Road Hazard Prediction System for Vehicle Speed Control
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Solution Overview
Problem
Existing vehicle safety systems, such as ABS and TCS, cannot predict future traction losses, making it difficult for vehicles to slow down before encountering dangerous conditions, which can lead to accidents due to slippery roads.
Innovation Solution
A computer-based system that receives vehicle status information, including location and speed, and obtains weather and road conditions to determine a suggested speed for an upcoming location, adjusting the vehicle's speed and following distance to prevent traction losses by using algorithmic or machine-learning models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ABS and TCS are used to aid a driver after traction is lost, then vehicle control is improved, but the ability to predict future traction losses is lost
Solution Approach 1:
The system performs preliminary actions by predicting future traction losses before they occur. It analyzes current vehicle dynamics, road conditions, and environmental factors to forecast potential traction issues ahead of time, allowing the vehicle to take preventive measures rather than reacting after traction is lost.
Solution Approach 2:
The system implements continuous feedback loops where sensor data from vehicle dynamics, road condition sensors, and environmental sensors are constantly monitored. This feedback is processed to update predictions of future traction losses, creating a closed-loop system that adapts to changing conditions and improves prediction accuracy over time.
2Device complexity
If the vehicle cannot predict future traction losses, then system complexity is reduced, but vehicle safety is worsened
Solution Approach 1:
The prediction system is segmented into multiple independent modules: environmental sensing subsystem, road condition sensing subsystem, vehicle dynamics monitoring subsystem, and prediction algorithm subsystem. Each module handles a specific aspect of the prediction task, making the overall system manageable and maintainable while providing comprehensive safety predictions.
Solution Approach 2:
The system introduces an intermediary prediction layer between the sensors and the vehicle control systems. This intermediary processing layer analyzes data from multiple sources, generates predictions about future traction losses, and then communicates these predictions to appropriate control systems, thereby enhancing safety without requiring direct complex integration between all sensors and actuators.
3Reliability
If the vehicle slows down before dangerous conditions are encountered, then accident risk is reduced, but driving efficiency is worsened
Solution Approach 1:
The system applies preliminary anti-action by identifying potential dangerous conditions ahead of time and taking countermeasures before the vehicle actually encounters the hazard. By predicting future traction losses and suggesting speed adjustments in advance, the system prevents accidents without requiring continuous aggressive braking or speed reductions.
Solution Approach 2:
The system dynamically adjusts speed recommendations based on real-time predictions of upcoming hazards. Rather than maintaining a constantly reduced speed, the system provides targeted speed suggestions only when and where needed based on predicted conditions, allowing the vehicle to maintain optimal speed in safe conditions while reducing speed proactively only when hazards are anticipated.
Data Source
AI summary
A cloud application may suggest speeds to vehicles based on weather and road conditions in order to improve vehicle safety. Status information associated with a vehicle may be received from one or more computing devices associated with the vehicle. The status information may comprise a location and a speed of the vehicle. A weather condition and a road condition associated with an upcoming location of the vehicle may be obtained. The upcoming location may be determined based at least in part on the received location of the vehicle. A suggested speed at the upcoming location may be determined for the vehicle based at least in part on the weather condition and the road condition. It may be determined that the received speed of the vehicle is greater than the suggested speed. The suggested speed may be sent to the one or more computing devices associated with the vehicle.