Vehicle Ride Control for Predictive Road Obstacle Mitigation
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Solution Overview
Problem
Current driver assist systems in autonomous vehicles lack the data and intelligence to effectively navigate road obstacles such as potholes and manholes, leading to an uncomfortable ride and increased wear and tear on vehicles.
Innovation Solution
A vehicle control system that uses bump prediction and mitigation, lane placement adjustments, and crowd-sourced data sharing to anticipate and avoid obstacles by monitoring leading vehicles and accessing a database of known hazards, allowing for proactive steering and suspension adjustments to maintain a smooth ride.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driver assist systems use conventional sensors and algorithms to detect road obstacles, then basic collision avoidance is achieved, but the systems lack the data and intelligence to effectively navigate obstacles like potholes and manholes, resulting in uncomfortable rides and increased vehicle wear
Solution Approach 1:
The patent combines multiple data sources including camera images, LIDAR data, map data, and real-time sensor information into a unified obstacle detection and classification system. This integration allows the system to achieve high reliability in detecting various road obstacles by cross-validating information from multiple sources rather than relying on a single sensor type.
Solution Approach 2:
The system introduces an artificial intelligence processing layer that acts as an intermediary between raw sensor data and control actions. This AI layer classifies obstacles, predicts their properties, and generates navigation commands, effectively bridging the gap between conventional sensors and the complex decision-making required for comfortable obstacle navigation.
2Loss of energy
If the vehicle maintains a steady course without adjustment, then fuel efficiency is improved, but the vehicle will hit obstacles causing discomfort and wear
Solution Approach 1:
The system performs preliminary obstacle detection and classification using camera images, LIDAR, and map data before the vehicle reaches the obstacle. By identifying potential hazards in advance and calculating optimal avoidance trajectories, the system can make smooth steering adjustments that minimize energy consumption while preventing obstacle impacts.
Solution Approach 2:
The navigation system dynamically adjusts the vehicle's course based on real-time obstacle detection and classification. Rather than maintaining a rigid steady course, the system continuously optimizes the trajectory to balance fuel efficiency with obstacle avoidance, making smooth, minimal adjustments only when necessary to navigate around detected hazards.
3Ease of operation
If the system uses extensive sensor arrays and AI processing to detect and avoid obstacles, then ride comfort is improved, but the device complexity and cost increase
Solution Approach 1:
The system applies different levels of detection and processing to different regions of interest. High-resolution camera images and LIDAR are focused on areas where obstacles are most likely to occur, while other areas use less intensive monitoring. This localized approach provides high ride comfort in critical zones without requiring intensive processing across the entire field of view.
Solution Approach 2:
The patent designs the sensor array and processing system to perform multiple functions simultaneously: obstacle detection, classification, distance measurement, and trajectory prediction. This multi-functionality reduces the need for separate specialized systems, thereby improving ride comfort through comprehensive obstacle awareness while limiting the increase in device complexity through shared hardware resources.
4Reliability
If the vehicle proactively adjusts steering and suspension to avoid obstacles, then passenger comfort and vehicle maintenance are improved, but the control system complexity increases
Solution Approach 1:
The system performs preliminary obstacle detection and classification before the vehicle reaches the obstacle, allowing advance preparation of avoidance maneuvers. By identifying obstacles early and calculating optimal trajectories in advance, the control system can execute smooth steering and suspension adjustments without requiring complex real-time reaction control, thereby improving vehicle maintenance through preventive navigation while limiting control system complexity.
Data Source
AI summary
Various systems and methods for providing a vehicle control system are described herein. A system for managing a vehicle comprises: a vehicle control system of a vehicle having access to a network, including: a communication module to interface with at least one of: a mobile device, the vehicle, and environmental sensors coupled to the vehicle; and a configuration module to identify a mitigation operation to be taken when predetermined factors exist; wherein the vehicle control system is to identify a potential obstacle in a travel route of the vehicle and initiate a mitigation operation at the vehicle.