Relationship between traffic operations and road safety

• Autor(a) principal: Andrade, Gustavo Riente de
• Data de Publicação: 2018
• Tipo de documento: Tese
• Idioma: eng
• Título da fonte: Biblioteca Digital de Teses e Dissertações da USP
• Texto Completo: http://www.teses.usp.br/teses/disponiveis/18/18144/tde-23012019-011508/
• topic: Acidentes; Crash severity; Crashes; Expressways; Modelagem; Modeling; Operação; Operations; Rodovias de pista dupla; Severidade; Urban arterials; Vias arteriais

Since before the release of the Highway Safety Manual research has been indicating the need to incorporate mobility and control aspects to road safety analysis. The first part of this work developed and implement in an existing computational engine a signal timing optimization method that considers mobility, safety, and emissions measures simultaneously. A sensitivity analysis was conducted to provide insight on the practical effects and order of relevance of 20 key input variables. Mobility improvement performance usually coincides with emissions improvements, but sometimes at the expense of safety. The second part of this work investigated the relationship between hourly traffic density and crash rates on Brazilian expressways with different characteristics, based on a database containing over 20,000 crashes and more than 35 million traffic volume observations and. The resulting curves for urban expressways follow a U shape, with minimum values associated with LOS B to C, while the relationships for rural expressways were found to be continuously increasing, suggesting that low volume rural roads are safer than the higher volume ones. The analysis of other influencing factors revealed that nighttime conditions, weaving segments and urban multilane highways could be related to higher crash rates. The third part of the project extends the analysis to crash severity modeling, using an ordered response choice model. The framework that better fit this database led to the development of two different models: single-vehicle crashes (SV) and multiple-vehicle crashes (MV), since the factors that explain the severity of crashes varies widely between these models. For instance, guardrails and barriers proved to effectively reduce severity for SV crashes, for which run-offs are the most severe crash type. The unique database used in this study also allowed for an investigation of the influence of prevailing traffic conditions on crash severity, while still controlling for all other factors. The results suggested that multiple-vehicle crash severity is negatively related with traffic density, while single-vehicle crashes are more closely related to speed. The findings of this work have implications to policy and design decisions, and the produced equation could be incorporated to active traffic management (ATM) and HCM reliability analysis.