Autonomous Vehicle Research: MassDOT Leads the Way

More U.S. states are considering legislation and regulations for highly automated vehicles (HAVs) testing. Twenty-four states and the District of Columbia have now enacted legislation regarding the testing of highly autonomous vehicles. Only Michigan currently allows the driverless HAVs on public roads; California is considering the same but has not approved it yet.

The federal policy (Federal Automated Vehicles Policy) provides guidance for those developing, testing, and deploying highly automated vehicles. The policy considers current and potential regulatory tools that could be used with these vehicles. The policy also describes the different responsibilities on the federal and state levels, and creates a model for state policy that recommends policy areas for states to consider for automated vehicles.

Figure 1: States with Enacted Legislation for Autonomous Vehicles

IOpicAs of July 27, 2017. Source: National Conference of State Legislatures. http://www.ncsl.org/research/transportation/autonomous-vehicles-self-driving-vehicles-enacted-legislation.aspx

In October 2016, Massachusetts Gov. Charlie Baker signed Executive Order No. 572, To Promote the Testing and Deployment of Highly Automated Driving Technologies (EO 572). EO 572 created a state government working group on autonomous vehicles (AV Working Group). The group’s charge is to “convene and consult with experts on motor vehicle safety and vehicle automation…and [to] work with the Legislature on any proposed legislation necessary to protect the public welfare.” The AV Working Group is led by Katherine Fichter, Massachusetts Department of Transportation (MassDOT) Assistant Secretary for Policy Coordination and Transportation Secretary Stephanie Pollack’s designee to the group. The AV Working Group also includes other MassDOT staff and representatives from the State Police, the Executive Office of Public Safety and Security, Housing and Economic Development, and the State Legislature.

One Center, at the UMass Transportation Center, has recently contracted with UMTC Research Affiliates, at UMass Lowell, to conduct research on the technological developments, regulatory requirements, funding opportunities, and potential benefits of the emerging AV technology to take appropriate actions for the benefit of the citizens of the Commonwealth. The affiliates associated with this research are Chronis Stamatiadis, Nathan Gartner, Yuanchang Xie, and Danjue Chen. This project will provide baseline information pertaining to strategic planning for connected vehicle (CV) technologies. This information will be used by MassDOT to develop a strategic plan for the development and deployment of connected vehicle technology and infrastructure in Massachusetts.

EO 572 authorized MassDOT, with input from the AV Working Group and other technical experts, to develop and issue guidance for testing highly automated vehicles on public roadways in Massachusetts, and includes a process for companies to obtain approval for such testing.

Highly automated vehicle testing on public roadways is under the authority of MassDOT. Presently in Massachusetts, most testing takes place in spaces and courses outside of MassDOT’s jurisdiction, such as universities, private indoor testing facilities, and the former Fort Devens military base.

As described by Boston National Public Radio station WBUR, nuTonomy, a Massachusetts Institute of Technology (MIT) spinoff company, began the first testing of highly automated cars on Boston roads in January 2017. The initial testing area was limited to a 191-acre industrial park in South Boston, the Raymond L. Flynn Marine Park, which has a simple road layout, no traffic signals, and only 3 miles of roadway. At first, testing was approved only for daylight hours and good weather, but then was expanded to nighttime and inclement weather. The company has now logged over 200 miles of automated vehicle driving in the industrial park, with no crashes or incidences. With these results, in April 2017, nuTonomy was granted approval to expand its HAV testing to the Seaport and Fort Point areas. A Boston Globe article discussed this approval and interviewed City of Boston and nuTonomy staff. The Seaport roadways are considerably more complex than the testing roads so far, including more complicated intersections, traffic signals, roadways with multiple lanes, bridges, and a rotary. As before, nuTonomy’s testing in the expanded area initially was for daylight hours and good weather only.

In June 2017, MassDOT granted permission for a second MIT-spinoff company, Optimus Ride, to test highly automated vehicles on Boston roads. As described in a Boston Globe article, Optimus Ride will initially test its vehicles only in the Raymond L. Flynn Marine Park, as nuTonomy did.

During their HAV roadway testing, nuTonomy and Optimus Ride both have a human operator sitting in the driver’s seat, ready to take over control of the vehicle if needed. This is currently standard for most on-road testing of HAVs. Some companies use two human workers, one in the driver seat and one in the front passenger seat, to help sustain vigilance and monitoring of the HAV’s driving and the ability to switch to manual driving mode if ever needed. As described in its road test application to MassDOT, after 200 miles of testing, Optimus Ride may request MassDOT permission to test its vehicles with passengers.

