Transit Tech – Mobility Lab https://mobilitylab.org Moving People... Instead of Just Cars Fri, 23 Jun 2017 21:55:16 +0000 en-US hourly 1 See how space for cars, trains, and bikes stacks up in New York City https://mobilitylab.org/2017/06/23/space-cars-trains-bikes-nyc-moovel/ https://mobilitylab.org/2017/06/23/space-cars-trains-bikes-nyc-moovel/#respond Fri, 23 Jun 2017 17:10:02 +0000 https://mobilitylab.org/?p=22827 How much space cities provide to different transportation options is an easily-visualized hint into how they prioritize different ways of getting around, a relationship made even more evident through the basic geometric inefficiencies of driving. As an exercise to investigate just how unfair this allotment of space can be, Moovel Lab, the creative side project of... Read more »

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How much space cities provide to different transportation options is an easily-visualized hint into how they prioritize different ways of getting around, a relationship made even more evident through the basic geometric inefficiencies of driving.

As an exercise to investigate just how unfair this allotment of space can be, Moovel Lab, the creative side project of app company Moovel, released a project that categorizes and directly compares all of the car, train, and bike space in New York City.

“What the Street!?” identifies and measures parking, rail, and street space from OpenStreetMap across New York City. Users are asked to input their guesses as to the percentage of public space given to each mode (hint: it’s stark) and can see the shape of each parking lot and street stacked in a graphical comparison.

Click on the individual bike lane, train right-of-way, or street, and OpenStreetMap opens to show you where it is. Scrolling through the 107 million square meters of New York “car space” makes quite an impression when compared to the small stacks of “bike space.”

Source: Moovel Lab.

Most interesting, perhaps, is the above triangle chart, which compares how much space is provided per mode against how people in that city actually get around. For New York, for example, the majority of residents get around by subway, hence the long differential down the rail side of the triangle. When you move people more efficiently through transit and bike infrastructure, the saved space becomes available for uses open to more people than just drivers. And on the flip side, Moovel Lab notes that the existing highways and parking lots are a strong incentive for many to choose driving over transit or biking.

Moovel Lab acknowledges that the project is limited by a number of factors and is not meant to be a scientific analysis of infrastructure. For one, the identification of different types of space depends on the accuracy of contributions from OpenStreetMap volunteers. Nevertheless, the project is a fun look into recognizing a relationship that’s often taken for granted.

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Post-Travis Kalanick, Uber needs to finally think deeply about its role in the world https://mobilitylab.org/2017/06/21/post-travis-kalanick-uber-needs-to-finally-think-deeply-about-its-role-in-the-world/ https://mobilitylab.org/2017/06/21/post-travis-kalanick-uber-needs-to-finally-think-deeply-about-its-role-in-the-world/#respond Wed, 21 Jun 2017 14:39:33 +0000 https://mobilitylab.org/?p=22802 With today’s news that Travis Kalanick has stepped down as chief executive of Uber, the ride-hailing giant has reached a crossroads on whether it will sink or swim. Its many months of trials and tribulations may be too much to overcome, and the boorish company culture that has come to light again and again will... Read more »

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With today’s news that Travis Kalanick has stepped down as chief executive of Uber, the ride-hailing giant has reached a crossroads on whether it will sink or swim.

Its many months of trials and tribulations may be too much to overcome, and the boorish company culture that has come to light again and again will no doubt prove too much for many former customers to overcome.

When Uber’s board essentially fired Kalanick, it wrote that he had “always put Uber first.”

That is not a good thing; that is part of the problem. By always putting Uber first, at all costs, he forgot that there’s a context to all this. What we’re learning from the early days of Uber is that perhaps the best way to fit into a particular universe is not to make enemies with everyone else in your immediate orbit (in this case, to name a few, taxicab companies and drivers, transit providers, and the occasionally unhappy customers you treat with disdain like mosquitoes).

In Uber’s quest to take over the world of tech-transportation, Kalanick and other leaders there have forgotten the many ways the company should be contributing to a better society.

We can thank Uber and other so-called “sharing economy” transportation companies (although the only part of Uber that truly meets this qualification is UberPool) for getting people to realize they don’t always have to drive everywhere, alone in private vehicles. Uber has become a powerful tool to persuade people to give up car ownership altogether.

Many cities have been working to integrate Uber, Lyft, and other companies into extending the reach of their fixed mass-transit systems. Hopefully that work continues because it really could improve problems created by pollution and traffic jams. Perhaps even better, transit agencies themselves, after years of sluggishly moving into the 21st century, are starting to copy the ways Uber has made travel so effortless because of information obtainable through technology.

In the end, if services like Uber can cut total vehicle trips in congested areas, then they can play a major role in helping city governments and planners design much more livable places. After all, if a city could reduce car ownership by 15,000 vehicles, $127 million could stay in the local economy.

That’s where Uber and its board could take a step back to think about how it wants to get, to cop a phrase from D.C. Metrorail, “back to good.”

