Evaluating the road safety effects of a fuel cost increase measure by means of zonal crash prediction modeling

Pirdavani, Ali; Brijs, Tom; Bellemans, Tom; Kochan, Bruno; Wets, Geert · 2013 · Crossref

DOI: 10.1016/j.aap.2012.04.008

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study evaluates the traffic safety impacts of Travel Demand Management (TDM) strategies, specifically a 20% increase in fuel costs, in Flanders, Belgium. While TDM measures primarily aim to improve transportation efficiency, their secondary effects on road safety are often overlooked. The research addresses the need for a proactive, planning-level approach to safety assessment, moving beyond reactive "hot spot" identification. To achieve this, the authors integrate Zonal Crash Prediction Models (ZCPMs) with an activity-based transportation model, allowing for the simulation of behavioral changes in travel demand resulting from policy interventions. The methodology utilizes the FEATHERS activity-based framework to simulate travel behavior for over six million agents in Flanders. This framework generates exposure metrics, such as Vehicle Kilometers Traveled (VKT) and Number of Trips (NOTs), for both a null scenario and a fuel-cost increase scenario. Crash data comprising fatal and injury incidents from 2004 to 2007 were aggregated across 2,200 Traffic Analysis Zones (TAZs). The researchers developed four distinct Negative Binomial ZCPMs within a Generalized Linear Modeling framework to predict crash frequencies. These models were disaggregated by crash severity (fatal/severe vs. slight injury) and crash type (Car-Car vs. Car-Slowmode, where slowmode includes pedestrians and cyclists). Predictor variables included exposure metrics, network characteristics (e.g., road capacity, intersection density), and socio-demographic factors (e.g., income level, urban/suburban status). The results indicate that combining flow-based (VKT) and trip-based (NOTs) exposure variables yields the best model fit. The simulation of a 20% fuel cost increase predicts a substantial reduction in total annual VKT, decreasing by 5.02 billion kilometers, which represents 11.57% of the total annual VKT in Flanders. Consequently, the total Number of Injury Crashes (NOCs) is predicted to decline by 2.83%. The study demonstrates that despite the global nature of the fuel price increase, the impact varies by zone due to differences in local characteristics such as income levels and public transportation availability. The significance of this work lies in its demonstration of how activity-based models can be effectively coupled with ZCPMs to assess the safety implications of TDM strategies. By modeling the behavioral responses to fuel cost changes—such as mode shifts and reduced travel demand—the study provides a more reliable assessment than traditional methods that assume fixed impacts. The findings confirm that fuel cost increases yield considerable traffic safety benefits alongside reductions in travel demand, offering planners a quantitative tool to evaluate the external safety effects of transportation policies during the planning phase.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• incidence prevalence
• urban rural setting
• regulatory evaluation
• induced exposure

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Applied Guidance: countermeasure evaluation
• Empirical Findings: crash risk outcomes