4. Technology & transportation

The Transportation Technology Stack

The transportation technology companies’ plans to dominate markets across geographies and transportation options would not be possible without the growth and interoperability of the transportation technology stack.

The stack provides location information on demand and allows users of city transportation systems to find out where they are, choose where they want to go, and pick a way to get there.

The stack is not fully integrated and currently traverses several companies, but it is also mov-ing from better interoperability to vertical aggregation.

The common goal seems to be to make navigation and transacting for urban transportation by any mode as seamless as possible for the user. The question up for grabs is, “Who will own and dominate the stack?” and thereby own the customer and the market.

Figure 6: The Transportation Information Infrastructure Stack


Nearly 20 years ago, Zipcar and Flexcar introduced by-the-hour car sharing to cities in North America. The two companies launched separately in 2000, from separate sides of the continent. The car-sharing services were premised on not needing to own a car, because you can have “wheels when you want them.”[13]

Car-sharing’s implied promise of not needing to own a car (or at least a second car) was probably the first major step in the disruption of the then existing paradigm of urban transportation.  Either you owned a car (or rented a car) or you took public transportation. Short-term car-sharing provided a new option. Zipcar and Flexcar were also the harbingers of how innovations in information technology would drive radical changes in mobility.

The idea of car-sharing and short-term car rental was not new[14] but where older models had come and gone, Zipcar and Flexcar found a path to growth and rapid adoption. They found a path by deploying digital technologies that were, at the time, just becoming ubiquitous: the web via the mobile internet.

What powered each service was a digitized online map and devices that could share a precise enough location on that map. This allowed customers to find and book the cars nearest to them. The business model was enabled by radical changes in how information was received, processed, and delivered.

The web, delivered faster via cable internet (no more dial-up) –and later by cell networks, allowed car-share members to select and book cars on short notice and with no paperwork. Radio transceivers and wireless data links allowed the companies to send commands remotely—for example, to verify radio-frequency ID (RFID)-equipped[15] membership cards and to unlock or even turn off the car. Text messaging (or SMS) provided two-way communication without need of an intermediary. The company could notify the member, and the member could extend reservations or log complaints over SMS.

Alongside these technologies grew:

  • the mobile internet[16];
  • commercial global positioning system (GPS) services;
  • digital geographic information systems (GIS);
  • smartphones;
  • web-based maps;
  • app ecosystems;
  • mobile payment gateways;
  • RFIDs and near-field communications;
  • general transit feed specification (GTFS);[17] and,
  • a host of other mobile and location technologies.[18]


These innovations transformed transportation through layers of information services that were as important, if not more so, than the physical vehicles that conveyed the service. Technology upended the traditional models of vehicle ownership, and afforded users more travel choices that fit their needs and lifestyles.

In the years since the two car-sharing companies launched, more new services were built on these technologies and more new companies emerged. Each new entrant sought to change the way people got around the city. Because these new services did not quite fit into existing regulatory categories, most cities were caught unawares as new mobility offerings just showed up on the streets.

As each new service arrived, municipal departments of transportation scrambled to make rules. Cities tried outright bans or created new permits, new regulations, new fees. None of these efforts came easily. Each was debated and contested. What was clear though was the blistering pace of adoption. People took to these new services. Cities were forced to adapt.

The new services were not without upsides for cities. There was the promise of reducing private vehicle use and maybe congestion. The underlying location-based information technology also held out the potential of providing insights on how vehicles and people moved across the city—a degree of granularity previously unavailable for transportation planning or traffic management purposes. So there were new debates around access to mobility data. Cities soon began requiring access to the information in return for permission to operate on the streets. All of this is still being litigated.

This year, a consortium of city transportation agencies, including Seattle and led by Los Angeles DOT, developed the mobility data specification (MDS). The specification is “comprised of a set of Application Programming Interfaces (APIs) that create standard communications between cities and private companies to improve their operations. The APIs allow cities to access data that can inform real-time traffic management and public policy decisions to enhance safety, equity, and quality of life.” The consortium of cities also formed the Open Mobility Foundation (OMF), “an open-source software foundation that creates a governance structure around open-source mobility tools, beginning with a focus on the Mobility Data Specification (MDS).”

OMF and the MDS could just be the next salvo in the running battle to regulate the urban transportation network through information. Two decades since the advent of web-enabled car-sharing, continuing innovations in technology (with the rapid developments in machine learning and artificial intelligence) promise even more innovation and disruption in urban mobility. And even more battles around data access, ethics, privacy, surveillance, and equity.


