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Journal articles on the topic 'At-grade crossings'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Yeh, Michelle, and Jordan Multer. "Applying a Sociotechnical Framework for Improving Safety at Highway-Railroad Grade Crossings." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 51, no. 24 (2007): 1550–54. http://dx.doi.org/10.1177/154193120705102408.

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To understand drivers' decisions and actions at grade crossings, we examined human factors contributing to noncompliance at grade crossings using a sociotechnical framework. This perspective allows driver behavior at grade crossings to be examined not as individual elements but rather as a function of how each element interacts with other elements within the system. In this paper, we present a model that addresses driver decision-making at grade crossings at a systems level. We identify and describe four elements of the grade crossing system influencing driver compliance: the design of the grade crossing environment, driver characteristics, the role of organizations and management, and social and political forces. We then apply the model to identify how failure to consider safety from a systems perspective contributed to the grade crossing accident that occurred in Fox River Grove, Illinois, in 1995.

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2

Estes, R. Matthew, and Laurence R. Rilett. "Advanced Prediction of Train Arrival and Crossing Times at Highway-Railroad Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 1708, no. 1 (2000): 68–76. http://dx.doi.org/10.3141/1708-08.

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There are many issues related to highway–railroad grade crossings. For historic and practical reasons, trains have the right-of-way at grade crossings, which results in delays to motorists. In addition, the differential in size, speed, and stopping ability between motor vehicles and trains raises many serious safety concerns. Historically, the methods used to address these delay and safety problems at grade crossings have been reactive in nature. For example, the Manual on Uniform Traffic Control Devices specifies a minimum of 20 s of warning time for active warning devices at grade crossings. Intelligent transportation system (ITS) technology offers potential solutions for increasing the warning time at grade crossings. Advanced on-board devices and off-track detection equipment can allow train position and speed to be monitored. This information can be shared through wireless and wireline telecommunications equipment being deployed for ITS. Transportation management center personnel can then predict the arrival and crossing times of trains at grade crossings. It is hypothesized that if the warning time could reliably be increased, the traffic-operation strategies in the vicinity of grade crossings could be more proactive, reducing delay to motorists and increasing safety for both trains and automobiles. The research focuses on a second-generation technology approach to an advanced prediction of train arrival and crossing (gate-up and gate-down) times at highway–railroad grade crossings, including problems faced at grade crossings, background on detection and prediction technology for grade crossings, the train monitoring system used as the test bed for the research, the development of the methodology, the results of the analysis, and the conclusions of the research and potential applications for the model.

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3

Hakkert, A. S., and V. Gitelman. "Development of Evaluation Tools for Road-Rail Crossing Consideration for Grade Separation." Transportation Research Record: Journal of the Transportation Research Board 1605, no. 1 (1997): 96–105. http://dx.doi.org/10.3141/1605-12.

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A program for expansion of Israeli railways has resulted in increased train speeds and frequencies on the most heavily used railway lines. These are situated in highly populated regions and are characterized by a significant amount of at-grade road-rail crossings. At-grade crossings present a barrier to road traffic and the danger of train-vehicle collisions. Because the current maximum train speed is about 120 km/hr, there was no clear policy concerning the need and the priority for grade separation at crossings. Simplified tools for rapid crossing evaluation when a crossing potential for grade separation is reviewed were developed. The evaluation tools include a criterion for preliminary crossing qualification and a formula for approximate evaluation of economic losses caused by at-grade crossing functioning. The field measurements and detailed investigation of the 31 most problematic locations provided a basis for building the tools. Two main factors leading to grade separation were considered: safety problems at the crossings and road vehicle delay costs. As demonstrated, the cost of accident risk at Israeli crossings does not significantly affect their ranking for grade separation. In consequence, the crossing parameters influence vehicle delays that constitute the basis for the simplified tools for preliminary crossing evaluation in Israel.

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4

Pasha, Junayed, Maxim A. Dulebenets, Olumide F. Abioye, et al. "A Comprehensive Assessment of the Existing Accident and Hazard Prediction Models for the Highway-Rail Grade Crossings in the State of Florida." Sustainability 12, no. 10 (2020): 4291. http://dx.doi.org/10.3390/su12104291.

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Accidents at highway-rail grade crossings can cause fatalities and injuries, as well as significant property damages. In order to prevent accidents, certain upgrades need to be made at highway-rail grade crossings. However, due to limited monetary resources, only the most hazardous highway-rail grade crossings should receive a priority for upgrading. Hence, accident/hazard prediction models are required to identify the most hazardous highway-rail grade crossings for safety improvement projects. This study selects and evaluates the accident and hazard prediction models found in the highway-rail grade crossing safety literature to rank the highway-rail grade crossings in the State of Florida. Three approaches are undertaken to evaluate the candidate accident and hazard prediction models, including the chi-square statistic, grouping of crossings based on the actual accident data, and Spearman rank correlation coefficient. The analysis was conducted for the 589 highway-rail grade crossings located in the State of Florida using the data available through the highway-rail grade crossing inventory database maintained by the Federal Railroad Administration. As a result of the performed analysis, a new hazard prediction model, named as the Florida Priority Index Formula, is recommended to rank/prioritize the highway-rail grade crossings in the State of Florida. The Florida Priority Index Formula provides a more accurate ranking of highway-rail grade crossings as compared to the alternative methods. The Florida Priority Index Formula assesses the potential hazard of a given highway-rail grade crossing based on the average daily traffic volume, average daily train volume, train speed, existing traffic control devices, accident history, and crossing upgrade records.

