Autonomous Vehicle Following Distance Using Pavement Friction Estimation
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Solution Overview
Problem
Maintaining an appropriate safe following distance between an autonomous vehicle and surrounding vehicles in varying dynamic and environmental conditions is challenging, as factors like vehicle type and pavement friction significantly impact braking performance, necessitating adaptive safety measures.
Innovation Solution
A safe following distance estimation system that uses sensors and a processor to gather data on adjacent vehicles and pavement conditions, estimating friction parameters and calculating a safe following distance based on this information to ensure proper spacing and prevent collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the safe following distance is increased to account for worst-case scenarios (large trucks with cargo, wet/snowy pavement), then collision avoidance capability is improved, but traffic network efficiency deteriorates due to excessive spacing
Solution Approach 1:
The system dynamically changes the safe following distance parameter based on real-time detection of vehicle type, load condition, and pavement friction coefficient, rather than using a fixed conservative distance. This allows the distance to be optimized for each specific scenario, improving safety when needed while maintaining efficiency when conditions permit
Solution Approach 2:
The safe following distance is made dynamic rather than static, adjusting in real-time according to the actual dynamic characteristics of the leading vehicle (mass, deceleration capability) and environmental conditions (pavement friction). This dynamic adaptation resolves the contradiction by allowing the system to be conservative when necessary and liberal when safe
2Reliability
If a fixed conservative safe following distance is used to ensure safety in all scenarios, then reliability is improved, but adaptability to different driving conditions deteriorates
Solution Approach 1:
The system changes the safe following distance parameter based on detected vehicle characteristics and environmental conditions, moving from a fixed conservative value to a variable value that adapts to different scenarios while maintaining safety margins
Solution Approach 2:
The system uses sensor feedback about the leading vehicle's mass, deceleration capability, and pavement friction conditions to continuously adjust the safe following distance, creating a closed-loop control system that adapts to different driving conditions while ensuring safety
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the real-time accuracy of safe following distance calculations, improving the reliability and safety of autonomous vehicles by adapting to different scenarios and displaying critical distance information to the driver for timely interventions.
Implementation Method 1
estimating friction parameters between wheels of the adjacent vehicle and the autonomous vehicle and the pavement
Data Source
AI summary
A safe following distance estimation system and an estimation method thereof are provided. The safe following distance estimation system adapted for an autonomous vehicle includes a sensor and a processor. The sensor senses an adjacent vehicle to generate first sensing data, and senses the autonomous vehicle to generate second sensing data. The processor estimates a first friction parameter between wheels of the adjacent vehicle and a pavement according to pavement material data, and estimates a second friction parameter between wheels of the autonomous vehicle and the pavement according to the second sensing data. The processor calculates a safe following distance between the autonomous vehicle and the adjacent vehicle according to the first sensing data, the second sensing data, the first friction parameter, the second friction parameter.