A Method to Verify Railroad Interconnect With Highway Traffic Signal Systems

2015 ◽  
Author(s):  
Adam Moore ◽  
Paul Zebell ◽  
Peter Koonce ◽  
Jon Meusch
Keyword(s):  
Traffic Signal ◽  
Department Of Transportation ◽  
Clearance Time ◽  
Highway Traffic ◽  
Signal Systems ◽  
Grade Crossing ◽  
Grade Crossings ◽  
State And Local

In response to increasing concern about railroad grade crossing safety, the Federal Railroad Administration and Department of Transportation issued Safety Advisory 2010-02 recommending in part “...that railroads conduct comprehensive joint inspections of highway traffic signal pre-emption interconnection with State and local highway authorities...” 2010-02 also recommends recording devices at interconnected highway-rail grade crossings. This paper addresses a method to facilitate these goals by enabling the highway authority to independently verify that rail equipment is functioning properly, and just as importantly, enabling the railroad to independently verify that the highway traffic signal equipment is providing adequate clearance time in advance of the arrival of the train in the crossing. The method involves adding two circuits between the rail equipment and the traffic signal equipment: a crossing island circuit, and a start of the traffic clearance phase indicator from the traffic signal to the rail equipment. This system has been implemented at two intersections in Portland, Oregon, with plans for further implementation.

Driver Behavior Analysis Using Vehicle Safety Systems’ Field Operational Test Data

2012 ◽  
Author(s):  
Tashi Ngamdung ◽  
Marco daSilva
Keyword(s):  
The United States ◽  
Older Drivers ◽  
Innovative Technology ◽  
Highway Traffic ◽  
Middle Aged ◽  
National Highway Traffic Safety ◽  
Operational Test ◽  
Field Operational Test ◽  
Grade Crossing ◽  
Grade Crossings

The United States Department of Transportation’s (US DOT) Research and Innovative Technology Administration’s John A. Volpe National Transportation Systems Center (Volpe Center), under the direction of the US DOT Federal Railroad Administration (FRA) Office of Research and Development (R&D), is leveraging the National Highway Traffic Safety Administration (NHTSA) sponsored Integrated Vehicle Based Safety System (IVBSS) Light Vehicle (LV) Field Operational Test (FOT) to collect and analyze drivers’ activities at or on approach to highway-rail grade crossings. Grade crossings in Michigan, Indiana, and Ohio were cross-referenced with IVBSS LV FOT research vehicle location to identify the time research vehicles were present at a crossing. The IVBSS LV FOT included 108 participants that took a total of 22,656 trips. Of the 22,656 total trips, 3,137 trips included a total of 4,215 grade crossing events. The analysis was based of drivers’ activities at the 4,215 grade crossing events. Both looking behavior and distractions did not significantly differ based on gender. However when analyzed per age-group, younger drivers (between 20 to 30 years old) were significantly more likely to be distracted than middle-aged drivers (between 40 to 50 years old) or older drivers (between 60 to 70 years old). For looking behavior, the data revealed that older drivers are more likely to look at least one way at or on approach to highway-rail crossing (43.8 percent exhibited this behavior) than either middle-aged drivers (35.0 percent exhibited this behavior) or younger drivers (25.3 percent exhibited this behavior).

Plan of Action To Reduce Vehicle-Train Crashes in Alabama

1998 ◽  
Vol 1648 (1) ◽  
pp. 8-18
Author(s):  
Brian L. Bowman ◽  
Kristen Stinson ◽  
Cecil Colson
Keyword(s):  
Action Plan ◽  
The State ◽  
Final Report ◽  
Judicial Reform ◽  
Department Of Transportation ◽  
Legislative Action ◽  
Intersection Safety ◽  
Grade Crossing ◽  
Grade Crossings ◽  
Comprehensive Study

In April 1996, the state of Alabama Legislature, through the passage of Act 503, directed the Alabama Department of Transportation (ALDOT) to conduct a comprehensive study of rail-highway grade crossings in the state and recommend methods to drastically reduce the number of vehicle-train crashes. Senate Act 503 states: “… That the Alabama Department of Transportation is directed to conduct a comprehensive study of the rail/highway grade crossings in the state and present a plan to this body recommending methods to dramatically reduce vehicle/train accidents by the first day of the 1997 Regular Session.” In response to Act 503, the Multimodal Bureau of ALDOT developed an Action Plan that compared Alabama’s grade crossing crash experience with the experience of the national and southeastern states to identify the prevalent characteristics, identified the perceived needs of safety and railroad professionals required to decrease vehicle-train crashes and crash severity, and compiled a list of recommendations and activities required for implementation. The activities and results of the Act 503 study documented in the final report are summarized (1). It discusses the engineering, economic, educational, enforcement, and emotional impediments to increasing rail-highway intersection safety and presents a broad range of realistic countermeasures. These countermeasures include legislative action; judicial reform; and enforcement, economic, and education initiatives.

