Dynamic Sensor Control for Vehicle Stop Reason Identification
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Solution Overview
Problem
Conventional roadside assistance systems fail to distinguish between urgent and non-urgent situations causing vehicle stops, leading to inefficient or inappropriate assistance, especially in unfamiliar areas where users may struggle to request help safely and effectively.
Innovation Solution
A system that analyzes real-time data to determine a vehicle's location and reason for stopping, using sensors and diagnostic codes to differentiate between urgent and non-urgent situations, and automatically requests assistance or provides information based on the situation, including notifications to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional roadside assistance systems are used, then vehicles can receive assistance when stopped, but the system cannot distinguish between urgent and non-urgent situations leading to inefficient or inappropriate assistance
Solution Approach 1:
The system dynamically adjusts its response based on real-time analysis of the vehicle's situation. It continuously monitors diagnostic codes, location data, and vehicle status to determine whether the stop is urgent or non-urgent, and adapts the assistance response accordingly - automatically requesting help for urgent situations while only offering assistance for non-urgent ones
Solution Approach 2:
The system incorporates feedback loops that analyze vehicle diagnostic data, location information, and stopping patterns to continuously improve its classification accuracy. The feedback mechanism allows the system to learn from previous identifications and refine its ability to distinguish between urgent and non-urgent situations over time
2Measurement precision
If the system collects and processes detailed sensor data to identify stop reasons, then the accuracy of issue identification improves, but the complexity of data processing increases
Solution Approach 1:
The system extracts and focuses on specific key indicators from the vast amount of available sensor data - primarily diagnostic codes, location information, and vehicle operational status. By selectively extracting only the most relevant data elements rather than processing all available data, the system achieves high identification accuracy while managing processing complexity
Solution Approach 2:
The data processing is segmented into distinct analytical stages: collecting raw sensor data, filtering for relevant parameters (diagnostic codes, location, vehicle status), analyzing the combination of factors to determine stop reason, and generating the appropriate response. This segmentation allows each stage to be optimized independently
3Ease of operation
If the system automatically requests roadside assistance for all stopped vehicles, then user convenience is improved, but unnecessary assistance requests increase wasting resources
Solution Approach 1:
The system changes the parameter of assistance request generation based on the classified stop reason. For urgent situations, it automatically generates assistance requests without user intervention. For non-urgent situations, it either generates no request or generates one only after explicit user confirmation, thereby changing the resource allocation behavior based on situation severity
Data Source
AI summary
Systems and apparatuses for identifying a type of issue associated with a stopped vehicle are provided. The system may determine a current location of the vehicle and determine whether the vehicle is currently located on a highway. In some examples, the determined location of the vehicle may cause the system to transmit instructions controlling an amount or type of data collected by sensors and/or transmitted to the system. If the vehicle is on a highway, the system may then determine whether the vehicle is stopped. If so, the system may determine a reason for the vehicle stopping. Upon determining that the vehicle is stopped for an urgent reason, the system may transmit a request for roadside assistance to a service provider computing device and may generate a first type of notification. Upon determining that the vehicle is stopped for a non-urgent situation reason, the system may generate and transmit a second type of notification for display.