Roadside Vehicle Sensors With Unique Identifiers for Low-Bandwidth Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Collecting and processing vehicle speed and position data in complex traffic scenarios is challenging due to the dynamic nature of vehicle movements and positions, necessitating efficient monitoring and communication systems for enhanced safety and control in autonomous driving environments.
Innovation Solution
A system of sensors placed along roads that communicate bidirectionally, generate unique Object Identification Characteristics (OICs) for vehicles, and share data with a central server to monitor and alert on vehicular events, reducing processing and bandwidth requirements by minimizing redundant data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are placed along the road to monitor vehicle positions and movements, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The road monitoring system is divided into multiple segments, each monitored by a separate sensor placed at predetermined distances apart. Each sensor independently monitors a specific segment of the road, and the complete picture is assembled by combining data from all sensor segments. This segmentation allows high measurement precision across the entire road while keeping individual sensor units simple and manageable.
2Reliability
If sensors communicate bidirectionally with a central server to share vehicle data, then reliability is improved, but use of energy increases
Solution Approach 1:
The sensor system implements bidirectional communication with a central server, allowing sensors to transmit detected vehicular events and receive feedback instructions. This feedback mechanism enables the system to maintain high reliability through continuous data sharing and coordinated response, while the central server can optimize communication timing to reduce overall energy consumption by sensors.
3Measurement precision
If the system monitors all vehicle characteristics continuously, then measurement precision is improved, but processing intensity increases
Solution Approach 1:
The system extracts and monitors only the most critical vehicle characteristics necessary for safety and traffic management, such as position, speed, and vehicular events, rather than continuously processing all possible vehicle data. This selective extraction maintains measurement precision for essential parameters while significantly reducing processing intensity and computational requirements.
4Loss of information
If sensors transmit all detected data to the central server, then loss of information is reduced, but loss of energy increases
Solution Approach 1:
The system transmits only the necessary partial data to the central server, filtering out redundant information locally at the sensors. Sensors transmit data selectively based on detected vehicular events and predefined monitoring criteria, maintaining information completeness for critical safety data while minimizing unnecessary data transmission that would consume bandwidth and energy.
Data Source
AI summary
Systems and techniques are described for identifying, monitoring, and sharing vehicle information amongst sensors. In some implementations, a system includes a central server and a plurality of sensors. The plurality of sensors are positioned in a fixed location relative to a roadway. Each sensor in the plurality of sensors is configured to: detect vehicles in a first field of view on the roadway. For each detected vehicle, each sensor is configured to identify features of the detected vehicle and perform operations for each feature. The operations include generating feature data representing the feature, generating a unique identification of the detected vehicle from the detected vehicles by concatenating the feature data representing the identified features of the detected vehicle, and adding the unique identification to a list.