Discovering Crash Severity Factors of Grade Crossing With a Machine Learning Approach

2019 ◽  
Author(s):  
Dahye Lee ◽  
Jeffery Warner ◽  
Curtis Morgan
Keyword(s):  
Machine Learning ◽  
The United States ◽  
Machine Learning Algorithms ◽  
Learning Approach ◽  
Highway Traffic ◽  
Extreme Gradient Boosting ◽  
Machine Learning Approach ◽  
Grade Crossing ◽  
Grade Crossings ◽  
Significant Factors

According to the Federal Railroad Administration (FRA) Highway-Rail Grade Crossing Accident/Incident database, more than 12,000 accidents occurred between 2012 and 2017 in the United States with casualties of around 3900. Despite repeated efforts to fully understand the risk factors that contribute to highway-rail grade crossing collisions, there still remain many uncertainties. A machine learning approach is proposed in this paper to find out significant factors, along with their individual impacts of crash severities at grade crossings. One of the most efficient and accurate machine learning algorithms, extreme gradient boosting (XGB or XGBoost), is applied to analyze 21 different accident and crossing -related characteristics per driver severities. The XGB model has been proven in previous studies across many research areas in transportation to outperform other machine learning-based methods and statistical classification methods, such as multinomial logit model, multiple additive regression trees, decision tree, and random forest, especially in prediction accuracy. Thereby, applying the algorithm is expected to provide highly reliable results to identify important factors that have impacts on injury severities at grade crossings. Such application will further aid the discovery of potential crossings with significant factors. The FRA’s Highway-Rail Grade Crossing Accident/Incident database from 2012 to 2017 is fused with the FRA Highway-Rail Crossing Inventory database for the analysis. Observations with missing information were removed from the original database. Crossing position under or over the railroad and pedestrian or other types of highway users were also not considered since they were not specifically of interest in this study. After the database cleaning process, it condensed to the total of 1,250 accidents out of the retrieved 12,630 from the combined database. The results show that adjacent highway traffic volume and train speed are the most significant factors causing accidents and injury severity. They are followed by the driver’s age and the estimated vehicle speed. It also indicated that truck-involved accidents and crossings with gates, flashing lights, and other types of warning devices combined, and highway user’s gender as a male also pertain to the higher injury rate. Through this study, it is possible to provide guidance to decision-makers in recognizing possible risks at-grade crossings that may cause driver casualties.

scholarly journals Effect of Dynamic Envelope Pavement Markings on Vehicle Driver Behavior at a Highway-Rail Grade Crossing

2014 ◽  
Author(s):  
Scott Gabree ◽  
Stephanie Chase ◽  
Marco daSilva
Keyword(s):  
The United States ◽  
Transportation Systems ◽  
United States Department ◽  
Department Of Transportation ◽  
Pavement Markings ◽  
Florida Department ◽  
Before And After ◽  
Grade Crossing ◽  
Grade Crossings ◽  
Stop Line

