title: Evaluating the road safety effects of a fuel cost increase measure by means of zonal crash prediction modeling.
abstract: Travel demand management (TDM) consists of a variety of policy measures that affect the transportation system's effectiveness by changing travel behavior. The primary objective to implement such TDM strategies is not to improve traffic safety, although their impact on traffic safety should not be neglected. The main purpose of this study is to evaluate the traffic safety impact of conducting a fuel-cost increase scenario (i.e. increasing the fuel price by 20%) in Flanders, Belgium. Since TDM strategies are usually conducted at an aggregate level, crash prediction models (CPMs) should also be developed at a geographically aggregated level. Therefore zonal crash prediction models (ZCPMs) are considered to present the association between observed crashes in each zone and a set of predictor variables. To this end, an activity-based transportation model framework is applied to produce exposure metrics which will be used in prediction models. This allows us to conduct a more detailed and reliable assessment while TDM strategies are inherently modeled in the activity-based models unlike traditional models in which the impact of TDM strategies are assumed. The crash data used in this study consist of fatal and injury crashes observed between 2004 and 2007. The network and socio-demographic variables are also collected from other sources. In this study, different ZCPMs are developed to predict the number of injury crashes (NOCs) (disaggregated by different severity levels and crash types) for both the null and the fuel-cost increase scenario. The results show a considerable traffic safety benefit of conducting the fuel-cost increase scenario apart from its impact on the reduction of the total vehicle kilometers traveled (VKT). A 20% increase in fuel price is predicted to reduce the annual VKT by 5.02 billion (11.57% of the total annual VKT in Flanders), which causes the total NOCs to decline by 2.83%.
authors.affiliation: Transportation Research Institute (IMOB), Hasselt University, Wetenschapspark 5 bus 6, B-3590 Diepenbeek, Belgium. ali.pirdavani@uhasselt.be
authors.forename: Ali
authors.initials: A
authors.lastname: Pirdavani
authors.forename: Tom
authors.initials: T
authors.lastname: Brijs
authors.forename: Tom
authors.initials: T
authors.lastname: Bellemans
authors.forename: Bruno
authors.initials: B
authors.lastname: Kochan
authors.forename: Geert
authors.initials: G
authors.lastname: Wets
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001334:Automobile Driving / Q000706:statistics & numerical data*; D005742:Gasoline / Q000191:economics*; D006801:Humans; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012449:Safety; D014195:Travel
chemical_list: D005742:Gasoline