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5

Saccomanno, Frank F., and Xiaoming Lai. "A Model for Evaluating Countermeasures at Highway–Railway Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 1918, no. 1 (2005): 18–25. http://dx.doi.org/10.1177/0361198105191800103.

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Current collision prediction models fail to account for the full spectrum of relevant factors affecting the number of collisions at specific highway– railway grade crossings. A number of reasons contribute to this failure, including biases in model parameters resulting from collinearity in the model inputs, absence of important variables in the prediction model caused by lack of statistical significance, the inability of models to consider higher-order interactions, and the presence of unexplained variation in the prediction estimates. These problems have compromised the use of collision prediction models in decisions concerning the development and evaluation of cost-effective safety treatments or countermeasures for application at specific crossings. This paper introduces a stratified collision prediction model for highway–railway grade crossings. The development of this model involves three steps: ( a) crossing inventory variables are expressed in terms of a limited number of orthogonal (nonlinear) underlying attributes or factors; ( b) factor scores are estimated for each crossing and factor, and these scores are used as “seed points” in a subsequent clustering exercise to yield groups or clusters of crossings with similar underlying attributes; and ( c) for each cluster, separate collision prediction models are developed and include important treatment input variables of interest to decision makers and planners. The paper describes an application of a stratified collision prediction model to Canadian highway–railway grade crossing inventory and collision occurrence data for the period 1993 to 2001. The usefulness of the model in estimating collision reduction benefits of selected treatments is illustrated with reference to two countermeasure strategies: upgrades in the type of warning device and the removal of whistle prohibition.

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6

Fischhaber, Pamela M., and Bruce N. Janson. "Preliminary Analysis of Light Rail Crashes in Denver, Colorado." Transportation Research Record: Journal of the Transportation Research Board 2275, no. 1 (2012): 12–21. http://dx.doi.org/10.3141/2275-02.

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This paper presents a preliminary analysis of light rail crashes at at-grade crossings in Denver, Colorado, based on Regional Transportation District data for 1999 through 2009. Differences in design and operation of at-grade crossings are discussed for light rail versus common carrier railroad (railroad). The differences appear to warrant the development of separate crash prediction and hazard index models because models developed for railroad at-grade crossing operations may not accurately predict the number and severity of crashes at light rail at-grade crossings. In addition, the models developed for railroads do not predict crashes at crossings for some traffic control device types such as traffic signals. The lack of information for crossings controlled by traffic signals in the railroad crash prediction equations is one reason why equations specific to light rail may need to be developed. This study identifies patterns in light rail crossing crash data that warrant further investigation and support the development of crash prediction models and hazard index equations specific to light rail at-grade crossing configurations and operations.

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7

Noyce, David A., and Daniel B. Fambro. "Enhanced Traffic Control Devices at Passive Highway-Railroad Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 1648, no. 1 (1998): 19–27. http://dx.doi.org/10.3141/1648-03.

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More than 2,000 crashes and 239 fatalities were reported at public passive highway-railroad grade crossings in 1994. Driver error, often due to a breakdown in communication between traffic control devices and the driver, is commonly cited as a factor in passive grade crossing crashes. The objective of this study was to evaluate an improved method for communicating with drivers in an effort to improve safety at passive grade crossings. Specifically, this study evaluated the effectiveness of a vehicle-activated strobe light and supplemental sign as enhancements to the railroad advance (W10-1) warning sign at a passive highway-railroad grade crossing near Temple, Texas. Three study methods were used to evaluate this enhanced sign system including a before and after speed study, a driver survey, and a driver observation study. The results indicated that average speeds on the approaches to the grade crossing were lower after the installation of the enhanced sign system. Drivers responded favorably to the enhanced sign system, and no adverse driver reactions were observed at the onset of the flashing strobe light. The strobe light was effective in directing drivers’ attention to the railroad advance warning and supplemental signs. The enhanced sign system appears to increase driver awareness of the passive grade crossing, cause some drivers to approach the grade crossing with additional caution, and reduce the average speed near the nonrecovery zone on both approaches.

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8

Park, Young-Jin, and Frank F. Saccomanno. "Evaluating Factors Affecting Safety at Highway–Railway Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 1918, no. 1 (2005): 1–9. http://dx.doi.org/10.1177/0361198105191800101.

