Distracted Driver Detection Using Wheel Speed and Proximity Data
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Solution Overview
Problem
Current distracted driver detection systems are complex and expensive, requiring advanced driver-assistance systems (ADAS) equipment, making them inaccessible and difficult to integrate into existing vehicles, and fail to effectively detect distracted drivers in stop-and-go traffic scenarios without using data from driver monitoring or ADAS equipment.
Innovation Solution
A computer-implemented method and system using conventional vehicle sensors like wheel speed and proximity sensors to detect if a vehicle is disrupting traffic flow and if the driver is distracted, without relying on ADAS data, and outputs alerts through the vehicle's infotainment system or haptic feedback to reengage the driver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If advanced driver-assistance systems (ADAS) equipment and driver monitoring equipment are used to detect distracted drivers, then detection accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a virtual model of expected driver behavior by analyzing vehicle operation data patterns. Instead of using complex ADAS hardware, the system copies the functional capability of driver monitoring through software-based analysis of existing sensor data, achieving detection accuracy without the physical complexity of dedicated monitoring equipment
Solution Approach 2:
The patent replaces mechanical/hardware-based driver monitoring systems with a software-based algorithmic approach. The distracted driver detection algorithm substitutes physical driver monitoring equipment with computational analysis of vehicle operation data, eliminating the need for complex mechanical sensor systems while maintaining detection capability
2Reliability
If advanced driver-assistance systems (ADAS) equipment is installed in existing vehicles, then distracted driver detection capability is improved, but ease of manufacture and integration worsen
Solution Approach 1:
The patent makes existing vehicle sensors serve multiple functions - they continue their original purposes while also providing data for distracted driver detection. The wheel speed sensors and proximity sensors are used both for their primary vehicle control functions and for the secondary function of detecting distracted driving patterns, eliminating the need for separate dedicated hardware
Solution Approach 2:
The system copies the detection capability function from complex ADAS systems by using existing vehicle sensors in a novel analytical way. Rather than installing new hardware, the patent replicates the essential detection function through software analysis of data from sensors already present in conventional vehicles
3Device complexity
If conventional vehicle sensors are used to detect distracted drivers, then device complexity is reduced, but measurement precision may worsen
Solution Approach 1:
The patent segments the detection task into multiple independent analysis components that process different sensor data types separately. The system divides vehicle operation data into distinct parameters (wheel speed patterns, proximity changes, acceleration profiles) and analyzes each segment independently before combining results, improving overall detection precision through systematic multi-factor analysis
Solution Approach 2:
The patent uses excessive data collection from existing sensors to compensate for the simplicity of individual measurement points. By gathering and analyzing multiple parameters beyond what a single sensor would provide (combining wheel speed, proximity, acceleration data), the system achieves high detection precision through the cumulative information from conventional sensors
4Measurement precision
If distracted driver detection algorithm analyzes multiple data parameters, then detection accuracy is improved, but use of energy increases
Solution Approach 1:
The patent implements periodic analysis of vehicle operation data rather than continuous processing. The distracted driver detection algorithm analyzes sensor data at specific intervals or triggered by certain conditions (such as changes in traffic flow patterns), reducing computational energy consumption while maintaining detection accuracy through strategically timed analysis cycles
Data Source
AI summary
A method for distracted driver detection and alert includes receiving vehicle speed data from one or more wheel speed sensors disposed on the vehicle and receiving proximity data from one or more proximity sensors disposed on the vehicle, the proximity data indicating a distance of the vehicle relative to any objects in front of the vehicle. The method also includes executing a distracted driver detection algorithm that uses the vehicle speed data and the proximity data to determine the vehicle is disrupting a flow of stop and go traffic and a driver of the vehicle is distracted from operating the vehicle. The method includes, based on determining that both the vehicle is disrupting the flow of stop and go traffic and the driver of the vehicle is distracted, instructing a system of the vehicle to output an alert to reengage the driver.