OVERVIEW

Intelligent Traffic Management System

Traffic congestion presents a significant challenge, impacting urban mobility, productivity, and pollution levels. To address this, we have implemented innovative solutions like Green Waves and the Predictive Dashboard. Green Waves introduces adaptive and stacking signals, dynamically adjusting signal timings based on real-time traffic flow data to prioritize congested areas. The Predictive Dashboard utilizes historical data analysis and future projections to anticipate congestion points, enabling proactive management. Dynamic warden deployment supplements this by efficiently deploying resources to predicted congestion areas, optimizing overall traffic management.

Problem

The city struggles with traffic management issues, resulting in long waits at traffic signals, traffic jams, and increased pollution. The absence of real-time traffic condition data hampers the effective deployment of traffic wardens. Additionally, the inability to predict traffic jams leads to inefficient traffic management efforts.

Solution

The Intelligent Traffic Management System was developed with two primary components: Green Waves and the Predictive Dashboard.

 

Green Waves

Green Waves uses adaptive signals that dynamically adjust signal timings based on real-time traffic flow data. For instance, if heavy traffic is detected on a particular road, the system extends the green light duration for that road. Additionally, stacking signals prioritize signal timings based on traffic flow data, allocating longer green signals to areas with heavier traffic and shorter green signals to those with less traffic.

 

Predictive Dashboard

The Predictive Dashboard leverages historical data analysis by examining past traffic patterns to predict congestion points. It also provides future projections, anticipating traffic conditions at specific times and locations, enabling proactive management. Dynamic staff deployment complements this by deploying traffic wardens to areas where congestion is predicted, ensuring a responsive and efficient traffic management approach.

Features & Benefits

Green Waves

Adaptive Signals

Dynamically adjusts signal timings based on real-time data. Reduces waiting times and congestion, leading to smoother traffic flow.

Traffic Stacking

Prioritizes signal timings based on traffic volume. Optimizes signal timings to ensure efficient traffic movement.

Predictive Dashboard

Real-Time Monitoring

Continuously monitors traffic conditions using data analytics. Provides up-to-date information on traffic conditions. 

Predictive Analytics

Uses historical data to predict future congestion points. Allows for proactive traffic management, reducing unexpected congestion.

Dynamic Traffic Warden Deployment

Allocates traffic wardens based on real-time needs. Ensures traffic wardens are deployed where they are needed most, improving traffic flow.

Environmental Benefits

Enhanced Public Safety

Reduced Emissions

By optimizing traffic flow and reducing idle times at signals, the system helps in lowering vehicle emissions. Improves air quality and reduces the city’s carbon footprint.

Efficient Traffic Management

Reduces the likelihood of accidents caused by congestion. Enhances overall public safety.

Technologies Used to Build the Solution

Python, Prediction Models, Computer Vision, ,MySQL/SQLite3, FastAPI, React, Local Servers