In terms of legislation and regulations for automated vehicles (AVs), in her keynote talk at a recent conference on Autonomous and Connected Vehicles held at Worcester Polytechnic Institute, Ms. Fichter indicated that Gov. Baker and MassDOT have taken the position that it is better not to regulate AVs through legislation. AV and HAV technologies are still evolving, and legislation can be difficult to modify once passed. In the Massachusetts Legislature, there are currently eight bills that have been filed related to AVs. On July 13, 2017, the AV Working Group held a legislative meeting to discuss them and hear more about them from their proponents. The MassRobotics Consortium has posted its notes from the meeting. Most of the bills include guidance for AV safety and for liability in the event of a crash involving an AV, with no liability assigned to the original manufacturer of a vehicle that has been later converted to an AV. Joint bills S. 1945/H. 1829 also request that all AVs be zero emission vehicles (ZEVs), encourage AVs to be for public transit only in areas with dense populations, provide guidance for AV data collection, and propose having a vehicle-miles-traveled (VMT) tax on AVs. The idea of a VMT-based tax raised questions and issues at the meeting, related to such issues as geographic equity, fuel consumption and encouraging efficient vehicles, and collection of vehicle owners’ travel data, as well as the need for additional revenues as more vehicles are converted to AVs and electric vehicles.

Among the other proposed AV legislation, H. 2742 requires that AVs used for the interstate transport of goods or for transporting eight or more people be required to have a human operator present who can intervene if needed. Bills S. 1938 and H. 3422 both focus on making AVs that do not require a human operator available to the public. Bills H. 1822 and H. 1897 each request that MassDOT submit a report to the state House and Senate leaders “recommending additional legislative or regulatory action that may be required for the safe testing and operation of motor vehicles equipped with autonomous technology.” H. 1897 requests such a report by June 2017, while H. 1822 requests it by March 2019.

At the end of the July AV Working Group meeting, Ms. Fichter recommended the next meeting would be in September 2017. At this meeting, people from the AV industry will present and provide their perspectives regarding AVs and HAV regulation, and how AV technologies will come to market.

 

 

 

Written by: Tracy Zafian, UMTC Research Fellow

 

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UMTC Affiliates & MassDOT Assistant Secretary Katherine Fichter Present at WPI Conference on Vehicle Automation

 

In May 2017, Worcester Polytechnic Institute (WPI) held its second annual Connected and Autonomous Vehicles Summer School speaker series, sponsored by the Institute of Electrical and Electronics Engineers Vehicular Technology Society (IEEE VTS). The event included two days of lectures and discussions.

CAV intersection
Photo source: U.S. Department of Transportation
  • Danjue Chen, Professor at UMass-Lowell and UMTC Affiliate, discussed the impacts of connected and automated vehicles (CAVs) on traffic operations and highway traffic flow, and how CAVs can help optimize roadway capacity and traffic control. Professor Chen is the featured researcher in this month’s Innovative Outlook (IO).
  • Hossein Pishro-Nik, Professor at UMass-Amherst and UMTC Affiliate, spoke about Vehicular Ad Hoc Networks (VANETs) for vehicle-to-vehicle and vehicle-roadway infrastructure communications. His talk discussed the relationship between communications and safety in VANETs, how VANETs can be customized for different traffic conditions and individual drivers, and the issues of privacy in VANETs and Internet-connected devices and applications. Professor Pishro-Nik’s research is described in more detail in another post.
  • Jason Rife, Professor at Tufts University, presented information on different GPS-based technologies and applications that can assist with automated vehicles and navigation, even in dense urban areas with limited sky visibility.
  • Bob Sletten, Engineering Manager at Autoliv, a company that develops automotive safety systems for auto manufacturers, spoke about radar technology in automotive applications.
  • Akshay Rajhans, Senior Research Scientist at MathWorks, spoke about model-based design for connected autonomous vehicles. As described in the WPI conference program, “model-based design makes use of computational models of systems under design that are developed, optimized and checked after correctness specifications throughout the design cycle.”
  • Alexander Wyglinski, WPI Professor and organizer of the conference, provided an overview of vehicular communication systems and the fundamental concepts for understanding, designing, and implementing them.

