Driver Assistance Acceleration Request for Time-Efficient Travel
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Solution Overview
Problem
Current driver assistance systems primarily focus on energy efficiency, neglecting time efficiency, which is crucial for drivers who need to arrive at their destination quickly, such as those on business trips, where saving travel time is more important than energy consumption.
Innovation Solution
A method that assists drivers by providing acceleration requests when event criteria are met, such as speed limit changes or removal of obstacles, to ensure optimal use of permitted speed limits, using predictive route data and environmental sensors to evaluate the driving situation and output visual, haptic, or acoustic notifications to prompt the driver to accelerate and reach the target speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If driver assistance systems focus on energy-efficient coasting operations, then fuel efficiency is improved, but time efficiency deteriorates
Solution Approach 1:
The system dynamically switches between energy-efficient coasting mode and time-efficient acceleration mode based on real-time driving situation analysis. When predictive route data indicates upcoming speed limit increases or obstacle removal, the system transitions from passive coasting to active acceleration, optimizing the trade-off between fuel consumption and travel time
Solution Approach 2:
The system changes the target speed parameter dynamically by analyzing predictive route data for speed limit changes. When higher speed limits are predicted ahead, the system adjusts the current speed target upward and generates acceleration requests, transforming the driving behavior from energy-optimized to time-optimized based on parameter changes in the driving environment
2Loss of energy
If drivers maintain lower speeds for energy efficiency, then fuel consumption is reduced, but arrival time worsens
Solution Approach 1:
The system performs preliminary analysis of predictive route data to identify upcoming speed limit increases before they occur. By detecting these changes in advance through navigation systems and environmental sensors, the system can prepare acceleration requests and notify the driver early, enabling timely speed increases that reduce travel time without excessive energy consumption
Solution Approach 2:
The system continuously monitors driving situation parameters including current speed, predictive speed limits, and obstacle positions. This feedback loop enables the system to determine when to transition from energy-saving mode to time-saving mode by comparing actual driving conditions against the predictive route model, generating acceleration requests when time efficiency becomes priorit
3Loss of time
If navigation systems calculate fastest routes, then time efficiency is improved, but driving style optimization deteriorates
Solution Approach 1:
The system segments the driving task into two components: route selection (handled by navigation system) and driving style optimization (handled by the assistance system). The assistance system analyzes the selected route's predictive data and generates specific acceleration requests and speed recommendations, dividing the overall time-optimization function into navigational planning and operational execution phases
Data Source
AI summary
A method is provided for assisting a driver in carrying out a time-efficient trip with a motor vehicle. The method includes outputting an acceleration request to the driver when at least one event criterion occurs, where the one event criterion includes the motor vehicle operating more slowly than a time-efficient target speed assigned to the current position of the motor vehicle.