scholarly journals Traffic accident monitoring system using deep learning

2018 ◽  
Vol 7 (2.21) ◽  
pp. 283
Author(s):  
A Manikandan ◽  
R Anandan
Keyword(s):  
Deep Learning ◽  
Traffic Management ◽  
Traffic Accident ◽  
Learning Algorithm ◽  
Road Accident ◽  
Stochastic Gradient Descent ◽  
Human Society ◽  
Accident Risk ◽  
The Road ◽  
Accident Data

A short time period in development of rural places and public vehicle transportation system globally increased. The road accident are increased by the traffic problems last five years. It is a big problem of human society. These traffic accident are how can we happen and how to solve traffic management. Here we collect the traffic accident data and GPS record data using these data to build a deep learning model of stochastic gradient descent learning algorithm method used to solve critical problem of a traffic accident risk.    

Share Market Data Prediction Strategies using Deep Learning Algorithm

2019 ◽  
Vol 13 ◽  
Author(s):  
A John. ◽  
D. Praveen Dominic ◽  
M. Adimoolam ◽  
N. M. Balamurugan
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Stock Market ◽  
Predictive Analytics ◽  
Learning Algorithm ◽  
Market Price ◽  
Stochastic Gradient ◽  
Stochastic Gradient Descent ◽  
Mining Machine ◽  
Gradient Descent Algorithm

Background:: Predictive analytics has a multiplicity of statistical schemes from predictive modelling, data mining, machine learning. It scrutinizes present and chronological data to make predictions about expectations or if not unexplained measures. Most predictive models are used for business analytics to overcome loses and profit gaining. Predictive analytics is used to exploit the pattern in old and historical data. Objective: People used to follow some strategies for predicting stock value to invest in the more profit-gaining stocks and those strategies to search the stock market prices which are incorporated in some intelligent methods and tools. Such strategies will increase the investor’s profits and also minimize their risks. So prediction plays a vital role in stock market gaining and is also a very intricate and challenging process. Method: The proposed optimized strategies are the Deep Neural Network with Stochastic Gradient for stock prediction. The Neural Network is trained using Back-propagation neural networks algorithm and stochastic gradient descent algorithm as optimal strategies. Results: The experiment is conducted for stock market price prediction using python language with the visual package. In this experiment RELIANCE.NS, TATAMOTORS.NS, and TATAGLOBAL.NS dataset are taken as input dataset and it is downloaded from National Stock Exchange site. The artificial neural network component including Deep Learning model is most effective for more than 100,000 data points to train this model. This proposed model is developed on daily prices of stock market price to understand how to build model with better performance than existing national exchange method.

scholarly journals The Effects of ITS Application in Speed Management on State Road From Mali Pozarevac to Kragujevac

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Tomislav Petrović ◽  
Miloš Milosavljević ◽  
Milan Božović ◽  
Danislav Drašković ◽  
Milija Radović
Keyword(s):  
Traffic Safety ◽  
Traffic Management ◽  
Quality Data ◽  
Transport Systems ◽  
Speed Limit ◽  
Accident Risk ◽  
The Road ◽  
Road Users ◽  
Speed Management ◽  
On The Road

The application of intelligent transport systems (hereinafter ITSs) on roads enables continuous monitoring of road users during a whole year with the aim to collect good-quality data based on which the more complex analyses could be done, such as monitoring of certain traffic safety indicators. Automatic traffic counters are one of the most commonly implemented ITSs for collecting traffic flow parameters that are relevant for traffic management on state roads in Republic of Serbia. This paper presents one of the possible ways to collect, analyze and present data on road users’ speeds using automatic traffic counters, where certain traffic safety indicators are analyzed in terms of road users’ compliance with the speed limit on the road section from Mali Pozarevac to Kragujevac. Based on the analyses of data downloaded from automatic traffic counters, it is observed that an extremely high percentage of vehicles drive at speed higher than the speed limit, indicating clearly to higher traffic accident risk, as well as to the need for a tendency to implement speed management on roads using ITS in the forthcoming period.

scholarly journals ROAD SAFETY CAMPAIGNS TO REDUCE TRAFFIC ACCIDENTS FOR YOUNG ROAD USERS