The keynote speaker at the gathering was Katherine Fichter, Assistant Secretary for Policy Coordination at MassDOT. Ms. Fichter discussed the potential future impacts of driverless vehicles under different scenarios, including a Driverless Utopia and a Driverless Nightmare that were described in Driving Towards Driverless Cars, a blog by Lauren Isaac. Under these scenarios, autonomous vehicles are expected to improve roadway safety, increase vehicle miles traveled, and reduce greenhouse gas emissions, but there are other potential impacts that are less certain. For example, will more driverless cars reduce urban sprawl or increase it, and how will the mobility of low-income people be impacted? As Ms. Fichter discussed, there are questions as well about how autonomous vehicles will be regulated and insured. One big challenge is that current regulations are all based on the idea that vehicles have human operators; this will need to change.

Written by Tracy Zafian, UMTC Research Fellow.

Customizing Your Self-Driving Car

In the future, intelligent transportation systems (ITSs) will involve connected vehicles, including driver-assisted vehicles and self-driving cars, as well as on-board mobile devices, sensors, and the software and algorithms that govern the functioning of these devices and their communications. Despite recent improvements, each year tens of thousands of lives are lost and billions of dollars are wasted because of traffic inefficiencies in the United States alone. Improvements in the transportation systems could have an enormous impact on lowering these statistics.

In this research, we aim to establish a new approach in design of safety systems, which is based on the individualization and customization of these systems to specific drivers and their environments. This means that wireless communication protocols, as well as algorithms that communicate to users, can be designed in an intelligent way in order to take advantage of all the statistical data that is available regarding the driver and his/her environment.

To accomplish this objective, we can use the technology to collect driver performance data and subsequently learn driver characteristics and driving strategies. This information, along with data collected from other vehicles and roadside units, can be used to customize the technology to each driver. With this, it is possible to adapt warnings or automatic control strategies to each driver. Meanwhile, vehicle-to-vehicle (V2V) communication can be dynamically tuned to make efficient use of finite bandwidth and guarantee the transmission of information critical to safety.

In this way, we should consider that there is an uncertainty of the message delivery between two specific vehicles, while other vehicles might also transmit simultaneously. Our research shows that by proper adaptation of wireless communication and warning algorithms, we can potentially reduce accident fatalities by a considerable amount.

To understand the benefit of V2V communication, consider a traffic stream where a chain of vehicles moves with same speed. When the first vehicle in the chain brakes, the driver of the following vehicle applies the brake after her perception reaction time (PRT). If no intervehicle communications are employed, vehicle Vi applies the brake after the sum of PRTs up to the driver i. With the communications, this time will change to the communications delay plus PRTs of the driver i. This is shown in Figure 1.

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Figure 1. Communications delay versus sum of PRTs, illustrating the time before a driver in a chain applies the brake

Some drivers may think that some of the received warning messages are not needed, because the drivers are aware of their own response time empirically and they know that they can react to stimuli fast. These warning messages are false alarms for these drivers. These warning messages may frustrate the drivers with an overly high number of false alarms, causing them to ignore warnings or even disable the system. To address this issue, we propose estimating the PRT of drivers and personalizing warning messages based on individual PRTs. Figure 2 shows that at the same accident probability for each driver, the false alarm rate can be reduced by at least 30% by employing the estimated individual distribution instead of the population distribution. Thus, it is of vital importance to minimize false alarms so that the system sends warnings only when they are needed.

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Figure 2. False alarm rate versus the probability of accident based on using average response time or individual

Now, we should determine how channel access probabilities of vehicles and vehicular communications can be adapted to drivers’ characteristics. In a network of vehicles, each vehicle transmits with a specific probability in the transmission medium. Large channel access probabilities lead the system to excessive interferences and, consequently, low probability of packets being successfully received (success probability), while very small values reduce the success probabilities since the probability of the favorite transmission is low itself. Therefore, there is an optimal value, given both the physical data obtained by vehicular networks and the communications protocol requirements, which results in lower collision probability of vehicles. We can find the expression of packet success probability in a network of vehicles based on channel access probability of vehicle.

We then use a recursive algorithm to tune the transmission probability of each vehicle based on the individual characteristics of drivers. The PRT of the driver, traffic conditions, and communications delay are three factors that play roles in assigning channel access probabilities to vehicles. In simple terms, we categorize the drivers into safe and unsafe drivers based on perception-reaction time. The unsafe vehicles are the ones whose drivers have long perception-reaction time and low distance to the vehicle in front. In other words, unsafe vehicles have higher collision probability. Then we assign different channel access probabilities to unsafe and safe vehicles respectively.

Figure 3(a) illustrates the collision probabilities when channel access probabilities are assumed to be equal for all vehicles. Figure 3(b) shows the scenario in which different channel access probabilities are assigned to unsafe and safe vehicles. The minimum collision probability in the second scenario improves by 25%.

