Convergence of Sharing and Automation: Need for Proactive Public Policy and Research Understanding

By Susan Shaheen and Adam Cohen

In recent years, on-demand passenger and courier services – known as Mobility on Demand (MOD) – have grown rapidly due to technology advancements; changing consumer patterns (both mobility and retail consumption); and a combination of economic, environmental, and social forces. MOD is an innovative concept based on the principle that transportation is a commodity where modes have economic values that are distinguishable in terms of cost, journey time, wait time, number of connections, convenience, and other attributes. Earlier this month, we wrote about innovations in goods delivery that are transforming transportation and consumer behavior as travelers increasingly turn to MOD. In this blog, we discuss four potential impacts of driverless vehicles and the need for proactive public policy to maximize the potential benefits and minimize potential adverse impacts.

Potential Impacts of Vehicle Automation

In the near future, automation could be the most transformative change transportation has seen since the advent of the automobile. While MOD is already impacting many cities, it has the potential to have even more notable impacts, particularly in four key areas:

Travel Behavior: It should be emphasized that the impacts of automation on travel behavior are uncertain and difficult to forecast due to a number of highly variable factors, most importantly societal acceptance and use. One potential outcome is that existing roadway capacity may increase due to more efficient operations associated with technology (e.g., closer vehicle spacing known as platooning, etc.). Additionally, operators could “right-size fleets,” providing consumers with vehicles sized based on the number of passengers and trip length. However, there is a possibility that automated vehicles (AVs) and shared AVs (SAVs) could induce demand by making motorized travel more convenient and affordable than personal driving. This could adversely impact congestion. Additionally, automation has the potential to fundamentally change historic relationships between public transportation and private vehicle use, which could support or detract from public transit ridership (we will discuss the future of public transportation in our next blog). In summary, the impacts of AVs on congestion will likely depend on whether the vehicles are predominantly shared or privately owned as well as public policy, such as pricing and restrictions on zero occupant vehicles.

Land Use and the Built Environment: AVs could result in reduced parking demand, particularly in urban centers that can create opportunities to repurpose urban parking with infill development. Infill development has the potential to increase urban densities and could in turn support higher-occupancy transportation modes. However, vehicle automation and telecommuting growth could also make longer commutes less burdensome, which could encourage suburban and exurban lifestyles.

Labor: Automation has the potential to reduce labor costs. However, automation is not likely to completely eliminate transportation jobs. With an aging population, we may likely need attendants to assist people with disabilities and older adults, security personnel, and a high-tech workforce to maintain an automated fleet.

Social Equity: While AVs have the potential to enhance access and economic opportunities for underserved communities, there are numerous challenges that could impact the equitable deployment of AVs. A few challenges could include: 1) affordability/payability (the services are simply too expensive for low-income households or require banking access); 2) availability (the services are not available equally in all neighborhoods); 3) accessibility (the services are not accessible to people with disabilities); and 4) digital poverty (the services require a smartphone or data plan to access). Additionally, AVs may employ machine learning and artificial intelligence that could create other equity concerns. While machine learning – if designed well — can help minimize human bias in decision making, it is also possible that such systems can also reinforce historic bias and discrimination in the transportation network. Just as humans learn to drive through experience, many perception algorithms use machine learning that is trained by events based on past experience. In a driverless vehicle future, machine learning may also impact where vehicles are pre-positioned, roam, charge, and other defining operational characteristics. Learning biases could create notable equity challenges in the future. There is a risk for discrimination when designing transportation algorithms for machine learning systems, including the potential for exclusionary transportation.

Need for Proactive Policy in a Driverless Vehicle Future

Public policy can have a notable influence on the success or potential challenges of driverless vehicles. Public agencies should consider proactively guiding public policy in four key areas to maximize the potential benefits of AVs:

Pricing: Public agencies should consider employing pricing based on occupancy, time of day, and congestion to encourage higher occupancy SAVs and discourage single- and zero-occupant vehicles.

Incentivizing Urban Growth and Urban Growth Boundaries: Metropolitan Planning Organizations, local governments, and other public agencies may want to consider policies that limit outward growth and encourage urban in-fill development to discourage the potential suburban and exurban growth pressure that AVs could create.

Workforce Development Programs: Local and state governments should develop workforce development programs designed to prepare for and respond to a driverless future. This should include a broad program encompassing job training/re-training and job placement resources to minimize the potential adverse labor impacts of vehicle automation.

