A comparative empirical analysis of statistical models for evaluating highway segment crash frequenc

来源 :Journal of Traffic and Transportation Engineering(English Ed | 被引量 : 0次 | 上传用户:kjc
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The present study conducted an empirical highway segment crash frequency analysis on the basis of fixed-parameters negative binomial and random-parameters negative binomial models.Using a 4-year data from a total of 158 highway segments,with a total of11,168 crashes,the results from both models were presented,discussed,and compared.About 58%of the selected variables produced normally distributed parameters across highway segments,while the remaining produced fixed parameters.The presence of a noise barrier along a highway segment would increase mean annual crash frequency by0.492 for 88.21%of the highway segments,and would decrease crash frequency for 11.79%of the remaining highway segments.Besides,the number of vertical curves per mile along a segment would increase mean annual crash frequency by 0.006 for 84.13%of the highway segments,and would decrease crash frequency for 15.87%of the remaining highway segments.Thus,constraining the parameters to be fixed across all highway segments would lead to an inaccurate conclusion.Although,the estimated parameters from both models showed consistency in direction,the magnitudes were significantly different.Out of the two models,the random-parameters negative binomial model was found to be statistically superior in evaluating highway segment crashes compared with the fixedparameters negative binomial model.On average,the marginal effects from the fixedparameters negative binomial model were observed to be significantly overestimated compared with those from the random-parameters negative binomial model. The present study conducted an empirical highway segment crash frequency analysis on the basis of fixed-parameters negative binomial and random-parameters negative binomial models. Using a 4-year data from a total of 158 highway segments, with a total of 11,168 crashes, the results from both models were presented, discussed, and compared. About 58% of the selected variables produced normally distributed parameters across highway segments, while the remaining produced fixed parameters. The presence of a noise barrier along a highway segment would increase mean annual crash frequency by0.492 for 88.21% of the highway segments, and would decrease crash frequency for 11.79% of the remaining highway segments.Besides, the number of vertical curves per mile along a segment would increase mean annual crash frequency by 0.006 for 84.13% of the highway segments, and would decrease crash frequency for 15.87% of the remaining highway segments.Thus, constraining the parameters to be fixed across all highway segments would lead to an inaccurate conclusion. Although the estimated parameters from both models showed consistency in direction, the magnitudes were significantly different. Out of the two models, the random-parameters negative binomial model was found to be significantly superior in granted highway segment crashes compared with the fixedparameters negative binomial model. On average, the marginal effects from the fixedparameters negative binomial model were observed to be significantly overestimated compared with those from the random-parameters negative binomial model.
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