Traffic Signal Coordination Using Predicted Vehicle Speeds
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Solution Overview
Problem
Current methods for managing traffic congestion do not effectively consider critical parameters such as vehicle stoppages, speed adjustments, and signal timing, leading to inefficient traffic flow and increased pollution.
Innovation Solution
A congestion management system that uses sensors and a trained traffic model to predict vehicle speeds and signal times, determining optimal speeds and signal timings to minimize vehicle stoppages and create a virtual green corridor, reducing congestion and improving fuel efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicles stop at traffic signals, then traffic flow is controlled, but travel time increases and congestion occurs
Solution Approach 1:
The system predicts future vehicle speeds and positions at intersection points before vehicles actually arrive, allowing the traffic signal controller to pre-adjust signal timings to optimize vehicle passage and minimize stops
Solution Approach 2:
The traffic signal timings are dynamically adjusted based on real-time vehicle speed predictions and actual traffic conditions, rather than using fixed timing schedules, enabling adaptive optimization of vehicle flow through the intersection
2Reliability
If vehicles stop frequently at traffic signals, then traffic is regulated, but fuel efficiency decreases
Solution Approach 1:
The system continuously receives vehicle speed data from sensors, compares predicted speeds with actual speeds, and uses this feedback to adjust traffic signal timings in real-time, creating a closed-loop control system that optimizes fuel efficiency while maintaining traffic regulation
3Reliability
If vehicles stop frequently at traffic signals, then traffic flow is managed, but pollution increases
Solution Approach 1:
The system uses real-time vehicle speed feedback from sensors to continuously optimize traffic signal timings, reducing unnecessary vehicle stops and thereby decreasing harmful emissions from idle and stop-and-go traffic conditions
4Ease of operation
If existing traffic management methods are used, then basic traffic control is provided, but critical parameters like vehicle stoppages and speed adjustments are not considered
Solution Approach 1:
The system introduces sensor devices and a prediction module as intermediaries between the traffic signals and vehicles, which collect vehicle speed data, predict future vehicle states, and use this information to optimize traffic signal timings beyond basic control
Data Source
AI summary
Disclosed herein is method and congestion management system for reducing road congestion. Traffic data related to plurality of vehicles is analyzed by a trained traffic model for predicting speed of each vehicle and signal time associated with intersection points. Optimal speed for each vehicle and an optimal signal time for each of the intersection points is determined based on analysis of the previous values and historic traffic data. The determined optimal speed and the optimal signal time are respectively provided to a vehicle control system associated with each vehicle and a traffic controller associated with each intersection point. In an embodiment, the method of present disclosure reduces traffic congestion on any selected portion of road. Further, the method of present disclosure eliminates and/or minimizes number of instances that a vehicle has to stop/start at the traffic signals, thereby enhancing fuel economy and reducing waiting time for the vehicles.