Traffic Safety Methodologies

Author(s):

Gary Davis

September 2007

Report no. CTS 07-11

Topics:

Planning, Safety

The main objective of this research was to review how, and to what extent, safety issues are treated in context-sensitive design activities. The ideal to which we refer is that safety issues should be an explicit and quantitative component of design decision-making. This means that ideally, numerical predictions of the safety effects of different design alternatives should be part of how those alternatives are evaluated. Because a review of safety in all its aspects is beyond the scope of this project, we focused on pedestrian safety and its relation to traffic-calming design elements. Safety is cited as a dominant concern in roadway design but, as Hauer (1988) has pointed out, a federal commission charged with evaluating the safety impacts of proposed highway rehabilitation initiatives found the existing knowledge base inadequate to the task. This concern and the knowledge gap have led to a major effort on the part of the Federal Highway Administration, the Association of American State Highway and Transportation Officials, and the Transportation Research Board to produce the first edition of a Highway Safety Manual (HSM). This document, similar in spirit to the Highway Capacity Manual, is aimed at providing transportation engineers with tools for explicitly predicted the changes in crash frequency expected from different roadway design components. Although quantitative safety prediction can be done for certain design elements, such as installation of a traffic signal at an intersection or removal of roadside obstacles, science-based prediction for the type and scope of design activities characterizing context-sensitive designs is much more difficult. This is especially true for predictions related to pedestrian safety, and produces a gap between the design ideal described above and design as it is practiced. It is recommended that measurement of safety effects be included as part of context-sensitive design projects, to expand the knowledge base on which a future prediction capability can be built.

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