UMTC Affiliates & MassDOT Assistant Secretary Katherine Ficher 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.

Hossein_Fig1new
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.

Hossein_Fig2new
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. 

Keeping Cyclists Safe! UMTC Research Spotlight on YouTube

 

Want to learn more about bicycle safety? PhD student Nicholas Fournier of UMass Amherst talks about his two research studies currently being conducted at UMass. Mr. Fournier is studying for a PhD in transportation engineering and an MS in regional planning at the University of Massachusetts, Amherst. View Mr. Fournier discussing his research at this link. One of the highlighted studies used the UMass advanced driving simulator to test how well drivers approaching intersections understand different on-road bicycle infrastructure, such as bike boxes and merged bike lanes, which are designed to reduce left-hook bicyclist-motor vehicle crashes and promote bicyclist safety. In the second study, Mr. Fournier developed a sine-wave model for estimating annual on-road bicycle travel demand in cities where bicycle demand can fluctuate considerably across seasons. The model reduces the number of sample counts needed to develop an estimate for bicycle demand, making it easier for researchers and practitioners in a city to measure bicycle ridership and the overall safety of their road infrastructure for bicyclists.

 

 

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.

peds_IO

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.

Graph_IO

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

Don’t Get Derailed: The MBTA Is Still a Safe Transit System; Investment in Infrastructure Is Needed to Keep It That Way

The Green Line had six trolley derailments in 2016, according to the recently updated National Transit Database, and as described in a recent Boston Globe article. Combined with two subway maintenance vehicle derailments, this positioned the MBTA as the transit agency with the most derailments last year in the United States.

So what is behind this data? Why should we look closer?

Greenline

In 2015, the National Transit Database derailment figures began including derailments of vehicles not intended for passengers, including maintenance vehicles. This increased the MTBA’s reported annual derailments slightly. It is also worth noting that these published figures do not include derailments for commuter rail systems, as those incidences are instead reported to the Federal Railroad Administration.

The MBTA is this country’s fifth-largest mass transit system, based on daily ridership, and has the busiest light rail system (Green Line and Ashmont-Mattapan high-speed line). Derailments are less common for parts of the MBTA system beyond the Green Line. In 2016, the MBTA had its first derailments on the Orange and Red lines since 2001; both derailments involved vehicles that are not for passengers.

Sensationalizing this data only serves to create poor public opinion, and the MBTA leadership feels confident the MBTA system, including the Green Line, is safe. In 2016, none of the derailments resulted from a collision, and no passengers or employees were injured in a derailment. The number of annual derailments for the MBTA is down significantly (over 75%) from a high of 29 derailments in 2007, and the MBTA is committed to reducing derailment on the Green Line further through improved maintenance and monitoring. Even when no one is hurt, derailments impact service delivery and can shut down lines or stations for hours.  They can also undermine riders’ support of and trust in the MBTA.

There are, however, other challenges to the MBTA system, including its age and need for additional funding, as well as for maintenance. The Green Line is the oldest subway line in the United States, with tunnel sections dating back to 1897, and it is one of the oldest light rail systems above ground as well. Other systems topping the 2016 list of derailments include New Orleans and the San Francisco Municipal Railway, which are also historic systems. This is another reminder of the importance of funding investments in maintaining and rebuilding aging infrastructure. The challenge isn’t limited to the MBTA. The U.S. DOT estimates a nearly $90 billion backlog in transit infrastructure maintenance, just to preserve existing systems. In 2015, the MBTA’s maintenance backlog was over $7 billion, and it would need to spend about $765 million annually to eliminate the maintenance backlog over 25 years.

Although rapid transit remains a safe way to travel compared to travel by car, recent crashes on commuter railroads in other parts of the country are drawing attention to the limitations of existing infrastructure. Investments are necessary to ensure safe, reliable, and efficient mobility for the economic competitiveness and vitality of cities like Boston for decades to come.

By: Tracy Zafian, UMTC Research Fellow, and Eric Gonzales, UMTC Research Affiliate

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