Road Pulse

Safety and comfort of road users is a matter of great concern. Due to increase in traffic violation police enforcement is necessary element in road safety. It is essential to build a safer and much more reliable and efficient traffic control and management system to avoid tragic events like road acc

Project Title

Road Pulse

Project Area of Specialization

Artificial Intelligence

Project Summary

Safety and comfort of road users is a matter of great concern. Due to increase in traffic violation police enforcement is necessary element in road safety. It is essential to build a safer and much more reliable and efficient traffic control and management system to avoid tragic events like road accidents etc. 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.

 We try to propose a system which can detect traffic violations like speed violation, stop line violation, red line violation etc. According to different road conditions our system will be able to provide an estimation of speed limit, vehicles count and accidents prediction. The accident prediction model is represented by a generalized linear model which, on the basis of the available data, determines the expected number of accidents for individual types of road segments. A critical road segment is defined as a segment where the reported number of accidents significantly exceeds the number of expected accidents on roads with similar geometric and traffic characteristics. This method can be used as an effective tool for road network safety management. This system will also help traffic administrators so a particular action can be taken in real time.

Project Objectives

• The project aims to automate the traffic rules violation detection system and make it convenient for the traffic police department to monitor the traffic and take action against the violated vehicle owner in a fast and efficient way. Detecting and recognizing the vehicle and their activities accurately is the main priority of the system.
• We want to design a generic model that would cover many separate related projects like Sensor less red light violation detection system and Vehicle detection and counting system based on vision
• Also we want to overcome the human errors in video surveillance
• Automatic traffic violation in Video analytics using can play an important role in getting in-depth insights into traffic conditions and these insights can help by routing this information to traffic administrators which can take an effective action on any type of event.
• By implementing such system labor cost can be reduced. Reduction in labor 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.
• Recently working traffic architecture are not so precise and results aren’t that much clear to investigate the driver. It only gathers vehicle info, so we want to cover all the flaws present in previous system

Project Implementation Method

Since there are many architectures are introduced to detect traffic violation automatically.    Architectures like spatial analysis were previously proposed for traffic accidents and vehicle communication system data and Vehicle detection through image processing for traffic surveillance and control only target spatial domain only.

So, we will not only manipulate spatial domain for our data but will also work on temporal domain. Our architecture will use 3D deep neural networks based models which extract useful features from videos both spatially and temporally.

Training process will start from converting the input video into frames. These 3D frames will be passed to our 3D architecture for training and learning purpose of our model. After that once this model is trained it will be tested on different datasets to check the accuracy and reliability. Then this architecture will be mounted in an application having an interactive UI for the automatic detection of traffic violation.

Application design will be quite simple, innovative and user friendly. Application will detect different violations in videos and will pop up a message or alarm to pin point the event. This will make easier for operator to differentiate between the violation event and other activities happening in the video. Furthermore, application will record data associated to these violations in a local data-base, and also allow visualization of the spatial and temporal information of these traffic violations. This information will be used by other modules in the app  like vehicle count and accident predictor to produce accurate output.

Benefits of the Project

Automated Traffic Enforcement works fine while the public is given the perception that they can be checked for traffic violations anytime, anywhere. Moreover, the violator has to be directly notified of a violation. The punishment, which mostly consists of the payment of a first-rate, desires to be paid quick and is perceived as high enough to behave as a robust deterrent. Administratively high-quality collection can be a tough and laborious system if the violator isn't inclined to pay. Therefore, it has to be definitely clear to the violator that

• The government have stable and correct evidence that the violation took place
•  There's no escape from the issued excellent
•  That the penalty will hold to increase with fee delays.

 Moreover, it has to be apparent that eventually, any non-paying violator could be ordered to seem earlier than a decide in court. Moreover, this will dramatically reduce the traffic violation and will help to reduce accidents. The system will automate the traffic rules violation detection system and make it convenient for the traffic police department to monitor the traffic and take action against the violated vehicle owner in a fast and efficient way. Detecting and recognizing the vehicle and their activities accurately is the main priority of the system.

Technical Details of Final Deliverable

The final product will be an android application that can run on supporting platforms. The application will use live stream from the security cameras and will detect the violation in real time. Detection will be done by our trained 3D neural network model that will extract the features both spatially and temporally. The application will have other options like vehicle count and accident predictor which will perform their specific functionalities.

Final Deliverable of the Project

Software System

Core Industry

Security

Other Industries

Others

Core Technology

Artificial Intelligence(AI)

Other Technologies

Others

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com