Driving Direction Determination Using Lateral Position Data
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Solution Overview
Problem
Determining the driving direction in complex road geometries is challenging, particularly in cases of wrong-way driving, which can lead to accidents and fatalities, and is further complicated in autonomous driving applications.
Innovation Solution
A system that uses sensor data, including location and lateral position data, to identify links and calculate half width data, determining the driving direction by comparing this data with vehicle width data and generating notifications based on confidence values to prevent accidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional navigation systems are used in complex road geometries, then basic navigation is provided, but accuracy in determining driving direction deteriorates leading to wrong-way driving
Solution Approach 1:
The system segments the determination of driving direction into multiple independent components: obtaining sensor data (location, lateral position, vehicle width), identifying links via map-matching, calculating half width data, and comparing parameters. This modular segmentation allows each component to be optimized independently while maintaining overall system accuracy in complex road geometries.
Solution Approach 2:
The patent introduces lateral position data as an additional dimensional parameter beyond traditional location data. By incorporating lateral position (distance from road centerline) and calculating half width data, the system creates a multi-dimensional assessment framework that enables more accurate driving direction determination in complex road geometries where traditional 2D location data insufficient.
2Measurement precision
If more sensor data is collected to improve driving direction accuracy, then measurement precision improves, but data processing complexity increases
Solution Approach 1:
The system extracts only the essential parameters needed for driving direction determination from sensor data: location data, lateral position data, and vehicle width data. By selecting and processing only these critical parameters rather than all available sensor data, the system maintains high measurement precision while minimizing data processing complexity and computational burden.
Solution Approach 2:
The system performs preliminary map-matching to identify the relevant road link before conducting the driving direction determination. This preliminary action of identifying the correct road segment and its geometric parameters (half width data) in advance simplifies the subsequent comparison process, reducing the overall data processing complexity while maintaining accuracy.
3Loss of time
If real-time sensor data processing is implemented to provide timely notifications, then response time improves, but computational load increases
Solution Approach 1:
The system implements partial processing by focusing computational resources only on the critical comparison between lateral position data and half width data to determine driving direction. Rather than processing all sensor data in real-time, the system performs only the essential calculations needed for wrong-way driving detection, reducing computational energy consumption while maintaining timely notification response.
Solution Approach 2:
The system uses pre-stored map data and pre-calculated road geometry parameters (half width data) to avoid redundant real-time computations. By having this reference data readily available, the system can perform rapid comparisons with current sensor data without requiring intensive real-time computation, thus reducing energy consumption while maintaining fast response times.
Data Source
AI summary
A system is disclosed for determining a driving direction. The system may include a memory configured to store computer-executable instructions; and at least one processor configured to execute the computer-executable instructions to obtain sensor data associated with a vehicle. The sensor data may include at least location data of the vehicle and lateral position data of the vehicle. Further, the processor is configured to execute the computer-executable instructions to identify a link associated with the sensor data, based on the location data and map data. Furthermore, the processor is configured to execute the computer-executable instructions to calculate half width data associated with the link based on the lateral position data and determine the driving direction for the vehicle based on the half width data, the lateral position data, and vehicle width data.