Abstract
In order to be effective, road safety officers must have a complete overview of the accidents in their area of responsibility, including information pertaining to the location and severity of the accidents, and how the number of accidents are developing over time. Ideally, this information is stored in a Geographic Information System (GIS) enabled database, which helps to facilitate data processing and analysis, which enables improved understanding of the reasons for the accidents and the proposals of how to improve road safety. This paper presents a case study based on accident reports from the Zurich City Police. Using a joint GIS and time series analysis based on negative binomial regression, the data is analyzed to identify trends in accident development for several accident subgroups (e.g. bicycle accidents, senior citizen accidents, e-bike accidents) and specific locations. The subgroup of bicycle accidents will be discussed in more detail. The time series analysis is corrected for exposure (e.g. the increasing number of e-bikes) and forecasts the number of accidents which are likely to occur in the future. Significantly higher numbers of accidents than those expected serve as an early warning that further investigation, leading to possible interventions, is required. The case study shows that with this information, it is possible to identify both geographical areas and accident subgroups that have deviating patterns in accident numbers, and should be further investigated. For bicycle accidents, 4 out of 12 districts exceed the average accident trend by over 95 and 3 districts have an accident number that is over 10 higher than that district's forecast, with the highest being 33 above the already increasing accident trend. Other accident subgroups are presented in summary form. The results of the analysis allow consistent and automated analysis across all potential areas for improving road safety, helping to focus the efforts of road safety managers on those areas where their efforts are most effective.
Highlights
Accident analysis is a fundamental part of road safety management
This paper shows how a joint Geographic Information System (GIS) and time series analysis can be used to analyze the accident situation in a city
This paper contributes to this approach by presenting a case study that uses a standard statistical model and standardized data, in order to have an overview on spatially distributed accident rate development, and enables road safety officers with less in-depth statistical knowledge to get an overview on the accident development in their areas of responsibility and enables them to act in a focused way
Summary
Accident analysis is a fundamental part of road safety management. The likelihood of occurrence of road accidents and their severity are influenced by various factors, whose effects are sometimes difficult to determine due to interactions between them. This paper shows how a joint GIS and time series analysis can be used to analyze the accident situation in a city. The second step is to conduct a trend analysis to determine the accident situation and its significance The results of these two steps are used to detect geographically distributed irregularities in the accident situation and irregularities within the subgroups (e.g., bike accidents, senior citizen accidents, etc.) and can be used by road safety managers, to help them focus their accident prevention interventions on those areas where their efforts are most effective. This paper contributes to this approach by presenting a case study that uses a standard statistical model and standardized data, in order to have an overview on spatially distributed accident rate development, and enables road safety officers with less in-depth statistical knowledge to get an overview on the accident development in their areas of responsibility and enables them to act in a focused way.
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