Autonomous Vehicle Speed Control Using Surrounding Traffic Median
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Solution Overview
Problem
Existing autonomous vehicle speed control systems are less effective when the front vehicle is far ahead, exceeding speed limits, or traveling significantly slower than other nearby vehicles, as they rely on a specific vehicle's speed rather than adapting to surrounding traffic conditions.
Innovation Solution
A vehicle system that uses sensors to detect the speeds of nearby vehicles, processes this data to determine a set point speed, and adjusts the host vehicle's speed based on the median or average speed of surrounding traffic while adhering to posted speed limits, allowing for smooth merging and passing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle sets its speed based on the front vehicle's speed, then the vehicle can maintain a specific distance from the front vehicle, but the system becomes less effective when the front vehicle is far ahead, exceeding speed limits, or traveling significantly slower than other nearby vehicles
Solution Approach 1:
The speed control system is enhanced to perform multiple functions: it can track the front vehicle's speed, detect speeds of multiple nearby vehicles via sensors, determine median/average speeds of surrounding traffic, and select appropriate speed references based on current traffic conditions. This multi-functional approach allows the system to adapt to various scenarios including front vehicle far ahead, exceeding speed limits, or traveling significantly slower than other vehicles.
Solution Approach 2:
The system dynamically adjusts its speed reference selection based on real-time traffic conditions. Instead of rigidly following the front vehicle's speed, the system can switch between different speed reference sources (front vehicle, surrounding traffic median, surrounding traffic average) depending on which is most appropriate for the current situation, making the speed control adaptable and reliable across diverse traffic scenarios.
2Device complexity
If the autonomous vehicle monitors only the front vehicle's speed, then the system complexity remains low, but the system cannot effectively handle situations where the front vehicle is far ahead or traveling at unusual speeds
Solution Approach 1:
The speed monitoring function is segmented into multiple independent components: a front vehicle speed sensor, additional sensors for detecting nearby vehicles, a processing system for calculating median and average speeds of surrounding traffic, and a control system for selecting appropriate speed references. This segmentation allows the system to handle diverse scenarios while maintaining modular architecture that manages complexity through functional decomposition.
3Ease of operation
If the autonomous vehicle adjusts speed based on surrounding traffic conditions, then the vehicle can seamlessly merge and pass, but the system requires additional sensors and processing to detect and analyze multiple vehicles' speeds
Solution Approach 1:
The sensor system is designed with multi-functionality, using the same sensors for both front vehicle detection and surrounding traffic monitoring. The processing system performs multiple functions including calculating front vehicle distance, determining median speed of surrounding traffic, calculating average speed of nearby vehicles, and selecting appropriate speed references. This multi-functional design enables seamless merging and passing capabilities while managing hardware complexity through versatile component utilization.
Data Source
AI summary
A vehicle system includes a sensor that detects a speed of at least one nearby vehicle and outputs a speed signal representing the speed of the at least one nearby vehicle. The vehicle system further includes a processing device programmed to determine a set point speed based on the speed signal output by the sensor. The processing device generates a command signal to control a host vehicle in accordance with the set point speed.