Abstract
At present, there are various traffic analysis approaches and tools accessible in all areas; nevertheless, there are not enough, or by all-means, resources, and supplies for the application of these tools, as these tools differ in their competencies, input supplies, and productivity. This paper aims to provide a new way for a cost-effective traffic analysis implementation, which does not require a lot of resources, combining two machine learning algorithms to count the vehicles, estimate their speed, and segment lanes from a video recording. The video recording can be done using a conventional mobile phone camera and can be processed using a simple hardware toolkit. To bear out the cost-effectiveness of the proposed procedure, we provide a cost comparison analysis with a radar-based mobile traffic counting device.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