A Comprehensive Equity Policy: Public agencies at all levels of government should consider a comprehensive equity policy to ensure SAVs are equally accessible and available to everyone. This should include policies that ensure access for people with disabilities, un- and under-banked households, low-income communities, households without access to smartphones or mobile data, and others. Additionally, this should include policies that prevent discrimination and bias from machine learning, artificial intelligence, and other systems that impact or guide the operations of AVs.

The public and private sectors, along with key stakeholders (e.g., non-governmental organizations, community-based organizations, and foundations) should partner to develop proactive policies to prevent and overcome these challenges. Proactive policy and research understanding will be critical to balance public goals with commercial interests and to harness and maximize the social and environmental effects of driverless vehicles.

Susan Shaheen and Adam Cohen are currently studying the impacts of connected and automated vehicles on state and local transportation agencies as part of the National Cooperative Highway Research Program (NCHRP) study 20-102(11).

Please note that this article expresses the opinions of the author and does not reflect the views of Move Forward.

 

Public Transit in the City of Tomorrow

By Tim Lane

 

The next 15 years promises to bring a sea change in how we commute as a society. We may very well look back on this moment in history as the transition point between static and fluid public transit. Today, under the established, static model, the public largely adheres to set schedules to commute around our cities. We travel within the constraints of the system. Tomorrow’s fluid model may look drastically different. Traditional modes like buses and light rail will be partnered with new advancements like autonomous car fleets and the Hyperloop. Stitched together, the transportation experience will be catered to the individual’s commuting needs.

 

“Broadly speaking it’s exciting that the mix is happening,” said Brooks Rainwater, senior executive and director of the National League of Cities’ Center for City Solutions. “These things that for so long were science fiction are now becoming fact.”

New Technologies

Perhaps one of the most exciting developments is the fast-approaching reality of autonomous car fleets. A recent report from the independent think tank ReThinkX found that by the year 2030, 95% of passenger miles in the US will be serviced by fleets of autonomous, electric vehicles. The biggest question, perhaps, is whether this advancement will progress in the public or private sector.

 

“Uber is pretty clearly reducing public transit use,” said Dave Chandler, Director of Economic Development at the Center for Neighborhood Technology. “The trend of public transport went up from 2008 until two years ago and has declined since. People look at it and think it’s probably Uber. It’s a competing model currently.”

 

This competing model could only become more formative if private companies perfect and invest in autonomous fleets that don’t value their public transport counterparts. However, there is a brighter possibility. One where cities step in with fleets of their own.

 

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“I think there could be autonomous fleets at the municipal level,” Rainwater said. “It might be hard to conceptualize right now, but London is already trying to create a co-op. It is a model where cities act much like car rental agencies. They already have a ton of experience with fleet management. It’s a skill that could be used.”

 

Another alternative to protecting and promoting public transit would be to forge tight, reciprocal relationships between cities and public transportation. This could improve the overall commuting experience and ensure ridership equity.
“I think as we move to autonomous models we are starting to see some of those private/public partnerships pop up,” Rainwater said. “I think we’ll only see that relationship deepen.”

 

With increased sharing of transit and rider information, commuters will be able to depend on accurate travel times. Meanwhile, if approached correctly, private companies could be pressured to be a complement, not a competitor, to public transportation as a whole.
“I have some optimism about things like Uber building in more equity that could change the equation,” Chandler said.

 

Hyperloop, though grander in scale and seemingly further out than autonomous cars, could also instigate a huge change in public transportation. By slashing commute times and freeing up highway space, the Hyperloop would be a boon on multiple fronts.

 

“Hyperloop could be a game changer for places like Baltimore and D.C.,” Rainwater said. “I think that if the private sector can prove the concept, then the public municipalities could follow.”

 

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Smart City Planning

Even with all of the exciting technological advancements around transportation, without a considered, encompassing vision by cities, public transit won’t advance to its full potential.

 

“I think there are two basic paths that we could go down,” Chandler said. “The bright path is based on the consideration that more and more people are living in cities. Public transit is the most efficient way to move around in a compressed, compact environment. And the really neat thing is what has happened in last 20 years. There have been examples of people — combinations of architects, developers, and local government — designing transit-oriented developments.”

 

By planning cities around basic public transit needs, people can be easily connected with jobs in the city. With more and more manufacturing and information-based jobs created each year, the demand for flexible, creative workspaces will only rise. The importance of getting people to and from these dense, urban environments quickly and efficiently will be huge.

 

“The interactive nature of urban design and transit is underappreciated,” Chandler said. “Transit needs that design in order to function well.”

 

There have also recently been encouraging advancements in cities with historically low-functioning public transit systems.