Read more about Kalanick leaving Uber at The New York Times

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Flying cars could happen. But they’ll probably create more problems than they solve – GreenTech Media https://mobilitylab.org/2017/06/12/flying-cars-could-happen-but-theyll-probably-create-more-problems-than-they-solve-green-technology/ https://mobilitylab.org/2017/06/12/flying-cars-could-happen-but-theyll-probably-create-more-problems-than-they-solve-green-technology/#respond Mon, 12 Jun 2017 14:35:23 +0000 https://mobilitylab.org/?p=22602 There’s a lot of excitement around flying cars right now – even if they are basically just giant drones. Whether piloted or autonomous, taxis or private vehicles, they’ve been hailed by futurists as the ideal way to reduce journey times across urban landscapes, thus easing city road congestion. But despite the media hype (or perhaps because... Read more »

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There’s a lot of excitement around flying cars right now – even if they are basically just giant drones. Whether piloted or autonomous, taxis or private vehicles, they’ve been hailed by futurists as the ideal way to reduce journey times across urban landscapes, thus easing city road congestion. But despite the media hype (or perhaps because of it), there are reasons to be skeptical of this vision.

Mobility Lab’s Howard Jennings, is quoted in the article: “The thought of millions of privately owned flying cars should raise red flags, just like personal cars should have decades ago. We’re already learning from projections that driverless vehicles could make traffic worse if we don’t make smart planning decisions and policies.”

The article also notes the demands flying cars could place on the environment.

Mobility Lab’s perspective on this point is that they could produce harmful levels of increased air pollution. Luckily, it seems all of the major players are examining how to make them powered by a hybrid of gas and electric. Battery technology to make flying cars fully electric powered is at the very least a good 10 years away. Noise pollution could be less of a concern because they might be similarly to quiet contemporary drones.

In terms of congestion, we would add that there’s no question airspace is much less congested than most roadways down on the ground, except for near the largest airports across the country. But if all these new aircraft are introduced, there will need to be a whole new level of effective management of skies.

Also see our recent article on whether flying cars might be introduced along the East Coast.

Read the complete article at GreenTech Media

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GMU “blueprint” study suggests avenues for expanding reach of Arlington’s transportation options https://mobilitylab.org/2017/06/08/gmu-blueprint-study-suggests-avenues-expanding-reach-arlingtons-transportation-options/ https://mobilitylab.org/2017/06/08/gmu-blueprint-study-suggests-avenues-expanding-reach-arlingtons-transportation-options/#respond Thu, 08 Jun 2017 13:45:06 +0000 https://mobilitylab.org/?p=22563 This is part one of a two-part series on a report by George Mason University graduate students. Students were tasked by Mobility Lab with creating a new transportation blueprint for Arlington, Va., geared toward connecting more people to its transportation network. This part focuses on passenger transportation – part two will examine freight and deliveries.... Read more »

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This is part one of a two-part series on a report by George Mason University graduate students. Students were tasked by Mobility Lab with creating a new transportation blueprint for Arlington, Va., geared toward connecting more people to its transportation network. This part focuses on passenger transportation – part two will examine freight and deliveries.

Arlington County, Va., has one of the nation’s most connected transportation networks, with nearly every resident living within a half mile of a transit option.

Even still, graduate students of Professor Jonathan Gifford’s transportation policy class at the George Mason University Schar School of Government and Policy have compiled recommendations – based on field observations and interviews – to make it easier for residents to forego a personal vehicle for other transportation options.

The recommendations generally fell into three areas: improving bus service, improving Metrorail connections, and improving transit information through technology.

Making ART bus service better

The report, entitled “Connected City: A Blueprint for Arlington County,” notes that Arlington Transit experiences problems familiar with many fixed-route bus systems: “ART faces service gaps in areas of Arlington County that are the least densely populated. For areas that have a higher population, buses often experience overcrowding.”

The students found that the ART 41, which runs from Columbia Pike to Courthouse, is the busiest route, with 34 percent of all ART trips in the 2015 fiscal year occurring on that route.

On the other end of the spectrum:

ART routes 53, 62, 74 and 92 fail to meet the productivity and cost-efficiency standards [identified in Arlington County’s latest transit development plan]. In 2015, these four routes combined had an operating budget of $1,264,897 (13 percent of the overall operating budget) and 131,397 riders (only 4.7 percent of total ridership). They recovered $116,245 (4 percent) of the $1,264,897 operating costs from riders’ fares in 2015.

So with some ART routes regularly experiencing overcrowding, some routes struggling to maintain ridership, and some areas where service is not convenient, the students recommend that county officials explore ways for on-demand taxi services to complement ART bus service.

Policy should require these partnerships replace underutilized bus routes with private ridesharing companies. It should also restrict service between origin, public-transit access points, and destination. Similar to other cities, cost savings as a result of bus replacement could be used to subsidize travel of passengers, or to low-income households.

More cities are considering similar kinds of public-private partnerships, but actual results have been difficult to come by so far. The report details one example worth following:

Direct Connect in Pinellas County, Fla., allows commuters to take Uber, United Taxi, or Wheelchair Transport to key bus stops and hop on a bus to their final destination. The county pays half of a commuter’s Uber fare (up to $3 per ride) if trips begin and end at designated stops, remain in a designated zone, and occur between 7 a.m. and 7 p.m. Monday through Saturday. The subsidy is applied by entering a promo code in the Uber app. United Taxi is used by those who do not have access to the smartphone apps needed for Uber rides. Its website shows that Lyft will be an option soon. Direct Connect replaces an under-performing route with an average weekday ridership of 26. While it costs  $160,000 to operate the connector, Pinellas Suncoast Transit Authority forecasts costs for Direct Connect to be around $80,000.

