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Development of A Freeway Accident Prone Area Image
Evaluation Criteria and Model
Kuo-Ping Hwang, Associate Professor Zon-Jeh Chung, Research Assistant
Department of Transportation and Communication Management Science
National Cheng-Kung University
ABSTRACT
In the subject of safety analysis, historical accident data are normally used as the dependent variable to correlate with highway geometric elements, vehicle characteristics, driver features, time, etc. The lack of reliable or sufficient data often makes accident cause analysis impossible. For traffic or highway engineers, accident analysis is often used to identify accident prone areas in order to design countermeasures to reduce accident casualties or to plea for proper funds to improve safety efficiency.
The purpose of this study is to establish both an evaluation criteria and a model to identify freeway accident prone areas. To achieve such a goal, the analytical hierarchical process (AHP) is used to obtain the evaluation criteria of accident causing factors.
The priority vectors for those factors are then used to compute an image hazardous index for each section of freeway. The image hazardous index together with other system variables such as toll plaza, interchange, etc. are then put into the evaluation model to arrive at an overall sectional accident prone index. Thereafter, accident prone areas are identified through use of the accident prone index. The development of such a procedure and evaluation model is designed to supplement the current deficiency of statistical models whenever historical accident data are unavailable.
To identify the occurrence frequency for each accident causing factor, a videologging system is developed and is used both to
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record and re-display the continuous freeway image. Those accident causing factors such as grade, length of grade, bridge abatement, gore, glare, etc. are then identified and scrutinized for further analysis.
In order to calibrate and field test the developed system, the southern section of Taiwan's Sun Yat-Sen freeway is selected for analysis. The section has a length of 131.94 kilometers and has an accident history of 91 A-1 records per year.
Keywords : accident prone area, image evaluation, analytical hierachical process, videologging
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