Automated Vehicle Emergency Stop Modes for Highway Risk Minimization
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Solution Overview
Problem
Existing advanced driver assistance systems (ADAS) fail to effectively minimize the risk of collisions during automated driving by not providing appropriate responses to unexpected events on the highway.
Innovation Solution
A vehicle system that includes sensors, a processor, and a controller to monitor the vehicle's state and surrounding environment, determine the type of emergency stop necessary to minimize collision risk, and execute the appropriate maneuver, such as straight-ahead, in-lane, half-shoulder, or full-shoulder stopping, using artificial intelligence to analyze images of the vehicle's state and environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle executes a minimal risk maneuver to minimize collision risk, then safety is improved, but the complexity of the control system increases
Solution Approach 1:
The emergency stop control is divided into multiple discrete types (straight-ahead stopping, in-lane stopping, half-shoulder stopping, full-shoulder stopping), each with specific execution conditions. This segmentation allows the system to select appropriate responses based on situation without requiring complex continuous decision-making algorithms.
Solution Approach 2:
The system pre-defines multiple emergency stop types and their execution conditions before runtime. When an unexpected event occurs, the processor quickly matches the current situation against pre-established conditions and executes the corresponding stop type, avoiding complex real-time optimization calculations.
2Measurement precision
If the vehicle monitors multiple state parameters and environmental information, then the accuracy of emergency stop determination is improved, but the amount of data processing and system complexity increases
Solution Approach 1:
The monitoring system is divided into distinct functional modules: a sensor module for detecting vehicle state information (brake control availability, steering control availability, lane change availability), a processor for determining emergency stop types based on pre-defined conditions, and a controller for execution. This modular segmentation simplifies data processing by assigning specific detection and determination tasks to dedicated components.
Data Source
AI summary
An embodiment method for operating a vehicle includes monitoring a state of the vehicle, determining a type of an emergency stop from a plurality of types of emergency stops based on the state of the vehicle, and executing the determined type of the emergency stop. An embodiment vehicle includes sensors, a processor configured to control automated driving of the vehicle based on state information of components of the vehicle and surrounding environment information of the vehicle detected by the sensors, and a controller configured to control an operation of the vehicle based on a control of the processor, wherein the processor is further configured to monitor a state of the vehicle, determine a type of an emergency stop from a plurality of types of emergency stops based on the state of the vehicle, and execute the determined type of the emergency stop by controlling the controller.