Hossein_Fig3a
Figure 3(a). Collision probabilities when channel access probabilities are equal for all vehicles
Hossein_Fig3b
Figure 3(b). Different channel access probabilities are assigned to unsafe and safe vehicles.

Our simulation results confirm that unsafe vehicles need to inform other vehicles of their perilous situation more frequently than do safer vehicles. In other words, with higher channel access probability for unsafe vehicles, we can achieve lower collision probabilities.

Written by Hossein Pishro-Nik, UMTC Research Affiliate and Associate Professor in the Department of Electrical and Computer Engineering (ECE) at UMass-Amherst. This research was supported by the National Science Foundation under Grant CCF– 0844725 (PI: Hossein Pishro-Nik). It is a joint work with ECE PhD students Mohammad Nekoui, Ali Rakhshan, and Mohammad Kohsravi, and Professor Daiheng Ni from the UMass-Amherst Department of Civil and Environmental Engineering. For more information and access to published papers, please visit http://www.ecs.umass.edu/ece/pishro/publications.html.

GM Rolling Out AV Fleet

General Motors Company (GM) announced in mid-June that it completed production of 130 self-driving Chevrolet Bolt electric vehicles for testing automated vehicle (AV) technologies on-road. These highly automated vehicles (HAVs) join GM’s more than 50 Chevrolet Bolts with AV technologies already operating on public roads in San Francisco, Detroit, and Scottsdale, Arizona. In April 2017, Spectrum, the flagship magazine for the Institute of Electrical and Electronics Engineers (IEEE), reported on GM plans to have as many as 300 more self-driving vehicles on-road, presumably including the recently completed 130 vehicles. According to Spectrum, GM would then have the largest HAV fleet on-road not only in the United States, but worldwide. Google-based Waymo has the second-largest AV fleet in the United States, with an estimated 160 vehicles on-road.

GM CEO & Chairman Mary Barra with a new Chevrolet Bolt AV (Photo by Paul Sancya, Associated Press)

In GM’s announcement regarding the 130 new self-driving Bolts, GM Chairman and CEO Mary Barra is quoted: “This production milestone brings us one step closer to making our vision of personal mobility a reality …. Expansion of our real-world test fleet will help ensure that our self-driving vehicles meet the same strict standards for safety and quality that we build into all of our vehicles.” CEO Barra has also said that “no other company today has the unique and necessary combination of technology, engineering and manufacturing ability to build autonomous vehicles at scale.”

The new self-driving version of the Chevrolet Bolt is the second generation of GM’s AVs and is capable of handling almost any roadway situation without human driver intervention. The new Bolts are equipped with the latest technologies in cameras, radar (LiDAR), sensors, and related hardware. “There are even a couple of cameras that are dedicated just to seeing traffic lights to make sure you don’t run red lights,” said Kyle Vogt, CEO of Cruise Automation, a self-driving software company that GM acquired in 2016. The GM HAVs always have an employee in the driver’s seat for safety reasons, just in case any intervention is needed. Almost all states with HAV regulations also have the requirement that a human operator be present.

In 2016, GM also partnered with and invested $500 million in ride-sharing company Lyft. In a recent Forbes article, Cruise CEO Vogt wouldn’t confirm a Reuters report that “thousands” of self-driving Chevrolet Bolt hatchbacks will go into service for ride-hailing company Lyft in 2018, but said it wouldn’t be surprising. “We’ve had a plan in place for a while and it’s going according to schedule. From what I can tell it’s much faster and going to happen much sooner than most people in the industry think,” Vogt said. “We’re planning to deploy in a rideshare environment, and very quickly.”

Written by Tracy Zafian, UMTC Research Fellow. 

Safety First! Are You a Distracted Driver or a Distracted Pedestrian?

The annual number of pedestrians hit and killed by vehicles in the United States is now at its highest level in more than 20 years. In March 2017, the Governors Highway Safety Association (GHSA) released a report showing an 11 percent increase rise in the number of pedestrian deaths between 2015 and 2016, and a 25 percent increase in these deaths over the past five years. The report estimates here were almost 6,000 pedestrian fatalities in 2016 and pedestrias now account for 15 percent of all traffic deaths. The rise in pedestrian fatalities from 2015 to 2016 was the highest annual increase in both the total number and percentage growth in the 40 years that these national data have been recorded.