The United States Department of Transportation’s (USDOT) John A. Volpe National Transportation Systems Center (Volpe Center), under the direction of the USDOT Federal Railroad Administration (FRA) Office of Research and Development (R&D), recently completed a study on the use of pavement markings to reduce instances of vehicles stopping on the tracks at grade crossings. Specifically, the study evaluated the effectiveness of pavement markings placed within the dynamic envelope, the region between and immediately adjacent to the tracks at a grade crossing, and new corresponding signage at the Commercial Boulevard grade crossing (ID# 628186E) in Ft. Lauderdale, Florida. The goal of this research study was to gain an understanding of the effect of dynamic envelope pavement markings and accompanying signage on driver’s not stopping while traversing the tracks. The addition of the dynamic envelope markings and signage is intended to make this area more pronounced, resulting in fewer motorists entering the dynamic envelope if they are unable to exit the other side. Researchers coded driver stopping behavior at this crossing before and after the surface treatments were installed. Vehicles were coded as having stopped in one of four zones: behind the stop line and gate arm (Zone 1), past the stop line but before the tracks (Zone 2), on the tracks (Zone 3), or immediately after the tracks (Zone 4). Stopping in Zone 3 is considered to be the most dangerous behavior that a driver could perform, while stopping in Zone 1 is the safest. The goal of the added markings and signage is to reduce the number of vehicles which come to a stop within the dynamic envelope, thus reducing the possibility that a vehicle is present on the tracks when a train approaches resulting in a collision. The addition of the dynamic envelope pavement markings and modified signage resulted in a statistically significant change in driver stopping behavior. Specifically, the pavement markings and signage reduced the proportion of vehicles that stopped in Zone 3, resulting in a 45% reduction in vehicles stopped in Zone 3 for eastbound vehicles and 14% for westbound vehicles. They also increased the proportion of vehicles stopping in Zone 1, which is the safest behavior a driver can perform (9% increase for eastbound and 6% increase for westbound). Additionally, fewer vehicles were found to stop in both Zone 2 and Zone 4, which are both moderately dangerous. Based on these results, the Florida Department of Transportation is exploring the use of this safety treatment at additional grade crossings with a high risk for unsafe vehicle stopping behavior.

Updating Annual Average Daily Traffic Estimates at Highway-Rail Grade Crossings with Geographically Weighted Poisson Regression

2019 ◽  
Vol 2673 (10) ◽  
pp. 105-117
Author(s):  
Huiyuan Liu ◽  
Myungwoo Lee ◽  
Aemal J. Khattak
Keyword(s):  
Poisson Regression ◽  
Future Research ◽  
Highway Traffic ◽  
Annual Average ◽  
Traffic Counts ◽  
Annual Average Daily Traffic ◽  
Grade Crossing ◽  
Safety Assessments ◽  
Grade Crossings ◽  
Safety Considerations

Highway-rail grade crossings (HRGCs) are unique nodes in the transportation system that facilitate the movement of rail and highway traffic. Various mathematical models are available that provide safety assessments of HRGCs. A chief ingredient of these models is the annual average daily traffic (AADT). One of the main sources of data for such models is the Federal Railroad Administration (FRA)’s Grade Crossing Inventory. A substantial portion of the AADT data in the inventory is outdated. This paper investigates the effects of using out-of-date rather than up-to-date AADT values, using two safety assessment models to isolate the differences. Results show that the use of out-of-date AADT data generates biased rankings of HRGCs based on safety considerations. Since collection of AADT data is resource-intense, a methodology based on a geographic information system for estimating updated AADT is presented. This methodology utilizes limited traffic counts that are supplemented with additional publicly available data. An application using a geographically weighted Poisson regression model for 14 HRGCs gave results that closely matched AADT values based on 2018 field traffic counts at those HRGCs. This method provides an alternative to costly field-data-based updating of AADT in the relatively extensive Grade Crossing Inventory database. Limitations of the research and suggestions for future research complete this paper.

scholarly journals LEGIBILITY OF URBAN HIGHWAY TRAFFIC SIGNS USING NEW RETROREFLECTIVE MATERIALS

Transport ◽  
2010 ◽  
Vol 25 (3) ◽  
pp. 229-236 ◽  
Author(s):  
John D. Bullough ◽  
Nicholas P. Skinner ◽  
Conan P. O’Rourke
Keyword(s):  
Urban Area ◽  
Performance Model ◽  
Visual Performance ◽  
Practical Significance ◽  
Department Of Transportation ◽  
Highway Traffic ◽  
Traffic Signs ◽  
Photometric Measurements ◽  
Highway Signs

Unlighted highway signs, which use newly developed retroreflective materials, were installed along the major expressway in an urban area by the local department of transportation. Photometric measurements of the signs were used to assess their legibility applying the relative visual performance model, in comparison to lighted signs, con‐ forming to recommended illumination practices. The calculated visibility of the measured unlighted signs was similar to that of the signs equipped with exterior sign illumination. The practical significance and limitations of the relative visual performance approach are discussed.

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