Coasting Distance Calculation for Driver Assistance
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Solution Overview
Problem
Drivers face challenges in maximizing coasting distance due to varying road and traffic conditions, making it difficult to improve fuel consumption without timely disengagement of the accelerator pedal, especially in electric vehicles where energy consumption is sensitive to power traveling, regenerative braking, wind direction, and wind velocity.
Innovation Solution
A driver assistance system that collects vehicle and environmental information, calculates coasting distances, and outputs messages to instruct drivers on optimal coasting based on vehicle position, speed, weight, weather, and road geometry, determining when coasting is feasible by comparing distances and speed thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of moving object
If a driver relies only on visual field to perform coasting by disengaging accelerator pedal, then the driver can operate the vehicle without additional systems, but the coasting distance cannot be maximized due to insufficient reaction time to varying road and traffic conditions
Solution Approach 1:
The system performs preliminary calculations of coasting distance based on vehicle information (weight, speed) and environmental information (road slope, curvature, weather) before the driver needs to make a decision. The controller pre-determines optimal coasting opportunities and provides advance guidance to the driver, allowing the driver to disengage the accelerator pedal at the right time to maximize coasting distance without needing to react instantly to changing conditions
Solution Approach 2:
The system introduces an intermediary controller that acts as a mediator between the driver and the complex task of optimizing coasting. The controller collects vehicle and environmental data, calculates coasting distances, and translates this information into simple driver guidance messages. This intermediary handles the computational complexity while presenting a simple interface to the driver, resolving the contradiction between maximizing coasting distance and maintaining ease of operation
2Measurement precision
If the system collects comprehensive vehicle and environmental information to accurately determine coasting opportunities, then the accuracy of coasting distance calculation is improved, but the information processing complexity and time required increase
Solution Approach 1:
The information processing task is segmented into distinct functional units: an information collection unit that gathers vehicle data (weight, speed, position) and environmental data (road slope, curvature, weather), and a controller that processes this segmented information to calculate coasting distance. This segmentation allows each unit to specialize in specific tasks, improving calculation accuracy while making the overall system more manageable and less complex
Solution Approach 2:
The system implements feedback by continuously monitoring vehicle information and environmental conditions, comparing actual conditions with calculated coasting parameters, and adjusting guidance accordingly. The controller uses feedback from sensors measuring vehicle weight, speed, and position combined with map data on road geometry and weather information to dynamically recalculate optimal coasting distances, ensuring high accuracy while processing information efficiently through iterative refinement
3Loss of energy
If the system provides real-time coasting guidance based on varying road and traffic conditions, then fuel consumption is improved, but the system requires continuous data collection and processing that increases energy consumption
Solution Approach 1:
The system performs preliminary calculations of coasting distance using vehicle information and environmental data before coasting is actually executed. By pre-calculating optimal coasting opportunities and distances based on road slope, curvature, and traffic conditions, the system enables the driver to coast more effectively, reducing fuel consumption. The energy spent on calculation is minimal compared to the fuel savings achieved through optimized coasting behavior
Solution Approach 2:
The system dynamically changes operational parameters based on real-time conditions. It adjusts coasting guidance by changing key parameters such as vehicle speed targets, coasting distance thresholds, and acceleration/disengagement timing based on vehicle weight, road slope, curvature, and weather conditions. This parameter adaptation allows the system to optimize fuel consumption across varying driving conditions while keeping processing requirements manageable through focused parameter monitoring rather than comprehensive continuous analysis
Data Source
AI summary
A system and method for assisting a driver are provided. The method includes receiving, by a controller, vehicle traveling information and calculating a first distance between a present vehicle position and an end node. In addition, the controller is configured to calculate a second distance between the present vehicle position and a preceding vehicle based on the receiving information and calculate a third distance in which coasting is available until a present vehicle speed reaches a predetermined target speed. The method further includes determining, by the controller, whether coasting is available based on the first distance, the second distance, the third distance in which coasting is available, and a present vehicle speed of the vehicle, and outputting, when coasting is available, a message that instructs coasting.