scholarly journals Modelling Road Accident using Poisson regression Models

2021 ◽  
Vol 9 (VI) ◽  
pp. 4635-4640
Author(s):  
Dvij Chaudhari
Keyword(s):  
Traffic Control ◽  
Poisson Regression ◽  
Road Safety ◽  
Road Accident ◽  
Road Accidents ◽  
Accident Prediction ◽  
Urban Road ◽  
Novel Approach ◽  
Road Speed ◽  
Generalised Linear Modelling

The objective of this research is to evaluate the safety of multi-lane urban roads in India. In this paper, a generalised linear modelling technique is applied for the analysis of the Indian Highway's road accident. The features of road, speed, and traffic data are analysed in Surat on four-lane urban roads. A novel approach to the model of accident prediction for an urban highway is being proposed to include daily average travel (ADT) and average spot speed (AS). The model was developed as a reliant variable and significant variables such as chain width, intersection no, ADT, AS, as separate variables for accidents per kilometre.. The results of the model provide a better assessment of accidents on a multilateral urban road. Because road accidents are different, statistical models do not adequately capture the characteristics of each section. As a result, the results of Poisson regression were the opposite of these variables. There was also no statistically significant type of traffic control. Significant statistically at level 0.05. Accident locations were assessed by correlating the severity of the accident with different attributes. This investigation will contribute to improving urban road safety.

scholarly journals Predicting and Preventing Recommender System for Telangana Road Accidents

2020 ◽  
Vol 8 (6) ◽  
pp. 1353-1358
Keyword(s):  
Road Safety ◽  
Recommendation System ◽  
Similarity Measures ◽  
Road Accident ◽  
Road Accidents ◽  
Driver Behaviour ◽  
Accident Prediction ◽  
The Road ◽  
Model Recognition

Today people are suffering with road accidents in world wide. Analyzing these Road accidents are the major challenge in identifying and predicting primary features related with catastrophes. All these features are valuable for anticipatory computes to conquer road mishaps. Integrating various analytics techniques can get better model recognition and avoid road mishaps. As road safety growing quiet apprehension, speedy analytics observes all safety techniques in dynamic to spot malfunction that may signifies road mishaps on identifying key features related with road , mishaps in Telangana state. In our propose work, a framework to analyze the road mishap with classification of accidents and clustering, which analyze mishap data of Telangana stated district wise. The proposed framework describes the recommendation system for predicting road accidents. For this, classify the road accidents into fatal, major and minor. We implemented district wise data into clustering and applying enhanced k-mean algorithm. Further, implemented similarity measures to detecting the places where the severity of accidents happened and also analysing the driver behaviour analysis while accidents occur. The implementation result reveals that the road accident prediction exhibits enhance in certain areas and those areas exists in districts should be the major concern to acquire anticipatory measure to conquer the road mishaps.

scholarly journals A Novel Approach in Evaluating the Impact of Vehicle Age on Road Safety

2020 ◽  
Vol 32 (6) ◽  
pp. 789-796
Author(s):  
Árpád Török
Keyword(s):  
Logistic Regression ◽  
Road Safety ◽  
Multinomial Logistic Regression ◽  
Road Accident ◽  
Road Segment ◽  
Novel Approach ◽  
The Impact

This study examines the correlation between road accident casualties and the age of the vehicle, assuming that the age of vehicles and the improvements in their safety designs are related. The study evaluates the impact of the interrelationship between road segment characteristics and road accident type on vehicle age at the time of the accident (AVC). To analyse the nested relationship between these variables, a multinomial logistic regression (MML) model has been developed. The result of the analysis also duly finds that vehicle age has an emphatic role in the occurrence of accidents.

Road Safety Model: Some Fundamental Ideas

1996 ◽  
Vol 1563 (1) ◽  
pp. 48-57 ◽  
Author(s):  
Francis P. D. Navin ◽  
Arthur Bergan ◽  
Guanyu Zhang
Keyword(s):  
Developing Countries ◽  
Road Safety ◽  
Developed Countries ◽  
Road Accident ◽  
Personal Safety ◽  
Road Accidents ◽  
Fundamental Relationship ◽  
The Social ◽  
Special Cases ◽  
Accident Statistics

