YouTube Research Spotlight: Research to Improve At-Grade Rail Crossing Safety

The UMTC Research Section Launches a Research Spotlight YouTube Channel. We are showcasing research currently being conducted on “At-Grade Rail Crossing Safety” by Radhameris Gomez.  Ms. Gomez is a PhD candidate in the UMass Transportation Engineering Program at the University of Massachusetts, Amherst. View the overview video (3 minutes) or the extended video (10 minutes) to find out how she became interested in studying transportation engineering.

TrailCrashes at roadway-railroad intersections happen far too often. Federal Railroad Administration data show that 2,025 such crashes occurred in the United States in 2016, resulting in 265 fatalities and 798 injuries. There have been a number of roadway-rail intersection crashes recently. For example, in Florida, an Amtrak train collision with a car left one person dead; in Arkansas, one person was killed and another injured when their car crossed into a train’s path; and in North Carolina, a train crashed into a car that stopped on the railroad tracks when the safety arms came down, and the car driver was killed. Earlier in March, a freight train collided with a charter bus in Mississippi that had become stuck on a rail crossing with low clearance on the crest of a slope. Four people were killed and others injured; it was the 161st crash since 1976 at that crossing. After a March snowstorm, a local DPW worker in Longmeadow, Massachusetts, died when his snowplow backed onto railroad tracks when a train was coming. At that intersection, there are no gate arms or traffic signals to help warn drivers when a train would be coming; there had been five other crashes and four other deaths at that location since the 1970s.

Previous studies have examined primary contributing factors for grade-crossing train-car crashes and how these crashes can be prevented. Jeff Caird and colleagues at the University of Calgary analyzed over 300 grade-crossing crashes in Canada (2002). They estimated that adding flashing lights to a rail crossing without them has the potential to reduce crashes by over 60 percent, as compared to crossbucks alone. Michael Lenné and colleagues at Monash University in Australia conducted a driving simulator study (2010) on driving behavior at three different types of at-grade rail crossings: stop-controlled, with flashing lights, and with a traffic signal. The researchers found that participants slowed their vehicles the most when approaching rail crossings with flashing lights.

By: Tracy Zafian, UMTC Research Fellow

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Pre-signals for Transit Priority

Transit preferential treatments can reduce transit delay and therefore improve the efficiency and reliability of transit systems. Examples include dedicated bus lanes, queue jump lanes, and transit signal priority. However, these treatments are not always feasible due to lack of funding or space. In addition, they can often have detrimental impacts on other users of the system. Sustainability goals that are set by a lot of planning and transit agencies demand solutions that more efficiently utilize existing infrastructure and capacity while providing priority to transit vehicles.

Pre-signals allow for provision of priority to buses traveling on dedicated bus lanes by taking advantage of existing infrastructure and utilizing intersection capacity more efficiently. Pre-signals are additional signals placed upstream of signalized intersections to facilitate provision of some level of priority to buses, as well as other modes, by allowing them to bypass standing queues of cars. Typically, operating pre-signals require the existence of at least two lanes in the direction of travel.

However, recent work has suggested that pre-signals can aid in the temporary utilization of contra-flow lanes for transit priority provision for single lane approaches [1]. In particular, pre-signals are used upstream of the main intersection signals to allow the bus to jump the car queues and be at the front of the queue at the main signal. Pre-signals are used in combination with dedicated bus lanes when there is a need to end the bus lane in advance to allow cars to discharge from the intersection using all lanes. For example, as seen in Figure 1 the dedicated bus lane ends at some distance upstream of the intersection to allow cars to use all three lanes while discharging from the intersection.

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Figure 1. Pre-signal at a three-lane approach with a dedicated bus lane.

The pre-signal works as a regular signal and is coordinated with the main signal to utilize maximum capacity. While the main signal is red, cars receive a red light at the pre-signal and are queued upstream of it. This ensures that a bus arriving during the red period can move to the stop line at the main signal and discharge immediately when the main signal turns green. Cars receive a green pre-signal such that no gaps are created in the traffic stream, and no green time at the main signal is lost when buses are not present. Regardless of the main signal’s phase, a bus approaching the intersection will trigger the pre-signal to turn red for cars, allowing the bus to move to the main signal without encountering conflicting maneuvers from cars.

An example of real-world pre-signal operations can be seen in this video. The video presents the operation of a pre-signal along Langstrasse in Zurich, Switzerland. A dedicated bus lane and one lane for cars exist upstream of the intersection but merge into a single mixed-use lane just upstream of the signalized intersection. A pre-signal at the location of the merge provides priority to buses when approaching the main signal. The pre-signal turns red when the bus is detected approaching the intersection. As a result, the bus travelling on the bus lane can bypass the queue of cars and enter the mixed-use lane at the intersection before the cars arrive. As soon as the bus bypasses the standing queue of cars, the pre-signal turns green again so that cars can proceed through the intersection after the bus.