If the year 2000 was the birth year of new mobility disruption, the year 2007 was the year of the growth spurt. The iPhone, the App Store, Google Maps, and Open Street Map all launched in 2007. The mobile web on iOS and then Android OS[19], powered by apps, made car-sharing even more convenient and memberships skyrocketed.[20]

In 2007, Paris also launched Vélib’, a 6,000-unit public bike-share system. The service was run as a concession funded by advertising. Other cities would soon copy the service and the business model and docked bike-share systems soon became a feature of most large American cities. Each city’s service was also funded either by private advertising or through public-private partnerships.

The pace of change also accelerated in the business space. Just seven years after their launch, Zipcar swallowed up Flexcar. Later, Avis would buy up Zipcar while the other incumbents in the car-rental market launched their own short-term car rental services with varying success.

The years 2012 and 2013 saw the launch of new ride-hail services Uber and Lyft.[21] Taxi and limousine services lost ground and taxi-medallions (the permit to operate a taxi) lost value. In New York City, the price dropped from a high of $1,000,000 per medallion in 2013, to just $650,000 in 2015.[22]

In 2016, app-enabled dockless bike-shares began showing up on city streets. A myriad companies, the largest ones coming from China, appeared seemingly overnight and deployed millions of bikes across cities in North America and the rest of the world.[23] Two years later, startups like Bird introduced shared electric kick scooters (a.k.a. e-scooters) to city streets.

Meanwhile, Google’s Self-Driving Car Project[24] (a.k.a. autonomous vehicles or “AV”)—which it launched in 2009—also began testing autonomous vehicles directly on city streets, often in partnership with local and state governments. Other companies would soon follow suit. (While the hype is waning, the numbers of AVs on the road and the services that provide them will likely only grow in the coming years.[25])

This year, established aviation companies like Boeing and Airbus, alongside ambitious startups, began testing urban air transport via passenger carrying unmanned drones, i.e. “flying AV taxis.” Clearly they see potential. One study estimated that there was a global market worth $318B that will grow between now and 2040.[26])

Drone deliveries, by land or air, have also debuted on city streets. This is on top of the explosive growth of urban goods deliveries, driven by online commerce sales paired with same-day or next day delivery service. Delivery companies are contemplating combining autonomous road vehicles with legged robots for doorstop drop-offs.

The market also continues to consolidate and the game continues to change. The private-sector actors[27] moved beyond their starting modes and are working to insert themselves at every transportation choice a user makes. Uber and Lyft have grown rapidly as ride-hail companies but each has acquired bike-share companies and rolled out e-scooters. On the promise of more growth, they raised more than a combined $10 billion when they launched their initial public offerings.

Bird, the company that introduced kick e-scooter services, is rolling out a seated scooter that looks very much like a pedal-less e-bike. Lime, which started as a dockless bike-share service expanded into e-scooters and now offers car sharing. Meanwhile, many of the original dockless bike share players like Mobo and oFo have folded and left the market.

All the private actors are now engaging public transportation and negotiating service deals (where on-demand service replaces low-volume transit routes) and/or payment options through their apps. Uber’s CEO declared that the company wants to be the “Amazon of transportation,”[28] referring to the market dominance of the online retailer.

But the risks of company and market failure are also growing. In August of
2019, Uber reported a net loss of $5.2 B just for that quarter. Lyft lost $644 M in the same period.[29] ReachNow, a car-sharing company, abruptly shut down when it’s owner, BMW Group, entered into a new mobility joint venture with Daimler Benz that owned Car2Go.

Reports said, “The closure was so abrupt, ReachNow included instructions for
customers [in the middle of] driving one of their free-floating BMWs at the
time they received the email.

‘If you are in an active rental, do not fear,’ the email said. ‘Please end your trip in the coverage area as normal when you are done.’”[30]

As in any disruption, the ground shifts underneath and the system becomes fragile, leaving travelers in the lurch.

Further Frames for Information Technology

Given the history of recent disruptions and innovations and given the structure of the technology stack every technology project that SDOT undertakes should be assessed using the frames of privacy, equity, safety and security, and resiliency. These frames must apply particularly for systems that push out information to the ecosystem. We discuss each frame below.


With more and more data being collected and analyzed about our travel behaviors, it’s becoming increasingly important to “balance the need between gathering information to provide needed services and protecting the public’s privacy.”[31] At no point should travelers, knowingly or otherwise, have their right to privacy threatened or compromised through the release of personally identifiable information. As caretakers and managers of Seattle’s public right of way, SDOT has a responsibility to safeguard traveler privacy. We will develop policy and regulations around privacy in partnership with both the public and service providers.

