The number of collisions and fatalities at rail-highway intersections has declined significantly over the past thirty years, despite considerable increases in the volume of both rail and highway traffic. This paper disaggregates the improvement into its constituent causes. Negative binomial regressions are conducted on a pooled data set for 49 states from 1975 to 2001. The analysis concludes that about two-fifths of the decrease is due to factors such as reduced drunk driving and improved emergency medical response that have improved safety on all parts of the highway network. The installation of gates and/or flashing lights accounts for about a fifth of the reduction. The development of the "Operation Lifesaver" campaign, that seeks to inform the public on appropriate conduct at crossings, in the 1970s and early 1980s; and the installation of "ditch lights" on locomotives in the mid 1990s, each led to about a seventh of the reduction. Finally, about a tenth is due to closure of crossings resulting from line abandonment or consolidation of little-used crossings.

Why has safety improved at rail-highway grade crossings?

\n In order to ensure the safety of railway transportation, it is necessary to regularly check for faults and defects in the railway system. Visual inspection technology is conducive to improving the low efficiency, poor economy and inaccurate detection results of traditional detection methods. This paper introduces the research and contribution of various scholars in the field of visual inspection, summarizes the application and development of visual inspection technology in the railway industry, and finally forecasts the future research direction of visual inspection technology.

A review of applications of visual inspection technology based on image processing in the railway industry

Video surveillance systems obtain a great interest as application-oriented studies that have been growing rapidly in the past decade. The most recent studies attempt to integrate computer vision, image processing, and artificial intelligence capabilities into video surveillance applications. Although there are so many achievements in the acquisition of datasets, methods, and frameworks published, there are not many papers that can provide a comprehensive picture of the current state of video surveillance system research. This paper provides a comprehensive and systematic review on the literature from various video surveillance system studies published from 2010 through 2019. Within a selected study extraction process, 220 journal-based publications were identified and analyzed to illustrate the research trends, datasets, methods, and frameworks used in the field of video surveillance, to provide an in-depth explanation about research trends that many topics raised by researchers as a focus in their researches, to provide references on public datasets that are often used by researchers as a comparison and a means of developing a test method, and to give accounts on the improvement and integration of network infrastructure design to meet the demand for multimedia data. In the end of this paper, several opportunities and challenges related to researches in the video surveillance system are mentioned.

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A Systematic Review of Intelligence Video Surveillance: Trends, Techniques, Frameworks, and Datasets

Benchmarking regions using a heteroskedastic grouped random parameters model with heterogeneity in mean and variance: Applications to grade crossing safety analysis

A knowledge graph-based approach for exploring railway operational accidents

Automated detection of grade-crossing-trespassing near misses based on computer vision analysis of surveillance video data

Rail plays a key role in the transportation of hazardous materials (hazmat) Improving railroad hazmat transportation safety is a high priority for both industry and government Many severe railroa

Accident-Cause-Specific Risk Analysis of Rail Transport of Hazardous Materials:

The volume of video data in the railroad industry has increased significantly in recent years. Surveillance cameras are situated on nearly every part of the railroad system, such as inside the cab,...

Video Analytics for Railroad Safety Research: An Artificial Intelligence Approach:

Human factors are major causes of train accidents in the United States. Understanding the safety risk of these accidents can provide insights into safety evaluation and improvement. This paper focu...

Zhipeng Zhang

Papers

Automated detection of grade-crossing-trespassing near misses based on computer vision analysis of surveillance video data

Accident-Cause-Specific Risk Analysis of Rail Transport of Hazardous Materials:

Video Analytics for Railroad Safety Research: An Artificial Intelligence Approach:

Analysis of human-factor-caused freight train accidents in the United States

Risk assessment of marine accidents with Fuzzy Bayesian Networks and causal analysis