The concept of pre-signals was first introduced to address lost time due to acceleration and perception/reaction time at the onset of green at signalized intersections and the first pre-signals were installed in Dusseldorf, Germany in 1954 [2]. This first study found that if there are only cars in a traffic stream, the equivalent of approximately 4 seconds of additional green time can be gained at intersections with the use of this type of pre-signal. More recent work has explored the use of pre-signals to increase intersection capacity by resolving various types of vehicular conflicts (e.g., between left and through moving vehicles that are either conflicting or compete for green time at the main signal) that would otherwise occur at the signalized intersection downstream [3,4]. A theoretical analysis of pre-signals for transit priority was first presented by Wu and Hounsell [5]. However, their proposed implementation included a constant pre-signal operation regardless of the arrival of a bus. To the best of our knowledge, real-world implementations of pre-signals are limited. A few locations are known in London, operating in a fashion similar to the one described in [5] and one location has been noted in Zurich, Switzerland.

We are currently working on identifying domains of application for implementation of individual transit preferential treatments or combinations of those for a variety of operating conditions for traffic and transit. Click here for a relevant presentation. 

By: Eleni Christofa, Ph.D., Assistant Professor, UMass Amherst and S. Ilgin Guler, Ph.D., Assistant Professor, The Pennsylvania State University 

[1] Guler, S.I., Gayah, V.V. and Menendez, M., 2016. Bus priority at signalized intersections with single-lane approaches: A novel pre-signal strategy. Transportation Research Part C: Emerging Technologies63, pp.51-70.

[2] Von Stein, W., 1961. Traffic flow with pre-signals and the signal funnel. Theory of Traffic Flow, Elsevier, Amsterdam.

[3] Xuan, Y., Gayah, V., Cassidy, M. and Daganzo, C., 2012. Presignal Used to Increase Bus-and Car-Carrying Capacity at Intersections: Theory and Experiment. Transportation Research Record: Journal of the Transportation Research Board, (2315), pp.191-196.

[4] Xuan, Y., Daganzo, C.F. and Cassidy, M.J., 2011. Increasing the capacity of signalized intersections with separate left turn phases. Transportation Research Part B: Methodological45(5), pp.769-781.

[5] Wu, J. and Hounsell, N., 1998. Bus priority using pre-signals. Transportation Research Part A: Policy and Practice32(8), pp.563-583.

 

T-Force Toolkit : Increasing Truck and Bus Traffic Enforcement

For a variety of reasons, routine traffic stops with large trucks and buses occur significantly less than traffic stops with passenger vehicles. Considering the detrimental effects of these crashes, it is critical that we incorporate truck/bus traffic enforcement into existing highway safety activities.

With this growing issue in mind, the University of Massachusetts Traffic Safety Research Program (UMassSafe) developed T-Force, Truck and Bus Traffic Enforcement Toolkit, providing a free one stop shopping tool for resources geared toward traffic patrol officers. T-Force is a three-part program with a goal of increasing the enforcement of moving violations such as speeding and lane violations. Different than programs aiming to inform specialized Motor Carrier Safety Assistance Program (MCSAP) officers, this information is intended for a wider audience, particularly officers conducting regular traffic enforcement.

The T-Force Toolkit is comprised of three main sections; including Fast Facts, Instructors Portal and Web Resources.

  • Fast Facts: This section of the Toolkit offers detailed information regarding the importance of traffic stops with trucks/buses, strategies for maintaining officer safety, how truck/bus traffic stops are different than those with passenger cars, the process of conducting an effective traffic stop and the details involved in CDL. Users can move quickly through this interactive tool, accessing only the information they need.
  • Instructors Portal: This section provides access to all of the materials needed to conduct the Safe and Effective Traffic Stops: Truck and Bus Traffic Enforcement training. This training, developed by UMassSafe, is currently being taught in several states across the country for local and state traffic patrol officers. Instructors can access all course materials on the website, including a guide for both instructors and participants as well as the PowerPoint presentation.
  • Web Resources: The web resources section provides access to an online library of videos, a discussion board to ask and answer questions, and links to other trainings and online resources.

For additional information  www.tforcetoolkit.com.

UMassSafe is a multidisciplinary traffic safety research group housed in the UMass Transportation Center at the University of Massachusetts. With the unique ability to examine highway safety from a variety of perspectives, UMassSafe provide tools and information in a format that is practical for a wide range of users from law enforcement personnel to statisticians at federal agencies. Working on issues related to commercial motor vehicle safety for over 15 years, UMassSafe has developed data query tools, crash corridor maps, and police training as well as conducted extensive crash data analysis and data quality improvement projects.

By: Robin Riessman and Jennifer Gazzillo, UMassSafe

UMass Researchers Crowdsource Data to Provide Travel Information

Dr. Lance Fiondella gave a talk on “Software Tools to Support Transportation Network Performance and Vulnerability Analysis.”  He highlighted his recent research, working closely with Venkateswaran Shekar, a PhD student, on developing a Smartphone Application that will be able to capture individual geographical coordinates to better understand individual travel behavior. The crowdsourced coordinates are uploaded every 3 seconds which allows the researchers to capture the travel path and time, and then calculate speed of an individual walking, biking or driving. There is also a feature that allows voluntary input of demographic data which will allow for more sophisticated data analysis on travel patterns across key demographics. Researchers are also looking into developing additional features such as allowing the user to call for help and the App will provide geographical coordinates.

Dr. Fiondella is an Assistant Professor at the University of Massachusetts Dartmouth in the Electrical and Computer Science Department. Check out the presentation here. Learn more about Dr. Fiondella here.

By: Melissa Paciulli