Real Time Traffic Management System
Real-Time Traffic Management System (RTMS) is the real-time monitoring of the traffic density and congestion using the image processing technique to measure the number of vehicles. Traffic reporting provides real-time distribution of information about road conditions such as traffic congestion, deto
2025-06-28 16:34:44 - Adil Khan
Real Time Traffic Management System
Project Area of Specialization Artificial IntelligenceProject SummaryReal-Time Traffic Management System (RTMS) is the real-time monitoring of the traffic density and congestion using the image processing technique to measure the number of vehicles. Traffic reporting provides real-time distribution of information about road conditions such as traffic congestion, detours, and traffic collisions. The reports help drivers anticipate and avoid traffic problems. Traffic reports, especially in urban cities, will also report on major delays to mass transit that does not necessarily involve roads. In addition to periodic broadcast reports, traffic information can be transmitted to users by our application. It will help improving the traffic conditions in the city and will keep the user up-to-date using our application. Our application will re-route the user to alternative ways using the manual analyzing techniques to improve the traffic conditions in the city for better and safer environment. The application will also navigate the user to its destination using the Geo Location of the user to the destination entered or pinned by the user. Also, integrating Car Accident Detection System in our application will keep the driver alert of being watchful for possible danger / accident.
Project ObjectivesOur objective is to provide a shortest and less congestive route to the user by using real-time traffic monitoring system. For this we are developing an application which may re-route the user to alternative ways. Our application shows the real-time results of traffic conditions not with number of GPS devices on the road but by the real-time analyzing by recording video form our cameras for car detection process on different location in the city. The application will also help drivers to prevent or reduce the severity of crashes or collisions.
The major objectives are as followed:
- To measure the real-time traffic density in the city through cameras.
- To have an application that will help user to use alternative ways.
- To decrease the traffic density and congestion.
- To navigate the user while traveling by using our application.
- To report on major delays to mass transit that will be transmitted to users by our application.
- To report / warn user about the distance among other vehicles preventing collisions or whiplashes.
The methodologies used for implementing the Real-Time Traffic Management System is briefly described accordingly to PMBOK (a set of standard terminology and guidelines for project management) that are as followed:
Initiation Phase:
The road network of any city is its lifeline and so monitoring this vital infrastructural resource is important. The problem of traffic jams and congestion are faced by most major cities of the Pakistan. For managing traffic, a city’s administration should have both real-time and historical data about the traffic conditions prevailing on the road network. This information can be used for quick reaction measures, such as, providing users to take alternative routes through our application. In the long run, however, this information can be used to plan a better road network by identifying areas of frequent congestion and building alternative routes. Although, there are so many accidents that happen every day due to a few seconds of distracted driving, or just human error. So minimizing the accident may save human life and will also imminent crash or collision of vehicles.
Planning Phase:
Our objective is to provide a shortest and less congestive route to the user by using real-time traffic monitoring system. For this we are developing an application which may re-route the user to alternative ways. Our application shows the real-time results of traffic conditions not with number of GPS devices on the road but by the real-time analyzing by recording video form our cameras for car detection process on different location in the city. The application will also help drivers to prevent or reduce the severity of crashes or collisions.
Execution Phase:
- Live Monitoring: System will monitor the traffic using video from our cameras by counting number of vehicles with the help of image processing.
- Traffic Reporting: System will also report on traffic density and congestion. In addition to periodic broadcast reports, traffic information can be transmitted to users by our application.
- Shortest Route: System will provide the shortest route to the user by analyzing the real-time traffic density in the city.
- Navigation: System will navigate the user to its destination.
- Geo Location: System will locate the user point where he is located at that moment.
- Car Accident Detection: System will detect the distance between the other vehicles and will report them with an alarm in application that will reduce road accidents.
Closing Phase:
The project is closed when the project is approved after testing and verification phase and the QA / QC is cleared and the requirements are totally similar to the user specification.
Benefits of the ProjectThe purpose of Traffic Management System is to improve transport operations and transport services profitability, reduce traffic jams and fatalities and maintain road infrastructure. Our application would reduce the number of accidents and damages occurred while driving that will alert the user / driver with a beep when any obstacle or vehicle is sensored near to the driver's vehicle.
The benefits of the project are as followed:
- Helping people save resources (time and fuel) while on the road.
- Users will be updated the real time traffic density of the route while on road that is being analyzed on the cameras .
- Users will be navigated to the best and shortest route while analyzing the traffic density of the roads until their destination.
- Users will be warned with a beep / alarm that will help them decrease the number of car accidents while on the journey.
OpenCV: OpenCV is a library of programming functions mainly aimed at real-time computer vision. To build our deep learning-based real-time object detector (vehicles) we will use OpenCV.
CNN: In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery. CNNs use relatively little pre-processing compared to other image classification algorithms. This means that the network learns the filters that in traditional algorithms were hand-engineered. This independence from prior knowledge and human effort in feature design is a major advantage. This will help analyzing the traffic density on the roads through live camera.
Android Studio: Android Studio is the official integrated development environment for Google's Android operating system designed specifically for Android development. Our application will be available on handheld devices for traffic reporting for users to avoid traffic congested routes.
Google Maps Android API: Google Maps Android API is part of the Google Play services platform. To use Google Maps, set up the Google Play services SDK in your app development project. Allow your users to explore the world with rich maps provided by Google. Identify locations with custom markers, augment the map data with image overlays, embed one or more maps as fragments, and much more. The Google Maps Android API allows you to include maps and customized mapping information in your application.
- Add maps to your app
- Customize the map
- Control the user's view
- Add Street View to your app
Arduino: Arduino is an open-source hardware and software user community that designs and manufactures single-board microcontrollers for building digital devices and interactive objects that can sense and control both physically and digitally allowing our application to connect to sensors for detecting object near vehicles for reduction in accidents.
Final Deliverable of the Project HW/SW integrated systemType of Industry IT , Transportation , Security Technologies Artificial Intelligence(AI), Augmented & Virtual Reality, Cloud Infrastructure, Wearables and Implantables, Big DataSustainable Development Goals Decent Work and Economic Growth, Industry, Innovation and Infrastructure, Sustainable Cities and CommunitiesRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 77358 | |||
| Samsung 4Channel 2 IP66 720T cameras with 500GB for bulk video record | Equipment | 1 | 49499 | 49499 |
| Arduino Uno R3 SMD with cable | Equipment | 1 | 685 | 685 |
| Bread Board GL-12 | Equipment | 2 | 127 | 254 |
| Jumper Wires 30cm | Equipment | 1 | 120 | 120 |
| JSN SR04T Waterproof Sensor for Car Accident Detection | Equipment | 6 | 1350 | 8100 |
| Transcend External Hard Drive 2TB for pocket storage of videos | Equipment | 1 | 11200 | 11200 |
| Printing (FYP Documentation) | Miscellaneous | 3 | 1500 | 4500 |
| Stationary and Overheads | Miscellaneous | 3 | 1000 | 3000 |