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

By Tracy Zafian, UMTC Research Fellow

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.

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The Phantom Bus Driver: Helsinki Rolls Out Autonomous Public Transit

By Adrian Ayala, UMTC Research Staff

Helsinki, Finland has long been on the forefront of developing cutting edge transportation technologies. By 2025, they hope to implement a “mobility on demand” system that would eliminate the need for private vehicles through the combination of bicycle-sharing, public transit, and on demand taxi services. One of Finland’s laws is particularly conducive to increasing the technology involved with transportation – they do not legally require vehicles on public roadways to have drivers within the vehicle.

phantom_bus_helsinki

In August, they began taking an even more dramatic step to revolutionizing their citizens’ daily transportation needs. Although autonomous busses have been seen before in more controlled environments such as college campuses, the Helsinki bus is the first of its kind to operate on public roads, interacting with live traffic and having to make complex driving decisions. As of November 1st, the busses are running a route between Tampere University of Technology and Hervantakeskus Shopping Centre. The brains behind the project plan on stopping the service at the first snow fall in order to test the vehicle under difficult conditions. By getting commuters out of private cars and into public transit, the city of Helsinki could decongest streets, creating a safer atmosphere for pedestrians, cyclists and drivers.

Developed by French company EasyMile in collaboration with the Metropolia University of Applied Sciences, the model, EZ10, is able to carry 12 passages, 6 sitting and 6 standing. It uses a system of sensors and software in order to be aware of its surroundings. Passengers can board and disembark at predetermined points along the route.

Although the busses are a large step forward in moving toward autonomous transportation, there are still various pitfalls that must be first overcome. First of all, the busses are not completely autonomous. There is an attendant in the front of the vehicle, ready to push the emergency stop if the situation arises. Furthermore, the busses are only currently running at 7 mph, making efficient travel a bit of a difficulty. Lastly, it is not capable of lateral movement – if the vehicle needs to swerve around an obstacle, the attendant must manually do so.

bus_2_helsinki

Currently, the best use for the autonomous bus is in last mile service. The city of Helsinki, along with the University, hope to use the bus to move people from a transportation hub, to a final destination in the home. The city does not plan to replace the entire public transit system with these autonomous vehicles, but rather, hopes to use them as supplements to the existing system in high use areas. The main usage Helsinki has in mind is using them as a feeder service, transporting people to faster, more efficient forms of transit. Although only cruising along at a snail’s pace, Helsinki hopes for the bus to finally reach the Finnish line.

A Seasonal Bicycle Demand Model Using A Sinusoidal Function

As urban populations increase, there is a growing need for efficient and sustainable transportation modes, such as bicycling. Unfortunately, the lack of bicycle demand data is a substantial barrier to efforts in designing, planning, and researching bicycle transportation. Estimating bicycle demand is especially difficult not only due to limited count data, but due to the fact that bicyclists are highly responsive to a multitude of factors, particularly seasonal weather conditions. Current bicycle demand estimation methods are increasingly improving and are capable of accurately adjusting for seasonal change in demand. However, these methods often require substantial data for each calibration, which is often difficult or impossible in locations with partial or minimal continuous count data. This research aims to help mitigate this challenge by developing an estimation method which uses a sinusoidal model to fit the typical pattern of seasonal bicycle demand expected in in many locations. This sinusoidal model utilizes a single calibration factor to adjust for scale of seasonal demand change and is capable of estimating monthly average daily bicycle counts (ADB) and average annual daily bicycle counts (AADB). This calibration factor can be established using a minimum of two short term counts to represent the maximum monthly ADB in summer and minimum monthly ADB in winter, or ideally with continuous counts. The calibration factor can then be applied to other locations that are expected to have similar seasonal patterns, even if they have different overall counts. To develop the model this research uses data from bike-share systems in four cities and permanent bicycle counters in six cities. Ultimately, this model functions as an alternative, or supportive, estimation method which allows for researchers and transportation agencies to approximate expected demand in locations that suffer from minimal seasonal bicycle demand data.