A fundamental relationship has been developed that explains road accident statistics in developed and developing countries. The model uses two variables, traffic hazard measured as deaths per vehicle and motorization measured as vehicles per person, to estimate personal hazard as deaths per person. Special cases of the model are those by Smeed, Trinca et al., and Koornstra. The model of fatalities has two extremes. Early motorization has high traffic hazard and personal safety is low and increasing. Full motorization is characterized by a moderate and falling traffic hazard and a low and decreasing personal safety. Between these extremes, there is a maximum number of fatalities per population. Models for personal injury and total road accidents in developed countries appear to follow a similar trend. Available world data fit the proposed relationships well. The models allow planners and engineers to estimate the future maximum road fatalities for developing countries. The model has been extended to incorporate an automobile ownership model that explains some of the growth in motorization. A traffic hazard model is also outlined, in part on the basis of the ideas developed by Koornstra. The extended models should allow a more detailed analysis of some of the social and engineering factors that contribute to road safety.

scholarly journals Studies on the impact of the technical characteristics of local roads on road safety

2019 ◽  
Vol 262 ◽  
pp. 05006
Author(s):  
Stanisław Gaca ◽  
Mariusz Kieć
Keyword(s):  
Road Safety ◽  
Road Traffic ◽  
Road Accidents ◽  
Safety Measures ◽  
Accident Prediction ◽  
The Road ◽  
Access Road ◽  
Local Roads ◽  
On The Road ◽  
The Impact

Local roads (district roads) constitute an important part of the road network in Poland, making up around 29.7 % (124,945 km) of all public roads. In 2017, 10,578 accidents, which is 35.7% of all accidents in Poland, took place on local roads. These roads are used primarily by regular users who are very familiar with the defects of these roads. This means that the effects of the low technical standard of local roads and the insufficient number of road traffic devices on the safety on the road can be partly compensated for by the fact that drivers adjust their behaviour to the conditions on the road. This hypothesis can be verified through developing dependency models of road safety measures of local roads’ and technical characteristics. The article presents the research carried out based on regression models of accident prediction. The models were developed with the use of the data on the road surroundings arrangement (built-up areas, access), road condition and the extent of signposting, including data on speed limits and overtaking as well as risk exposure variables. Due to the incomplete data on accidents and the small number of accidents, different approaches to the modelling of the number of road accidents were applied.

scholarly journals The Effects of Roadside Hazards on Road Accident Severity

2019 ◽  
Vol 49 (2) ◽  
pp. 319-339 ◽  
Author(s):  
Marcin Budzyński ◽  
Kazimierz Jamroz ◽  
Łukasz Jeliński ◽  
Anna Gobis
Keyword(s):  
Road Safety ◽  
Road Accident ◽  
Road User ◽  
Road Accidents ◽  
Safety Equipment ◽  
Design Rules ◽  
The Road ◽  
Run Off ◽  
Safety Strategies ◽  
Accident Severity

Abstract The risk of becoming involved in an accident emerges when elements of the transport system do not operate properly (man – vehicle – road – roadside). The road, its traffic layout and safety equipment have a critical impact on road user safety. This gives infrastructural work a priority in road safety strategies and programmes. Run-off-road accidents continue to be one of the biggest problems of road safety with consequences including vehicle roll-over or hitting a roadside object. This type of incident represents more than 20% of rural accidents and about 18% of all road deaths in Poland. Mathematical models must be developed to determine how selected roadside factors affect road safety and provide a basis for new roadside design rules and guidelines.

scholarly journals A Mechanistic Model for Predicting Accident Potential of Vehicles Transiting in Nigerian Roads

2019 ◽  
pp. 1-10
Author(s):  
Ama Agwu ◽  
Nwogu Chukwunoso ◽  
Nwankwojike Bethrand
Keyword(s):  
Environmental Factors ◽  
Prediction Model ◽  
Road Safety ◽  
Mechanistic Model ◽  
Road Accidents ◽  
Percentage Contribution ◽  
Accident Prediction ◽  
Accident Probability ◽  
Accident Data ◽  
Mechanical Factors

An accident prediction model was developed for determining the accident potential of a vehicle while on transit. The model identifies the various factors responsible for vehicle crashes. With the help of accident data obtained from the database of the Nigerian Federal Road Safety Corps (FRSC), the percentage contribution of each factor is calculated. These accident-cause factors were further grouped into three distinct classes: Human factors (HF), Mechanical factors (MF) and Environmental factors (EF). Analysis of the accident data showed that HF is the chief cause of most road accidents recorded, followed by MF and EF with probabilities of 0.846, 0.138 and 0.016 respectively. Also, driver age, travel distance and maintenance frequency of the vehicle were considered in the development of the model. The model gives an output ranging from 0-1. Values close to 0 mean low accident probability while values close to 1 signify high accident probability. Application and adherence to this model will significantly reduce the frequency of road accidents. Finally, transport companies and fleet operators are therefore encouraged to embrace and use this innovation for safer operations.

