Adaptive Traffic Signal Management Using Machine Learning
Traffic congestion is a big problem nowadays and it is very common problem around different countries in world. The intelligent/smart traffic signaling system is crucial for an effective flow of traffic and have got much attention of researchers. Over the last few years some intelligent systems have
2025-06-28 16:30:08 - Adil Khan
Adaptive Traffic Signal Management Using Machine Learning
Project Area of Specialization Artificial IntelligenceProject SummaryTraffic congestion is a big problem nowadays and it is very common problem around different countries in world. The intelligent/smart traffic signaling system is crucial for an effective flow of traffic and have got much attention of researchers. Over the last few years some intelligent systems have been developed using different technique in different countries of world. In Pakistan, our current traffic signals are still handcrafted. Traffic congestion is also a cumbersome task for traffic Wardens. They have to set time for each signal manually. In this regard, this project aims at developing adaptive traffic signaling system for urban areas which will dynamically adjust signal timings according to density of traffic. In this project, an intelligent system using deep reinforcement learning model will be developed to assign the time to a signal depending upon the ratio of vehicles on each side of intersection dynamically. By this way traffic congestion on intersection will be reduced in an effective and efficient manner.
Project ObjectivesThe goals of project are immense as it is a requirement of our country. We will research and try to develop a system with maximum accuracy and results. Our goal is to develop a system that will be helpful and beneficiary for every citizen of Pakistan.
- Smooth traffic flow by reducing congestion
- Remove problem of waiting on signals
- Dynamically adjust traffic signal
- Will save time of peoples on road
- Help in reducing pollution as there will be less traffic jam on signals
As describe/mention in summary that we are going to use deep reinforcement learning technique of machine learning. First of all, we will design and train our agent by using simulation and dataset. Our system will take picture of traffic on intersection in real time and once we get picture of traffic system will detect/calculate the number of vehicles from picture and then our agent will do further processing on that data and assign time to each side on that specific intersection. And ultimately our system will enhance traffic congestion problem. It is an iterative process and system will do analysis every time and assign time dynamically. Our system will also enhance itself as time passes.
First of all, our agent will get the current situation of environment/traffic from in the form of state. Agent will get the number of vehicles on every side of intersection. At the same time, agent will also get the reward from environment which will tell our agent about the action given by environment when last evaluation was performed. Once our agent gets the information of current traffic in the form of state and last condition/result of traffic after performing evaluation in form reward. Our agent will do again evaluations on the basis of state and reward. After performing evaluation our agent will return an output to our environment and will assign time to traffic signal
Benefits of the ProjectOne of the biggest issue of our country is traffic and as life is getting busy by every passing day. We have to wait for long signal on intersections even if there is no traffic on other side of intersection. Our system will smooth the flow of traffic by dynamically adjusting traffic light which ultimately reduce congestion. As there will be no congestion, eventually it will save the time of peoples on road.
System will help the department of traffic to manage traffic. Otherwise if there is congestion on an intersection a warden has to stay on that intersection so that he can regulate traffic. Intelligent traffic light system will remove the problem of extra waiting on signals. And helps people to reach their destination on time. As there will be less traffic jam, it will also reduce pollution.
Technical Details of Final DeliverableIn the end, an application will be developed which will be integrated with agent. Agent will adjust signals lights dynamically on real time traffic and installed on single board computer (Jetson Nano). Application will allow user to visual traffic flow and also provides provision to control signal manually in case of any inconvenience.
Final Deliverable of the Project HW/SW integrated systemCore Industry TransportationOther Industries IT Core Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Sustainable Cities and CommunitiesRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 80000 | |||
| ANNKE 4K UHD 8CH Package (4 Cameras, 1 DVR, 2 TB HDD and all cables) | Equipment | 1 | 51500 | 51500 |
| NVIDIA Jetson Nano Developer Kit | Equipment | 1 | 18500 | 18500 |
| Jetson Nano Cover Case + Adapter + Mermory Card + Cables | Miscellaneous | 1 | 4000 | 4000 |
| NVIDIA Jetson Nano Wifi Adapter | Miscellaneous | 1 | 2500 | 2500 |
| Wifi Device + Other Fyp related items | Miscellaneous | 1 | 3500 | 3500 |