01030703

Component

https://doi.org/10.3141/1950-09

http://scholar.google.com...ayed&publication_year=2006

This paper describes the use of several recently developed macrolevel collision prediction models (CPMs) in two road safety planning applications. Data from several urban neighborhoods in the Greater Vancouver Regional District (GVRD) in the province of British Columbia, Canada, were used to present and test model-use guidelines in two road safety planning applications. In the first case study, an areawide traffic calming collision modification factor was estimated for GVRD urban areas, for “total” and “severe” collisions, to be in the range of –0.40 and –0.39, respectively. In the second case study, four neighborhood network structures were evaluated, and two test networks that appeared safer than conventional grid and cul-de-sac neighborhood street patterns were revealed, mostly because of the increased use of three-way intersections. Moreover, cul-de-sac networks appeared to be much safer than grid networks, by nearly three to one. The results suggested that the models and model-use guidelines could complement and enhance traditional road safety improvement programs and could provide new and improved empirical tools for planners and engineers to do road safety planning. It is hoped that development of guidelines for macrolevel CPM use will facilitate improved decisions by community planners and engineers and, ultimately, neighborhood traffic safety for residents and other road users.

01030706

English

pp 73-82

2006

Transportation Research Record: Journal of the Transportation Research Board

0309099595

Print

Figures (1) ; References (15) ; Tables (9)

Case studies; Crash modification factors; Crash risk forecasting; Cul de sacs; Highway safety; Neighborhoods; Planning; Three leg intersections; Traffic calming

Greater Vancouver Regional District

Macro-level

British Columbia

Highways; Planning and Forecasting; Safety and Human Factors; I81: Accident Statistics

TRIS, TRB, ATRI

Mar 3 2006 10:23AM

• Application of "Highway Safety Manual" Draft Chapter: Louisiana Experience
• Bayesian Multivariate Poisson Regression for Models of Injury Count, by Severity
• Calibration of Safety Prediction Models for Planning Transportation Networks
• Comparison of Two Negative Binomial Regression Techniques in Developing Accident Prediction Models
• Describing the Evolution in the Number of Highway Deaths by Decomposition in Exposure, Accident Risk, and Fatality Risk
• Effects of Sample Size on Goodness-of-Fit Statistic and Confidence Intervals of Crash Prediction Models Subjected to Low Sample Mean Values
• Refinement of Accident Prediction Models for Spanish National Network
• Use of Propensity Score Matching Method and Hybrid Bayesian Method to Estimate Crash Modification Factors of Signal Installation
• Using the Rural Two-Lane Highway Draft Prototype Chapter