The GHSA figurpedses are calculated based on pedestrian fatalities for January to June 2016 and then extrapolated for the rest of the year. For this six-month period, 2,660 pedestrians died in traffic crashes nationwide. Four states accounted for 43 percent of these fatalities: California (405 pedestrian deaths); Florida (277); Texas (242); and NewYork (137). Massachusetts had 38 pedestrian deaths in this time frame( 1.4 percent of the total).

Source: Seattle Times

The GHSA identified several factors that could be contributing to the rise in pedestrian deaths, including the following.

  • More driving. People are driving more now, with the economy improving and gas prices down from their historic high levels ($4+/gallon) earlier this decade. Federal Highway Administration data released in February 2017 show that in 2016, people in cars, minivans, SUVs, and trucks drove a record 3.22 trillion miles on the nation’s roads and highways. This is an increase of 3 percent over 2015, and the fifth straight year of increased total mileage.
  • Alcohol. According to the GHSA report, 15 percent of pedestrian taffic deaths involve a drunk driver, and 34 percent of the pedestrians killed in traffic accidents themselves have blood alcohol levels above the legal limit of 0.08.
  • Lack of pedestrian visibility. Many of the pedestrian fatalities occurred in conditions where the pedestrians may not be very visible to drivers. The GHSA found that 74 percent of pedestrian deaths occurred at night, and 72 percent of those killed were not at a roadway intersection.
  • In recent years, as cell phones and other portable communication and entertainment devices have become more ubiquitous, there has been an increase in crashes and injuries attributed to distraction. Drive distraction is considered one of the top three causes of traffic fatalities in general—the other top causes are alcohol and vehicle speed—and one of three main causes for pedestrian fatalities. The National Highway Transportation Safety Administration (NHTSA) found that driver distraction contributed to 3,477 traffic crash-related deaths and 391,000 injuries in 2015. As discussed in a recent National Public Radio piece, there are also concerns about the impact of pedestrians’ own distractions on pedestrian safety

A comprehensive research literature review on the impact of electronic device use on pedestrian safety was conducted by Robert Scopatz and Yuying Zhou (2016). The literature review was part of a larger research project examining whether electronic device use by drivers and pedestrians significantly affects pedestrian safety. The literature review included sections on distracted pedestrians, distracted drivers, and pedestrian-driver interactions, and examined real-world studies, simulator studies, and other collected data in these three areas. There have been no studies thus far showing a direct cause-and-effect link between distraction and pedestrian crash risk. Nonetheless, there is clear evidence that distracted drivers face increased crash risks and that distraction impacts how pedestrians walk, react, and behave, including safety-related behaviors

Scopatz and Zhou found only one study (Brumfield and Pulugurtha, 2011) to date that examined pedestrian-vehicle conflicts and the role of distraction due to handheld electronic device use. That study’s researchers observed 325 pedestrian-vehicle interactions at seven midblock crosswalks on a university campus in Charlotte, North Carolina. They found that 29 percent of pedestrians and 18 percent of drivers were noticeably distracted (talking on a cell phone or texting) at the time the pedestrian and vehicle were nearing the crosswalk. Further, the researchers calculated that distracted drivers were more than three times more likely to be involved in a conflict at the midblock crosswalks than distracted pedestrians. Government legislators in Montreal, Quebec, and New Jersey have proposed banning cell phone texting for pedestrians while they are crossing the street. These proposals have not received much support thus far.

Research is needed to dig deeper into the issues around pedestrian fatalities with specific focus on distraction.

Some key questions remain:

  • How distractions (for drivers and pedestrians) exacerbated by hazards that are already present?
  • With the encouragement of Bicycling and Pedestrian activity for healthy communities, how will this impact the grown problem?
  • What type of solutions are States considering for solutions? One recent report published in March of 2017,  Consensus Recommendations for Pedestrian Injury Surveillance aims to offer guidance in tracking, recording and prevention.

By: Tracy Zafian, UMTC Research Fellow with input from Affiliate Researcher, Karin Goins from UMass Medical

 

Are Pedestrian Fatalities Related to Income and Race?

Pedestrian fatalities in the United States rose by 25 percent over the past 5 years, according to a 2017 report by the Governors Highway Safety Association (GHSA). As pedestrian fatalities have increased, some populations are more at risk than others.