Improving accessibility to Metrorail stations

A highlight of Arlington’s “first/last mile” options is the continued enhancement of bike- and carsharing throughout Arlington. But the students see room for improvement by way of Uber and Lyft: for people who can’t incorporate Metro conveniently as part of their trips.

Although some partnerships like this have struggled to succeed – take Bridj’s recent Kansas City program, for example – the students note that partnerships with Uber, Lyft, or other potential providers are still worth exploring and “would not only improve transit service in Arlington County, but could potentially reduce the cost of their public-transit programs.” The report cites examples from several cities to show how this could work:

  • Uber became the official ride-hailing partner of Chicago-area commuter rail agency Metra, with agreements to encourage rides to transit and an Uber payment of $900,000 for ads in Metra stations.
  • Ford’s Chariot vans service fixed routes to transit. It operates in San Francisco, Austin, and Lake Tahoe, with expansion to more cities planned this year.
  • Scoop offers ridesharing for co-workers, and it has a cost structure in place that could be attractive for companies to offer their employees.

Make transit technologies easier for Arlington residents

With technological applications in transportation moving rapidly, the students concluded that access to information is lagging when it comes to learning about and using Arlington’s transportation options.

Mobile networks play a vital role in day-to-day life and real-time tracking of services has become a necessity for busy commuters. Current smartphone applications are constrained by variations in technology platforms and do not allow real-time tracking for all of Arlington County’s transit services. [Uber and Lyft] are also not integrated with these platforms. Mobility Lab’s web-based service, CarFreeAtoZ, has worked toward integration by providing travelers with a comprehensive multimodal trip planning tool. Developing this tool as a mobile application would create greater convenience for commuters.

Whether or not the county should get involved in building an app may be up for debate, but the students explained during their presentation that this could be another area ripe for public-private partnering. Several noted that the Transit app is regarded as a leading real-time information app, and that Boston’s MBTA, for one, has an agreement to promote using it to navigate the city’s system, clearing up the problem of having to choose from many competing apps. The endorsement also allows Transit to work closely with the transit authority on piloting new features.

In a related vein, while Arlington performs TDM outreach through programs that educate residents, businesses, and property managers about existing options, the students recommended that the county could “develop strategies to facilitate two-way dialogue that encourages more public feedback on future transportation decisions.”

The My Arlington app could be more user-friendly in facilitating user feedback (much like how the ArlingtonVA Service Request app allows for the reporting of non-emergency issues) and could incorporate more engaging real-time transit information. However, the students said these apps alone are not sufficient to generate meaningful community engagement. They also noted that more intercept surveys of people at or near transit stations could provide additional input on how to improve Arlington’s options.

Taken together, the recommendations suggest improving access for Arlington residents to transportation options through a combination of better information and service.

Next, look for our summary of the group’s findings on how freight movement impacts congestion in the county.

Photo: People getting on and off an ART bus in Arlington County, Va. (Sam Kittner for Mobility Lab; www.kittner.com)

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Vision Zero video tool analyzes intersections for dangerous traffic conflicts https://mobilitylab.org/2017/06/01/video-tool-intersections-traffic-conflicts-vision-zero/ https://mobilitylab.org/2017/06/01/video-tool-intersections-traffic-conflicts-vision-zero/#comments Thu, 01 Jun 2017 18:33:18 +0000 https://mobilitylab.org/?p=22522 Volunteers will “teach” the program to better identify people walking and biking Despite signing onto Vision Zero, a campaign that aims to eliminate traffic-related deaths and serious injuries, Washington, D.C. and other large cities have struggled to make progress in reducing deaths on their streets. While traffic deaths in D.C. have held steady in the high 20s... Read more »

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Volunteers will “teach” the program to better identify people walking and biking

Despite signing onto Vision Zero, a campaign that aims to eliminate traffic-related deaths and serious injuries, Washington, D.C. and other large cities have struggled to make progress in reducing deaths on their streets.

While traffic deaths in D.C. have held steady in the high 20s over the past few years, traffic fatalities nationwide have increased by 6 percent, just from 2015 to 2016. Traffic safety data, especially, can be difficult to quantify and analyze in support of VZ plans. However, a new tool is in development that will provide planners with insight to better understand where they should target their safety efforts.

Franz Loewenherz, a transportation planner in Bellevue, Washington, has, in partnership with Microsoft and a number of city departments of transportation, developed a video analytics program to evaluate the safety of any intersection with a traffic camera. The program analyzes various road users – cars, bicyclists, pedestrians – in short clips of about 10 seconds, and follows their behaviors. This way, the tool can identify dangerous situations – like near-misses between people on bikes and drivers – and give planners the opportunity to make proactive changes that improve an intersection’s safety before people are hurt.