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Various countermeasures can be introduced to reduce collisions at highway–railway grade crossings. Existing improvements to crossings include the installation of flashing lights or gates, the addition of extra warning devices such as four-quadrant barriers or wayside horns, and the enforcement of speed limits on the approaching highway. Statistical models are needed to ensure that countermeasures introduced at a given crossing are both cost-effective and practicable. However, in large part because of issues of colinearity, poor statistical significance, and parametric bias, many existing statistical models are simple in structure and feature few statistically significant explanatory variables. Accordingly, they fail to reflect the full gamut of factor inputs that explain variation in collision frequency at individual crossings over a given period of time. Before statistical models can be used to investigate the cost-effectiveness of specific countermeasures, models must be developed that more fully reflect the complex relationships that link a specific countermeasure to collision occurrence. This study presents a sequential modeling approach based on data mining and statistical methods to estimate the main and interactive effects of introducing countermeasures at individual grade crossings. This paper makes use of Canadian inventory and collision data to illustrate the potential merits of the model in decision support.

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9

Park, Young-Jin, and Frank F. Saccomanno. "A structured model for evaluating countermeasures at highwayrailway grade crossings." Canadian Journal of Civil Engineering 32, no. 4 (2005): 627–35. http://dx.doi.org/10.1139/l05-017.

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Various countermeasures can be introduced to reduce collisions at highwayrailway grade crossings. These countermeasures may take different forms, such as passive and (or) active driver warning devices, supplementary traffic controls (four quadrant barriers, wayside horn, closed circuit television (CCTV) monitoring, etc.), illumination, signage and highway speed limit, etc. In this research, we present a structured model that makes use of data mining techniques to estimate the effect of changes in countermeasures on the expected number of collisions at a given crossing. This model serves as a decision-support tool for the evaluation and development of cost-effective and practicable safety program at highwayrailway grade crossings. The use of data mining techniques helps to resolve many of the problems associated with conventional statistical models used to predict the expected number of collisions for a given type of crossing. Statistical models introduce biases that limit their ability to fully represent the relationship between selected countermeasures and resultant collisions for a mix of crossing attributes. This paper makes use of Canadian inventory and collision data to illustrate the potential merits of the proposed model to provide decision support.Key words: highwayrailway grade crossing, collision prediction model, countermeasures, Poisson regression.

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10

Cho, Hanseon, and Laurence R. Rilett. "Forecasting Train Travel Times at At-Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 1844, no. 1 (2003): 94–102. http://dx.doi.org/10.3141/1844-12.

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The ability to accurately forecast train arrival times is essential for the safe and efficient operation of highway–railroad grade crossings (HRGCs). Trains in the United States are required to give a minimum of 20 s of warning time before arriving at an HRGC. With the recent development of new detection-equipment technology, detectors potentially could be employed further upstream of the HRGC, which would result in earlier detection times. This information would be particularly useful for preemption strategies at signalized intersections located near the HRGC (IHRGCs). For example, earlier warning times could be used to reduce or eliminate the risk of unsafe pedestrian movements at IHRGCs. In this study, a modular artificial neural network (ANN) was used to forecast the train arrival time at an HRGC. An ANN was adopted because there is a nonlinear relationship between the independent variables such as train speed profile and the dependent variable arrival time at an HRGC. A modular approach was used because the trains often have different characteristics depending on their cargo and the operational rules in effect at the time they are detected. Because the train detection is continuous, different models were developed for each separate data input. In this case, the prediction interval update was assumed to be 10 s and 24 models were developed. Approximately 499 trains were used for training the ANN and 183 trains were used for testing. It was found that a modular architecture gave superior results to that of a simple ANN model, standard regression techniques, and current forecasting methods for the entire detection time period. It was found that, with an increase in detection time, the forecast accuracy increases for all methods and the prediction interval tends to decrease.

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11

Gent, Steve J., Scott Logan, and David Evans. "Automated-Horn Warning System for Highway-Railroad Grade Crossings: Evaluation at Three Crossings in Ames, Iowa." Transportation Research Record: Journal of the Transportation Research Board 1708, no. 1 (2000): 77–82. http://dx.doi.org/10.3141/1708-09.

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Traditionally, locomotive engineers begin sounding the train horn approximately one-quarter mile from the crossing to warn motorists and pedestrians approaching the intersection. To be heard over this distance, the train horn must be very loud. This combination of loud horns and the length along the tracks that the horn is sounded creates a large area adversely impacted by the horn noise. In urban areas, this area likely includes many nearby residents. The automated-horn system provides a similar audible warning to motorists and pedestrians by using two stationary horns mounted at the crossing. Each horn directs its sound toward the approaching roadway. The horn system is activated using the same track–signal circuitry as the gate arms and bells located at the crossing. Once the horn is activated, a strobe light begins flashing to inform the locomotive engineer that the horn is working. Horn volume data collected near the crossings clearly demonstrate the significant reduction of land area negatively impacted by using the automated horns. Residents overwhelmingly accepted the automated-horn systems and noted a significant improvement in their quality of life. Motorists preferred the automated-horn systems, and locomotive engineers rated these crossings slightly safer compared with the same crossings in the before (train horn) condition.

