Vehicle Control Strategy Adaptation Using Historical Zone Data
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Solution Overview
Problem
Existing systems fail to effectively adapt vehicle control strategies to navigate through increasingly complex and varied environmental and safety restrictions along fixed routes, leading to driver stress and potential safety hazards, especially for vehicles like buses operating on reoccurring routes.
Innovation Solution
The use of historical data from previous vehicle passages to inform and adapt vehicle control strategies, including operating parameters such as speed, energy source selection, and subsystem management, to ensure compliance with environmental and safety requirements of specific zones, while optimizing energy consumption and reducing stress for drivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If navigation systems provide alternative routes to avoid restrictive zones, then driver stress is reduced, but route flexibility and operational efficiency are compromised
Solution Approach 1:
The system performs preliminary actions by charging the energy storage system before entering restrictive zones, ensuring compliance without needing alternative routes. This advance preparation eliminates driver stress while maintaining the original route and operational efficiency.
Solution Approach 2:
The system uses historical data from previous vehicle passages to optimize control strategies for upcoming restrictive zones. This feedback mechanism enables accurate prediction of energy requirements and optimal charging timing, resolving the contradiction between ease of operation and productivity.
2Object-generated harmful factors
If vehicles comply with environmental restrictions in restrictive zones, then environmental sustainability is improved, but energy consumption increases
Solution Approach 1:
The system charges the energy storage system in advance before entering restrictive zones, ensuring zero or low emissions compliance while optimizing total energy consumption. By preparing beforehand, the vehicle avoids inefficient last-minute energy management during zone traversal.
Solution Approach 2:
The system dynamically adjusts control parameters such as charging power, speed, and energy source selection based on upcoming restrictive zones. These parameter changes enable compliance with emission restrictions while minimizing overall energy consumption through optimized control strategies.
3Measurement precision
If historical data is used to predict energy consumption, then prediction accuracy is improved, but data processing complexity increases
Solution Approach 1:
The system extracts only the most relevant features from historical data, such as typical energy consumption patterns for specific zones and conditions. By focusing on key parameters rather than processing all raw data, the system achieves high prediction accuracy while keeping data processing complexity manageable.
Data Source
AI summary
A method and system are provided for adapting a vehicle control strategy of an on-road vehicle following a reoccurring fixed route to a predetermined destination, which fixed route extends through at least one geographical zone associated with at least one environmental restriction. When it is determined that the vehicle is approaching the geographical zone, historical data collected from previous passages of one or several vehicles through the zone is accessed, and the vehicle control strategy inside the geographical zone is adapted based on the historical data and the environmental restriction.