But before this program can officially generate recommendations, it needs to learn more. Its developers are currently crowdsourcing involvement from volunteers to teach the computer how to better recognize relevant subjects. According to Loewenherz, the program is more than 90 percent accurate in identifying cars, but still struggles with people walking and biking. As participants manually categorize the various objects passing through their frame, they build a baseline knowledge for the computer to automatically determine what it sees more accurately across multiple contexts.

So far, a number of local departments of transportation throughout the U.S. have contributed about 20 intersections’ worth of footage, creating hours of material for participants to catalogue. The platform will display the same clips to multiple people, using the “wisdom of the crowd,” as Loewenherz describes it, to rectify inaccuracies and fine-tune identification. The more people who contribute, the more the program learns, and the better the data planners have to work with.

A sample view of several pedestrians identified within a downtown Seattle intersection.

Gathering proactive data

In analyzing everyday street movements, the program  captures important information about vehicle conflicts that is not necessarily tracked by traditional incident reporting. Loewenherz explains that most agencies “wait for people to become statistics … and generate enough data points” to determine dangerous spots and take reactive safety measures.

On the other hand, Loewenherz says the machine-learning approach should “create a system that provides advance knowledge of how effective changes are” in improving intersections. Most evaluations of safety campaigns, through engineering or enforcement, rely on putting observers at the problem spot to manually track how people on the street act before and after implementation, and only at select times. Not surprisingly, the results don’t always paint a complete picture.

With video analytics, agencies can see immediately what effect their street redesigns and outreach changes have as they’re carried out. In addition, Loewenherz explains that “while [agencies] implement a treatment, they see what approach gives them more bang for the buck” in reducing the number of traffic conflicts, such as choosing between engineering changes or enforcement tactics.

Using protected bike lanes as an example, Loewenherz explained that anecdotal feedback from riders could suggest positive results, but there can be scant data to support that. Creating a program to constantly count how users and behaviors shift after a street design has been changed provides evidence-based insight into the lane’s effects, from which planners can learn.

Loewenherz expects this program will develop a wealth of collective knowledge for participating agencies by creating scalable, accessible, and actionable data from multiple jurisdictions. Ultimately, the data should help cities better learn from each other and better understand how they can eliminate dangerous traffic situations.

Part of the broader solution

“We can’t achieve Vision Zero without this,” Loewenherz claims. Without a proactive model for analyzing their efforts, cities can’t get ahead of dangerous traffic situations, and therefore can only address problems after it’s too late for some people.

“We have a shared responsibility to address this,” Loewenherz explains. Governments, businesses, and citizens are coming together in a concerted effort to prevent deaths and injuries before they happen, and new insights from the video analysis tool could be a crucial step toward achieving Vision Zero.

To try your hand at teaching the analytics program, click here.

Photo, top: A mockup of data generated through the program (courtesy of Video Analytics Towards Vision Zero).

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Cities will need to fight zero-occupant miles with “TDM for autonomous vehicles” https://mobilitylab.org/2017/05/30/tdm-for-autonomous-vehicles/ https://mobilitylab.org/2017/05/30/tdm-for-autonomous-vehicles/#comments Tue, 30 May 2017 19:20:50 +0000 https://mobilitylab.org/?p=22466 The advent of autonomous vehicles is fraught with uncertainty, especially when it comes to their impacts on traffic, travel choices, and the broader transportation system. They offer many potential benefits, but many potential negative impacts, depending in part on how they are deployed. While widespread adoption may still be decades away, significant numbers will begin... Read more »

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The advent of autonomous vehicles is fraught with uncertainty, especially when it comes to their impacts on traffic, travel choices, and the broader transportation system.

They offer many potential benefits, but many potential negative impacts, depending in part on how they are deployed. While widespread adoption may still be decades away, significant numbers will begin to be on the roads in less than 10 years, according to manufacturers and other observers. Ultimately, many expect them to have major transformational effects on our transportation systems and built environment.

Today’s policymakers have an opportunity to implement plans that will guide the efficient usage of AVs and rider choices that may affect us for generations. To do so, it’s worth considering AV impacts as a potential transportation demand management problem – and preparing TDM-type policies to address them.

When it comes to the most pressing issues to be addressed in the deployment of autonomous vehicles, safety and infrastructure do not necessarily top the list of urgent needs. Federal and state policies are already looking to address these. Since safety is one of the major motivations for adopting autonomous technologies, and a top concern for skeptical consumers, agencies and automakers are prioritizing it. Either they will be made safe, or they won’t be on the roads.

Meanwhile, the exact impacts to communities and traffic systems are poorly understood, and have not been addressed in the ongoing conversation to the extent that they should be. Ironically, the efficiency of AVs has long been touted as a solution to traffic, but new research is beginning to suggest that AVs will, in fact, generate more of it. Simply put, there is no guarantee the traffic effects of AVs will be handled. It is entirely possible that they will spread widely and, without adequate policies, many places may never manage their impacts. We never fully anticipated the impacts of conventional cars as they were being developed, and we have been living with many unintended consequences in the form of our communities for the last 100 years.