Dangerous by Design 2016, an analysis by Smart Growth America (SGA) of pedestrian fatalities over a 10-year period (2005–2014), looked at data from the 104 largest metro areas in the United States and for each state, by income and by race. This analysis found that the poorer a metro area is, the more likely that pedestrians are to be hit and killed by a motor vehicle. There are a number of contributing factors to this finding. For one, poorer communities and neighborhoods typically have less road infrastructure to support pedestrian safety than more affluent places, including fewer safe, well-maintained sidewalks with adequate night lighting, fewer safe mid-block and intersection crosswalks, and fewer traffic calming measures such as narrow roads and speed humps. Additionally, residents in poorer communities and neighborhoods, especially in urban areas, have lower levels of car ownership and more dependence on walking and transit. This leads them to walk more frequently and makes them more likely to walk to destinations that are not considered pedestrian friendly, such as big shopping centers and along high traffic volume roadways with little pedestrian infrastructure.

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Source: Transportation for America.

SGA’s research found connections between pedestrian deaths and median household income and also between pedestrian deaths and race. People of color were overrepresented among pedestrian families in 42 of 49 states and the District of Columbia, and for the United States as a whole. Overall, people of color comprised just over one-third of the U.S. population but almost half of the pedestrian deaths. The greatest proportional risks were for African Americans, with 12 percent of the population and 19 percent of pedestrian deaths, and for Native Americans, with 0.7 percent of the population and close to 3 percent of the deaths. The racial disparities were especially dramatic in some states. In Louisiana, people of color were nine times more likely to be killed than white people, and in Texas, the risk was almost three times as great. In Massachusetts, the risk was only slightly elevated; people of color comprised 22 percent of the state population and 24 percent of the pedestrian fatalities.

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Source: Smart Growth America, Dangerous by Design 2016.

As with the income-based findings on pedestrian fatalities, the race-related findings reflect the fact that, as with low-income communities, communities comprising mainly people of color have more residents without car access who walk for transportation and they walk more often and for longer distances. However, SGA found that even after controlling for their residents’ amount of walking, these communities still had higher rates of pedestrian deaths. This suggests that these communities have disproportionately unsafe conditions for pedestrians

To date, only a few experimental studies have been conducted on-road to measure the likelihood of drivers’ responses yielding to pedestrians of different races. The first such study took place at a midblock marked crosswalk in downtown Portland, Oregon, and was conducted by Tara Goddard and Kimberly Barsamian Kahn, both from Portland State University, and Arlie Adkins from the University of Arizona (2016). For this research, individual male pedestrian participants, who were all clearly identifiable as either African American or white, stood at the edge of the crosswalk, looking as though they’d like to cross. The researchers measured the number of cars that passed each pedestrian before a driver stopped at the crosswalk for them, and the amount of time each pedestrian had to wait to cross. Each of the six pedestrian participants—three white and three African American—were of similar build, wore similar clothing, and were instructed to behave similarly. The researchers observed a total of 173 driver-pedestrian interactions. On average, the African American pedestrians waited 32 percent longer and were passed by twice as many cars before crossing, as compared to the white pedestrians.

University of Nevada researcher Courtney Coughenour and colleagues conducted a similar study in Las Vegas. As she described in a discussion earlier this year with National Public Radio correspondent Shankar Vedantam, for their study, the researchers included two different midblock crosswalks, one in a low-income neighborhood and one in a high-income neighborhood, and two female pedestrian participants, one white and one African American. The pedestrians were both of similar build, wore identical outfits, and acted similarly while they waited at the edge of the crosswalk for drivers to stop for them. The midblock crosswalks were on multilane roads. The researchers measured both the number of cars that passed in the nearest lane before stopping for the pedestrian and the number of cars that drove around the pedestrian while they were crossing the street. In total, 124 pedestrian crossings were observed for the two crosswalks. Overall, drivers were less likely to stop for the pedestrians waiting to cross at the high-income crosswalk than the low-income one, regardless of race. At the high-income crosswalk, once the pedestrian was in the roadway, drivers were statistically more likely to pass through the crosswalk and not yield to the African American pedestrian than they were with the white pedestrian. Drivers were also less likely to yield to the African American pedestrian at the high-income crosswalk than at the low-income crosswalk. One contributing factor to these results could be that the high-income crosswalk was on a street with more travel lanes and a higher posted speed limit, 45 mph, than the street with the low-income crosswalk, 35 mph.

In both crosswalk-pedestrian race studies, no information was collected on any of the drivers, such as their race, income, or how they made their decision on whether or not to stop for pedestrians at the crosswalks. Nonetheless, it appears that some drivers could have some race or class-related conscious or unconscious biases in this regard. Of most concern from a safety perspective is drivers’ failure to yield to African American pedestrians already crossing the street in the high-income neighborhood in the Las Vegas study. The failure of drivers to yield at multilane midblock crosswalks is a known cause of many pedestrian fatalities and injuries, and the results here suggest driver biases could put some pedestrians more at risk than others.

