Autonomous Track Driving Assistance for Optimal Racing Line Guidance
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Solution Overview
Problem
High-performance sports cars are underutilized on public roads due to speed limits, and inexperienced drivers face challenges in understanding optimal driving techniques, leading to inefficient performance and safety risks, while existing driver assistance systems interfere too much and fail to optimize cost functions like time or mileage effectively.
Innovation Solution
A method for performance-enhancing driver assistance using a road vehicle equipped with localization, ADAS sensors, a control system, and an interface to optimize driving commands based on environmental and dynamic data, calculating an optimal trajectory and suggesting corrective actions to the driver, while also allowing autonomous control to maintain safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electronic driver assistance devices continuously intervene to prevent dangerous driving, then safety is improved, but driving pleasure and performance enjoyment are reduced
Solution Approach 1:
The system dynamically adjusts the level of intervention based on detected driving conditions. When dangerous situations are detected, corrective commands are applied; when normal driving occurs, the system remains passive. This dynamic behavior allows the system to maintain safety when needed while preserving driving pleasure during normal operation.
Solution Approach 2:
The system changes the parameter of intervention intensity based on the detected driving situation. By monitoring various vehicle parameters and driving behavior, the system adjusts whether to intervene or remain passive, effectively changing the intervention parameter from constant to conditional, thus resolving the contradiction between safety and driving pleasure.
2Ease of operation
If informative messages are provided to the driver instead of automatic intervention, then driving pleasure is improved, but safety assurance is reduced
Solution Approach 1:
The system applies partial intervention only when necessary for safety, rather than continuous intervention or purely informative messages. By applying corrective commands selectively in dangerous situations while remaining passive during normal driving, the system achieves both safety assurance and driving pleasure through balanced partial action.
3Speed
If the driver attempts to maximize speed on public roads, then performance is improved, but safety risks increase due to speed limits and driving ability
Solution Approach 1:
The system continuously monitors driving conditions, vehicle state, and environmental factors, providing feedback through selective intervention. When the driver attempts unsafe high-speed maneuvers, the system detects the dangerous condition and applies corrective commands to bring the vehicle back to safe operating parameters, thus managing the trade-off between performance and safety through real-time feedback.
4Reliability
If existing driver assistance systems change commands based on current vehicle state, then immediate safety is improved, but optimization of cost functions like time and mileage is not achieved
Solution Approach 1:
The system calculates optimal trajectories in advance based on the desired cost function (time, mileage, etc.) and current vehicle state. By pre-computing the optimal path and comparing it with actual driving, the system can provide corrective commands that both ensure immediate safety and optimize long-term performance objectives, achieving both safety and productivity goals.
Data Source
AI summary
A method for the performance-enhancing driver assistance of a road vehicle driven on a track. The method comprises the steps of defining a dynamic model of the road vehicle, determining the actual position and orientation of the road vehicle, detecting a plurality of space data concerning the structure of the track, detecting a plurality of dynamic data of the vehicle, determining a passing through point of the road vehicle arranged in front of the road vehicle, solving an optimum control problem aimed at optimizing a cost function, taking into account, as boundary conditions, the plurality of environmental data, the actual position and the passing through point, so as to compute a mission optimizing the cost function, and driving the vehicle in an autonomous manner so as to show to the driver the mission optimizing the cost function.