Centralized Traffic Management Using Disparate Data Sources
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Solution Overview
Problem
Existing intersection preemption systems for managing traffic congestion are costly, complex, and often respond only to local line-of-sight traffic conditions, which can lead to counterproductive adjustments and increased accident risk.
Innovation Solution
A computer system that receives information from disparate data sources about traffic conditions in an environment with multiple intersections and roadways, identifies events such as accidents or changes in traffic patterns, and performs remedial actions like providing alerts or modifying traffic signal timing to improve traffic flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If camera or sensor is installed at every intersection with corresponding transmitters in emergency vehicles, then traffic preemption capability is improved, but system cost and complexity increase
Solution Approach 1:
The patent introduces a central server as an intermediary that receives data from multiple disparate sources (traffic cameras, sensors, emergency vehicle GPS, weather services, event data) and processes this information centrally. This mediator approach eliminates the need for complex point-to-point communication infrastructure at each intersection while maintaining comprehensive traffic monitoring and preemption capabilities through centralized data aggregation and analysis.
2Measurement precision
If intersection preemption system is based on line-of-sight, then local traffic condition response is improved, but overall traffic condition awareness deteriorates
Solution Approach 1:
The patent merges data from multiple previously separate sources including local intersection cameras, regional traffic sensors, emergency vehicle location data, weather conditions, and special event information into a unified comprehensive traffic management system. This combination allows the system to maintain precise local detection capabilities while simultaneously achieving broad regional awareness by aggregating information from across the entire service area.
Solution Approach 2:
The system transitions from two-dimensional line-of-sight visual detection at individual intersections to a multi-dimensional data aggregation model that incorporates spatial distribution across multiple locations, temporal patterns from historical data, and various data types from disparate sources. This dimensional expansion enables comprehensive regional traffic awareness while preserving local detection precision through the same central processing architecture.
3Speed
If traffic signal timing is adjusted suddenly for emergency vehicle, then emergency vehicle response time is improved, but driver confusion and accident risk increase
Solution Approach 1:
The system performs preliminary actions by continuously monitoring traffic conditions and pre-calculating optimal signal timing adjustments before emergency vehicles arrive. When an emergency vehicle is detected, the system has already prepared the sequence of green light adjustments needed, allowing for smooth progressive signal changes rather than sudden abrupt modifications. This preliminary preparation enables fast emergency response while maintaining driver safety through predictable, gradual transitions.
Solution Approach 2:
The patent implements dynamic traffic signal control that adapts signal timing in real-time based on current traffic conditions, emergency vehicle location, and predicted arrival times. Rather than fixed or suddenly changed timing, the system dynamically adjusts green light durations and phases progressively as the emergency vehicle approaches, creating a moving wave of green lights that optimizes response time while providing drivers with anticipatory notice of upcoming signal changes, thereby reducing confusion and maintaining safety.
Data Source
AI summary
A computer system that performs a remedial action is described. During operation, the computer system may receive information corresponding to traffic conditions in an environment (such as traffic flows in at least a portion of a city), where the information is associated with different types of sources distributed in the environment, and the environment includes multiple intersections and roadways. Then, the computer system may identify an event in at least a portion of the environment based at least in part on the information, such as predicting a change in a traffic condition in the environment in a subsequent time interval. Next, the computer system may perform a remedial action based at least in part on the identified event, such as: providing an alert about the event; providing an instruction based at least in part on the event; and/or modifying traffic management in at least the portion of the environment.