What we do know is that AVs will create an unprecedented convenience in driving. By eliminating most of the hassles of driving, such as parking and lost productivity time, AVs will induce not only more trips, but longer ones. Additionally, AVs waiting to pick up new riders will add “deadheading” miles. For traffic, the only thing worse than a single-occupant vehicle is a zero-occupant vehicle. Placed all together, this suggests they will almost certainly increase vehicle-miles traveled, energy use, and emissions. These impacts might be locked in by further sprawl and other shifts toward less efficient land-use patterns.

google AV - Phil Hollenback

How people start to use AVs will matter in terms of the traffic impacts they create. Personal autonomous vehicles, according to a landmark 2015 Urban Mobility study by the International Transit Forum and Corporate Partnership Board, will generate up to 35 percent more VMT than conventional personal cars. Those in a shared “fleet” model would generate less. Meanwhile, AVs in a taxi model, carrying single passengers all the way to their destinations, would create 90 percent more VMT than typical taxies. Using those taxis as a connection to transit with multiple passengers, however, would only produce 6 percent more VMT.

To avoid the worst of these traffic scenarios, policy needs to be deployed with an eye towards minimizing the added miles and the demand for situations involving zero-occupant vehicles.

When it comes down to it, the demand guiding AV impacts is a hybrid of a person’s choice, as in their decision to initiate the trip, and the self-driving technology itself. Both together could be regarded as the typical “commuter” of modern TDM thinking. Whereas traditional TDM focuses on commuter choices, AV TDM might address the ways in which the AV technology is employed and how those cars carry passengers.

In short, policymakers should adapt transportation demand management principles to autonomous vehicles, using a mix of incentives and disincentives to guide choices.

As with TDM best practices, a few ideas should form a hierarchy of priorities for states, cities, and transportation agencies. First off, policies should always seek to encourage AVs that move more people in fewer vehicles. While the driverless technologies make point-to-point drop-offs possible, the realities of cities and highways means that they simply cannot accommodate one AV per person.

Second, similar incentives should be in place to guide people and employers towards more efficient choices. The deployment and pricing models offered by automotive and tech companies should be structured to make shared AVs, not personal AVs, the model of choice. This is a complicated endeavor, but important to the success of AVs in providing improved mobility and not increased congestion. As mentioned above, AVs that feed into transit systems create the lowest amount of VMT and, in many cases, might expand the reach and usefulness of those transit systems. Current TDM policies, such as employer transit benefits that make transit more affordable and useful to commuters, might help guide their use of AVs as a complement to transit, too.

Lastly, policymakers should seek to create pricing policies in anticipation of the traffic-inducing effects of personal AVs. The program might be created in escalating prices, as to disincentivize the least efficient choices. A VMT fee would discourage longer trips in general, while a higher single-occupant fee would encourage AV riders to share rides. Lastly, a zero-occupant fee, addressing the miles added by AVs circling between pick-ups or headed home to park, would warrant the highest fee. “ZOV” miles represent an entirely new congestion danger, as they may be generated from the mere convenience of AV owners asking their cars to circle while they pick up groceries, but can add up to significant traffic consequences.

The national dialogue around AV policy is a unique chance to rethink how we prioritize our transportation systems and the incentives within it. A century ago, when the internal combustion engine automobile began to proliferate, cities missed this opportunity to guide how they affected communities.

Rather than adapting places around AVs, modern policies need to shape AV usage and behaviors to keep building better communities.

Photos: Top, an autonomous Uber test vehicle in Pittsburgh (Foo Conner, Flickr, Creative Commons). Embedded, a Google AV on a California highway (Phil Hollenback, Flickr, Creative Commons).

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Analysis suggests autonomous transit would be most efficient use of AV technology https://mobilitylab.org/2017/04/27/autonomous-transit-technology-art/ https://mobilitylab.org/2017/04/27/autonomous-transit-technology-art/#comments Thu, 27 Apr 2017 14:42:37 +0000 https://mobilitylab.org/?p=22139 Authors make the case for employing AVs in ways to minimize VMT increases Mobility Lab has often stressed the importance of autonomous vehicles being introduced as fleets rather than personally owned, so what might those fleets look like? How would this emerging technology be applied to the transit solutions already known to work? If autonomous rapid transit –... Read more »

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Authors make the case for employing AVs in ways to minimize VMT increases

Mobility Lab has often stressed the importance of autonomous vehicles being introduced as fleets rather than personally owned, so what might those fleets look like? How would this emerging technology be applied to the transit solutions already known to work?

If autonomous rapid transit – also referred to some places as “ART” – became widely used, it could reduce vehicle-miles traveled and limit the associated impacts of private AVs. Imagine small buses and shuttles as a new form of transit, moving along in dedicated lanes or car-free city centers.

As Peter Calthorpe and Jerry Walters write in their article on the Urban Land Institute’s Urbanland blog, “Autonomous Vehicles: Hype and Potential,” autonomous rapid transit could be just that: a low-cost, 24/7 service, that avoids meandering miles and miles without passengers (as AV taxis might operate, on their way to pick up passengers).