ICCD ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 601-606
Author(s):  
Widodo Budi Dermawan ◽  
Dewi Nusraningrum
Keyword(s):  
School Environment ◽  
Road Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
School Administrators ◽  
Road User ◽  
The Road ◽  
Road Users ◽  
Accident Data

Every year we lose many young road users in road traffic accidents. Based on traffic accident data issued by the Indonesian National Police in 2017, the number of casualties was highest in the age group 15-19, with 3,496 minor injuries, 400 seriously injured and 535 deaths. This condition is very alarming considering that student as the nation's next generation lose their future due to the accidents. This figure does not include other traffic violations, not having a driver license, not wearing a helmet, driving opposite the direction, those given ticket and verbal reprimand. To reduce traffic accident for young road user, road safety campaigns were organized in many schools in Jakarta. This activity aims to socialize the road safety program to increase road safety awareness among young road users/students including the dissemination of Law No. 22 of 2009 concerning Road Traffic and Transportation. Another purpose of this program is to accompany school administrators to set up a School Safe Zone (ZoSS), a location on particular roads in the school environment that are time-based speed zone to set the speed of the vehicle. The purpose of this paper is to promote the road safety campaigns strategies by considering various campaign tools.

Augmenting Classifiers Performance through Clustering

2018 ◽  
Vol 8 (1) ◽  
pp. 57-68 ◽  
Author(s):  
Sachin Kumar ◽  
Prayag Tiwari ◽  
Kalitin Vladimirovich Denis
Keyword(s):  
Traffic Accident ◽  
Latent Class ◽  
Safety Concern ◽  
Health And Safety ◽  
Road Accident ◽  
Support Vector ◽  
Road Accidents ◽  
Real World Data ◽  
The Public ◽  
Accident Data

Road and traffic accident data analysis are one of the prime interests in the present era. It does not only relate to the public health and safety concern but also associated with using latest techniques from different domains such as data mining, statistics, machine learning. Road and traffic accident data have different nature in comparison to other real-world data as road accidents are uncertain. In this article, the authors are comparing three different clustering techniques: latent class clustering (LCC), k-modes clustering and BIRCH clustering, on road accident data from an Indian district. Further, Naïve Bayes (NB), random forest (RF) and support vector machine (SVM) classification techniques are used to classify the data based on the severity of road accidents. The experiments validate that the LCC technique is more suitable to generate good clusters to achieve maximum classification accuracy.

scholarly journals Road Safety Assessment Considering the Expected Fatal Accident Density

2020 ◽  
Vol 15 (2) ◽  
pp. 31-48
Author(s):  
Vilma Jasiūnienė ◽  
Rasa Vaiškūnaitė
Keyword(s):  
Road Safety ◽  
Safety Assessment ◽  
Safety Management ◽  
Road Accident ◽  
Fatal Accident ◽  
Road Infrastructure ◽  
The Road ◽  
Management Procedures ◽  
Accident Data ◽  
Wide Road

Network-wide road safety assessment throughout the whole network is one of the four road infrastructure safety management procedures regulated by Directive 2019/1936/EC of the European Parliament and of the Council of 23 October 2019 Аmending Directive 2008/96/EC on Road Infrastructure Safety Management and one of the methods for determining the direction of investment in road safety. So far, the implementation of the procedure has been lightly regulated and adapted using various road safety indicators. The paper describes the evaluation of road accident data that is one of the criteria for conducting a network-wide road safety assessment. Taking into consideration that networkwide road safety assessment is a proactive road safety activity, the paper proposes to conduct road safety assessment considering the expected fatal accident density. Such assessment makes it possible to assess the severity of accidents, and the use of the predicted road accident data on calculating the introduced road accident rate contributing to the prevention of accidents. The paper describes both the empirical Bayes method for predicting road accidents and the application of one of the road safety indicators – the expected fatal accident density – to determine five road safety categories across the road network. The paper demonstrates the application of the proposals submitted to Lithuanian highways using road accident and traffic data for the period 2014–2018.

scholarly journals A Simple Vehicle Counting System Using Deep Learning with YOLOv3 Model

2020 ◽  
Vol 4 (3) ◽  
pp. 462-468 ◽  
Author(s):  
Muhammad Fachrie
Keyword(s):  
Deep Learning ◽  
Learning Algorithm ◽  
Traffic Monitoring ◽  
Computational Time ◽  
Vehicle Speed ◽  
Robust Performance ◽  
Counting System ◽  
The Road ◽  
Vehicle Identification ◽  
Traffic Violation

