Advisory Vehicle Speed Control for Dynamic Traffic Matching
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Solution Overview
Problem
Existing driving automation systems fail to ensure a safe and comfortable ride for users by accurately adjusting vehicle speed based on real-time environmental conditions and surrounding traffic, leading to potential collisions and discomfort.
Innovation Solution
The implementation of an advisory speed assistance (ASA) module that generates an advisory speed based on environmental information, including surrounding vehicle locations, headings, and speeds, historical data, and current conditions, which is integrated with the arbiter to set the commanded speed of the ego vehicle, ensuring a safe and comfortable ride.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle follows the legal speed limit, then the vehicle operates within legal boundaries, but the vehicle may not match surrounding traffic conditions leading to potential collisions and discomfort
Solution Approach 1:
The system continuously monitors surrounding traffic conditions, vehicle speeds, and environmental factors, then feeds this information back to dynamically adjust the advisory speed. This closed-loop feedback mechanism enables the vehicle to adapt to changing traffic conditions while maintaining safety, resolving the contradiction between following fixed speed limits and adapting to variable traffic environments.
Solution Approach 2:
The system transitions from static speed limit adherence to dynamic speed adjustment by continuously calculating an advisory speed based on real-time environmental information, surrounding vehicle speeds, and traffic conditions. This dynamic approach allows the vehicle to optimize safety and comfort by adapting to current traffic conditions rather than rigidly following predetermined speed limits.
2Reliability
If the vehicle adjusts speed to match surrounding traffic, then collision risk is reduced, but the system complexity increases due to multiple sensors and processing requirements
Solution Approach 1:
The system integrates multiple sensors and data sources into a unified advisory speed calculation framework that serves multiple functions: collision avoidance, comfort optimization, and traffic flow adaptation. By making the system multi-functional, the complexity is justified through multiple benefits, and the same infrastructure supports various safety and comfort objectives simultaneously.
Solution Approach 2:
The advisory speed acts as an intermediary between the driver and the complex sensor array, translating multiple environmental factors and surrounding vehicle data into a single, actionable speed recommendation. This intermediary approach simplifies the user interface while maintaining the sophisticated processing needed for comprehensive collision avoidance and traffic adaptation.
3Ease of operation
If the advisory speed is generated based on comprehensive environmental information, then the driving experience is optimized, but the processing time and computational load increase
Solution Approach 1:
The system performs preliminary calculations and predictions about optimal speed based on current environmental conditions and historical traffic patterns. By pre-processing data and anticipating future traffic states, the system reduces real-time computational burden while maintaining optimized driving experience, as much of the complex analysis is prepared in advance rather than calculated from scratch during critical moments.
Data Source
AI summary
One example discloses a system for advisory vehicle speed assistance, including: a controller coupled to receive a set of environmental information based on a location of an ego vehicle; wherein the environmental information includes a legal speed limit at the location; wherein the controller is configured to generate an advisory speed for the ego vehicle based on the set of environmental information; and wherein the advisory speed is different from the legal speed limit.