Introduction 

Violation of traffic rules is a critical and rising issue presently. Fast reaction and prevention of traffic violation plays a key role to ensure safety of vehicles and citizens. For this purpose, in Pakistan surveillance cameras are installed everywhere to prevent traffic violations but they are unable to detect events like red-light violation, wrong way driving etc. due to the faulty architecture. In Pakistan traffic issues are rising day by day which are causing many causalities like accidents, loss of innocent lives and compromise in safety of citizens. Recently a survey related to the accidents causing deaths in Pakistan increases dramatically due to the traffic violations.So to minimize such alarming factors we should provide an automated solution using latest technology which will help to reduce these factors.

Rising traffic congestion,rules violation and accidents due to lack of proper traffic management and surveillance need to be addressed with smart solutions. Like automated detection of rules violations, vehicles congestion etc. integrated with video analytics that can effectively aid traffic administration. 

By implementing such system labour cost can be reduced.  Reduction in labour will also eliminate many other factors like lack of attention while monitoring many cameras at the same time, pin pointing such events when and where are they happening etc.

Automatic traffic violation in Video analytics using can play an important role in getting in-depth insights into traffic conditions [4] and these insight can help by routing this information to traffic administrators which can take an effective action on any type of event. Surveillance cameras are cheap and ubiquitous, but the labour required for monitoring them increases the cost now a day. Because generally it happens that the surveillance cameras are not monitored by proper attention and it is also difficult for a person to pin point a violation between large number of screens. Usually, either no video is monitored at all or infrequent video is observed, alternatively it is used only for reviewing the incident just for once. But they are also helpful as they are capable of detecting events instead of passive recording. They make use of the events as they appear to happen and in accordance to it, take appropriate actions such as alerting the traffic management department. This is the utmost requirement of automatic violation detection system. 

So, our main objective is to derive an optimized and effective solution in traffic violation matter which can detect any type of violation such as red light violation, wrong-way vehicle detection, over speeding and stop line violation etc. Our proposed system will be flexible in nature. Flexibility allows user add new module to system easily. Some other information can also be infer from this system like vehicle count, provide a prediction of an accident using traffic pattern etc. This system will help the Traffic management authorities in accurate violations detection so proper action can be taken in real time and prevent accidents and guarantee citizens safety.

Machine learning algorithms and digital image processing methods are being used for these types of problems [5] still there are many complexities which require greater computation and adaptiveness in algorithms which is possible but are time taking

They are many solutions proposed to detect the abnormal patterns in traffic but they require proper guidance how to interact with application’s UI, costly hardware such as costly sensors to detect any type of violation and heavy GPU for processing video streams and are cost effective. So we try to propose a system based solution by training our model with latest and 3 to 4 types of datasets which will cover all type of traffic violation. The system will be cheaper eliminating the costly hardware like GPU’s, sensors etc. Other factors are discussed below.

Motivation and Scope 

The main motive to design and develop such system is to reduce the amount of road accidents by ensuring proper traffic regulation and management. Reduction in number of road accidents will result in the reduction of human injuries, death rate and financial loss.

This system will also help and assist law enforcement agencies to minimize the traffic violations which will ultimately reduce the risk factor for pedestrians etc. Accuracy and quick processing will help such departments to take regarding set of action in real time. Interactive and user friendly UI will allow law enforcement agencies to use of the 3D trained model quite effectively. The initial scope of the project involves the detection of traffic rules violation like red light violation, wrong way moving vehicle, stop line violation etc. and vehicle count, but gradually we will try to extend our domain toward new modules for example accident prediction using road patterns which will play an important role in current traffic situations.

Assumptions: Our model will be trained using three different datasets which cover’s almost all types of violation. Also datasets will be taken from quite reliable resources

Datasets used in our project 

AI City Challenge 2019

• No of classes = 2

• Classes Names

• Plain Dataset which means no annotations were provided with the dataset.

• Lane Violation & Vehicle Crash

• 100 Train + 100 Test Videos

Web Application User Interface & Demo

Android Application UI & Demo

Tools and Technologies 

Tools and technologies that will be used for this project:

For Web Application Development

For Mobile Interfaces (UI) :

Project Repo & Related Links

Github Link:

https://github.com/FYP-Road-Pulse

Web + Android Demo:

https://drive.google.com/drive/folders/1k0tpwEiaks7xueJwV7-um_wfYIet4OCV?usp=sharing

Custom Trained Model YOLO + Custom Files

https://drive.google.com/drive/folders/1LvB4cocywQEMWkJFqPkWBklP1dulnqkq?usp=sharing