Vehicle Movement-Based Tailback Detection at Traffic Lights
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Solution Overview
Problem
Existing methods for determining the length of a motor vehicle backlog at traffic signal systems and associated waiting times are not accurate and cannot be predicted independently of infrastructure connections.
Innovation Solution
A method and system that receive movement data from vehicles to determine stopping processes, spatial and temporal distributions, and forecast backlog length and waiting time without requiring an infrastructure connection, using data processing units and integrating map and sensor data for enhanced accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If infrastructure connection (direct data connection to traffic light system) is used, then measurement precision of backlog length and waiting time is improved, but device complexity and ease of operation are worsened due to required direct communication infrastructure
Solution Approach 1:
The system performs backlog detection autonomously using only its own sensor data (GPS, accelerometer, camera) without requiring external infrastructure connections. The vehicle's onboard processing unit independently determines stopping processes and predicts backlog characteristics, making the system self-sufficient and eliminating dependency on traffic light system communications.
Solution Approach 2:
The patent uses map data as an intermediary to correlate the vehicle's position with traffic light locations. By combining sensor-derived stopping process data with pre-stored map information about traffic signal positions, the system achieves accurate backlog measurement without direct connection to the traffic light control system.
2Reliability
If infrastructure connection is required, then reliability of traffic signal phase information is improved, but adaptability to different locations and ease of deployment are worsened
Solution Approach 1:
The system infers traffic signal phase information (green/red light states) autonomously by analyzing its own movement patterns and stopping processes. The processing unit detects correlations between vehicle deceleration/acceleration events and inferred signal phases, making the system adaptable to any location with traffic lights without requiring local infrastructure setup or communication.
Solution Approach 2:
The system uses feedback from its own sensor measurements (GPS position, speed, acceleration) to continuously refine its predictions of backlog length and waiting time. By comparing observed stopping processes with predicted patterns, the system adapts to different traffic light configurations and locations while maintaining reliable information about signal phases.
3Loss of information
If infrastructure connection is used, then information completeness is improved, but loss of time for system setup and deployment is worsened
Solution Approach 1:
The system performs all necessary data collection and processing actions in advance using only onboard sensors. By continuously monitoring and analyzing the vehicle's own movement data in real-time, the system prepares backlog predictions without requiring any time-consuming infrastructure setup, connections, or external system configurations at the deployment location.
Data Source
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AI summary
A method for determining the length of a tailback (R) of motor vehicles (10) at traffic light system (12) and a waiting time (T) which is caused by the tailback (R), comprising the steps of receiving (20) movement data (10') from motor vehicles (10) by means of a data reception unit (4), determining (22) stopping processes of motor vehicles (10) at a traffic light system (12) on the basis of the movement data (10') by means of a data-processing unit (2), determining (24) the spatial and chronological distribution of the stopping processes of the motor vehicles (10) by means of the data-processing unit (2), determining (26) the maximum length of the tailback (R) of motor vehicles (10) and its timing by means of the data-processing unit (2), and producing (28) a prediction relating to a buildup and/or reduction of the tailback (R) of the motor vehicles (10) and a waiting time (T) up to the point when the tailback (R) is passed through by means of the data-processing unit (2), wherein the creation (28) of a prediction does not require any connection to infrastructure.