Smart Traffic Control Using Range and Bearing Data Processing Techniques
This project is proposing an innovative traffic control solution by fusing two information?s coming from the camera images and 2D laser scanner. Currently many different technologies are is use to observe traffic density on any road. For example, by using load cells variations, by image-base
2025-06-28 16:35:54 - Adil Khan
Smart Traffic Control Using Range and Bearing Data Processing Techniques
Project Area of Specialization Artificial IntelligenceProject SummaryThis project is proposing an innovative traffic control solution by fusing two information’s coming from the camera images and 2D laser scanner.
Currently many different technologies are is use to observe traffic density on any road. For example, by using load cells variations, by image-based traffic detection or by inductive loop method. In this work an additive laser scanner-based traffic detection scheme will be implemented using images of the same scene. Raspberry-pi will be installed for collecting the data from the sensors and transmitting it to the main server. Data received will be processed from which traffic density will be calculated. Estimated traffic density will be used to set the offset for each traffic signal at the intersection.
Project ObjectivesObjectives:
- Improve efficiency of existing system
- Improve the traffic flow
- Control signals in accordance with the traffic load
- Reduce the man-power
The System would be Installed across a pedistrian bridge with lidar(Range Sensor) attached capturing frames of every second
•Saves time
•Less fuel consumption
•Improvement of regulations
•Easy installation
•Low maintenance & Cost effective
Technical Details of Final DeliverableThe traffic control systems installed currently use the properties of inductive loops which are non-adaptive with respect to the increasing number of vehicles on the roads. Therefore, roads get congested and blockages are often observed at the intersections. Considering wastage of two highly important resources that is fuel and time, to overcome such issues we proposed a system to improve the inefficient present-day technology. Our system would overcome most of the drawbacks of today’s technology.
Our system would comprise of following elements which will increase the efficiency of the traffic management.
1.CAMERA: Cameras would be installed at intersections to monitor the traffic dynamically and to collect data for the signal controlling and transfer it to the main server for further process. The picture below describes the actual arrangement of the cameras.
2. RANGE SENSOR: Laser sensor would be implanted alongside the camera to improve the accuracy of the system in unusual circumstances and to overcome the weather challenges or visibility issues where the cameras cannot cope up with the desired efficiency. The laser would detect the presence of vehicles on the junctions as shown below.
3.TRANSIMISSION: The data collected from the two sensors would be passed on through a channel using a module to encode the data and a transmitter that would provide a wireless channel which would be processed at the main server according to our need. The principle of transmission revolves around the fundamentals of the “cloud” concept.
4.PROCESSING: As soon as data has been received on the server, we will process the data using the image processing technique through OPENCV libraries and will compute the vehicle density and alongside with that we can even identify the type of vehicle. Furthermore, the results of laser sensor would indicate some histograms or some voltage levels (not tested yet). Both these results would be then integrated to generate a cumulative result to find out the density of the traffic.
5.CONTROLLING: Once the calculations are complete, the server will dedicate specific offsets for red and green indicators.
Final Deliverable of the Project Hardware SystemType of Industry Transportation Technologies Artificial Intelligence(AI), Internet of Things (IoT), RoboticsSustainable Development Goals Sustainable Cities and CommunitiesRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 52200 | |||
| Raspberry pi 3B | Equipment | 1 | 6700 | 6700 |
| Night vision cameras | Equipment | 2 | 5000 | 10000 |
| RP lidar (2D laser Scanner) | Equipment | 1 | 30000 | 30000 |
| 12V 7 Amp Power supply | Equipment | 1 | 4000 | 4000 |
| Mechanical Structure | Equipment | 1 | 1500 | 1500 |