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12

Carlson, Paul J., and Kay Fitzpatrick. "Violations at Gated Highway–Railroad Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 1692, no. 1 (1999): 66–73. http://dx.doi.org/10.3141/1692-08.

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13

Khattak, Aemal J., and Gregory A. McKnight. "Gate Rushing at Highway–Railroad Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 2056, no. 1 (2008): 104–9. http://dx.doi.org/10.3141/2056-13.

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14

Yang, Jingsi, Xuedong Yan, Qingwan Xue, et al. "Exploring the Effects of Signs’ Design and In-Vehicle Audio Warning on Driver Behavior at Flashing-Light-Controlled Grade Crossings: A Driving Simulator-Based Study." Journal of Advanced Transportation 2019 (December 31, 2019): 1–20. http://dx.doi.org/10.1155/2019/2497459.

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The complex environment at grade crossings and the severe collision consequences give rise to the concern of safety condition at crossings among traffic control authorities. Optimizing conventional devices and applying emerging technologies are worthwhile measures to improve the safety conditions at grade crossings. In this study, a flashing-light running (FLR) warning system was proposed to reduce crossing violation and improve performances of drivers at flashing-light-controlled grade crossings (FLCGCs). Forty-four fully licensed drivers aged between 30 and 48 years participated in a driving simulator study to investigate the efficacy of two countermeasures of the system: proposed design of signs and pavement markings (PSM) for grade crossing, and two-stage in-vehicle audio warning (IVAW) technology. A range of flashing light trigger timing and two foggy conditions were designed in this experiment to test the system applicability. Drivers’ gender and vocation were considered as well to examine drivers’ adaptation to the new proposed system. Five variables were collected and analyzed in this study to investigate the effectiveness of the system, i.e., drivers’ compliance, approaching mean speed, brake reaction time, deceleration, and red-to-crossing time. Results showed that drivers’ driving performances were improved in both PSM only condition and PSM + W condition. The FLR warning system could eliminate the negative effects of foggy weather and reduce gender differences in driver behaviors to some extent. These findings suggested that the FLR warning system has a potential to reduce the probability of grade crossing collisions.

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15

Stephens, Burton W., and Gary Long. "Supplemental Pavement Markings for Improving Safety at Railroad–Highway Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 1844, no. 1 (2003): 18–24. http://dx.doi.org/10.3141/1844-03.

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An evaluation was performed of special X-box pavement marking configurations at railroad–highway grade crossings, originally used in several European countries. The intent is to provide motorists with supplemental visual cues about whether sufficient space is available for safe storage of a vehicle beyond the track for a motorist to proceed across. It is intended for application where nearby intersections can cause queues to back up to the track. These conspicuous markings, configured as an X in a box, were tested at two Florida locations, one in an urban area and one in a rural area, over a 1 ½-year period. The rates of cars hazardously stopping on or closely adjacent to the railroad tracks at the crossings were compared under pre- and postinstallation conditions. Results at the rural location showed a decline of more than 60% in hazardous stoppage rates over an extended period. No significant differences were found between the pre- and postinstallation tests at the urban location. A control site was utilized near the crossing in the urban location, and it showed no significant differences between the two test periods that were concurrent with the analysis at the treated site. Recommendations are provided for application of these markings at grade crossing sites in rural and urban locations.

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Mansel, Douglas M., Vernon H. Waight, and John T. Sharkey. "Supervised Interconnection Circuits at Highway–Rail Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 1692, no. 1 (1999): 74–81. http://dx.doi.org/10.3141/1692-09.

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17

Lerner, Neil D., and Donna J. Ratte'. "Drivers as Decision Makers at Rail-Highway Grade Crossings." Proceedings of the Human Factors Society Annual Meeting 34, no. 14 (1990): 1042–46. http://dx.doi.org/10.1177/154193129003401418.

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18

Khattak, Aemal, and Zheng Luo. "Pedestrian and Bicyclist Violations at Highway–Rail Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 2250, no. 1 (2011): 76–82. http://dx.doi.org/10.3141/2250-10.

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19

Tung, Li-Wei, and Aemal Khattak. "Distracted Motor Vehicle Driving at Highway–Rail Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 2476, no. 1 (2015): 77–84. http://dx.doi.org/10.3141/2476-11.

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20

Medina, Juan C., and Rahim F. Benekohal. "Macroscopic Models for Accident Prediction at Railroad Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 2476, no. 1 (2015): 85–93. http://dx.doi.org/10.3141/2476-12.

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21

Mok, Shannon C., and Ian Savage. "Why Has Safety Improved at Rail-Highway Grade Crossings?" Risk Analysis 25, no. 4 (2005): 867–81. http://dx.doi.org/10.1111/j.1539-6924.2005.00642.x.

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22

Tenkink, Erik, and Richard Van der Horst. "Car driver behavior at flashing light railroad grade crossings." Accident Analysis & Prevention 22, no. 3 (1990): 229–39. http://dx.doi.org/10.1016/0001-4575(90)90015-d.

