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An Analysis of Expressways Accidents in Singapore
Diagnosis
Based on the available attributes of the accident data it has been observed that the distribution of accidents varies depending on the time of a day, the type of road surface at the time of accident, the type and number of vehicles involved in the collision and so on. The following section describes how GIS software may be used to highlight specific accident types.  Fig 3: Accident-Prone Areas: Spatial distribution of accidents by road surface Accident based on type of road surface Pavement surface characteristic is one of the important factors, which determines the safety of a vehicle when negotiating a curve or at the time of sudden application of brakes. Present study reveals that major percentage of accidents occurred at both accident-prone and rest of areas when the road surface condition was dry. But comparing the percentage of accidents which occurred when the surface was wet it has been found that the accident-prone areas contribute more, leaving us the clue for viewing such accident location distributions to look for the factors and take countermeasures. Accident based on vehicle involvement The accidents are also grouped based on the vehicle involvement and it has been observed that around 58% of the expressway accidents were multiple vehicle accidents and the rest were single vehicle accidents. Further the collision of a vehicle with stationary objects has been more in accident-prone areas. On the other hand even though most of the multiple vehicle accidents are caused as a result of head to rear type of collision, the percentage of sideswipe collision is found to be more in accident-prone areas, which needs to be focused. Hence analysis of specific types of accidents may reveal important geometric and traffic control and regulatory factors which are responsible for their causation. Further while investigating the distribution of accidents over different times of the day, it is found to be almost uniform over the evening peak and night time but slightly higher during the morning peaks. Fatality percentage is clearly higher during night. When considering the speed limit there is a clear demarcation between the accident percentage contribution and the other lower speed limit zones. These types can also be visually studied for their distribution patterns. Framing various combinations of above accident types can still improve the analysis. They help to localize accidents and thus arrive at some more useful conclusions. Further the determination of accident-prone areas can well be approached using only accidents that result in personal injury or death, as the cause of such severe accidents cannot be reasonably attributed to randomness. Hence by proceeding in this way and having the information about the spatial distribution of accidents it is possible to model the accidents with different geometric, traffic control/ regulatory factors and environmental factors that might be responsible for a particular type of accident. |