Road Accident Analysis Factors

2012 ◽  
Vol 253-255 ◽  
pp. 1741-1746
Author(s):  
Hamed Esmaeeli ◽  
Iman Abbaszadehfallah ◽  
Othman Bin Chepuan ◽  
Seyed Hossein Hosseini
Keyword(s):  
Robust Regression ◽  
Developed Countries ◽  
Road Accident ◽  
Work Zone ◽  
Car Ownership ◽  
Accident Analysis ◽  
Effective Parameters ◽  
Accident Rate ◽  
Vehicle Accident ◽  
Regression Techniques

A large number of fatalities on road are occurred by vehicle accident. One of most significant causes of accident on road is increasing car ownership in last decade. The study is conducted to determine a relationship between car ownership and accident rate. The most effective parameters on increasing accident rate in developed countries are studied. This paper investigates a model that forecast the rate of accident on based on previous collected car ownership data. Meanwhile, those parameters can change the rate of car ownership such as income, distance between residential area and work zone, the number of employee over family size and registered car over employee are studied. The study is conducted on based on Australia data and Robust- regression techniques are used to analyse the data. The result shows robust regression reached the most effective coefficient to reduce fatalities on road.

Road Accident Analysis using Machine Learning

2020 ◽  
Author(s):  
Jayesh Patil ◽  
Mandar Prabhu ◽  
Dhaval Walavalkar ◽  
Vivian Brian Lobo
Keyword(s):  
Machine Learning ◽  
Road Accident ◽  
Accident Analysis

scholarly journals Long-term needs of motor vehicle accident victims: are they being met?

2001 ◽  
Vol 24 (1) ◽  
pp. 128 ◽  
Author(s):  
Sue Jeavons
Keyword(s):  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Psychological Trauma ◽  
Road Accident ◽  
Psychological Services ◽  
Insurance Companies ◽  
Emotional Needs ◽  
The Road ◽  
Vehicle Accident ◽  
Support Team

This paper uses the context of a longitudinal rural study, which examined the extent of psychological trauma andpredictors of that trauma following road accidents, to highlight issues for road accident survivors. It then outlines whatcounselling and psychological services are currently offered to road accident victims by the insurance companies andby a voluntary agency, the Road Trauma Support Team. Overall it appears that psychological and emotional needs ofsurvivors are not always acknowledged or provided for.

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.

GIS for Road Accident Analysis in Hong Kong

Annals of GIS ◽  
2004 ◽  
Vol 10 (1) ◽  
pp. 58-67 ◽  
Author(s):  
Poh Chin Lai ◽  
Wing Yee Chan
Keyword(s):  
Hong Kong ◽  
Road Accident ◽  
Accident Analysis

scholarly journals Econometric applications of high-breakdown robust regression techniques

2001 ◽  
Vol 71 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Asad Zaman ◽  
Peter J. Rousseeuw ◽  
Mehmet Orhan
Keyword(s):  
Robust Regression ◽  
Regression Techniques
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