Further, autonomous transit could be like bus rapid transit, but without the cost of paying for a driver. It could also, according to Calthorpe and Walters, run more efficiently by “tailoring capacity by time and place to match demand,” could cut travel time, and could function more like an on-demand service during off-peak hours. On-demand service during off-peak hours would reduce inefficient low-occupancy service, eliminate late-night shut-downs, and allow the service to operate 24/7 without ever running zero occupancy vehicles.

Calthorpe and Walters cite an unpublished study by their consulting groups Fehr & Peers and Calthorpe Associates that explores the option of replacing proposed BRT along Geary Boulevard in San Francisco with ART. In two dedicated lanes, the authors imagined replacing buses with platooning fleets of four-person AVs, which would gather three or four passengers and take them to their destinations, skipping unnecessary bus stops along the way.

In the end, Calthorpe and Walters suggest ART reduced travel times by 35 percent compared to the BRT proposal, and by 50 percent compared to private vehicles in their corresponding lanes. Rush-hour ART could also carry as many as 3,000 to 4,000 people each hour, the same as current international BRT systems. That’s more than five times the capacity of an urban car lane, they write.

ART could also attract riders more accustomed to driving themselves rather than taking transit, given its relative privacy, direct-to-destination service, and shorter travel times.

Addressing autonomous tech’s benefits and consequences

While ART sounds like a great transit option, there’s much we still don’t know about the technology behind it. Applying autonomous possibilities in a transit context, even early on, could be important because widespread use in personal vehicles carries the high possibility of traffic and sprawl-inducing effects.

Personal autonomous vehicles are generally known for their potential to operate well with other AVs, syncing to move as a so-called “platoon” and working together at intersections. But throw in bikes, pedestrians, person-driven cars, motorcycles, and everything else, and what do you have? Inefficient traffic flow and more congestion, say Calthorpe and Walters. More research is confirming that personal AVs could worsen traffic nightmares.

Induced trips could be added in the form of, for example, trips taken because the stress of driving is no longer a factor, empty cars running errands for people, and having “zero-occupancy vehicles” picking up people. Calthorpe and Walters say this increase in VMT could cause sprawl.

In a taxi model, AV cars then could also roam in between passengers, ratcheting up VMT per passenger. So high, that in the next 30 years, it would exceed the past 30 years’ rate of VMT growth by five times.

But if AVs are shared and used as mass transit connections, they might actually lower VMT. This is where the efficient transit function that Calthorpe and Walters put forth pays off.

“There are a lot of positives to an AV transit-like fleet,” said Paul Mackie, Mobility Lab’s communications director. “For one, they could make access to society a lot easier for people who can’t drive, like some seniors and those with disabilities.

“If we can take some of the people who currently drive alone and make it easy for them to instead take autonomous rapid transit straight to work or at least to a bus or train, then those who are driving will be a lot less miserable in traffic. Given the high cost of personal AVs, governments will have the time to figure out how this transportation system of the future is going to work.”

Photo: A bus passes a pedestrian on Geary Boulevard in San Francisco, the focus of Calthorpe and Walter’s analysis. (Gabriel White, Flickr, Creative Commons).

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Biking in Arlington gets a boost from Safetrack and warmer winter weather https://mobilitylab.org/2017/04/18/biking-arlington-gets-boost-safetrack-warmer-winter-weather/ https://mobilitylab.org/2017/04/18/biking-arlington-gets-boost-safetrack-warmer-winter-weather/#respond Tue, 18 Apr 2017 19:21:06 +0000 https://mobilitylab.org/?p=21964 Has there been an increase in biking in Arlington due to Washington D.C.’s region-wide SafeTrack initiative to repair Metrorail? It’s a difficult question to answer at this point. BikeArlington has already reported that there were increases up to 75 percent over 2015 daily averages in bike traffic at the Rosslyn-Custis Trail bike counter during the... Read more »

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Has there been an increase in biking in Arlington due to Washington D.C.’s region-wide SafeTrack initiative to repair Metrorail? It’s a difficult question to answer at this point.

BikeArlington has already reported that there were increases up to 75 percent over 2015 daily averages in bike traffic at the Rosslyn-Custis Trail bike counter during the first surge back in June 2016.

How much were this and other increases caused by SafeTrack or simply a product of a trend of bicycle traffic building up steadily over the years?

I took a look back at 2013, 2014, and 2015 data (see the graphs I created at the bottom of this article) in order to compare cycling daily averages from these times to the SafeTrack surge averages in 2016 and 2017. I controlled for weather to some extent, since it has such a significant impact on cycling and walking.

It seems that the only major difference from previous analyses is that increases in later surges are attributable to trends over the years of increasing winter ridership.

For the Surge 8 through 11 time period (in 2016, from August 27 to December 20), trail use had shown a decrease over the same time period from 2013 to 2014, but then it steadily increased after 2014 (except during Surge 9 on the Mount Vernon Trail). This could be attributed to some of the increase in winter ridership during SafeTrack to overall increasing trail use since 2014.

Ideally, this is the desired effect too. As transportation options become more plentiful and more well known, it makes sense that, over the years, cycling numbers increase.