 

Written By: Tracy Zafian, UMTC Research Fellow

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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DC Metro : Getting Back on Track

One year ago, in March 2016, the entire Washington, DC, subway system was closed for 29 hours for emergency inspections. This shutdown came after a number of electrical fires oin the subway system, involving fraying third-rail electrical cables. In January 2015, a Washington Metro train encountered heavy smoke near the L’Enfant station due to a third-rail electrical issue and was forced to cease service. One passenger died from smoke inhalation and others were injured. On March 14, 2016, an electrical fire, caused by the same electrical issues as the Nee L’Enfant station incident, occurred near another station. There were fortunately no fatalities. Still, the Metro management shut down subway service a few days later to allow for a system-wide inspection of all third-rail power cables to proactively address system safety before further incidents.

Run by the Washington Metropolitan Area Transit Authority (WMATA), Metro is the second-highest use rapid transit system in the United States, behind just  the New York City subway system, in terms of passenger trips, serving over 700,000 riders per weekday.  Metro is just over 40 years old and faces the many of the same challenges as older US transit systems, including inadequate funding and maintenance backlogs.

In May 2016, WMATA introduced SafeTrack, a comprehensive accelerated maintenance and repair program for implementing safety recommendations and needed upgrades to rail infrastructure.  SafeTrack involves the use of “surges,” intensive work on specific sections of the rail network and the shutting down of one or both tracks in those sections during this work, together with the reduction of Metro operating hours at night and on weekends to make more tracks available for maintenance.

Last week, the US Government Accountability Office (GAO) released a report on its audit of the SafeTrack program.  GAO found that WMATA did not following leading management practices and “(1) comprehensively collect and assess data on its assets, (2) analyze alternatives, or (3) develop a project management plan”  prior to implementing SafeTrack.  In response to the GAO findings, Metro General Manager and CEO Paul Weidefeld stated that WMATA didn’t have time for comprehensive data collection before starting SafeTrack, because safety issues and delayed maintenance had reached a critical point and needed to be addressed as soon as possible. GAO recommends that WMATA develop a full asset inventory and a project management plan for those needed projects that may not qualify as major capital projects.  WMATA is now working to address GAO’s recommendations.

The GAO report found that SafeTrack “will require an additional $40 million in fiscal year 2017 funding.” It is not yet clear where that funding will come from.  Although many transit systems are challenged by inadequate funding, Metro is specifically impacted by one funding issue not faced by other large US transit systems:  Metro has no dedicated funding or revenue sources for its operating budget. WMATA relies heavily on year-to-year subsidies from the governments of Virginia, Maryland, and the District of Columbia, which each have budget constraints and funding priorities of their own. In 2016, 47% of Metro’s budget came from local and state subsidies and 45% from fare revenue. In contrast, for the MBTA, 62% of the budget comes from dedicated revenue (such as the sales tax) and 33% from fares.  In New York, the MTA’s budget relies 36% on dedicated funding, 52% on fare revenue, and 8% on local and state subsidies.  WMATA currently has an almost $300 million annual budget gap.

DCMETRO

The Federal Transit Authority (FTA) provided some funding for SafeTrack repairs and maintenance. Increasingly, business leaders, DC officials, and others are calling for a dedicated source of funding or regional sales tax surcharge to support Metro operations. So far, these requests have faced opposition from Virginia and Maryland officials.  Proponents argue that dedicated funding is not only important for Metro system safety, but could relieve traffic congestion and spur economic development as well.

Also, last week, board members of Metrolink, the regional rail system in Los Angeles, met with the Metro Board Safety Committee to share Metrolink’s firsthand experience with the importance of making safety a priority.  The Metrolink officials showed a poignant video that Metrolink made following the most deadly crash in Metrolink history, a 2008 crash in which 25 people were killed when a commuter train collided with a freight train.  The video focuses on commitment and responsibilities of the Metrolink board regarding safety.  At the meeting,  Metro board member Michael Goldman suggested Metro could create its own video on the safety in the Metro system for its board members and the public.

