Vehicle Control System for Automatic Climate Adjustment via Approach Detection
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Solution Overview
Problem
Current remote vehicle control methods require manual user intervention, leading to inconvenience and forgetfulness, especially in adjusting vehicle states like temperature before starting, which hinders the realization of intelligent vehicle control.
Innovation Solution
A method and apparatus that determine a planned route between a vehicle and a target object, detect the probability of the target object approaching the vehicle, and automatically control vehicle systems based on this detection, allowing for pre-adjustment of vehicle states without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual remote control via vehicle key or mobile phone client is used, then the user can control vehicle functions, but the user burden increases and automation is reduced
Solution Approach 1:
The vehicle system automatically detects the user's approach via positioning information, calculates probability of approach, and autonomously activates control policies without requiring manual remote control operations. The system serves itself by monitoring its own state and user context, eliminating the need for user intervention in routine control tasks.
Solution Approach 2:
The system performs preliminary actions by detecting user approach probability in advance and pre-activating control policies before the user actually reaches the vehicle. This allows the vehicle to prepare optimal control states (such as climate control, security systems) proactively based on predicted user arrival, rather than waiting for manual commands.
2Ease of operation
If manual remote control is required before starting the vehicle, then vehicle states can be adjusted, but user forgetfulness occurs and convenience decreases
Solution Approach 1:
The system continuously monitors user positioning information and provides feedback by calculating real-time probability of approach. This feedback loop enables the system to adjust control policies dynamically based on actual user movement patterns, ensuring reliable execution of control actions while reducing the likelihood of user forgetfulness through automated reminders and proactive activation.
3Extent of automation
If automatic control based on positioning is implemented, then user burden is reduced, but system complexity increases
Solution Approach 1:
The automatic control system is segmented into distinct functional modules: positioning information acquisition module, probability calculation module, and control policy execution module. Each module handles a specific aspect of the automation process, making the overall complex system manageable through functional decomposition and independent development of each component.
Data Source
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AI summary
A method for vehicle control is provided, which includes: acquiring a parking position of a vehicle when it is detected that the vehicle has stopped; acquiring a current position of a target object, the current position representing a position of the target object; determining a planned route according to the current position and the parking position, the planned route representing a feasible route between the target object and the vehicle; detecting a probability of the target object approaching the vehicle according to the planned route to acquire a detection result; and determining a control policy for the vehicle according to the detection result. This method effectively combines determination of a target object approaching the vehicle with automatic control of the vehicle, and enhances the intelligence of remote automatic control of the vehicle.