Looking at the Surge 12 (which ended in February 2017) time period, however, all previous years showed a decreasing trend, with the SafeTrack surge creating quite an increase in ridership, going above even the 2013 numbers. Part of this can be attributed to an unseasonably warm February.

How much of this increase can be attributed to SafeTrack versus summer-like weather?

In the fall, trends stay fairly steady. SafeTrack caused quite an increase in traffic, and David Patton, Arlington County’s bicycle and pedestrian planner, says, “[Over] seven years of data for [the Custis Rosslyn bike counter], there is about a 3.5 percent compounded increase [for bikes]. It’s not a straight line – highly conditioned by weather – but on a slow upward trend.”

Henry Dunbar, program director of Bike Arlington, added, “It’s really difficult to pinpoint how much direct effect SafeTrack had on bike ridership. A lot of the original mode switching likely went back to riding Metro after the early surges proved to be not that disruptive, but we won’t know for certain until some more in-depth surveys are done. For now, the bike counter data alone can only tell us so much.”

The pattern over the years is very curious too: decreasing ridership in the summer, followed by stable ridership in the fall, and increasing ridership in the winter, until January.

Stable and increasing ridership are understandable, as Americans become more multi-modal.

The decreasing summer trends are questionable, also because they are not steadily decreasing. This means that there could be an anomaly in one of the years that is causing this shift. Is it really decreasing as people choose not to bike, or is it all due to external factors not accounted for?

The patterns surrounding Surge 12 are quite curious as well. The initial surge was thought to have caused such a large increase due to its novelty, but Surge 12 has none of this novelty, and compares in magnitude to the increase of Surge 1.

“This is interesting,” said Dunbar. “I have to wonder if that wasn’t aided by a stretch of really nice weather.”

W&OD Cyclists

W&OD Bon Air West Counter Cyclists

Rosslyn-Custis Cyclists

Rosslyn-Custis Counter Cyclists

Mount Vernon Trail Cyclists

Mount Vernon Trail South Airport Counter Cyclists

Photo: Capital Bikeshare user in Arlington by DOT DC; Graphics by Angela Urban.

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WMATA Metrobus data projects explore effects of fare payments, disruptions https://mobilitylab.org/2017/04/18/wmata-bus-techies-data/ https://mobilitylab.org/2017/04/18/wmata-bus-techies-data/#respond Tue, 18 Apr 2017 18:23:23 +0000 https://mobilitylab.org/?p=21941 Other presenters at Transportation Techies’ Bus Hack Night shared projects to help riders better understand their local bus routes Though the D.C. region has one of the busiest bus systems in the country, with more than 120 million trips in 2016, it’s still part of the nationwide movement to stem recent bus ridership declines. As such, WMATA is... Read more »

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Other presenters at Transportation Techies’ Bus Hack Night shared projects to help riders better understand their local bus routes

Though the D.C. region has one of the busiest bus systems in the country, with more than 120 million trips in 2016, it’s still part of the nationwide movement to stem recent bus ridership declines. As such, WMATA is looking to better understand how to provide reliable, efficient service that keeps daily riders and draws others back.

Catherine Vanderwaart of WMATA’s Office of Intermodal Planning is working on just that. Speaking at Tuesday’s Transportation Techies meetup, “Bus Hack Night,” she presented a wide range of findings pulled from multiple aspects of bus performance and rider behavior.

bus transaction time - wmata

Chart by Catherine Vanderwaart, WMATA

Vanderwaart presented the time costs of fare payment and her findings that tapping a SmartTrip card averages two to four seconds per transaction. The time it takes passengers to pay by cash or reload their card varies widely, however, taking anywhere from 10 to 60 seconds per person, which can impact a bus’s dwell time at a stop, and therefore its overall performance. Because this dwell time accounts for 19 to 25 percent of a bus’s run-time, according to another WMATA staff member, speeding up the payment and boarding process could make a noticeable difference along some routes.

Given its unique service changes, WMATA’s ongoing SafeTrack campaign has provided abundant information on how riders react to disruptions. Vanderwaart’s office has collected data on the shuttle buses (called “bus bridges”) that connect closed stations to better understand how to deploy them. Since, prior to SafeTrack, self-reported data only existed on established routes, the agency at first faced delay issues with its shuttles, but eventually established methods to automatically track shuttle ridership. With more robust tracking during each surge, WMATA now has a better sense of how to space out the bus bridges and improve their service.

surge 4 shuttle times

A day of shuttles from Surge 4. Chart by Catherine Vanderwaart, WMATA.

Vanderwaart also presented lessons from last year’s system-wide rail safety shutdown, which provided a unique chance to examine reactions on bus ridership. Using anonymous SmartTrip data from the previous 30 days as a baseline for typical ridership, Vanderwaart compared it with those riders’ behaviors during the shutdown to determine how people shifted their commutes. Those who typically combine bus and rail dropped out of the system that day – avoiding transit or working remotely – but a large number of new or infrequent users tried the bus. Overall, Metrobus saw 20,000 more riders, a 5 percent increase, than on a typical day.

