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Publication Number: FHWARD98133
Date: October 1998 

Accident Models for TwoLane Rural Roads: Segment and Intersections5. ModelingSummary A variety of modeling techniques  Poisson, negative binomial, extended negative binomial, and logistic  have been applied in this chapter, along with measures of overdispersion, goodnessoffit, and concordance. In general the Poisson models, negative binomial, and extended negative binomial models give mutually consistent values for regression coefficients. The T_{1} statistic indicates that overdispersion is present and thus that negative binomial models are to be preferred. The logistic models are not particularly satisfactory, perhaps because of the relative infrequency of serious accidents and the relatively greater importance of missing variables. The segment models  our final model is in Table 27  support the assertion that most of the variables in the study are significant. Some variables that correlate with accidents (e.g., commercial traffic percentage T) are omitted because they are not as significant as competing variables. However, the chief variables  exposure, lane and shoulder width, Roadside Hazard Rating and driveway density, and the alignment variables  are all represented. Differences between States appear to be genuine and are captured by the variable STATE. When we pass to the negative binomial and the extended negative binomial, the coefficient estimates are reapportioned somewhat as overdispersion and localized vertical and horizontal measures make their contribution to the variation in accident counts. With regard to intersections, the final models are presented in Table 35. Minnesota data are taken as fundamental because the Washington intersection data are nonrandom and less reliable. Furthermore, the criteria for significance are relaxed so that "best guess" coefficients for alignment design variables can be presented. The effects of number of driveways, Roadside Hazard Rating, the angle variables, and channelization show notable variation between the threelegged intersections and the fourlegged. Number of driveways has unexpected sign (negative) on threeleggeds in both States. Roadside Hazard Rating has unexpected sign (negative) on fourleggeds in both States. The acute/obtuse angle variable HAU behaves as expected on fourleggeds but not on threeleggeds, but another angle variable, deviation DEV from 90°, is more significant on fourleggeds. The presence of major road turning lanes increases accidents on threeleggeds but decreases them on fourleggeds. In the final models of Table 35 number of driveways (wrong sign) is omitted from the threelegged intersections, while Roadside Hazard Rating (wrong sign) and right turn lanes (insignificant) are omitted from the fourlegged intersections. Some noteworthy differences also appear between the Minnesota and Washington models, for example, the insignificance of Roadside Hazard Rating in Minnesota segments (due perhaps in part to less variation), the anomalous sign of lane width in Washington segments (perhaps related to design differences), differences in the commercial traffic percentage variable T between the two States, and insignificance of most variables on the Washington threelegged intersections. The combined segment model (Table 27) and the Minnesota intersection models (Table 35) exhibit the effects of the chief variables, while minimizing anomalies found in some variables and in Washington intersection data.

Topics: research, safety, rural roads, interchanges, intersections, twolane highway Keywords: research, safety, rural roads, interchanges, intersections, twolane highway, Minnesota, traffic accidents, crash data, mathematical models TRT Terms: Traffic accidentsMinnesota, Rural roadsMinnesota, RoadsMinnesotaInterchanges and intersections, Traffic accidentsWashington (State), Rural roadsWashington (State), RoadsWashington (State)Interchange and intersections, Two lane highways, Mathematical models, Accident data Updated: 04/12/2012