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23

Mathew, Jacob, Rahim (Ray) F. Benekohal, and Juan C. Medina. "Nested Sorting and Clustering for Visualization of Accidents in Highway–Rail Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 2608, no. 1 (2017): 46–57. http://dx.doi.org/10.3141/2608-06.

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Safety at railroad grade crossings is a critical issue for highway and rail networks. Relevant databases can be analyzed to find the causes of or factors contributing to crossing accidents so that appropriate counter-measures can be applied. Manually establishing the order of the contributing factors of the accidents and extracting useful information from accident databases are not feasible because of the enormous number of possible permutations of contributing factors. This paper presents a new automated method for sorting and clustering accident attributes to identify and visualize trends in the accident databases. The method is called modified nested sorting and crossing cluster (M+C). The method creates a dynamic tree visualization that highlights attributes resulting in the greatest accident concentration along a tree branch, uncovering the most common nested accident factors. This approach is a significant improvement over static methods that rely on a fixed hierarchy of attributes. With the M+C method, a unique hierarchy of the attributes can be determined for a single crossing or for a set of crossings. This approach is completely data driven and is suitable for corridors and large groups of accidents that are otherwise difficult to analyze. The method is illustrated for single crossings and a corridor with several crossings identified from the FRA online database. Absolute sorting and nested sorting are discussed, and the evolution of M+C is presented. The M+C method is useful for assessing many single grade crossings or crossings that are along a corridor or within a region.

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24

Singh, Prashant, Junayed Pasha, Amir Khorram-Manesh, Krzysztof Goniewicz, Abdolreza Roshani, and Maxim A. Dulebenets. "A Holistic Analysis of Train-Vehicle Accidents at Highway-Rail Grade Crossings in Florida." Sustainability 13, no. 16 (2021): 8842. http://dx.doi.org/10.3390/su13168842.

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Highway-rail grade crossing (HRGC) accidents pose a serious risk of safety to highway users, including pedestrians trying to cross HRGCs. A significant increase in the number of HRGC accidents globally calls for greater research efforts, which are not limited to the analysis of accidents at HRGCs but also understanding user perception, driver behavior, potential conflicting areas at crossings, effectiveness of countermeasures and user perception towards them. HRGC safety is one of the priority areas in the State of Florida, since the state HRGCs experienced a total of 429 injuries and 146 fatalities between 2010 and 2019 with a significant increase in HRGC accidents over the last years. The present study aims to conduct a comprehensive analysis of the HRGCs that experienced accidents in Florida over the last years. The databases maintained by the Federal Rail Administration (FRA) are used to gather the relevant information for a total of 578 crossings that experienced at least one accident from 2010 to 2019. In contrast with many of the previous efforts, this study investigates a wide range of various factors, including physical and operational characteristics of crossings, vehicle and train characteristics, spatial characteristics, temporal and environmental characteristics, driver actions and related characteristics, and other relevant information. The outcomes of this research will help better understanding the major causes behind accidents at the HRGCs in the State of Florida in a holistic way by considering a variety of relevant factors, which will assist the appropriate stakeholders with implementation of safety improvement projects across the state.

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Coleman, Fred, and Young J. Moon. "System Simulation of Dual-Gate At-Grade Railroad-Highway Crossings: Development and Verification." Transportation Research Record: Journal of the Transportation Research Board 1605, no. 1 (1997): 88–95. http://dx.doi.org/10.3141/1605-11.

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A simulation model of a dual-gate railroad-highway grade crossing was developed, validated, and applied to six crossings on the Chicago–St. Louis High Speed Passenger Rail Corridor. Simulation was used to demonstrate the feasibility of modeling the interaction of active safety devices, driver behavior, and vehicular and train traffic, and the dual-gate model served as the basis for development of a four-quadrant gate simulation model. Findings from the dual-gate simulation indicate that aggressive or inattentive drivers in the nonrecovery zone frequently exceed stopping distances and more beyond gate arms, and therefore are likely to proceed at high risk of a collision between their vehicle and a train.

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Desta, Robel, Daric Tesfaye, and János Tóth. "Microscopic Traffic Characterization of Light Rail Transit Systems at Level Crossings." Advances in Civil Engineering 2021 (May 26, 2021): 1–11. http://dx.doi.org/10.1155/2021/5574848.

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The movement of the light rail vehicles (LRVs) is highly interrupted at level crossings during peak hour times, especially when the intersections are not regulated by a coordinated signal system. Traffic modelling ensures better understanding and interpretation of complex traffic interactions. This study is aimed at modelling light rail transit (LRT) system operational characteristics at level crossings in Addis Ababa City using VISSIM software. The studied scenarios at Sebategna (All Way Stop Controlled, AWSC) and CMC (Roundabout) level crossings are the baseline without LRT scenario, the actual scenario with collected LRV headways, twice arrival frequency scenario, signalized actual LRV arrival, and signalized twice actual LRV arrival. The relative comparisons among the tested scenarios depicted that significant travel time savings can be achieved in some approaches if more green time is offered to nonconflicting phases during a light rail crossing. Overall, the average additional delays at level crossings increase from the base scenario with increasing light rail crossing frequencies, and delay at the level crossing is the second important variable that contributes to the variability of train travel time at peak hours. If it is a must for an intersection to have a rail road to pass through the median, different options should be verified based on the trade-off between the operational cost of the level crossing and the cost incurred if it is grade separated.