Deep Learning is a popular Machine Learning algorithm that is widely used in many areas in current daily life. Its robust performance and ready-to-use frameworks and architectures enables many people to develop various Deep Learning-based software or systems to support human tasks and activities. Traffic monitoring is one area that utilizes Deep Learning for several purposes. By using cameras installed in some spots on the roads, many tasks such as vehicle counting, vehicle identification, traffic violation monitoring, vehicle speed monitoring, etc. can be realized. In this paper, we discuss a Deep Learning implementation to create a vehicle counting system without having to track the vehicles movements. To enhance the system performance and to reduce time in deploying Deep Learning architecture, hence pretrained model of YOLOv3 is used in this research due to its good performance and moderate computational time in object detection. This research aims to create a simple vehicle counting system to help human in classify and counting the vehicles that cross the street. The counting is based on four types of vehicle, i.e. car, motorcycle, bus, and truck, while previous research counts the car only. As the result, our proposed system capable to count the vehicles crossing the road based on video captured by camera with the highest accuracy of 97.72%.

High-Risk Road Accident Corridors in Dhaka, Bangladesh

2013 ◽  
Vol 65 (3) ◽  
Author(s):  
Ishtiaque Ahmed ◽  
Bayes Ahmed ◽  
Mohd. Rosli Hainin
Keyword(s):  
High Risk ◽  
Traffic Accident ◽  
Safety Management ◽  
Road Transport ◽  
Road Accident ◽  
Highway Safety ◽  
Road Accidents ◽  
Highway Safety Manual ◽  
Roadway Safety ◽  
Accident Data

Bangladesh has one of the highest fatality rates in road accidents and to address the safety problem is a serious concern. Dhaka is the most vulnerable city of the country. Bangladesh Road Transport Authority maintains a database of accidents using outdated software that lacks in geo-referencing facility.  This makes the analysis of accident locations a challenging task. The area for this study was the Dhaka Metropolitan Police area where the concerned forty one police stations are responsible for collecting traffic accident data. The Highway Safety Manual identifies the “Network Screening” as the first step of the Roadway Safety Management Process. This study focuses on locating the accidents on urban roadways in Dhaka and identifies thirty corridors and ranks them using geo-referenced data through developing and using a GIS database. Dhaka-Mymensing Road was found to be the most vulnerable road corridor followed by Airport Road and Mirpur Road respectively. The study recommended special attention and special “Diagnostic” studies as explained in the Highway Safety Manual for the high-risk corridors and to put emphasis on the accident data collection and reporting system. Adoption of modern technologies like GPS and GIS in collecting and reporting of the traffic accident data was emphasized.

ROAD ACCIDENT COST PREDICTION MODEL USING SYSTEMS DYNAMICS APPROACH

Transport ◽  
2008 ◽  
Vol 23 (1) ◽  
pp. 59-66 ◽  
Author(s):  
Pachaivannan Partheeban ◽  
Elangovan Arunbabu ◽  
Ranganathan Rani Hemamalini
Keyword(s):  
Cost Model ◽  
Economic Value ◽  
Road Accident ◽  
Substantial Part ◽  
Systems Dynamics ◽  
Investment Projects ◽  
The Road ◽  
Statistical Life ◽  
Accident Data ◽  
Year 2000

Accident costs are an important component of external costs of traffic, a substantial part is related to fatal accidents. The evaluation of fatal accident costs crucially depends on the availability of an estimate for the economic value of a statistical life. This paper aims to develop a model for road accident through systems dynamics approach. To build an accident model, various factors causing the road accident and cost were identified. This model is capable of calculating the accident rate and its costs for the future. In this study the accident caused by bus alone is considered. The cost model is dealt more in this study as it requires more complex assessment. The accident model is built on the year 2000 data and predicted the accidents up to 2020 for every 5‐year interval. The accident model is valuated by comparing the predicted and actual accident data for the year 2005. Three scenarios were studied by changing the income growth rate and discount rate. Finally, best scenario is suggested for implementation. The outcome of the study is highly useful for the planners, administrators and police to make their decisions effectively for road safety investment projects.

scholarly journals Contactless Automated Express Evaluation of Damages to a Car Body by Visual Parameters

