Wrong-Way Driving Detection Using Sensor Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current vehicle warning systems are inadequate for detecting wrong direction driving in real-time, especially in areas without high-definition maps, leading to delays in response and potential hazards for other vehicles.
Innovation Solution
A system comprising sensors, processors, and computer-readable instructions that determine lane geometry and direction of travel using sensor data, identifying non-compliant vehicles driving in the wrong direction and transmitting warnings to other vehicles and authorities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-definition maps and GPS are used to detect wrong direction driving, then detection accuracy is improved, but system complexity and dependency on external data increase
Solution Approach 1:
The system uses its own sensors (cameras, LIDAR, radar) to detect lane markings, road geometry, and vehicle positions, making the system self-sufficient without requiring external GPS or high-definition map data. The sensors process local environmental information to determine wrong-way driving conditions.
Solution Approach 2:
The patent replaces GPS-based mechanical positioning systems with sensor-based optical and electromagnetic detection systems. Instead of relying on satellite signals and map data, the system uses cameras to detect lane markings, LIDAR for 3D mapping, and radar for vehicle detection, substituting complex external data dependencies with direct environmental sensing.
2Adaptability or versatility
If real-time detection without GPS or map data is implemented, then system adaptability is improved, but measurement precision may deteriorate
Solution Approach 1:
The system employs multiple sensor types (cameras, LIDAR, radar) that can function in various conditions and environments. These sensors can detect lane markings, road geometry, and vehicle positions through different physical principles, making the system adaptable to different road types, weather conditions, and locations without requiring GPS or map data.
Solution Approach 2:
The system uses sensor-detected lane markings and road geometry as intermediaries to determine the correct direction of travel. Instead of relying on GPS coordinates or map data, the sensors capture visual and spatial information about the road infrastructure, which serves as an intermediary reference to identify wrong-way driving conditions with high precision.
3Loss of time
If sensors and processors are used to detect wrong direction driving, then response time is improved, but energy consumption increases
Solution Approach 1:
The sensors continuously monitor the driving environment, capturing lane markings, road geometry, and vehicle positions in real-time. This continuous data flow allows the system to immediately detect wrong-way driving conditions without delay, maintaining constant vigilance through uninterrupted sensor operation and real-time processing.
Solution Approach 2:
The system divides the detection task into separate functional modules: camera-based lane marking detection, LIDAR-based 3D mapping, radar-based vehicle detection, and central processing for wrong-way determination. This segmentation allows each sensor to focus on specific detection aspects, improving overall efficiency and reducing redundant energy consumption while maintaining fast response times.
Data Source
AI summary
Systems, vehicles and methods for determining wrong direction driving are disclosed. In one embodiment, a system for determining a vehicle traveling in a wrong direction includes one or more sensors that produce sensor data, one or more processors, and one or more non-transitory computer-readable medium storing computer readable-instructions. When the computer-readable instructions are executed by the one or more processors, the computer-readable instructions cause the one or more processors to determine one or more lanes within a roadway using the sensor data, determine a direction of travel of the one or more lanes using the sensor data, and identify a non-compliant vehicle traveling in a direction in the one or more lanes that is different from the determined direction of travel in the one or more lanes.