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Micro and macro level safety analysis at railroad grade crossings.
  • Published Date:
    2016-03-01
  • Language:
    English
Filetype[PDF-3.40 MB]


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  • Abstract:
    Railroad grade crossings are potential conflict points between train and highway vehicles, and train and pedestrians. Grade crossings pose a risk to all the travelers and the degree of risk depends on factors such as train and vehicle volumes, presence and operation of traffic control devices (TCD), speed of trains and vehicles, geometry of the crossing, interaction with interconnected intersection, pedestrians, number of tracks, etc. The risk assessment at grade crossings is important to prioritize locations for safety improvements and for assigning economic resources to locations that could provide the greatest returns in investments.

    To assess the safety and risk of grade crossings, one may utilize macroscopic models derived from regression analysis using data from an entire state or country. Macroscopic analysis is mainly used to study the correlation between crossing characteristics (i.e. conflicting volumes and their physical characteristics) and the past accident frequency, to generate predictions about accidents in the future. A common macroscopic model currently used is the US DOT Accident Prediction Formula, which predicts the annual number of crashes at a given crossing. While this model provides useful information for ranking grade crossings for resource allocation, it was developed in the late 1970s and thus it has potential for improvement.

    The analysis of macroscopic models is one of the two main topics from this study, where a series of alternative models are explored and compared to the US DOT formula. Through these comparisons, it is possible to understand strengths and weaknesses of the current state-of-practice and also to identify models for future improvements. A multi-scale analysis using macro models with input from a micro analysis is also planned for the future.

    In addition to macroscopic analysis, the second main topic discussed here is the analysis of accidents from a microscopic perspective, where individual characteristics of accidents at a given location are investigated to determine potential contributing factors. A microscopic analysis procedure is described in this study takes into account detailed information such as driver characteristics, surrounding development type, lighting conditions, weather and visibility, direction of travel, speed and location of vehicle and train, etc. The proposed microscopic analysis is used to discover local trends that could not be identified at a macro scale and may help in assessing the risk at a crossing. Examples for the use of the micro analysis are provided to show the benefits of such a combined methodology and its potential use as a tool for on-site inspection.

    The next sections describe the macroscopic approach using the US DOT formula, the exploration of alternative models, and their performance for assessing the risk using data from Illinois as an example. Then, the micro analysis is described and exemplified as a tool for risk analysis and trend discovery. Finally, conclusions are presented along with proposed directions for future research and improved risk assessments.

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