Urban Sprawl |
Fringe Area Development |
Urban Agglomeration |
Emerging Technologies |
An Analysis of Expressways Accidents in Singapore
Kamalasudhan A, Mitra S, Bo Huang and Chin H C
Department of Civil Engineering,
National University of Singapore, Singapore
Accident data, collected for many years, serve as the ground base for programs designed to reduce the number of traffic accidents. These accident databases are usually in the form of linear record file system, which enable an extensive amount of research to be undertaken using statistical methods. But both the databases as well as the analyzed information lacked visibility, which is essential for better understanding and good decision-making (1). Further many of the required analyses have a strong locational element, and as such they may suggest some form of geographic computer based data management system. GIS has been identified as an excellent system for storing and managing these types of data and also as a potential tool for improving accident analysis process. One of the reasons is that it provides an efficient system of linking a large number of disparate databases and also provides a spatial referencing system for reporting output at different levels of aggregation. Even though traffic safety seems to have many easy and logical connections to GIS, and its applications have even been proposed earlier (2), the development of a useful GIS database proved to be more difficult than anticipated. Works are limited to just visual interpretations of displayed aggregate accident data (3).
Traffic safety programs can provide benefits only when effective countermeasures are applied to the locations and areas that really need safety treatment. Hence the practice in analyzing accident data has always been preceded with identification of high accident locations followed by identification of factors and selection of countermeasures. Several techniques for identification of accident locations have been established (4), but GIS has only been applied to display such locations (5) and to analyze problematic cases (7).
The fundamental objective is to determine the factors that contribute to accidents at those spots and to take actions that will reduce crash frequency or severity. Determining such factors like roadway features and road user characteristics is usually done through a macroscopic study involving a large accident database (6). However making inferences from a single site, solely based on historical data does not always yield consistent results, because accidents do not usually occur at the same specific location. They may be distributed over an area although they may be caused by factors in a specific location. Hence it is more appropriate to identify accident-prone areas, with a subset of locations having high number of accidents instead of accident spots. Identification of accident-prone areas is best done on a GIS platform, which can facilitate further investigation of accident causation.
The goal of this study is to identify accident-prone areas using GIS tools. Specifically this involves plotting individual accident locations, identifying accident-prone areas using GISís spatial analysis tools, and presenting a diagnosis of accident characteristics by different types at these high accident locations.
The accident data used in the study are taken from the National Road Accident Database, while the expressway data have been collected using GPS. A brief description of the expressway and accident data is provided below.