By: Tracy Zafian, UMTC Research Fellow

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‘Look Mom, no hands….’ TRANSFER CONTROL TO YOUR CAR? Not that far off in the future

lookmanohandsIn the fall of 2016, the US Department of Transportation announced new policies and initiatives for autonomous vehicles (AV) and AV research. The new Federal Automated Vehicles Policy is based on the US DOT’s view that  automated, autonomous vehicles can help promote safety, mobility, sustainability. With the increase use of AVs and semi-autonomous vehicles, there are some potential safety concerns as well, including relating to the ability of people using such vehicles to respond to potential hazards and potentially hazardous situations.

Siby Samuel, PhD, a UMTC Research Affiliate in Industrial Engineering at the University of Massachusetts-Amherst, and colleagues, including Shlomo Zilberstein in the Computer Science Department, have been studying the topic of semi-autonomous vehicles and safety for a number of years. Their research has focused on situations where the control of driving transfers to the vehicle in uncomplicated driving environments (such as a limited access highway), but where drivers still need to be prepared to take back control of the vehicle  to address potential hazards that arise.  This level of driving automation is known as Level 3 automation. Zilberstein and two of his graduate assistants, Kyle Wray and Luis Pineda, are researching how to transfer control “quickly, safely and smoothly back and forth” between the system and the person operating it. All of these studies were conducted on UMass’s Advanced Driving Simulator ( http://www.ecs.umass.edu/hpl/ ).

“The real trend in artificial intelligence is to build systems that can collaborate with people,” Zilberstein said. (Daily Hampshire Gazette)

At the Transportation Research Board (TRB) Annual Meeting in January 2017 Dr. Samuel’s team presented two recent studies on Level 3 driving automation and the time it takes for drivers to be able to respond to potential hazards when the driving control of the vehicle needs to switch from the automated system to the driver.

An earlier study by Samuel and Zilberstein also looked at this transfer of control on the driving simulator.  Participants were instructed to transfer control to automation upon hearing an audio alert “transfer control”, and then later they were told with another audio alert “take over control” when they were to resume manual control of the vehicle. During the automated driving phase, participants were instructed to do tasks on a computer tablet. This study found that the minimum transfer of control altering time required for drivers in a Level 3 driving environment to respond to a potential hazard was 8 seconds when the hazard was expected, when the roadway environment was not changing during the transfer of control process, and when they were doing tasks on a computer tablet during the automation part of the drive. In other words, it took 8 seconds for these drivers to anticipate hazards at a rate equivalent to that of drivers who were manually driving their vehicles and weren’t distracted with in-vehicle tasks.   In one study presented at this year’s TRB meeting, Samuel and colleagues found that more informative audio alerts, for example a message telling a participant about at at-grade rail crossing or a lane reduction ahead could reduce the needed time for participants to respond to a potential hazard by as much as 40% or 4 seconds.

UMass Affiliate Researchers make headlines on driverless cars:
http://www.gazettenet.com/University-of-Massachusetts-researchers-study-how-to-make-self-driving-cars-safer-3711488 (Daily Hampshire Gazette)

By: Tracy Zafian, UMTC Researcher

2016 Commercial Vehicle Safety Research Summit

The University of Massachusetts Traffic Safety Research Program (UMassSafe) held a Commercial Vehicle Safety Research Summit in November of 2016 to promote best practices for advancing safety through partnerships among law enforcement and state driver’s license agencies with universities.  With more than 100 attendees from across the Northeast, the 2-day Summit, funded by the Federal Motor Carrier Safety Administration (FMCSA), addressed key issues related to crash prevention including driver distraction and autonomous vehicles, as well as homeland security, drugged driving, social media and workforce development.

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“Innovation is rapidly changing the transportation sector.  The Federal and state governments must keep up while never losing sight of protecting the traveling public,” said FMCSA Deputy Administrator Daphne Jefferson, one of the keynote speakers. “This summit enables us to learn from each other and build partnerships with universities to realize the safety benefits of innovation and automation.”

The goals of the summit were based upon the premise that an integrated approach and effective partnerships can reduce the number of truck and bus crashes and fatalities.  Massachusetts has enjoyed positive safety results because of the successful partnership that now exists between UMassSafe, the Massachusetts State Police Commercial Vehicle Enforcement Section and MassDOT’s Registry of Motor Vehicles Division. Using this experience as an example, summit organizers encouraged other state participants to develop or expand the connection between universities and state agencies involved in crash prevention efforts.

The FMCSA funded project continues with the implementation of a UMassSafe Technical Assistance Center (TAC) in order to provide assistance for law enforcement and licensing agencies as well as universities, acting as a resource and information center building on the momentum of the Summit.  Additional information can be accessed at www.umasstransportationcenter.org/cvsummit.

By: Robin Riessman, UMassSafe