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Investigating different road safety implications of two TDM policy measures : fuel-cost increase and teleworking Pirdavani, Ali ; Brijs, Tom ; Bellemans, Tom ; Wets, Geert

By: Contributor(s): Publication details: Linköping VTI, 2013Description: 21 s, CDISBN:
  • 9789163729737
Subject(s): Online resources: In: Proceedings of the 16th International Conference Road Safety on Four Continents: Beijing, China. 15-17 May 2013Bibl.nr: VTI 2013.0031Location: VTI, Ex 1: RefNotes: Konferens: Road safety on four continents: 16th international conference, 2013, Beijing, China Abstract: Travel demand management (TDM) consists of a variety of policy measures that affect the transportation system’s effectiveness by changing travel behavior. Although the primary objective to implement such TDM strategies is not to improve traffic safety, their impact on traffic safety should not be neglected. The main purpose of this study is to investigate differences in the traffic safety consequences of two TDM scenarios; a fuel-cost increase scenario (i.e. increasing the fuel price by 20%) and a teleworking scenario (i.e. 5% of the working population engages in teleworking). Since TDM strategies are usually conducted at a geographically aggregated level, crash prediction models (CPMs) that are used to evaluate such strategies should also be developed at an aggregate level. Moreover, given that crash occurrences are often spatially heterogeneous and are affected by many spatial variables, the existence of spatial correlation in the data is also examined. The results indicate the necessity of accounting for the spatial correlation when developing crash prediction models. Therefore, zonal crash prediction models (ZCPMs) within the geographically weighted generalized linear modeling (GWGLM) framework are developed to incorporate the spatial variations in association between the number of crashes (NOCs) (including fatal, severe and slight injury crashes recorded between 2004 and 2007) and a set of explanatory variables. Different exposure, network and socio-demographic variables of 2200 traffic analysis zones (TAZs) in Flanders, Belgium, are considered as predictors of crashes. An activity-based transportation model is adopted to produce exposure metrics. This enables to conduct a more detailed and reliable assessment while TDM strategies are inherently modeled in the activity-based models. In this study, several ZCPMs with different severity levels and crash types are developed to predict the NOCs. The results show considerable traffic safety benefits of conducting both TDM scenarios at an average level. However, there are certain differences when considering changes in NOCs by different crash types.
Item type: CD
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Konferens: Road safety on four continents: 16th international conference, 2013, Beijing, China

Travel demand management (TDM) consists of a variety of policy measures that affect the transportation system’s effectiveness by changing travel behavior. Although the primary objective to implement such TDM strategies is not to improve traffic safety, their impact on traffic safety should not be neglected. The main purpose of this study is to investigate differences in the traffic safety consequences of two TDM scenarios; a fuel-cost increase scenario (i.e. increasing the fuel price by 20%) and a teleworking scenario (i.e. 5% of the working population engages in teleworking). Since TDM strategies are usually conducted at a geographically aggregated level, crash prediction models (CPMs) that are used to evaluate such strategies should also be developed at an aggregate level. Moreover, given that crash occurrences are often spatially heterogeneous and are affected by many spatial variables, the existence of spatial correlation in the data is also examined. The results indicate the necessity of accounting for the spatial correlation when developing crash prediction models. Therefore, zonal crash prediction models (ZCPMs) within the geographically weighted generalized linear modeling (GWGLM) framework are developed to incorporate the spatial variations in association between the number of crashes (NOCs) (including fatal, severe and slight injury crashes recorded between 2004 and 2007) and a set of explanatory variables. Different exposure, network and socio-demographic variables of 2200 traffic analysis zones (TAZs) in Flanders, Belgium, are considered as predictors of crashes. An activity-based transportation model is adopted to produce exposure metrics. This enables to conduct a more detailed and reliable assessment while TDM strategies are inherently modeled in the activity-based models. In this study, several ZCPMs with different severity levels and crash types are developed to predict the NOCs. The results show considerable traffic safety benefits of conducting both TDM scenarios at an average level. However, there are certain differences when considering changes in NOCs by different crash types.