Vehicle Lane Change Control via Traffic Density Assessment
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Solution Overview
Problem
Current driver assistance systems struggle to accurately judge and prevent dangerous lane changes, particularly when high speed differences exist between lanes, leading to potential collisions due to late detection of following vehicles.
Innovation Solution
A control system that uses environmental sensors to detect following vehicles, determine lane associations, and assess traffic density to provide safe/unsafe lane change indications and perform autonomous lane changes based on determined traffic conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional environmental sensors are used to detect following vehicles, then the system structure remains simple, but the detection precision deteriorates due to high speed differences between lanes causing late detection
Solution Approach 1:
The patent divides the detection task into multiple specialized sensor units: radar sensors for detecting vehicles in adjacent lanes, lidars for measuring distances to multiple vehicles simultaneously, and cameras for visual confirmation. This segmentation allows each sensor type to optimize for its specific detection function, improving overall measurement precision without requiring a single overly complex sensor system
Solution Approach 2:
The control system integrates multiple sensor types (radar, lidar, camera) into a unified multi-functional platform that performs various detection functions: detecting vehicle presence, measuring distances, determining speeds, and identifying lane positions. This universal system handles both low-speed and high-speed detection scenarios simultaneously, improving detection precision across different speed differences while managing complexity through integrated control
2Reliability
If the system monitors only vehicles directly behind the own vehicle, then the device complexity remains low, but the reliability deteriorates due to inability to judge traffic density in adjacent lanes
Solution Approach 1:
The system expands monitoring from a single dimension (vehicles directly behind) to multiple spatial dimensions by detecting vehicles in adjacent lanes using radar and lidar sensors positioned on the vehicle. This multi-dimensional monitoring captures traffic density information across lateral dimensions, improving lane change safety assessment while managing complexity through geometric sensor arrangement
Solution Approach 2:
The system continuously monitors and stores traffic density information in adjacent lanes before a lane change is initiated. By preliminarily detecting and recording the positions and speeds of vehicles in neighboring lanes, the system prepares safety assessment data in advance, ensuring reliable lane change decisions without requiring complex real-time calculations at the moment of lane change
3Productivity
If the system provides only basic vehicle detection warnings, then the ease of operation remains high, but the productivity deteriorates due to inability to enable autonomous lane changes
Solution Approach 1:
The control system dynamically adjusts its operation mode based on detected traffic conditions. When traffic density in adjacent lanes is low and safety conditions are met, the system autonomously executes lane changes to improve productivity. When conditions are uncertain or complex, the system transitions to providing warning indications to the driver, maintaining ease of operation. This dynamic adaptation resolves the contradiction between automation efficiency and operational simplicity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances driver safety by providing timely warnings and reducing the risk of collisions during lane changes by accurately assessing traffic density and speed differences, making lane changes safer for both human-driven and autonomous vehicles.
Implementation Method 1
These determine, for example by means of radar, lidar, video or the like, whether another vehicle, road user or object is located to the side of and/or behind the vehicle
Implementation Method 2
These determine, for example by means of radar, lidar, video or the like, whether another vehicle, road user or object is located to the side of and/or behind the vehicle
Data Source
AI summary
Control system, which is adapted for application in a vehicle and intended to detect following vehicles on the basis of environmental data which are obtained from one or several environmental sensors disposed on the vehicle. The environmental sensors are adapted to provide an electronic controller of the control system with the environmental data which reflect the area in front of, laterally next to and/or behind the vehicle. The control system is at least adapted and intended to detect one or several other vehicles participating in traffic behind the own vehicle with the environmental sensors. A lane associated with each other vehicle, in which the other vehicle(s) drive(s), is detected. A traffic density of the own lane and/or of at least one adjacent lane by the other vehicle(s) is determined. On the basis of the determined traffic density (i) an indication on a safe or unsafe lane change to a specific of the at least one adjacent lane is output and/or (ii) an autonomous lane change to the specific of the at least one adjacent lane is performed by the own vehicle if the determined traffic density allows a safe change of lane.