 

“It’s really cool to see Denver and LA, which were built as very different cities, now trying to stitch it together,” Rainwater said. “It’s exciting to see the cultural pressures pushing people in this direction.”

The Morning Commute in 15 Years

A typical morning commute might begin by leaving your apartment located in the new development by the river. This and other areas are now designed with efficient transportation in mind, as well as the usual amenities.

 

From there, you hop into an autonomous transit car that’s been pre-scheduled, via your phone, to arrive at your doorstep at 7:30 AM. On any given morning, different neighbors might also share the ride, depending on time, day, route, and destination. The city’s transit system will take into account traffic patterns, commute time, and overall system efficiencies to decide the next stage in your journey.

 

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The car drops you at a bus stop along a main thoroughfare, and a minute later the bus arrives. There’s no need to pay to board — your progress is tracked anonymously using the latest in blockchain tech, and your account debited automatically. The bus glides down streets in a dedicated lane, making great time thanks to less congestion. But also, thanks to the city’s convenient new on-demand services, which means bus stops can now be spread farther apart, requiring fewer stops.

 

Then maybe you realize you’re running late for a meeting you forgot — across town from the office. You tap the new coordinates into your phone and are given new options in real time: Either pay for a private service to meet you at the next stop (unfortunately, all on-demand city cars are tied up in rush hour traffic), or have the city’s transit app reroute your commute. You’re instantly given an exact time of arrival and can alert your coworkers if you’ll be late, or rest assured knowing that you’ll make it on time.

 

While there may be big technological jumps in the next 15 years, the biggest change will be to the overall experience as a whole. We’ll still rely on modes of transit like buses and light and heavy rail, but utilized in concert with newer advancements like autonomous fleets and the hyperloop. The city of tomorrow will feature a fluid transit menu of options, working together for quick, efficient travel.

 

Will we still hate our daily commutes? Maybe. It will always be more difficult to rewire human nature than technology. But with the right planning, tracking and mix of smart systems, we’ll have to work a lot harder to complain about such an easy ride.

 

How Bluetooth and WiFi Are Easing Bangkok’s Traffic

For years, Thailand’s Department of Highway (DOH) faced the challenge of trying to ease traffic and reduce the massive gridlocks in Bangkok. The city is considered to have some of the worst traffic in the world, especially in mid-April during Thailand’s New Year, or Songkran, and during the international New Year. These holidays are notorious for causing major congestion, as millions leave the capital to celebrate with their families.

The DOH needed a solution to help provide live and detailed traffic information, so they turned to BlipTrack in 2015. BlipTrack mounted Bluetooth/WiFi sensors at strategic points along the city’s roads to measure and provide travel time and traffic flow information, and predict traffic build-up. The project has since seen so much success that Thailand’s DOH is now expanding the technology to cover additional roads in Bangkok.

The sensors, covering roughly a 600 km section of highway in and around Bangkok, detect Bluetooth or Wi-Fi devices found in mobile phones and in-car audio and communication systems. By re-identifying the devices from multiple sensors, specific and accurate statistical information, such as the travel times, average speeds, dwell times and movement patterns, becomes available.
 
BlipTraffic
 
The DOH specifically wanted to measure and compare travel times on the Intercity Motorway, The Bangkok Expressway and neighboring routes in Bangkok. The idea was to present real-time traffic information to road users via the department’s “Highway Traffic” mobile app and help them make informed decisions when planning their trip.

The mobile app, which provides information on travel times, fastest routes and other traffic information, is continuously updated in line with the actual behavior of road users. So by considering their route and the time they depart, motorists help keep the traffic moving. The collected data will ultimately produce economic benefits by reducing travel times, fuel consumption and vehicle emissions.

This was the first project ever in Thailand that implemented this kind of technology in the traffic field. The solution gives more accurate travel time data compared to spot speed data collected from radar and ANPR cameras. Furthermore, the origin/destination data is used by city engineers to gain an in-depth insight into the understanding of traffic flows and the development of traffic jams in order to optimize the road network and reduce congestion.

According to Songrit Chayanan, Director of Samut Sakhon Highway District, “the solution has helped Thai citizens to travel home faster during two major traffic events: Songkran and New Year holidays. The system allowed not only road users to decide route choices via travel time info online but also the Thai Highway Police to manage traffic in real-time.”

 


Please note that this article expresses the opinions of the author and does not reflect the views of Move Forward.

#TransitTrends Episode 8: Traffic sucks, so why do we sit in it?

It’s a known fact that bad habits are hard to break. If it was simple, we would never procrastinate, be in incredible shape and accomplish all of the goals we ever set.


