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Examining Potential Safety Risks Associated with the Introduction of Light Rail Transit

This study will entail a two-tiered analysis. The first analysis will entail a systematic examination of national trends in light rail safety performance. The second tier will investigate the design-level factors that may be responsible for the crash risk associated with light rail transit.

This study will provide a detailed analysis of the safety impacts of two recently-developed light rail systems in the U.S.: Orlando SunRail and Charlotte Lynx. Most observational before-after studies in road safety research consist of an examination of a single location or, at most, a handful of locations. For this study, we have complete land use, development, safety, and transportation data for two light rail systems, comprising 50 miles of service, 27 individual stations, and hundreds of intersections where surface streets cross light rail tracks.

This study will examine the frequency and severity of each of these crash types before and after the introduction of light rail service. At a minimum, this study will produce the following:

  • A national assessment of the risk factors associated with light rail transit service.
  • The identification of the modal characteristics of injuries and deaths associated with light rail transit.
  • An understanding of the temporal and climactic factors associated with crashes involving light rail vehicles.
  • An examination of how modifications of the built environment as a result of light rail service may influence traffic-related deaths and injuries along corridors and near transit stops.
  • An understanding of the design-level factors that may increase, or decrease, the incidence of deaths and injuries associated with the provision of light rail service.

Developing a Taxonomy of Human Errors and Violations that Lead to Crashes

Human errors and violations are highly relevant to the safe systems approach as human error tends to dominate crash occurrence, contributing to 80%-90% of crashes. A better understanding of “critical reasons for the critical pre-crash events” has significant potential in reducing deadly behaviors on roadways. A key gap in the literature relates to the origin of the different types of human errors, e.g., whether they begin with intentional actions or unintentional actions, and how they relate to the built environment.

The project will:

  • Review relevant work that will be integrated into a taxonomy and identify gaps in literature
  • Process and prepare the SHRP naturalistic driving study (NDS) database and develop framework
  • Develop a methodology to classify crash-contributing errors
  • Develop a “safety matrix” that quantifies the contributions of different factors for different scenario
  • Apply a modeling approach for analyzing relationships
  • Use the safety matrix to explore implications for road safety in the future
  • Final report and dissemination

Relevant Papers:

  • Khattak, A. J., Wali, B., & Ahmad, N. (2019). A Taxonomy of Naturalistic Driving Errors and Violations and Its Variations Across Different Land-Use Contexts – A Path Analysis Approach. In Transportation Research Board 98th Annual Meeting, Washington DC, United States, 2019 (No. 19-05054).

Investigating the Vulnerability of Motorcyclists to Crashes and Injury

Motorcyclists represent a segment of vulnerable road users that have very high levels of risk mostly because of their lack of protection when involved in a crash. Motorcyclist fatalities in the U.S. increased by 257 from 2015 to 2016, a 5.1% increase. This study will focus on analyzing a unique database of motorcycle crashes, exploring how key risk factors vary by demographics and from one context to another, i.e., the settings in which motorcycle travel takes place.

The project will be organized into the following tasks:

  • Review current literature
  • Access and prepare the motorcycle crash causation study data and propose analysis framework
  • Evaluate risks associated with motorcyclists’ conspicuity-apparel type, apparel conspicuity and helmets
  • Investigate how rider inexperience and age are related to crash outcomes, especially injury crashes
  • Explore how automation may eliminate errors
  • Consolidate the findings, write a final report, and disseminate the results to stakeholders

Relevant Papers:

  • Wali, B., Khattak, A. J., &  Khattak, A. J. (2018) A Heterogenity Based Cased- Control Analysis of Motorcyclist’s Injury Crashes: Evidence from Motorcycle Crash Causation Study. In Accident Analysis & Prevention. 119: 202-214
  • Wali, B., Khattak, A. J., & Ahmad, N. (2019). Modeling Injury Severity Score as a More Precise Measure of Motorcyclist Injuries: A Correlated Random Parameter Corner Solution Framework. In Transportation Research Board 98th Annual Meeting, Washington DC, United States, 2019  (Lectern Session: No. 19-05185).
  • Wali, B., Khattak, A. J., Khattak, A. J., & Ahmad, N. (2019). A Heterogeneity Based Case-Control Analysis of Motorcyclist’s Injury Crashes: Evidence from Motorcycle Crash Causation Study. In Transportation Research Board 98th Annual Meeting, Washington DC, United States, 2019 (Lectern Session: No. 19-05159).

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