Methodological development for selection of significant predictors explaining fatal road accidents

Dadashova, Bahar; Arenas-Ramírez, Blanca; Mira-McWilliams, José; Aparicio-Izquierdo, Francisco

doi:10.1016/j.aap.2016.02.003

Cited by 23 publications

(32 citation statements)

References 62 publications

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“…Various additional factors may potentially affect accident forecasting. According to international research studies (Table 1), time-series methods have been applied for accident prediction; for example, Quddus [9], Ramstedt [10], Dadashova et al [11], García-Ferrer et al [12], Zheng and Liu [13], Sanusi et al [14], Parvareh et al [15] and Dadashova et al [16]. The Autoregressive integrated moving average (ARIMA) model has mostly been applied to time-series analysis.…”

Section: Previous Study In Road Accident Predictionmentioning

confidence: 99%

Forecasting Road Traffic Deaths in Thailand: Applications of Time-Series, Curve Estimation, Multiple Linear Regression, and Path Analysis Models

2020

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In 2018, 19,931 people were killed in road accidents in Thailand. Thus, reduction in the number of accidents is urgently required. To provide a master plan for reducing the number of accidents, future forecast data are required. Thus, we aimed to identify the appropriate forecasting method. We considered four methods in this study: Time-series analysis, curve estimation, regression analysis, and path analysis. The data used in the analysis included death rate per 100,000 population, gross domestic product (GDP), the number of registered vehicles (motorcycles, cars, and trucks), and energy consumption of the transportation sector. The results show that the best three models, based on the mean absolute percentage error (MAPE), are the multiple linear regression model 3, time-series with exponential smoothing, and path analysis, with MAPE values of 6.4%, 8.1%, and 8.4%, respectively.

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Section: Previous Study In Road Accident Predictionmentioning

confidence: 99%

Forecasting Road Traffic Deaths in Thailand: Applications of Time-Series, Curve Estimation, Multiple Linear Regression, and Path Analysis Models

2020

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“…During the financial decision-making process and for the safety of humans, it is necessary to analyze the road safety performance of roads [98]. To conduct the research regarding road safety performance analysis benchmarking has a vital role [16][17][18]. Following the concept of multiple outputs and multiple inputs, data envelopment analysis (DEA) is one of the popular methods based on the linear program ( Figure 3).…”

Section: Road Accident Risk Index and Benchmarkingmentioning

confidence: 99%

“…Because of that reason, hotspot identification of accident-prone locations remains a focal point of interests for transportation engineers. That is why a series of researches were involved in relationship analysis of accidents [12][13][14][15][16][17][18][19][20][21][22][23] in context of volume/capacity (V/C) [18,19,24,25], vehicles miles travelled (VMT) [17,[26][27][28][29], vehicles hours travelled (VHT) [25,30,31], speed [18,20,24,[32][33][34][35][36][37][38], flow [12,13,32,35,36,39], and geometric design [35,[40][41][42][43][44]. Different methods were applied to locate the risky road segments to be treated for safety level enhancement.…”

Section: Introductionmentioning

confidence: 99%

Road Infrastructure Analysis with Reference to Traffic Stream Characteristics and Accidents: An Application of Benchmarking Based Safety Analysis and Sustainable Decision-Making

Shah

Ahmad

2019

Applied Sciences

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Road infrastructure sustainability is directly associated with the safety of human beings. As a transportation engineer and policymaker, it is necessary to optimize the funding mechanism for road safety improvement by identifying problematic road segments. Infrastructure improvement is one of the key targets for efficient road safety management. In this study, data envelopment analysis (DEA) technique has been applied in combination with a geographical information system (GIS) to evaluate the risk level of problematic segments of a 100 km-long motorway (M-2) section. Secondly, the cross efficient method has been used to rank the risky segments for prioritization and distribution of funding to improve the road safety situation. This study will help in efficiently identifying the risky segments for safety improvement and budget allocation prioritization. GIS map will further improve the visualization and visibility of problematic segments to easily locate the riskiest segments of the motorway.

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“…The overall results of the study show that narrow main lane, shoulder lane, median lane and slow lane, might increase the accident severity. Higher superelevation and steeper slope also will increase the severity of the accident (Dadashova et al 2016a). …”

Section: Road Safety Improvement Measuresmentioning

confidence: 99%

“…Other means must be implemented as well. For example, in order to decrease the rate of heavy accidents, a number of measures must be applied, amongst which are the enforcement of road safety policies and innovations in car engineering (Ernstberger et al 2015;Dadashova et al 2016a) and emergency medicine, alcohol level control, seat belt usage enforcement (Ernstberger et al 2015), periodic medical examination (Etehad et al 2015), information campaigns, local warning systems (Bergel-Hayat et al 2013), driver behavior surveillance, legislative measures, investment in road maintenance, vehicle characteristics (Dadashova et al 2016b).…”

Section: Road Safety Improvement Measuresmentioning

confidence: 99%

The Key Issues of Road Design Found from Road Safety Inspections and Road Safety Audits

Tumavičė¹,

Vitkienė²,

Kaniušėnienė³

et al. 2017

Proccedings of 10th International Conference "Environmental Engineering"

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Abstract. In order to reduce accident rate on roads and streets more and more various road safety measures are being implemented each year. Nevertheless, road safety problem exists in most countries. For example, even though accident rate in Lithuania was almost halved (6372 to 3161 yearly accidents) from years 2004 to 2015, fatality rate is still quite high -8.3 per 100000 people. New regulations, approved in 2008, dictate the need of carrying out road safety audits and road safety inspections for all road and street design projects. This paper presents most common road design errors and methods of fixing those errors based on Vilnius Gediminas Technical University Road Research Institute road safety auditors' experience from years 2011 to 2016. Most common safety problems are organized and presented in groups ordered by their importance. Recommendations on how to improve road safety audit and inspection procedures in the future are formulated, as well as suggestions on improving road project design stage by taking most common flaw priority into consideration.

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Methodological development for selection of significant predictors explaining fatal road accidents

Cited by 23 publications

References 62 publications

Forecasting Road Traffic Deaths in Thailand: Applications of Time-Series, Curve Estimation, Multiple Linear Regression, and Path Analysis Models

Forecasting Road Traffic Deaths in Thailand: Applications of Time-Series, Curve Estimation, Multiple Linear Regression, and Path Analysis Models

Road Infrastructure Analysis with Reference to Traffic Stream Characteristics and Accidents: An Application of Benchmarking Based Safety Analysis and Sustainable Decision-Making

The Key Issues of Road Design Found from Road Safety Inspections and Road Safety Audits

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