Smart control of traffic light system using image processing / Mutmainnah Radhiah Mohamad Jeffery
Nowadays, with the growing number of vehicles in Malaysia, traffic congestion at junctions has become a serious issue among motorists. The density of vehicles is increasing day by day, thus, there is a need of adaptive traffic signals which are able to do real time monitoring of traffic density inst...
Saved in:
| Main Author: | |
|---|---|
| Format: | Student Project |
| Language: | English |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/104903/1/104903.pdf https://ir.uitm.edu.my/id/eprint/104903/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Mara |
| Language: | English |
| Summary: | Nowadays, with the growing number of vehicles in Malaysia, traffic congestion at junctions has become a serious issue among motorists. The density of vehicles is increasing day by day, thus, there is a need of adaptive traffic signals which are able to do real time monitoring of traffic density instead of depending on sensors and hardwired at the time of installation. This study describes a system which make used of image processing in controlling the traffic in an effective manner by taking images of each lane at a junction. Basically, more time is allocated for the vehicles on the densest road to pass compared to other less dense road. A step by step of image acquisition and image processing with several methods used in MATLAB is explained in this study. Basically, the processed image is matched with the template image by using feature based image matching technique and the priorities of having green signal is given to the densest lane while the other lanes are given their green signal based on their decreasing priorities. In doing so, the complete flow of image acquisition, image processing, image matching and the allocation of green signal by using four sample of images (lane 1, lane 2, lane 3 and lane 4) with different traffic density is discussed with proper schematics. The Arduino is used as a microcontroller which responsible in controlling the changes of each signal as well as the duration of the traffic lights signal based on the traffic density at each particular lane. The outcome of this study shows that the smart traffic light control system could improve traffic congestion at junction and avoid the time of green light being wasted on an empty road. This could benefit the motorists from wasting their time on the road waiting for their green signal. |
|---|