SDOT is mandated by municipal code to collect data essential our mission “to deliver a transpor­tation system that provides safe and affordable access to places and opportunities,” and as data becomes more extensive and precise, the information infrastructure managed by SDOT must value and prioritize traveler privacy to be a trusted, secure public service.[32]

In Seattle, policies are currently in effect requiring any proposal for new procurement of data to undergo a privacy assessment, and resources are provided to ensure privacy protections are embedded from the start. Privacy champions in each city department act as liaisons to help staff and spread awareness of privacy issues. Data collection is also guided by the city’s Demographic and Survey Data Collection Playbook. (SDOT’s own sensor infrastructure is subject to review and approval to hew to the city’s rules on protecting privacy.[33]

Any SDOT information technology project should consider the following:

  • Ongoing alignment with the City of Seattle’s Privacy Principles, policy and processes
  • Alignment with the City of Seattle Surveillance Ordinance. This ordinance regulates the use evaluation, and procurement of technologies that “observe or analyze the movements, behavior, or actions of identifiable individuals in a manner that is reasonably likely to raise concerns about civil liberties, freedom of speech or association, racial equity or social justice.”
  • Policy development, data procurement, and digital infrastructure initiatives guided by users’ privacy needs and underscored by designing proactively for privacy protections.
  • SDOT and the city’s long-term leadership as protectors of traveler privacy
  • Ongoing alignment with transportation agencies; for example:
  • The principles set forth by the National Association of City Transportation Officials (NACTO)’s Managing Mobility Data policy guidance
  • The principles set forth by the Open Mobility Foundation (curators of the MDS)
  • National standards for data privacy as proposed by Transportation for America:
    • Compliance with city, state, and federal privacy regulations, standards, and policies especially as it pertains to Washington State’s Public Records Act.
    • The prioritization of data collection from vehicles over users, especially location-based data
    • A clear policy of protecting personally identifiable information from public disclosure without prior aggregation or obfuscation
    • The use of the service is not tied to access to personal data or device
    • Opt-in requirements for access to any element of a user’s device including camera, contacts, or location
    • Operators clearly articulate the data they are collecting from users and explain why they are collecting it
    • A prohibition on the sale of data to third-party entities

Special Privacy Considerations

Different users may have different privacy needs, and equity is entwined with privacy issues–a relationship that deserves special consideration.

For example, individuals who are of undocumented immigration status or who have experienced domestic violence may be more vulnerable if certain types of traveler information, such as origin-destination data, are made accessible to the public or discovered through a data breach. People and households with lower incomes are also more at risk of data privacy violations.[34]

For this reason, we strongly emphasize alignment with the City of Seattle’s privacy principles, particularly Principle 2: “We collect and keep only what we need.” This will help us design systems that support equity in privacy, individual wellbeing, and public benefit. Also, under Executive Order 2016-8 affirming Seattle’s status as a “welcoming city,” city employees will not ask about immigration status.[35]

Privacy in the Right of Way

Measuring the flow of traffic can serve as a great analogy for the balance between anonymized public data collection and its benefits to the public good. Collection of transportation data is one of the oldest and most visible forms of data gathering. Vehicles, pedestrians and others using the right of way have been monitored by municipalities and other transportation agencies for nearly a hundred years, either by observational studies or by sensors placed temporarily or permanently in the roadway. Analysis of this data is essential to understanding traffic flows and designing for more fluid transportation.

Whereas traffic volume data was previously captured manually by observational studies, data can now be collected electronically by, for instance, detecting a traveler’s WiFi-enabled device as it passes through a sequence of sensors, or from an outside service provider’s mapping app in exchange for directions. These are, in effect, tracking individual users as they travel through space, raising questions about surveillance. To ensure traveler privacy, this data is anonymized and aggregated.

But even when steps are taken to anonymize and aggregate data, we need to remain vigilant. Researchers have recently developed an algorithm that can identify 99.98 percent of American individuals using nearly any public dataset that meets certain criteria (e.g., having at least 15 attributes such as zip code and gender associated with the data points)[36]. Supposedly anonymized transportation datasets often meet these criteria.

