A highway vehicle reduction coefficient dynamic calculation algorithm and system based on multi-source sensing data
By acquiring roadside perception data and pre-set vehicle control strategies, and dynamically calculating vehicle conversion factors, the problem of low accuracy of vehicle conversion factors for autonomous trucks operating on highways is solved, achieving higher assessment accuracy.
CN116013075BActive Publication Date: 2025-12-05YUNKONG ZHIXING (SHANGHAI) AUTOMOTIVE TECH CO LTD
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Patent Information
- Application Number
- CN202310013320.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-01-05
- Publication Date
- 2025-12-05
- Estimated Expiration
- 2043-01-05
AI Technical Summary
Technical Problem
Existing methods for determining vehicle conversion factors are inadequate for the needs of large-scale operation of autonomous trucks on highways, resulting in low accuracy.
Method used
By acquiring target roadside perception data and combining it with preset vehicle control strategies, the dynamic headway of different vehicle types is determined, and the vehicle conversion factor is calculated based on the dynamic headway. In particular, corresponding control strategies are set for autonomous trucks.
Benefits of technology
It improves the accuracy of vehicle conversion factors, adapts to the operational needs of autonomous trucks on highways, and enhances the accuracy of traffic flow assessment.
✦ Generated by Eureka AI based on patent content.
Abstract
This application provides a dynamic calculation algorithm and system for highway vehicle conversion coefficients based on multi-source perception data. In this scheme, after acquiring target roadside perception data, a dynamic headway is determined for different vehicle types based on a preset vehicle control strategy and the target roadside perception data. Then, based on the dynamic headway for different vehicle types, the vehicle conversion coefficient for each vehicle type is determined. The vehicle types include at least autonomous trucks, and the vehicle control strategy is set based on autonomous trucks. Because this application can correspond to different vehicle control strategies and determine the dynamic headway for different vehicle types based on the determined vehicle control strategy, thereby determining the vehicle conversion coefficient, the method in this application is more targeted and can improve the accuracy of the vehicle conversion coefficient.
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