The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Development of a multivariate logistic model to predict bicycle route safety in urban areas
Author:	Allen-Munley, Cheryl
View Online:	njit-etd2003-067 (xviii, 206 pages ~ 17.2 MB pdf)
Department:	Executive Committee for the Interdisciplinary Program in Transportation
Degree:	Doctor of Philosophy
Program:	Transportation
Document Type:	Dissertation
Advisory Committee:	Daniel, Janice Rhoda (Committee chair) Liu, RongFang (Committee member) Bladikas, Athanassios K. (Committee member) Mouskos, Kyriacos (Committee member) Nissen, Gerald J. (Committee member)
Date:	2003-05
Keywords:	bicycle route bicycle model logistical model bicycle safety accident prediction transportation modeling
Availability:	Unrestricted
Abstract:	In response to the renewed appreciation of the benefits of bicycling to the environment and public health, public officials across the nation are working to establish new bicycle routes. During the past two decades, a number of methods have been endorsed for the selection of "suitable" bicycle routes. These methods are limited in that they do not explicitly address bicycle safety nor do they reflect urban conditions. The purpose of this research is to develop an objective bicycle route safety rating model based on injury severity. The model development was conducted using a logistic transformation of Jersey City's bicycle crash data for the period 1997-2000. The resulting model meets a 90% confidence level by using various operational and physical factors (traffic volume, lane width, population density, highway classification, the presence of vertical. grades, one-way streets and truck routes) to predict the severity of an injury that would result from a crash that occurred at a specific location. The rating of the bicycle route's safety is defined as the expected value of the predicted injury severity. This rating is founded on the premise that safe routes produce less severe accidents than unsafe routes. The contribution of this research goes beyond the model's predictive capacity in comparing the safety of alternative routes. The model provides planners with an understanding, derived from objective data, of the factors that add to the route's safety, the factors that reduce safety and the factors that are irrelevant. The model often confirms widely held beliefs as evidenced by the finding that highways with steep grades, truck routes and poor pavement quality create an unfavorable environment for bicyclists. Conversely, the model has found that increased volume and reduced lane width, at least in urban areas, actually reduce the likelihood of severe injury. Planners are encouraged to follow the lead of experienced bicyclists in choosing routes that travel through the urban centers as opposed to diverting bicyclists to circuitous routes on wide, low volume roads at the periphery of cities.