiency
Solution Approach 2:
The system changes the routing parameter selection criterion from purely distance or time-based to include backlight margin values. By incorporating the backlight margin parameter into the route evaluation, the system selects routes that minimize the risk of backlighting, thereby improving traffic light recognition accuracy without significantly compromising travel efficiency
2Reliability
If the vehicle avoids routes with potential backlighting, then traffic light recognition accuracy improves, but travel time may increase
Solution Approach 1:
The system calculates backlight margin values for all possible routes and selects the route with the maximum backlight margin, even if it is not the shortest route. This partial avoidance of backlighting (focusing only on critical stop lines) achieves sufficient recognition accuracy while minimizing travel time penalty
Solution Approach 2:
The system creates a virtual model of each route including stop line positions, sun position calculations, and backlight margin evaluations. By working with these copied data representations rather than physically testing each route, the system can efficiently compare multiple routes and select the optimal one without actual time loss
Data Source
AI summary
A travel route setting system is provided. A passage time estimation section estimates a passage time at which a vehicle passes each of stop lines located before traffic lights present in a traveling direction on each of routes from a vehicle position to a destination. A solar position calculation section calculates a position of the sun at the passage time of each of the stop lines based on the position and the passage time of each stop line. The backlight margin value calculation section calculates a backlight margin value. A route backlight margin value calculation section calculates a route backlight margin value based on the backlight margin value of each of the stop lines present on each of the routes from the vehicle position to the destination. A route determination section determines a travel route from the vehicle position to the destination using the route backlight margin values.