Curve Speed Restriction Using Adaptive Vehicle Speed Models
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Solution Overview
Problem
Existing vehicle speed control systems fail to accurately adapt vehicle speed through curves, leading to potential hazardous accidents due to exceeding maximum allowed speeds.
Innovation Solution
A method and system that utilizes a vehicle speed model selected based on parameter values, incorporating machine learning algorithms trained with historical driving data, to calculate a recommended speed through curves, considering factors like road curvature, inclination, and driver style, and adjusts speed using criteria such as threshold accelerations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single vehicle speed model is used for all driving conditions, then the system complexity is reduced, but the accuracy of vehicle speed control in curves deteriorates
Solution Approach 1:
The patent segments the vehicle speed control system by dividing it into multiple vehicle speed models (first vehicle speed model and second vehicle speed model) that are selected based on different driving conditions. This segmentation allows each model to be optimized for specific conditions, improving accuracy without requiring a single overly complex model to handle all scenarios.
Solution Approach 2:
The system dynamically selects between different vehicle speed models based on real-time driving conditions. The controller determines which model to use by evaluating current conditions, allowing the system to adapt its complexity level according to the situation, thereby maintaining accuracy while managing overall system complexity.
2Measurement precision
If multiple vehicle speed models are used for different driving conditions, then the accuracy of vehicle speed control improves, but the device complexity increases
Solution Approach 1:
The patent divides the control system into distinct vehicle speed models segmented by driving condition types. Each model handles specific conditions, which improves accuracy for those conditions while keeping individual model complexity manageable. The segmentation strategy prevents the need for a single monolithic complex model.
Solution Approach 2:
The controller acts as an intermediary that manages the selection between multiple vehicle speed models. This intermediary component coordinates the complexity by choosing the appropriate model based on driving conditions, allowing the system to benefit from multiple specialized models without the full complexity of all models being active simultaneously.
3Productivity
If vehicle speed is not adequately restricted in curves, then the vehicle can maintain higher speed and productivity is improved, but safety deteriorates due to potential hazardous accidents
Solution Approach 1:
The patent changes the speed parameter dynamically based on driving conditions, particularly curve detection. When a curve is detected, the system adjusts the vehicle speed to an appropriate restricted level using the selected vehicle speed model. This parameter change ensures safety in curves while allowing higher speeds in safe conditions, balancing productivity and reliability.
Solution Approach 2:
The system continuously monitors driving conditions and provides feedback to the controller, which then adjusts the vehicle speed accordingly. This feedback mechanism ensures that speed restriction is applied when curves are detected while maintaining higher speeds when conditions permit, thereby balancing safety requirements with productivity goals.
Data Source
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AI summary
A method for restricting the speed of a vehicle (100) traveling in a curve (102). Receiving (S102) multiple road data samples (106a-c) comprising location points. Determining (S104) a parameter value for each of a first set of vehicle speed affecting parameters. Selecting (S106) a vehicle speed model based on the first set of parameter values. Determining (S108) a parameter value for each of a second set of vehicle speed affecting parameters. Calculating (S110) a recommended speed for the vehicle for at least one of the road samples based on the selected model and the parameter values of the second set of vehicle speed affecting parameters, providing (S112) an instruction for adapting the vehicle speed to the recommended speed at the location point of the at least one road sample.