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Alligood, Anna Bovbjerg, Manali Sheth, Anne Goodchild, Edward McCormack, and Polina Butrina. "Rails-Next-to-Trails: A Methodology for Selecting Appropriate Safety Treatments at Complex Multimodal Intersections." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 10 (2018): 12–27. http://dx.doi.org/10.1177/0361198118792763.

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There are more than 212,000 at-grade railroad crossings in the United States. Several feature paths running adjacent to the railroad tracks, and crossing a highway; they serve urban areas, recreational activities, light rail station access, and a variety of other purposes. Some of these crossings see a disproportionate number of violations and conflicts between rail, vehicles, and pedestrians and bikes. This research focuses on developing a methodology for appropriately addressing the question of treatments in these complex, multimodal intersections. The methodology is designed to be able to balance a predetermined, prescriptive approach with the professional judgment of the agency carrying out the investigation. Using knowledge and data from the literature, field studies, and video observations, a framework for selecting treatments based on primary issues at a given location is developed. Using such a framework allows the agency to streamline their crossing improvement efforts; to easily communicate and inform the public of the decisions made and their reasons for doing so; to secure stakeholder buy-in prior to starting a project or investigation; to make sure that approach and selected treatments are more standardized; and to ensure transparency in the organization to make at-grade crossings safer for pedestrians and bicyclists, without negatively impacting trains or vehicles.

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Easa, Said M., Xiaobo Qu, and Essam Dabbour. "Improved Pedestrian Sight-Distance Needs at Railroad-Highway Grade Crossings." Journal of Transportation Engineering, Part A: Systems 143, no. 7 (2017): 04017027. http://dx.doi.org/10.1061/jtepbs.0000047.

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29

Ling, Ziwen, Christopher R. Cherry, and Nirbesh Dhakal. "Factors influencing single-bicycle crashes at skewed railroad grade crossings." Journal of Transport & Health 7 (December 2017): 54–63. http://dx.doi.org/10.1016/j.jth.2017.01.004.

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Li, Meng, Guoyuan Wu, Yue Li, Fanping Bu, and Wei-bin Zhang. "Active Signal Priority for Light Rail Transit at Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 2035, no. 1 (2007): 141–49. http://dx.doi.org/10.3141/2035-16.

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31

Gitelman, Victoria, A. Shalom Hakkert, Etti Doveh, and Ayala Cohen. "Screening Tools for Considering Grade Separation at Rail-Highway Crossings." Journal of Transportation Engineering 132, no. 1 (2006): 52–59. http://dx.doi.org/10.1061/(asce)0733-947x(2006)132:1(52).

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32

Ko, Byungkon, Scott S. Washburn, Kenneth G. Courage, and H. Michael Dowell. "Evaluation of Flexible Traffic Separators at Highway–Railroad Grade Crossings." Journal of Transportation Engineering 133, no. 7 (2007): 397–405. http://dx.doi.org/10.1061/(asce)0733-947x(2007)133:7(397).

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Malloy, Brett R., Jerry G. Rose, and Reginald R. Souleyrette. "Rehabilitation of Railway–Highway At-Grade Crossings: Recommendations and Guides." Transportation Research Record: Journal of the Transportation Research Board 2545, no. 1 (2016): 100–114. http://dx.doi.org/10.3141/2545-11.

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34

Easa, Said M. "Reliability-based design of sight distance at railroad grade crossings." Transportation Research Part A: Policy and Practice 28, no. 1 (1994): 1–15. http://dx.doi.org/10.1016/0965-8564(94)90038-8.

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35

Coleman, Fred, and oung J. Moon. "Design of Gate Delay and Gate Interval Time for Four-Quadrant Gate System at Railroad-Highway Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 1553, no. 1 (1996): 124–31. http://dx.doi.org/10.1177/0361198196155300118.

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A design methodology for gate delay and gate interval time for at-grade crossings using four-quadrant gates is developed. The design approach is based on the concept of dilemma zones related to signal change intervals at signalized intersections. The design approach is validated based on data from six sites in Illinois on a proposed high-speed rail corridor. Gate delay and gate interval times are determined that provide an optimal safe decision point to allow a driver to stop before the crossing or to proceed through the crossing without becoming trapped by the exit gates.

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Kang, Yashu, and Aemal Khattak. "Cluster-Based Approach to Analyzing Crash Injury Severity at Highway–Rail Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 2608, no. 1 (2017): 58–69. http://dx.doi.org/10.3141/2608-07.

