Adaptive Cruise Control With Variable Time Gap on Curves
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Solution Overview
Problem
Existing adaptive cruise control (ACC) systems have fixed time headways that do not adjust with changes in vehicle velocity, leading to potential collisions and inadequate response strategies for scenarios like cornering, overtaking, and lane changing, resulting in poor user experience and safety issues.
Innovation Solution
An ACC device and method that utilizes a variable time gap calculation model to adjust cruising velocity based on real-time changes in the time headway, incorporating cornering and overtaking strategies to enhance safety and responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the host vehicle speed is limited to below the target speed in a curve, then the risk of vehicle rollover is reduced, but the vehicle performance and driving efficiency deteriorate due to excessive speed reduction
Solution Approach 1:
The system dynamically adjusts the speed limitation parameter based on curve characteristics. Instead of applying a fixed speed limit below target speed, the controller calculates an appropriate speed limit by considering curve radius, gradient, and super elevation, allowing the speed parameter to change adaptively to maintain both safety and driving efficiency
Solution Approach 2:
The speed limitation strategy transitions from static to dynamic by continuously monitoring curve parameters and adjusting the target speed accordingly. The system uses real-time data from sensors to modify speed commands, enabling the vehicle to maintain optimal speed through varying curve conditions rather than applying uniform speed reduction
2Reliability
If the host vehicle speed is limited to below the target speed regardless of curve characteristics, then the vehicle rollover risk is reduced, but the appropriateness of speed limitation deteriorates leading to unnecessary speed reduction
Solution Approach 1:
The system applies different speed limitation strategies to different sections of the road based on local curve characteristics. By evaluating curve radius, gradient, and super elevation at each location, the controller tailors the speed limitation to the specific local conditions rather than applying a universal speed reduction rule
Solution Approach 2:
The system performs preliminary evaluation of curve parameters before applying speed limitation. By detecting curve characteristics in advance and calculating the appropriate speed limit beforehand, the system prepares the optimal speed command that balances safety requirements with driving efficiency before the vehicle enters the curve
3Productivity
If the curvature threshold is set high to avoid excessive speed reduction, then the driving efficiency is maintained, but the detection precision of dangerous curves deteriorates leading to missed rollover prevention
Solution Approach 1:
The system changes from using a single curvature threshold to using multiple parameters including curve radius, gradient, and super elevation in combination. This multi-parameter approach allows the system to detect dangerous curves with higher precision without relying on an overly sensitive curvature threshold that would cause excessive speed reduction
Solution Approach 2:
The detection system transitions from one-dimensional curvature detection to multi-dimensional evaluation by incorporating gradient and super elevation parameters. This dimensional expansion enables more accurate identification of dangerous curves through comprehensive parameter analysis rather than relying solely on curvature magnitude
4Adaptability or versatility
If multiple parameters (curve radius, gradient, super elevation) are used to determine speed limit, then the speed limitation appropriateness is improved, but the device complexity increases due to additional sensors and calculations
Solution Approach 1:
The system achieves multi-functionality by using a single controller to perform multiple tasks: detecting curve parameters, calculating speed limits, and controlling vehicle speed. The controller integrates various sensor inputs and performs comprehensive speed limitation control without requiring separate dedicated devices for each function
Solution Approach 2:
The system merges the detection and control functions into a unified process. By combining curve parameter detection with speed limit calculation and execution in one integrated control flow, the system reduces overall complexity compared to having separate independent systems for each function
Data Source
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AI summary
The present disclosure provides an adaptive cruise control (ACC) device and method for a vehicle. The ACC method includes: enabling an ACC function based on an operating signal of a driver, and after the ACC function is enabled, setting, by the driver, a cruising velocity in an ACC mode; determining, by an ACC module, whether there is another vehicle in front of a current vehicle; and if there is no vehicle in front of the current vehicle, enabling the current vehicle to travel at the cruising velocity set by the driver; or if there is another vehicle in front of the current vehicle, enabling, by the ACC module, a variable time gap calculation model to calculate a time headway between the current vehicle and the front vehicle in real time, and adjusting, by the ACC module, the cruising velocity of the current vehicle based on the time headway calculated in real time; and when the current vehicle is cornering in the ACC mode, adjusting, by the ACC module, the cruising velocity of the current vehicle based on a cornering strategy. The present disclosure utilizes the variable time gap calculation model to calculate the time headway in real time and allows a prompt response to acceleration and deceleration of the front vehicle, thereby greatly shortening response time of the driver. An ACC system in the present disclosure has rich functions and can meet diverse needs of users.