Traffic Density Estimation System

The goal of this project is to introduce and present a machine learning application that aims to improve the quality of life of people in our country. In particular, we investigate the use of machine learning solutions to tackle the problem of traffic congestion in Pakistan. To accomplish this aim,

Project Title

Traffic Density Estimation System

Project Area of Specialization

Artificial Intelligence

Project Summary

The goal of this project is to introduce and present a machine learning application that aims to improve the quality of life of people in our country. In particular, we investigate the use of machine learning solutions to tackle the problem of traffic congestion in Pakistan. To accomplish this aim, we present an end-to-end system comprising of

1) A traffic density estimation algorithm at traffic junctions/signals and

2) A suitable traffic signal control algorithms that make use of the density information for better traffic control.

Traffic density estimation can be obtained from traffic junction images or real-time video feed using various machine learning techniques (combined with CV tools). At first, we will conduct experiments on our algorithms, using the publicly available traffic camera dataset to demonstrate the feasibility of this approach. With these traffic density estimates, different traffic algorithms can be applied to minimize congestion at traffic junctions in general.

Project Objectives

1) Automatic traffic monitoring in real time using existing video feeds by detecting and tracking vehicles.
2) Accident detection and alerting local authorities for faster response time.
3) Reporting initial assessments and exact location of the incidents to the authorities.
4) Cloud based system with login and a dashboard interface for providing insights for traffic offenders, frequent slow drivers, traffic in/out flows, easy searchable video clips for the incidents and other traffic analytics.

Project Implementation Method

We are going to use the tools of Artifial Intelligence and Machine Learning. We are going to fetch the real-time video feed data from our cameras, and then process it. The image detections algorithms will be applied at this phase. Then an estimation of density of traffic will be calculated with an algortihm, which we will design ourselves. After the correct traffic estimation, we will regulatee the traffic signals according to the traffic desnsity.

Our model that will regulate the traffic signals will use the Machine Learning algorithms, by training it for the desired goal through Data Science algorithms. The goal is to make an AI powered INtelligent Traffic Density Estimation System that will make the life of the people easier by simpling down the transportation system. 

Benefits of the Project

Potential applications which estimates the traffic density at traffic lights/junctions using public cameras to adapt the traffic lights accordingly to get the best result and some other real world applications are discussed below:
Even if traffic is flowing very slowly, streets could handle the traffic flow much more efficiently. The key for this is that all cars have to move at constant speed without much braking and accelerating. Therefore, an intelligent traffic system could detect the amount of cars at every position, estimate the velocity of the cars in a later stage, and ultimately adapt the traffic lights accordingly to get the optimal outcome even in case of extraordinary situations such as changing weather, accidents or other unplanned traffic fluctuations. Efficiency can be gained by locally adapting the traffic lights, considering the local traffic situation.
Our Traffic Density Estimation system is just a single step on a journey of complete AI-controlled transportation system. This can evolve into an AI powered smart traffic surveillance that will be able to perform:

1) Automatic traffic monitoring in real time using existing video feeds by detecting and tracking vehicles.
2) Accident detection and alerting local authorities for faster response time.
3) Reporting initial assessments and exact location of the incidents to the authorities.
4) Cloud based system with login and a dashboard interface for providing insights for traffic offenders, frequent slow drivers, traffic in/out flows, easy searchable video clips for the incidents and other traffic analytics.

Technical Details of Final Deliverable

The final deliverable of our project will be an AI powered Traffic Density Estimation System that will fulfill all the necesities and solve enough problems of the socity in terms of traffic issues.
For our system to be employable some certain requirements must be fulfilled. In the following we show the necessities for our intelligent traffic control:
1) Real Time: Receiving a camera footage must lead to an instantaneous estimation and to the needed Traffic light adaption.
2) Fail Safeness: Since a wrongly working traffic light system is highly dangerous it must be absolutely failsafe.
3) Work under different conditions: Our software must be versatile and should work in different situations (changing lighting, weather and traffic conditions) as well as at different places or under emergency conditions (e.g. emergency clearance of path for ambulance, clearance and alternate routes in case of protocols, etc.).
4) Streaming Data: We are going to constantly receive data from the cameras. Therefore, we must be able to perform Stream Processing (incrementally).

Final Deliverable of the Project

HW/SW integrated system

Type of Industry

IT , Transportation

Technologies

Artificial Intelligence(AI), Internet of Things (IoT), Wearables and Implantables, Others

Sustainable Development Goals

Good Health and Well-Being for People, Industry, Innovation and Infrastructure, Sustainable Cities and Communities, Climate Action, Partnerships to achieve the Goal

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com