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The presence of unobserved heterogeneity in crash data can result in estimation of biased model parameters and incorrect inferences. The research presented in this paper investigated severity of crashes reported at highway–rail grade crossings by appropriately clustering the data, accounting for unobserved heterogeneity. A combination of data mining and statistical regression methods was used to cluster crash data into subsets and then to identify factors associated with crash injury severity levels. This research relied on highway–rail accident, incident, and crossing inventory databases for 2011 to 2015 obtained from FRA. Three clustering methods— K-means, traditional latent class cluster, and variational Bayesian latent class cluster—were considered, and the variational Bayesian latent class cluster method was chosen for partitioning the data set for model estimation. Unclustered data as well as the clustered subsets were used to estimate ordered logit models for crash injury severity. A comparison revealed that the cluster-based approach provided more relevant model parameters and identified factors relevant only to certain clusters of the data.

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Cyr, Justin D., John W. Shaw, and Peter T. Savolainen. "Motor Vehicle Crashes Involving Railroad Crossing Signal Masts and Guardrails." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 12 (2019): 191–203. http://dx.doi.org/10.1177/0361198119857952.

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The installation of “active” warning devices, such as crossing signals and gates, is a principal element of state and federal railroad crossing safety programs, and their effectiveness in preventing vehicle–train collision is well documented. While most active crossings are occupied by trains only a few minutes each day, non-crashworthy items are frequently present at active crossings including crossing signal masts, crossing gate mechanisms, cantilever supports, and signal controller bungalows. Various agencies utilize longitudinal guardrail systems to protect errant motorists from striking non-frangible crossing signal hardware. This study sought to determine whether such guardrails influence the prevalence and severity of motor vehicle strikes involving crossing hardware. A review of 10 years of police crash-report narratives in Iowa, United States (U.S.) indicates an average of 15.6 crashes per year at 1,853 crossings involving signal masts, signal guardrails, or related infrastructure. Over this period, one fatality and five serious injuries occurred as a result of these crashes. The crash-injury severity distributions appeared similar in crashes with and without guardrail, and regression models showed that guardrail presence did not affect the rate of crashes involving railroad apparatus. Although the use of longitudinal guardrail systems did not appear to have a strong effect on crash rates or severity at active grade crossings, other methods for reducing crash prevalence and severity could be explored in future research, such as the development of crashworthy signal assemblies for flashing-signal-only crossings and the redesign of gate and cantilever supports to increase separation from the traveled way.

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Khan, Waleed A., and Aemal J. Khattak. "Injury Severity of Truck Drivers in Crashes at Highway-Rail Grade Crossings in the United States." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 10 (2018): 38–47. http://dx.doi.org/10.1177/0361198118781183.

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The physical and operational characteristics of large trucks distinguish them from other types of vehicles in terms of facility design needs and safety requirements. A critical node in the surface transportation network is the highway-rail grade crossing (HRGC) because it represents a conflict point between different modes of transportation. The focus of this research was to identify factors related to different injury severity levels of truck/truck-trailer drivers in crashes reported at HRGCs. This study utilized a mixed logit model to investigate injury severity of those drivers and relied on 2007–2014 Federal Railroad Administration (FRA) crash and inventory data involving trucks/truck-trailers. Results showed that truck/truck-trailer drivers’ injuries in crashes reported at HRGCs were positively associated with train speed, when train struck the road user (truck/truck-trailer), when the driver “went around crossing gates”, older drivers, crashes reported in rural areas, and crashes at crossings with a minimum crossing angle of 60–90 degrees. Presence of crossbucks, gates, track obstructions, and HRGCs located within 500 feet of a highway were associated with relatively less severe driver injuries. The paper provides recommendations for safety improvements at HRGCs and recommendations for future research.

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Kallberg, Veli-Pekka, Matti Anila, Kirsi Pajunen, Mikko Kallio, and Jouni Hytönen. "Assessment and Improvement of Safety at Finnish Railway–Road Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 1801, no. 1 (2002): 54–60. http://dx.doi.org/10.3141/1801-07.

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Hsu, Chung-Jen, and Elizabeth G. Jones. "Transmission Range Evaluations for Connected Vehicles at Highway-Rail Grade Crossings." Designs 1, no. 1 (2017): 2. http://dx.doi.org/10.3390/designs1010002.

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41

Yeh, Michelle, and Jordan Multer. "Traffic Control Devices and Barrier Systems at Grade Crossings: Literature Review." Transportation Research Record: Journal of the Transportation Research Board 2030, no. 1 (2007): 69–75. http://dx.doi.org/10.3141/2030-10.

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Sharma, Soumya, and Srinivas S. Pulugurtha. "Modeling Crash Risk at Rail-Highway Grade Crossings by Track Class." Journal of Transportation Technologies 09, no. 03 (2019): 261–75. http://dx.doi.org/10.4236/jtts.2019.93016.

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Saunders, William J., Saleh R. Mousa, and Julius Codjoe. "Market basket analysis of safety at active highway-railroad grade crossings." Journal of Safety Research 71 (December 2019): 125–37. http://dx.doi.org/10.1016/j.jsr.2019.09.002.