The same part of the brain that decides whether or not you’re going to quit smoking also decides whether or not you plan to drive to work or school alone every day in traffic. It’s truly fascinating to be on a crowded street or highway and notice just how many people are driving alone. It’s even more interesting to think about how many of those people could have done something different like hopping on the bus, carpooling, riding a bike or even walking.

The million dollar question in cities across America revolves around why more people neglect to try different transportation options. Perhaps today’s commuters didn’t even consider the numerous options or take the time to research them.

Dr. Bob Duke and Dr. Art Markman sat down with Transit Trends host, Erica Brennes, to take a deeper dive into the brains behind traffic. The duo are professors at The University Of Texas at Austin, and recently wrote the book Brain Briefs.

What is your commuting behavior like? Do you ever break the single occupancy vehicle habit? If so, let us know by leaving a comment on this video.

Stay up to date with the latest Transit Trends episodes by subscribing to the moovel YouTube Channel! Leave a comment below or tweet us using #TransitTrends if you have a topic you’d like us to discuss in the future.


Please note that this article expresses the opinions of the author and does not reflect the views of Move Forward.

Your Mobile Phone Can Help Predict Traffic Jams

Traffic jams often come from shock waves that start when someone hits their brakes. The faster the traffic, the bigger the gaps, and the more abrupt the braking. The effect of breaking works its way back down through the traffic, and the many stops have a reinforcing negative effect on the queue, which ultimately causes even more congestion.

One way to reduce traffic shock waves, is to adjust speed limits to delay the onset of congestion and help recover from it. By adjusting speed limits to provide the optimum gap between cars, more cars can get through at any one point.

With the help of real-time traffic data, using Bluetooth/WiFi sensors and radars to measure travel time, speed, occupancy and flow, and looking at past traffic conditions, it is possible to predict congestion. This rapid detection allows road authorities to detect incidents and congestion in a matter of seconds and to take proactive steps to initiate countermeasures, such as adjusting speeds, changing traffic light settings or dispatching traffic regulators.

Multiyear evaluations of Variable Speed Limits (VSL) impact on traffic safety indicate a reduction in accident numbers by as much as 20% to 30% after VSL installation.

The solution works by placing sensors at strategic points along the road. The sensors detect Bluetooth or WiFi devices, found in mobile phones and in-car communication systems. By re-identifying the devices at multiple sensors, travel times, average speeds, dwell times and movement patterns can be measured and calculated.

The collected data can also be used to display queue warnings, travel times and route choices on digital road signs and mobile apps. This live information allows road users to make smarter travel choices and enjoy a stress-free and pleasant travel experience. As the information is continually updated in step with the actual behavior of road users, the motorists themselves are helping to keep the traffic moving.

Studies show that queue warnings reduce speeds and encourage drivers to drive in a uniform fashion, thus preventing congestion and accidents.

Real-time congestion and speed and flow monitoring also allow traffic managers to gain an in-depth insight into the understanding of traffic flows. They also help monitor the development of traffic jams, to proactively manage the road network on a holistic scale, build predictive traffic models and help the daily commute.

Compared to other technologies, such as camera and inductive loops, the combination of measurement with Bluetooth/WiFi and radar provides a more cost effective solution, that is less impacted by wear and tear and weather conditions. It provides more precise and detailed view of the current traffic flow and speed patterns for the individual lanes and road segments.

The main benefits of variable speed limits and displayed travel times, queue warnings and route choices include:

  1. Smoother traffic flows with less stop/starts

  2. More reliable travel times

  3. Fewer traffic collisions

  4. Lower fuel consumption and vehicle emissions

The Bluetooth/WiFi solution mentioned above, named BlipTrack, is successfully employed in optimization efforts in road traffic in Switzerland, Ireland, New Zealand, UK, USA, Canada, Denmark, Sweden and Norway. In addition, the solution is implemented in more than 25 international airports, including Schiphol Airport in Amsterdam, JFK Airport in New York, Toronto Pearson, Dubai, El-Prat Airport in Barcelona, Dulles Airport in Washington, Copenhagen, Oslo, Malpensa and Linate Airports in Milano, Manchester, Brussels, Dublin, San Diego, Helsinki, Auckland, Montreal, Genève, Birmingham, Bristol, Cincinnati, Brussels South Charleroi, Keflavik, Billund and Aalborg. In recent years, the solution has also been rolled out in ports in Denmark and UK, train stations in Holland, ski resorts in USA, amusement parks, and at events all over the world.

Please note that this article expresses the opinions of the author and does not reflect the views of Move Forward.