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原文传递 PREDICTION OF RISK OF WET-PAVEMENT ACCIDENTS: FUZZY LOGIC MODEL.

题名：	PREDICTION OF RISK OF WET-PAVEMENT ACCIDENTS: FUZZY LOGIC MODEL.
作者：	Xiao-J; Kulakowski-BT; El-Gindy-M
关键词：	Accident-data; Average-daily-traffic; Fuzzy-logic; Mathematical-models; Mathematical-prediction; Pennsylvania-; Risk-analysis; Skid-number; Skidding-; Speed-limits; Traffic-accidents; Traffic-data; Wet-pavements; Wet-weather
摘要：	Researchers developed a fuzzy-logic model for predicting the risk of accidents that occur on wet pavements. Preventing wet-pavement accidents has been an extremely difficult and elusive task because they are stochastic events whose occurrence is related to a variety of factors, including vehicle, roadway, human, and environmental characteristics. Conventionally, researchers use linear or nonlinear regression models and probabilistic models to predict wet-pavement accidents. However, these models often are limited in their capability to fully explain the process when the underlying physical system possesses a degree of nonlinearity. Therefore, the potential of applying fuzzy logic in this area might be promising. Two fuzzy-logic models were developed and evaluated using accident data and the corresponding traffic data collected from 123 sections of highway in Pennsylvania from 1984 to 1986. The models use skid number, posted speed, average daily traffic, percentage of wet time, and driving difficulty as input variables and the number of wet-pavement accidents as the output variable. The first model is based on Mamdani's fuzzy-inference method, and the second is a Sugeno-type fuzzy-logic model using the fuzzy-clustering method. The two fuzzy-logic models show superiority over the probabilistic model and the nonlinear regression model. Results indicate that, in addition to predicting the risk of wet-pavement accidents, the fuzzy-logic model can be applied conveniently to determine specific corrective actions that should be undertaken to improve safety.
总页数：	Transportation Research Record. 2000. (1717) pp28-36 (12 Fig., 9 Ref.)
报告类型：	科技报告