By Nicholas Fournier, Eleni Christofa, and Michael A. Knodler Jr., UMass-Amherst Researchers

 

Evolving Strategies for Demand Responsive Transit

ada_maryland

For people who are unable to drive or use conventional transit (e.g., fixed route buses and trains), getting around can be a real challenge. One group is receiving increasing attention in the transportation community: people with physical or mental disabilities that prevent them from being able to use existing buses and trains. The Americans with Disabilities Act of 1990 (ADA) requires transit agencies to operate curb-to-curb paratransit with ¾ mile of fixed route bus services for these. Although ADA paratransit constitutes only 1% of transit trips in U.S., the services make up 8% of the operating costs. Furthermore, demand for ADA paratransit increased by 41% from 2000 to 2010, and the trend of increasing demand and increasing cost is expected to continue as the American population gets older [1]. This presents a major challenge for transit agencies: equitable service must be provided for customers with disabilities, but increasing costs threaten the ability of agencies to continue providing adequate ADA paratransit along with conventional services. Recent and ongoing research at UMass Amherst addresses multiple strategies for managing ADA paratransit needs.

One way to approach the problem of mounting paratransit costs is to focus on optimizing the operations. Recent studies of ADA paratransit demand and operation patterns in New Jersey have shown that the total operating cost in a service region can be modeled based on the area of the region, the rate that trips are requested per time, and the allowable time window for an on-time pick-up [2].  There are ways to geographically align service regions to cover large areas in order to minimize the negative effects of making customers transfer.  It can be beneficial to break up large regions into zones such that one zone provides service within a dense urban core, and another zone provides service to more distributed areas [3].

Another approach to the problem is to manage demand by incentivizing users to travel at times of day when there is excess system capacity. The current ADA regulation requires agencies to schedule paratransit service within one hour of the customer’s requested pick-up time and to charge no more than 1.5 times the fare of conventional transit service. Peaks in demand at certain times of day leave agencies with no choice but to purchase more vehicles and hire more drivers, but these resources are costly when they go unused at other times of day. A time-varying fare, within the ADA constraints, could incentivize users with flexible schedules to travel at less costly times of the day to improve the system’s overall efficiency [4].

An emerging question is what role existing ADA paratransit should play in serving this population in the long term. We know that shared-ride services are most efficient in areas with dense demand.  In the suburban fringe, there are many trips that could be served more cost-effectively by taxis or on-demand mobility services (e.g., Uber, Lyft). In the Boston area, where the average cost of serving a one-way paratransit trip is $46.88, the MBTA is piloting a program to subsidize taxi trips for some users [5]. Despite concerns about vehicles being physically equipped and drivers having appropriate training to serve customers with disabilities, demand responsive services that allow vehicles to be shared by multiple user groups hold great promise for bringing down the cost of providing high-quality ADA paratransit service. Perhaps the changes that emerging technologies are bringing for mobility services will be a great equalizer that can afford the same transportation choices to people with disabilities as the rest of the general public. One thing is certain, the future users are going to require flexible and efficient transportation systems to meet their diverse needs.

By: Dr. Eric Gonzales

  1. American Public Transit Association (APTA) (2012). 2012 Public Transportation Factbook. Available online from: http://www.apta.com/resources/statistics/Documents/FactBook/
    APTA_2012_Fact%20Book.pdf
  2. Rahimi, M., Amirgholy, M., Gonzales, E.J. (2014). Continuum approximation modeling of ADA paratransit operations in New Jersey. Paper Number 14-4864. Transportation Research Board 93rd Annual Meeting, 12–16 January, Washington, D.C.
  3. Rahimi, M., Gonzales, E.J. (2015). Systematic evaluation of zoning strategies for demand responsive transit. Paper Number 15-4023. Transportation Research Board 94th Annual Meeting, 11–15 January, Washington, D.C.
  4. Amirgholy, M., Gonzales, E.J. (2015). Demand responsive transit systems with time dependent demand: User equilibrium, system optimum, and management strategy. Transportation Research Part B, doi:10.2016/j.trb.2015.11.006.
  5. Massachusetts Bay Transportation Authority (MBTA). Riding the T. Available online from: http://www.mbta.com/riding_the_t/accessible_services/?id=7108

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, UMTC Manager of Research