Rail–highway grade crossing crashes may be caused by long vehicles with low clearances becoming stranded when attempting to negotiate rail–highway crossings with steeply graded profiles—hump crossings. Although design standards have been established to encourage the construction that most vehicles are able to successfully navigate, the combination of grade profile and cross-section interacting with unique vehicle dimensions may lead to instances where vehicles may have difficulty crossing. This article describes a three-dimensional (3D)-based (LiDAR) methodology to identify and evaluate the severity of hump crossings. A five-level criterion is proposed to rate the magnitude of contact. The methodology is demonstrated by modeling seven common low-clearance vehicle types at three types of hump crossings. Field testing indicates a good correlation between the predicted degree of vehicle-crossing conflicts and those observed in the field. Results are applicable to operations (e.g., truck routing) or for maintenance and reconstruction programs. Future research could extend the methodology to tunnel and bridge clearances, real-time warning systems, autonomous vehicles, or even nontransportation applications.
|Number of pages||14|
|Journal||Computer-Aided Civil and Infrastructure Engineering|
|State||Published - Feb 1 2017|
Bibliographical noteFunding Information:
The authors would like to thank Christopher VanDyke of the Kentucky Transportation Center for his significant work improving the readability of the manuscript as well as anonymous reviewers for their valuable suggestions. Funding for this research was provided by the NURail Center, University of Illinois at Urbana - Champaign under Grant No. DTRT12-G-UTC18 of the U.S. Department of Transportation, Office of the Assistant Secretary for Research & Technology (OST-R), University Transportation Centers Program. The contents of this article reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the U.S. Department of Transportation's University Transportation Centers Program, in the interest of information exchange. The U.S. Government assumes no liability for the contents or use thereof. The authors also acknowledge financial support from the National Natural Science Foundation of China (Fund # 51368021).
© 2016 Computer-Aided Civil and Infrastructure Engineering
ASJC Scopus subject areas
- Civil and Structural Engineering
- Computer Science Applications
- Computer Graphics and Computer-Aided Design
- Computational Theory and Mathematics