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Mobility Management and the Smart Use of Technology

by Chris Zeilinger, Community Transportation Association of America

How do we make the best use of technology in mobility management? That’s an important question, and was one of the themes running through a May 2016 workshop held by the U.S. Department of Transportation and the Intelligent Transportation Society of America on “The Impact of Technology on Demand-Responsive Transportation in the Era of Smart Cities.”

As could be expected, much of this workshop revolved around trending topics in transit technology, such as mobile interfaces, gamification, open-source systems for data exchange, etc. But there also was an undercurrent that touched on the basics of transportation technology, and it’s these basics that may augur the greatest future potential for mobility management.

Four of these basics become readily apparent. They are (a) route optimization, (b) traveler information, (c) transactional data, and (d) personal data and privacy. Let’s take a quick look at each of these.

Route Optimization

For nearly 200 years, variations of the “traveling salesman problem” have provided a creative challenge for planners, system designers, researchers, and programmers. The problem, if it’s not familiar to you, is how to find the shortest possible route for connecting a large number of points with a minimum of duplication; in the transportation world, this is realized as the desire for optimally routing vehicles through multiple destinations. It’s a problem that defies easy solution, and is something of a “holy grail” in software and programming circles—transportation and otherwise, as achieving this suggests significant cost savings and efficiencies may be realized. There’s a certain bit of truth to this, as machine-optimized routing of vehicles often is 5–10% more efficient than manual vehicle routing. Still, systems are well advised to compare the costs of software to the cost-savings of any efficiencies gained.

Traveler Information

The advent of mobile data technologies has been one of the most exciting fields of development, at least for the users of transit services. Most fixed-route transit services now have their schedule information available for user interaction through the transit feature on Google Maps, or any other platform using the General Transit Feed Specification (GTFS) format for transit route data. In the mobile data environment, third-party products such as those of moovel (a subsidiary of the European auto company Daimler AG) or TransLōc, plus myriad other mobile data applications specific to metropolitan areas, are placing more and more real-time information on transit service and options at the fingertips of transit users.

Companies such as Lyft, Splt, and Uber have shaken up many things around the traditional methods of interacting with demand-response transportation. One of the avenues of disruption has been the way in which these companies and others like them provide real-time information to customers on the vehicle locations and even descriptions of the vehicles and the drivers, so that customers standing on a busy curbside aren’t left wondering which vehicle is the one they’re seeking to ride. From an algorithmic point of view, the one-to-one spontaneous trip arranging such as traditional Lyft and Uber services is complex, but even more complex are spontaneous arranging of trips where one vehicle may be taking different people between diverse origins and destinations at the same time, such as the service model of Bridj, which has begun exploring service partnerships with traditional public transit agencies in Kansas City and elsewhere.

Most of these mobile data platforms have been specific either to individual companies, or tied to specific modes, primarily transit (although one could argue that Google’s Waze app is a rapidly expanding form of real-time traveler information specific to the highway sector). Truly useful traveler information would transcend individual modes, so that the user of a mobile phone app or a website not only gets schedule and status information of specific modes or providers, but also is able to determine which mode is most desirable for the journey, even allowing for the preferred mode to be walking or using one’s personal bicycle. So far, RideAmigos appears to be one of the few significant players in this trans-modal space, but it seems like an environment that can be of growing attractiveness to more planning agencies, local governments, mobility managers and others with mode-agnostic interest in mobility. Another approach is that taken by moovel’s “RideTap” service, which is a mobile phone app that actually is an aggregator of participating entities’ own apps, made more seamless through the RideTap integrator.

Transactional Data

Even though we’re well into the 21st century, many users of traditional taxi and transit services feel that their transportation providers remain mired in some antediluvian modality, at least where fare payment is concerned. This is an age where cups of coffee can be purchased with the tap of a smart phone, where parking meters take credit cards and provide exact information on pricing and time limitations, where public libraries will let customers pay their overdue book fines on Apple Pay, PayPal, or credit. However, the transit fare payment technology continues to be based on cash and coin, slowly growing to credit/debit card acceptance, proprietary magnetic stripe cards, and the use of smart card technologies. And in the taxi industry, cash remains king, with most taxi operations reluctant to accept credit/debit cards, never mind other fare payment media.

Although these legacy approaches of fare payment are rugged and reliable, they carry their own challenges. For one, customers don’t like them, now that we are in an era when more and more people are essentially cashless, relying on cards and electronic payment media for everyday transactions. A second challenge is that cash always carries the risk of theft and fraud. For a third thing, the costs of handling, securing, and accounting for cash are pretty significant, even in a small organization. And fourth, the time that customers spend queued up at a farebox trying to find exact change adds significantly to the amount of time buses dwell at bus stops, which may worsen the public’s existing experience of transit as an undesirably slow mode of mobility.

In addition to improved customer satisfaction, there are other reasons why transit providers may want to examine the full range of current payment technologies. As alluded to above, there may be reduced administrative expense and reduced risk of fraud or theft. Moving away from cash-centered technologies to electronic media makes it easier to participate in fare arrangements involving multiple providers, such as the Puget Sound Orca card, the San Francisco Bay area Clipper card, or the Boston area Charlie card. Electronic media also make it easier for employers and workers to participate in pre-tax commuter benefit programs under Section 132(f) of the Internal Revenue Code, and offer increased potential for other third-party payers to use these media as virtual vouchers for transit benefits as part of social service, workforce development, or medical transportation programs.

While not always that advanced, there’s a very important reason that drives most transit agencies’ decisions about their uses of technology: the most valuable technology is that which helps the organization get paid, whether it’s the interface between the agency and those programs to whom it sends bills for service (such as Medicaid agencies or their brokers), or between the agency and its funders in state, local, or federal government agencies. Good, reliable billing and reporting systems that track those data elements from which payments are made do much for the transportation provider’s bottom line.

Travel Data is Valuable Information

There’s a reason why Google has dominated transit trip planning through its Google Maps service, and there are reasons why both Google and the Chinese technology firm Baidu have invested hundreds of millions of dollars in Uber, or why Alibaba (another Chinese technology firm) has invested millions in Lyft. The business aspect of the whole “transportation network company” sector is notable: these firms have almost no tangible assets – they own no rolling stock, no buildings, no other infrastructure – and yet have a collective market valuation of around $80 billion. The value of these investments does not lie in the innovative provision of transportation information or services; rather, the value is in knowing the habits, travel patterns, and interests of a rapidly expanding body of users—people whose information is of immense interest to advertisers and purchasers of consumer data.

In short, technology is bringing some revolutionary new concepts to public transportation and mobility management, but this change may not be what was first expected. What we’re seeing is that there is a lot of value – and a lot of creative new approaches – in providing more integrated traveler information services, including travel alternatives across multiple modes, the ability to request and arrange spontaneous transportation services, and the ability to integrate payment with the trip-arranging process. What’s more, these services are available to anyone with a computer, tablet or smart phone, and can be available to third-party trip arrangers, such as mobility managers, family members, case managers, social workers, or others.

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This post was written by on August 12, 2016 7:34 am

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