Identifying Prohibited Vehicles on Highways using Deep Learning Techniques
Hashim Sajid Khan, Department of Computing, Abasyn University, Peshawar, Pakistan.
Syed Atif Ali Shah, Department of Computster Science, Air University, Islamabad, Pakistan.
Muhammad Khan Afridi, Department of Computing, Abasyn University, Peshawar, Pakistan.
Corresponding Author:
Hashim Sajid Khan (hashimsajidkhan@gmail.com)
Abstract:
Highways are connecting roads among different cities for faster transportation. However, these highways are not open for all types of vehicles. There are some constraints along with some regulations while traveling on these highways. A class of automobiles are allowed while some of them are not allowed. These forbidden automobiles are slower in speed and have some other issues thus can cause an accident. An auto-rickshaw/loader is a power-driven advancement of the conventional drag rickshaw or cycle rickshaw Used as a vehicle, carrying few passengers or luggage. It is quite similar to a common four-wheel vehicle and thus not easy to distinguish from distance. Similarly, manual carts and bikes are also forbidden on highways. The specs of the auto rickshaws are similar to a car but lack some of the capabilities and abilities; for example, it has a car-like shape but is deficient in handling, which makes them dangerous on highways. Though it’s not a two-wheeler and the number of passengers makes it legit for the highway but several issues outlaw it on a highway; for Example speed, handling, aerodynamics, etc. In manual procedures, it's not easier to watch each vehicle entering and highway. An automatic system is required to distinguish between these vehicles. Thus we have designed and trained a Machine Learning model to detect all these forbidden automobiles on a highway without human intervention our system is capable of recognizing it even from a distance and thus helps us control such types of breaching.
Keywords:
Neural Network; Machine Learning; Highways Security; Deep Learning