Travel Control Plan Generation for Proactive Vehicle Adaptation
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Solution Overview
Problem
Conventional automatic vehicle control systems can only respond to variations in the peripheral environment after they occur, limiting their ability to maintain a travel policy that balances comfort, fuel efficiency, and safety, as they perform consequential control rather than proactive management.
Innovation Solution
A travel control plan generating system that stratifies control into upper and lower level plans, allowing for flexible response to peripheral environment changes while ensuring travel policies are met, using upper level plan generation, lower level plan inference and evaluation, and inter-vehicle communication to select appropriate control strategies based on safety, comfort, and environmental considerations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional automatic vehicle control systems determine control policy based on current state parameters (relative speed and distance), then the control system is simple to implement, but the system can only respond after conditions have already changed, limiting flexibility and leeway in responding to peripheral environment variations
Solution Approach 1:
The control system is segmented into multiple functional modules: state parameter acquisition module, prediction module (inferring future states), evaluation module (assessing multiple control policies), and selection module (choosing optimal policy). This segmentation allows the system to perform proactive multi-scenario planning while maintaining manageable complexity through modular design.
Solution Approach 2:
The system performs preliminary actions by predicting future state parameters at multiple time points and evaluating multiple control policies in advance. Instead of reacting to current conditions only, the system proactively assesses potential future scenarios and selects control policies before conditions deteriorate, providing leeway and flexibility in response.
2Reliability
If consequential control is performed based on current state parameters, then the control logic is straightforward, but the response to condition variation is limited and may contravene travel policy in terms of comfort and fuel efficiency
Solution Approach 1:
The system implements feedback mechanisms where prediction results and evaluation outcomes are fed back into the control policy selection process. Multiple control policies are evaluated based on predicted future states, and the selection is made based on which policy best satisfies travel policy requirements for comfort and fuel efficiency, ensuring reliable compliance.
Solution Approach 2:
The control logic transitions from static reactive control to dynamic proactive control. The system dynamically adjusts control policies based on predicted future conditions rather than fixed responses to current states, allowing flexible adaptation while maintaining travel policy compliance through systematic evaluation criteria.
3Adaptability or versatility
If a single control policy is determined from current state parameters, then the control decision is quick to make, but the system cannot flexibly respond to variation in peripheral environment conditions
Solution Approach 1:
The system performs preliminary evaluation of multiple control policies and their expected outcomes in advance. By assessing multiple scenarios and selecting the optimal policy before execution, the system reduces the need for time-consuming real-time adjustments while maintaining high adaptability to peripheral environment variations.
Solution Approach 2:
The control decision-making process is segmented into distinct phases: prediction of future states, evaluation of multiple control policies against travel policy criteria, and selection of optimal policy. This segmentation allows systematic processing that balances comprehensiveness with efficiency, enabling flexible response without excessive time loss.
Data Source
AI summary
A travel control plan generating system 1 includes: upper level plan generating means 22a for generating an upper level plan corresponding to a travel policy of a vehicle A; lower level plan generating means 22b for generating a lower level plan, which is a plan for achieving the upper level plan and includes at least a travel course; lower level plan obtaining means 16, 30 for obtaining a lower level plan including at least a travel course of a peripheral vehicle B, C; evaluating means 24 for evaluating the lower level plan of the vehicle A in accordance with a predetermined index, taking into account the lower level plan of the peripheral vehicle B, C; and lower level plan selecting means 26 for selecting a lower level plan to be executed by the vehicle A on the basis of an evaluation performed by the evaluating means 24.