External Vehicle Driving State Detection Using Lateral Distance Variation
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Solution Overview
Problem
Conventional vehicles without advanced driving assistance systems struggle to accurately detect the driving state of external motor vehicles, particularly those with partial or autonomous driving capabilities, which can lead to unpredictable behavior in traffic scenarios.
Innovation Solution
A method and device using conventional sensors to detect the driving state of external motor vehicles by measuring distances and speed, determining if the vehicle is in an assistance-supported or non-assistance-supported state by comparing longitudinal and lateral control data, and adjusting measurement intervals based on vehicle type and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional sensors are used to detect external motor vehicles, then device complexity is reduced and cost is lowered, but measurement precision and reliability of detecting driving state deteriorate
Solution Approach 1:
The patent segments the detection task into multiple independent measurement components: longitudinal distance measurement, lateral distance measurement, and temporal interval measurement. Each component uses simple conventional sensors optimized for its specific function, avoiding the need for a single complex sensor system while achieving reliable driving state detection through the combination of segmented measurements
Solution Approach 2:
The patent dynamically adjusts the measurement interval based on the detected speed of the external motor vehicle. When the vehicle is moving faster, measurements are taken more frequently, and when slower, less frequently. This dynamic adaptation maintains detection reliability across varying operating conditions while keeping the sensor system simple and avoiding continuous high-rate measurement
2Reliability
If assistance-supported driving systems are deployed in more vehicles, then reaction time and safety improve, but predictability of traffic behavior deteriorates
Solution Approach 1:
The patent implements feedback by detecting the driving state of external vehicles and using this information to adapt the own vehicle's driving behavior. The system continuously monitors lateral distance variations of external vehicles and adjusts its own lateral control accordingly, creating a feedback loop that improves safety while making traffic interactions more predictable through coordinated responses
Solution Approach 2:
The patent performs preliminary detection and classification of external vehicle driving states before critical situations arise. By continuously monitoring and identifying assistance-supported vehicles in advance, the system can proactively adjust its behavior patterns, maintaining safety margins and predictable interaction modes before unexpected maneuvers occur
3Manufacturing precision
If lateral control is performed automatically in assistance-supported vehicles, then manufacturing precision of driving path improves, but difficulty of detecting and measuring driving state by conventional sensors increases
Solution Approach 1:
The patent exploits the self-characteristic of assistance-supported vehicles: they naturally maintain more constant lateral distances to references (road markings, curbs) compared to human-driven vehicles. The detection system simply observes this self-generated pattern without needing to interpret complex control signals or vehicle states, turning the vehicles' own control behavior into a detectable signature
Solution Approach 2:
The patent changes the detection parameter from attempting to directly measure vehicle control status (which is difficult) to measuring the observable consequence: lateral distance variation over time. This parameter transformation converts an invisible control state into a visible spatial pattern that conventional sensors can reliably detect
Data Source
AI summary
A method that determines a driving state of an external motor vehicle includes: detecting the external motor vehicle by at least one sensor, the external vehicle moving in a longitudinal direction; determining a reference for a motion of the external motor vehicle transverse to the longitudinal direction; determining a first distance between the external motor vehicle and the reference at a first point in time; determining a second distance between the external motor vehicle and the reference at a second point in time lying after the first point in time; determining a difference between the first distance and the second distance; and determining the driving state as assistance-supported if the difference is less than or equal to a specified value.