126 research outputs found
Incorporating real-time traffic and weather data to explore road accident likelihood and severity in urban arterials
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Investigation of Pedestrians’ Accident Patterns in Greater Athens Area
No full textAbstractEach year, more than 200 pedestrians are involved in severe road accidents in Greece. This study aims to shed some light on vehicle-pedestrian crashes, which resulted in killed or severely injured pedestrians. For that purpose, data from year 2009 were used. The database consists of 206 killed and severely injured pedestrians in the greater Athens area. A cluster analysis is carried out in order to investigate the existence of pedestrians’ accident patterns by means of categorizing their profiles according to their personal attributes, as well as other recorded characteristics of the accident. In order to conduct the analysis, nine variables were considered, namely the age, gender and nationality of pedestrians, type and age of the vehicle involved, location (intersection or not), day of the week, time (day or night/dusk) and finally pedestrians’ position and action (not walking on the pavement, legal crossing, midblock crossing, not walking on the zebra crossing, red crossing, other action/position). The results revealed two groups of pedestrians. The characteristics of each group and their major differences will help researchers to draw important conclusions in order to carry out further research and also policy makers to promote appropriate measures in order to improve the safety of those vulnerable road users
Utilizing real-time traffic and weather data to explore crash frequency on urban motorways: a cusp catastrophe approach
No full textThe investigation of crash frequency with freeway traffic and weather data has recently received significant attention by researchers. This paper extends previous research by proposing nonlinear models for modeling crash frequencies which incorporate real-time traffic and weather data collected from an urban motorway in Athens, Greece. Cusp catastrophe theory is applied and compared with traditional statistical models such as the negative binomial model. The results of crash frequency models provide evidence of the potential applicability of the cusp catastrophe theory to road safety, however it seems that linearity of the system is preserved. Hence, traditional models such as the negative binomial model are proved equally capable of describing the underlying phenomenon, even though the goodness-of-fit is not as good as that of the cusp model. Therefore, the explanation of crash frequency phenomenon only with nonlinear model can be supported. A number of interesting findings have also been disclosed. Firstly, is that rainfall intensity has a strong linear impact on crashes (high rainfall intensity causes more crashes). On the other hand, average flow is indicated to have a strong non-linear relationship with crash frequency. Finally, more research is needed to further understand the applicability of cusp catastrophe theory in road safety
An advanced multi-faceted statistical analysis of accident probability and severity exploiting high resolution traffic and weather data
No full textAn Exploration of Road Safety Parameters in Belarus and the European Union
No full textAbstractThe objective of the present paper is, through analysing basic road safety parameters in Belarus and the European Union (EU), to explore, compare and outline the key parameters contributing to road fatalities in the recent years in Belarus and EU.Initially, the action plans and safety performances for both Belarus and EU Member States are assessed, based on various indicators and specific time periods. The assessment revealed that during the period 2000–2010, although road fatalities in Belarus decreased about 25%, the overall road safety performance is rather weak compared to the majority of EU States (-43%). During the period 2011–2013, Belarus achieved a noticeable decrease by another 25% reduction in road fatalities, a performance figuring among the best in EU.As to address the parameters related to road fatalities, lognormal regression models were developed and applied to vehicle fleet and demographical data for Belarus and the EU and elasticity values were calculated for the identification of the comparative effect of each variable.The examination of Belarus and certain neighbor EU States revealed that there are some important road safety similarities. In both cases, an increase in the percentage of pedestrian fatalities is related to vehicle type. The results of this research could be proved beneficial for the identification of appropriate measures addressing the underlying road safety issues in Belarus.In conclusion, it was found that the current road safety performance in Belarus is improving rather slowly and requires further effort from all road safety authorities and other stakeholders in Belarus. Belarus presents the second worst performance in pedestrian fatalities compared to the EU Member States, and therefore special emphasis should be given to road safety measures (behaviour, infrastructure, vehicle) focusing on pedestrian safety
Predicting Road Accidents: A Rare-events Modeling Approach
No full textAbstractModeling road accident occurrence has gained increasing attention over the years. So far, considerable efforts have been made from researchers and policy makers in order to explain road accidents and improve road safety performance of highways. In reality, road accidents are rare events. In such cases, the binary dependent variable is characterized by dozens to thousands of times fewer events (accidents) than non-events (non-accidents). Instead of using traditional logistic regression methods, this paper considers accidents as rare events and proposes a series of rare-events logit models which are applied in order to model road accident occurrence by utilizing real-time traffic data. This statistical procedure was initially proposed by King and Zeng (2001) when scholars study rare events such as wars, massive economic crises and so on. Rare-events logit models basically estimate the same models as traditional logistic regression, but the estimates as well as the probabilities are corrected for the bias that occurs when the sample is small or the observed events are very rare. Consequently, the basic problem of underestimating the event probabilities is avoided as stated by King and Zeng (2001). To the best of our knowledge, this is the first time that this approach is followed when road accident data are analyzed. Instead of applying a traditional case-control study, the complete dataset of hourly aggregated traffic data such as flow, occupancy, mean time speed and percentage of trucks, were collected from three random loop detectors in the Attica Tollway (“Attiki Odos”) located in Greater Athens Area in Greece for the 2008–2011 period. The modeling results showed an adequate statistical fit and reveal a negative relationship between accident occurrence and the natural logarithm of speed in the accident location. This study attempts to contribute to the understanding of accident occurrence in motorways by developing novel models such as the rare-events logit for the first time in safety evaluation of motorways
A meta-analysis of the impacts of operating in-vehicle information systems on road safety
No full textThis study aims to estimate the overall impact of distraction due to operating in-vehicle information systems (IVIS) and similar devices while driving on road crashes. While similar research has been undertaken investigating the issue, varying results have been reported so far. Therefore a two-step approach was adopted: initially a review of the literature was conducted to identify key high quality studies and the parameters that they examined. Afterwards, meta-analyses were applied in order to estimate the overall effects of operating IVIS while driving on the absolute proportion of crashes (i.e. the proportion of total crashes due to IVIS). After applying a random effects meta-analysis to the findings of existing studies, it was found that 1.66% of crashes occur due to operating devices in total. In addition, it is indicated that about 0.6% of safety-critical incidents for professional drivers are due to in-vehicle device operation. The odds of crashes influenced by IVIS operation were also estimated and were found to be very low. From the findings of the present review and the meta-analysis, it is suggested that device operation as a risk factor while driving is a less researched aspect of driver distraction than others, and more studies would improve result estimates and transferability, especially for professional drivers. This study summarizes concisely the current effect of driver interaction with in-vehicle information systems on crashes, which might become considerably pertinent in view of the increasing deployment of vehicles with increasing levels of automation.Safety and Security Scienc
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