Zone-Based Traffic Control Using Smart Cameras
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Solution Overview
Problem
Existing traffic control systems rely on costly inductive loops that degrade over time and fail to differentiate the number and type of vehicles, leading to inefficient traffic signal changes.
Innovation Solution
A zone-based traffic control system using smart traffic cameras and processors to detect the number and type of vehicles within defined zones, sending signals to adjust traffic signals based on pre-set rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If inductive loops are used to detect vehicles, then vehicle presence can be detected, but the system becomes costly and requires manual road surface modification
Solution Approach 1:
The patent replaces the mechanical inductive loop system (requiring road surface cutting and installation) with an optical camera-based detection system. The camera captures images of vehicles in detection zones, and image processing algorithms identify vehicle presence, eliminating the need for physical road modifications while maintaining detection capability.
Solution Approach 2:
The patent uses optical copies (images) of vehicles captured by cameras as a substitute for direct physical detection by inductive loops. The image data serves as a copy that contains sufficient information to determine vehicle presence and characteristics without requiring physical interaction with the vehicles through road-embedded sensors.
2Measurement precision
If standard inductive loops are used, then vehicle detection is possible, but the system cannot differentiate the number and types of vehicles
Solution Approach 1:
The patent divides the detection area into multiple zones (e.g., first detection zone, second detection zone) and uses zone-based rules to evaluate different vehicle configurations. By segmenting the detection space and analyzing vehicle distribution across zones, the system can determine both the number of vehicles and their types based on their spatial arrangement and detection zone activation patterns.
Solution Approach 2:
The patent adds spatial dimensionality to vehicle detection by using multiple detection zones and analyzing the positional relationships of vehicles within these zones. Instead of a single binary detection state, the system evaluates vehicle number and type by examining which zones are activated and how vehicles are distributed across the spatial grid, thereby recovering information that would otherwise be lost.
3Adaptability or versatility
If inductive loops are deployed, then traffic signal control can be adjusted, but the system accuracy degrades over time and due to environmental conditions
Solution Approach 1:
The patent replaces the electrical inductive loop system with an optical camera-based system that is not subject to the same degradation mechanisms. Cameras and image processing algorithms do not suffer from soil corrosion, wire breakage, or signal interference caused by environmental factors, providing more reliable and consistent detection accuracy over time while maintaining traffic signal adjustment capabilities.
4Loss of information
If zone-based detection with multiple rules is implemented, then vehicle number and type can be differentiated, but the device complexity increases
Solution Approach 1:
The patent uses a single camera system that performs multiple functions: detecting vehicle presence, counting vehicles, identifying vehicle types, and determining spatial distribution. The same camera and image processing pipeline serve all these purposes by analyzing different aspects of the captured images, thereby achieving complex vehicle characterization without proportionally increasing hardware complexity.
Solution Approach 2:
The patent segments the detection area into multiple zones and applies zone-based rules to simplify the analysis of vehicle configurations. By dividing the complex scene into manageable spatial regions and evaluating vehicle distribution across these zones, the system can differentiate vehicle number and type using relatively simple rule-based logic rather than requiring complex artificial intelligence models.
Data Source
AI summary
Systems and methods for triggering changes to traffic signals based on the number and/or types of vehicles occupying a detection zone are disclosed. One aspect of the present disclosure includes a device with memory having computer-readable instructions stored therein and one or more processors. The one or more processors are configured to execute the computer-readable instructions to receive identification of zones and corresponding traffic light rules for a traffic intersection; and for each identified zone, detect a number of objects in the zone; based at least in part on the number of objects detected in the zone, determine if a corresponding condition is met; and upon determining that the corresponding condition is met for the zone, send a corresponding output signal to a traffic signal controller to change a traffic signal for the zone.