2019 ◽  
Vol 18 (6) ◽  
pp. 471-475
Author(s):  
M. Tarasovа ◽  
N. Filkin ◽  
R. Yurtikov
Keyword(s):  
Road Safety ◽  
Human Factor ◽  
Road Accident ◽  
The Body ◽  
Road Accidents ◽  
Car Body ◽  
The Road ◽  
Accident Data ◽  
Established Fact ◽  
Time Required

Explosive development of computer technologies and their availability made it possible to extensively focus nowadays on emerging state-of-the-art technologies, digitalization, artificial intelligence, and automated systems, including in the field of road safety. It would be reasonable to implement some technical devices in this respect to remove human factor and automate some procedures completed at the scene of a road accident. Automatically filled up road accident inspection records and, mainly, diagrams of the accident will reduce time required for the examining inspector and remove human factor. Ultimately, an automated road accident data sheet is suggested to be established. To tackle the issues above requires a technique to determine whether the produced damages to the car body result from the same road accident. The fact remains that there are circumstances when even vehicle trace examination would not do the job, in case of multiple corrosive damage to the body. In view of the above, a technique designed to determine whether the damages produced are caused at the same point of time gains its ground. A technique for a time-related corrosion examination is offered herein to cut expenditures for diagnostics and expert examination of road accidents. That will also eliminate the matters of argument with respect to the road accident evaluation in court. Among added benefits of the technique are that it is simple, quick to implement, and requires no human involvement. It is a well-established fact that each chemical element or a mixture of substances has its own timeinvariant color attributes which allows to determine availability of one or another substance during corrosion of metal surfaces, by emission from the surface in question.

scholarly journals PENINGKATAN KESELAMATAN JALAN PADA BLACK SPOT JALAN PROVINSI DI KABUPATEN SLEMAN

2021 ◽  
Vol 21 (2) ◽  
pp. 109-122
Author(s):  
One Sigit Hermanto ◽  
Agus Taufik Mulyono ◽  
Latif Budi Suparma
Keyword(s):  
Road Safety ◽  
Traffic Management ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Safety Evaluation ◽  
Black Spot ◽  
The Road ◽  
Technical Requirements ◽  
Black Spots ◽  
Rumble Strip

Abstract   The fatality rate of traffic accidents in Sleman Regency is increasing every year. This study aims to identify black spots and set priorities for repairing road infrastructure components needed to improve road safety on 3 provincial roads in Sleman Regency. The black spot is determined using the Accident Equivalence Number Method and the Upper Control Limit. The evaluation carried out resulted in the 3 worst segments on each observed road segment. The results of the road safety evaluation show that the technical implementation of traffic management and engineering, the technical use of road components, and the technicality of road equipment are the 3 technical requirements of the road with the lowest level of application. To improve road safety, this study recommends adding rumble strips, adding signs, relocating roadside hazards, and adding sidewalks and crossing zones.   Keywords: fatality; black spots; traffic accident; road; road safety.     Abstrak   Tingkat fatalitas kecelakaan lalu lintas di Kabupaten Sleman meningkat setiap tahun. Penelitian ini bertujuan untuk mengidentifikasi black spot dan menetapkan prioritas perbaikan komponen infrastruktur jalan yang diperlukan untuk meningkatkan keselamatan jalan di 3 ruas jalan provinsi di Kabupaten Sleman. Black spot ditentukan dengan menggunakan Metode Angka Ekivalensi Kecelakaan dan Batas Kontrol Atas. Evaluasi yang dilakukan menghasilkan 3 segmen terburuk pada setiap ruas jalan yang diamati. Hasil evaluasi keselamatan jalan menunjukkan bahwa teknis penyelenggaraan manajemen dan rekayasa lalu lintas, teknis pemanfaatan bagian-bagian jalan, dan teknis perlengkapan jalan merupakan 3 persyaratan teknis jalan dengan tingkat penerapan terendah. Untuk meningkatkan keselamatan jalan, studi ini merekomendasikan penambahan rumble strip, penambahan rambu, merelokasi hazard yang terdapat di tepi jalan, serta penambahan trotoar dan zona penyeberangan.   Kata-kata kunci: fatalitas; black spot; kecelakaan lalu lintas; jalan; keselamatan jalan.

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