scholarly journals Analysis of Road Accidents Using Data Mining Techniques

2018 ◽  
Vol 7 (3.10) ◽  
pp. 40 ◽  
Author(s):  
Ms Nidhi. R ◽  
Ms Kanchana V
Keyword(s):  
Road Safety ◽  
Preventive Measures ◽  
Road Accident ◽  
The State ◽  
Road Accidents ◽  
Bayesian Techniques ◽  
Vehicle Accidents ◽  
The People ◽  
The Government ◽  
Using Data

Road Accident is an all-inclusive disaster with consistently raising pattern. In India according to Indian road safety campaign every minute there is a road accident and almost 17 people die per hour in road accidents. There are different categories of vehicle accidents like rear end, head on and rollover accidents. The state recorded police reports or FIR’s are the documents which contains the information about the accidents. The incident may be self-reported by the people or recorded by the state police. In this paper the frequent patterns of road accidents is been predicted using Apriori and Naïve Bayesian techniques. This pattern will help the government or NGOs to improve the safety and take preventive measures in the roads that have major accident zones.  

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 Statistical Analysis and Development of Accident Prediction Model of Road Safety Conditions in Hisar City

2021 ◽  
Vol 889 (1) ◽  
pp. 012034
Author(s):  
Keshav Bamel ◽  
Sachin Dass ◽  
Saurabh Jaglan ◽  
Manju Suthar
Keyword(s):  
Traffic Accidents ◽  
Linear Regression Analysis ◽  
Severity Index ◽  
Road Accident ◽  
P Value ◽  
Road Accidents ◽  
Accident Prediction ◽  
New Information ◽  
Margin Of Error ◽  
Accident Data

Abstract The severity of road accidents is a big problem around the world, particularly in developing countries. Recognizing the major contributing variables can help reduce the severity of traffic accidents. This research uncovered new information as well as the most substantial target-specific factors related to the severity of road accidents. T-stat, P-value, Significance and other test values are determined to check the dependency of dependent variable on independent variable in order to obtain the most significant road accident variables. In this research, a comparative analysis of accident data from Hisar and Haryana are compared. According to the findings, Haryana’s accident severity index (46.20) was higher in 2019 than Hisar’s (36.01), while Hisar had fewer accidents per lakh population (33.34) than Haryana (38.40). The outcomes of the study were used to develop an effective and precise accident predicting model is developed for Hisar city and state Haryana using a statistical method. Four models were created using linear regression analysis, two each for Hisar and Haryana. These models produce good results with a margin of error that is within acceptable bounds (0-5%), allowing them to be used to predict future traffic accidents and deaths.

scholarly journals Identification of Road Accident by using Black Spot Method Between Panthaghati to Dhalli Road

2020 ◽  
Vol 9 (2) ◽  
pp. 723-728
Keyword(s):  
Road Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Black Spot ◽  
Research Paper ◽  
Road Accident ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
The Road ◽  
Black Spots

In India road accidents are very serious problem because of large population and high traffic density of vehicles. Most of the road accidents occur mainly due to the negligence of driver and poor infrastructure only a few accidents occur due to the technical error of vehicles. The main purpose of this research paper is prevention of road traffic accidents and improvement of road safety in Shimla. Road safety is very important aspect of today’s life, so it is important that everybody should aware about road safety. To do this study a section of 12km length is chosen between Panthaghati to Dhalli in district Shimla on NH 5 where accidents black spots are identified for the section by analyzing secondary data used to prevent road accidents. In this study primary data is used for observing the road conditions and secondary data is used to find accidents black spot. Black Spot is a point or a place on the road where road accident occurs repeatedly one after another which is known as accident black spot. To identify these black spots we use weighted severity index (WSI) method. It is one the most reliable and effective method for determining the most proven accidents black spots. Shimla is a hilly area and it has narrow roads, blind curve and black spots which increase the chances of road traffic accidents. In past recent years road traffic accidents are increasing in Shimla and this study deals with identification of major issues causing road traffic accidents. This research paper helps to improve the road safety in Shimla because in this study the analysis has been done to identify the major problems responsible for gradually increasing road accidents. This research paper is also used in future research paper as reference purpose and it will also provide an overview to other researchers who want do their research on similar kind of topics.

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