Autonomous Vehicle Yellow-Light Crossing Decision at Intersections
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Solution Overview
Problem
Autonomous vehicles face challenges in determining whether to stop or proceed through an intersection when encountering a yellow traffic light, as existing methods may lead to accidents due to sudden stops or incorrect timing, especially considering surrounding vehicles and legal requirements.
Innovation Solution
The system uses a combination of sensor data, detailed map information, and pre-stored or received information about traffic signal timing to estimate the vehicle's location and decide whether to stop or proceed, taking into account the required deceleration, speed profile, and legal requirements such as having the rear wheels within the intersection before the light turns red.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle stops automatically at the intersection when the traffic signal turns yellow, then the vehicle complies with traffic laws and avoids running red lights, but sudden stops may cause accidents with vehicles behind and reduce traffic flow efficiency
Solution Approach 1:
The system performs preliminary actions by detecting the yellow traffic signal early and calculating the required stopping distance and deceleration rate before the vehicle reaches the intersection. This allows the vehicle to begin decelerating in advance smoothly, rather than making sudden stops, thereby maintaining traffic law compliance while reducing accident risk to vehicles behind.
Solution Approach 2:
The system dynamically adjusts the stopping behavior based on real-time conditions including the vehicle's current speed, distance to the intersection, and surrounding traffic environment. By continuously monitoring these parameters and adjusting deceleration rates accordingly, the system ensures compliance with traffic laws while minimizing sudden stops that could cause accidents or disrupt traffic flow.
2Productivity
If the autonomous vehicle accelerates to pass through the intersection before the light turns red, then the vehicle maintains traffic flow efficiency, but it may not be able to stop safely if the light turns yellow and increases accident risk
Solution Approach 1:
The system performs preliminary assessment when detecting a yellow traffic signal by calculating the distance to the intersection and the deceleration required to stop safely before the red light. This preliminary calculation allows the vehicle to determine in advance whether it can safely stop or should proceed, enabling informed decisions that maintain traffic flow while ensuring safe stopping capability when conditions permit.
Solution Approach 2:
The system continuously monitors the vehicle's speed, position, and the traffic signal state, using this feedback to adjust its decision-making. By constantly updating the calculation of stopping distance and required deceleration based on real-time feedback, the system can dynamically switch between accelerating to maintain flow and preparing to stop safely, depending on the evolving situation.
3Measurement precision
If the autonomous vehicle uses complex perception systems and detailed map information to make accurate intersection decisions, then the decision accuracy improves, but the system complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary calculations of stopping distance and deceleration requirements based on pre-stored traffic signal timing information and current vehicle state. By preparing these calculations in advance using available data, the system achieves accurate intersection decisions without requiring overly complex real-time computation, thus balancing decision accuracy with system complexity.
Solution Approach 2:
The system uses pre-stored traffic signal timing information and highly detailed map information that were collected and processed in advance. This self-service approach allows the vehicle to make accurate intersection decisions by utilizing pre-prepared data and pre-calculated parameters, reducing the need for complex real-time perception and computation while maintaining high decision accuracy.
Data Source
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AI summary
Aspects of the disclosure relate to determining whether a vehicle 100 should continue through an intersection 502. For example, the one or more of the vehicle's computers 110 may identify a time when the traffic signal light 526 will turn from yellow to red. The one or more computers may also estimate a location of a vehicle at the time when the traffic signal light will turn from yellow to red. A starting point 350 of the intersection may be identified. Based on whether the estimated location of the vehicle is at least a threshold distance past the starting point at the time when the traffic signal light will turn from yellow to red, the computers can determine whether the vehicle should continue through the intersection.