Turning around bus performance

JD Godchaux, of civic tech group NiJeL, worked with TransitCenter to convert New York MTA buses on-time performance into an advocacy tool for better bus policy. Bus Turnaround NYC collects historical data on every bus route in New York and provides a performance report card. These categorize the problems facing the Metropolitan Transportation Authority’s bus system and help explain why it is losing ridership despite a growing population. Now, Bus Turnaround is developing report cards for the buses of every elected official’s district in the region, to draw attention to the need for a better bus network and the ways to fix it.

Back in D.C., the District Department of Transportation’s District Mobility project has helped to visualize the broad concepts of congestion and reliability and their effects on accessibility. The site’s tools show the most crowded roads, bus routes, and even individual stops, as well as on-time performance in an effort to define and measure the idea of urban mobility.

What’s in a wait?

On the ground, there are a number of tools in development to help passengers understand the services available to them and how long one can expect to wait for a bus.

  • Michael Eichler of WMATA shared Metrobus Explorer, which maps the Metrobus system and shows users how they can navigate it from any point. By selecting an individual stop, or drawing a box around a group of them, users can identify routes and the frequency of buses at each location and get a sense for how the tangle of lines translate into bus lines.
  • Mobility Lab’s Michael Schade built a similar tool that maps all of the region’s transportation operators. Users can select agencies to see their service area, and select individual routes to highlight and to pick out their stops in order to see how they fit into the region’s larger transportation network. Schade built this using MapZen’s Transitland project, a “community-edited data service” that aggregates the feeds of transportation services around the world, which MapZen’s Dave Nesbitt briefly demoed.
  • MetroHero, Max Grossman, and Daniel Turse are all building tools to estimate bus wait times and when to expect them. Turse’s wait-time tool uses PlanItMetro’s historical data, which includes bus positions but also time between stops, dwell time, and what every bus did at every stop, such as skipping one. With that, the tool helps users determine how wait times vary for any route across the region and by time of day.
  • Grossman’s DC Latebus uses WMATA’s live bus position information to visualize bus lateness along every segment of a route. By comparing arrival times at each stop to the published schedule, the tool measures median deviation to show which parts of every route are most likely to bog down your bus. Grossman and Turse’s projects launched a discussion of how to measure bus delay, especially taking into account how riders might ignore schedules and focus more on frequency.
  • MetroHero‘s bus-tracking tool, a beta webpage in the same fashion of their original Metrorail app, shows current bus positions along their routes, and allows users to click on each one for performance information. Users can also click on specific stops to see estimated arrival times, and how many stops separate them from each predicted bus.
  • Ranjani Prabhakar of Fehr & Peers dove into the gritty details of traffic planning by explaining the Poisson Distribution that planners can use to predict the probability of events over time, such as if cars traveling behind a bus might be backed up into the “upstream” intersection. By understanding the flow of traffic on any stretch of road, and how buses travel along them, planners can work out the likelihood that a bus stop’s location will cause nearby vehicles to actually increase congestion.

Photo: A Metrobus picks up passengers in Rosslyn, Arlington, Va. (Sam Kittner for Mobility Lab, www.kittner.com).

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A visualized day of New York’s transit options, working together https://mobilitylab.org/2017/04/11/nyc-visualization-transit-options/ https://mobilitylab.org/2017/04/11/nyc-visualization-transit-options/#comments Tue, 11 Apr 2017 19:54:48 +0000 https://mobilitylab.org/?p=21882 New York City is blessed with a lot of ways to get around town. From MTA buses to regional Metro-North rail lines to the omnipresent subway, the overall transportation system moves millions of people every day. A new visualization puts 24 hours of them together, showing how each works together in the broader context over... Read more »

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New York City is blessed with a lot of ways to get around town. From MTA buses to regional Metro-North rail lines to the omnipresent subway, the overall transportation system moves millions of people every day.

A new visualization puts 24 hours of them together, showing how each works together in the broader context over the course of a day.

Multimodal Symphony from Will Geary on Vimeo.

Will Geary, a graduate student at Columbia University, recently constructed the video by incorporating transit data from a number of sources. Speaking with John Metcalfe of CityLab, he explained how, depending on the option and the availability of the transit data, some of the sets were taken from schedules, while others were real trips.

“Data on taxi and Citi Bike trips are drawn from a single day in 2015, and most of the rest he obtained via schedules downloaded from various transit agencies. ‘So this is static data according to the timetables, not real-time data that would reflect delays or deviations from the schedule,’ he says. ‘It is also worth noting that information is only available on the pickup and drop-off locations for each taxi and Citi Bike trip—not the actual route taken—so the visualization simply draws a straight line from point A to point B.'”

In the transportation demand management industry, programs emphasize “transportation options” in spreading out the demand for streets across many different modes, from transit to vanpools to bikes.

What Geary’s visualization captures is not only the origins and destinations of that demand (typically from the entire region into Manhattan, and also a steady stream to and from the three airports) but also how the different modes complement each other. Northeast Regional Amtrak trains bring commuters into midtown from New Jersey and Connecticut, while buses fill in gaps in the outer boroughs. Other options, like the barely-visible navy bikeshare dots, provide options for unique shorter trips where a bus may not make sense.

While few other cities have the spread of transit options New York does, it’s enlightening, and even fun, to see the system working in a broader sense.

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