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Saccomanno, Frank F., Peter Young-Jin Park, and Liping Fu. "Estimating countermeasure effects for reducing collisions at highway–railway grade crossings." Accident Analysis & Prevention 39, no. 2 (2007): 406–16. http://dx.doi.org/10.1016/j.aap.2006.08.016.

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Fan, Wei, Linfeng Gong, Edward Matt Washing, Miao Yu, and Elias Haile. "Key factors contributing to crash severity at highway-rail grade crossings." Journal of Modern Transportation 24, no. 3 (2016): 224–35. http://dx.doi.org/10.1007/s40534-016-0110-x.

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Linja, Anne, Pasi Lautala, David Nelson, and Elizabeth S. Veinott. "Rail Safety: Examining the Effect of Driving Experience and Type of Crossing on Safety Concerns." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (2020): 1461–65. http://dx.doi.org/10.1177/1071181320641348.

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Vehicle-train collisions at Highway-Rail Grade Crossings continue to be a safety concern and despite improvements in warnings, many of these incidents are attributed to human error. In some cases, distractions other than railroad traffic, such as nearby highway intersections, may create additional burdens for drivers’ decision making. In this study, we systematically examined safety concerns across two types of Highway-Rail Grade Crossings: non-short storage and short-storage. In a controlled experiment, 48 college-aged drivers viewed a series of driving scene images and identified, rated, and explained up to five safety concerns in each image. Participants reported more safety concerns and higher average severity of those concerns for short-storage rail crossings than non-short storage, but these findings did not depend on rural vs. urban driving experience. Content analysis of the 1,230 safety concerns using chi-squared analysis revealed differences in attention to dynamic safety concerns by rail crossing type, but not to static concerns.

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Kavoosi, Masoud, Maxim A. Dulebenets, Junayed Pasha, et al. "Development of Algorithms for Effective Resource Allocation among Highway–Rail Grade Crossings: A Case Study for the State of Florida." Energies 13, no. 6 (2020): 1419. http://dx.doi.org/10.3390/en13061419.

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Smart cities directly rely on a variety of elements, including water, gas, electricity, buildings, services, transportation networks, and others. Lack of properly designed transportation networks may cause different economic and safety concerns. Highway–rail grade crossings are known to be a hazardous point in the transportation network, considering a remarkable number of accidents recorded annually between highway users and trains, and even solely between highway users at highway–rail grade crossings. Hence, safety improvement at highway–rail grade crossings is a challenging issue for smart city authorities, given limitations in monetary resources. In this study, two optimization models are developed for resource allocation among highway–rail grade crossings to minimize the overall hazard and the overall hazard severity, taking into account the available budget limitations. The optimization models are solved by CPLEX to the global optimality. Moreover, some heuristic algorithms are proposed as well. A case study focusing on the public highway–rail grade crossings in the State of Florida is performed to evaluate the effectiveness of the developed optimization models and the solution methodologies. In terms of the computational time, all the solution approaches are found to be effective decision support tools from the practical standpoint. Moreover, the results demonstrate that some of the developed heuristic algorithms can provide near-optimal solutions. Therefore, the smart city authorities can utilize the proposed heuristics as decision support tools for effective resource allocation among highway–rail grade crossings.

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Liu, Huiyuan, Myungwoo Lee, and Aemal J. Khattak. "Updating Annual Average Daily Traffic Estimates at Highway-Rail Grade Crossings with Geographically Weighted Poisson Regression." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 10 (2019): 105–17. http://dx.doi.org/10.1177/0361198119844976.

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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.

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Wang, Xu, Jiangchen Li, Can Zhang, and Tony Z. Qiu. "Active Warning System for Highway-Rail Grade Crossings Using Connected Vehicle Technologies." Journal of Advanced Transportation 2019 (February 11, 2019): 1–11. http://dx.doi.org/10.1155/2019/3219387.

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Highway-rail grade crossing (HRGC) collisions are a significant safety concern around the world. HRGC collisions have a high risk of injuries and fatalities. To mitigate that risk, safety countermeasures for both active and passive HRGCs have been implemented. Leveraging the latest developments in connected vehicle (CV) technologies, CV-based warning systems perform well in safety applications for roadway networks. However, few have been developed to focus on safety improvements specifically for HRGCs. To bridge this gap, this paper proposes a novel active warning system that was created with readily available CV technologies and devices. A crossing risk assessment model was developed and evaluated in simulation and field applications. The proposed model predicts the crossing risk probabilities in the near future. When road users are in great risk of a collision, the warning system sends out auditory and visual alerts and displays the estimated waiting time. The test results reveal that the proposed warning system is promising for field implementation to improve safety at grade crossings.

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Khattak, Aemal J. "Reducing Undesirable Actions of Motor Vehicle Drivers at Railroad–Highway Grade Crossings." Transportation Research Record: Journal of the Transportation Research Board 2030, no. 1 (2007): 54–58. http://dx.doi.org/10.3141/2030-08.

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