Traffic volume data is one potentially sensitive type of data collected within the transportation system. Data is collected daily that could potentially identify individuals and compromise their privacy. Others include:

  • Permit data
  • Customer service information
  • Financial information from any transactions
  • Meeting sign-in forms and surveys
  • Any private data provided by mistake
  • Closed-circuit television imagery
  • Parking studies that gather license-plate numbers
  • Website analytics



In 2005, the City of Seattle became the first city in the nation to adopt a formal framework to address institutional racism— the Seattle Race and Social Justice Initiative (RSJI). In the years since, city departments have adopted RSJI principles and processes, and added supplemental efforts of their own to support equity in ways unique to their work.

In response, SDOT established programs and workgroups such as the Office of Equity and Inclusion, the Transportation Equity Program, New Mobility Data and Equity Support, and Women- and Minority-Owned Business Enterprise (WMBE) initiative.

Any SDOT information technology project should align with these efforts. It should consider three main types of information equity that are critically important to users:

  • Transportation information access
  • Privacy of transportation user information
  • Equitable service outcomes of transportation information use



Equitable information access

Several factors affect how accessible transportation information is to different demographics. The following is a list of the information access concerns that should be considered when deploying technology:

Diverse user information needs

To travel safely and efficiently, transportation system users of different demographics may require different information. For example, a low-income user heading to an overnight shift will likely have very different information needs than a high-income user heading to work during weekday commute hours. In fact, the transportation information needs of any individual user may shift depending on the time of day or day of the week (e.g., commuting to work during the week vs. taking a child to an appointment on a weekend).

Access to technology

Travelers increasingly need access to the internet and digital devices to obtain useful, real-time transportation information. In addition to planning for use of internet-delivered information channels, SDOT should plan for the use of information channels that require minimal access to technology. This redundancy of information access not only makes the system more equitable, but also improves resilience in the face of system outage.


If providers share information that users need in ways not understandable to the user, because the information is either in an unfamiliar language or at too advanced a reading level, the information is useless to the user. Each SDOT technology project should increase language accessibility.

Physical access

Hearing impairment, vision impairment, and different forms of neurodiversity may affect the way some users experience our transportation ecosystem. Technology projects should consider users’ needs, not just in terms of what information they require, but also what accommodations may improve their experience.

Equitable service outcomes

“Data driven” does not always mean equitable. In fact, in some cases, it can mean the opposite. For example, if transportation service providers optimize their algorithms to maximize profits, some communities may be left underserved. Artificial intelligence (AI) and machine learning (ML) algorithms can also perpetuate and exacerbate historical inequities[37]. This is because AI and ML algorithms are trained on historical data – when historical data reflect biases in our institutions and process, or when training data are selected in a biased way, the biases may be carried over to (but also hidden in) the outputs of predictive algorithms trained on these data.

SDOT should take a user-needs-first approach to designing and deploying information technology. This means ensuring not only that we provide information to users in an equitable way, but that the outcomes of the way system actors use information are also equitable.

Making Information Accessible

Travelers must be able to access information that allows them to complete their trip safely and efficiently, regardless of whether they have a smart device or internet access. According to the 2018 Seattle Technology Access and Adoption Study[38], the percentage of Seattle households with internet access increased from 85% in 2013 to 95% in 2018. Internet-capable mobile phone ownership rose from 58% to 93% during the same period. This is an encouraging trend, but it also means that roughly 1 in 20 residents are unable to use internet-based services to plan their trip at home, and 1 in 13 residents are unable to access internet-based transportation information while traveling.

Meanwhile, one out of four (23%) Seattle residents identified “a limiting factor to not using the internet more.” Top reasons included:

  • Internet service is too expensive
  • Too slow/frustrating/internet doesn’t work well
  • Service plans from internet provider are confusing
  • Not interested or don’t need/want to use it
  • I don’t know how to use the internet
  • I don’t have a device to access the internet
  • I have no time to learn about it or how to use it


The inability to access information fell disproportionately on low income households. The study showed that 21% of households with incomes under $25K and 10% of households with incomes between $25K and $50K do not have a mobile or smartphone. Certain groups were also more likely to report barriers:

  • 54% of those living at or below 135% of the Federal Poverty Limit
  • 49% of Black residents of the city
  • 38% of older adults (65 years of age or older)
  • 33% of those living in South Seattle (Council District 2)
  • 31% of Asian residents of the city
  • 30% of those who live alone

Also, “more than one out of ten (13%) residents rely on someone else to help them access or navigate the internet.”

While most transportation information is delivered via mobile devices, the Access and Adoption Study revealed that, compared to residents who have internet access from multiple devices at home, residents who rely on cell phones to access the internet are:

  • more likely to be unemployed and more likely to be disabled
  • more likely to live alone
  • more likely to live at or below 135% of the Federal Poverty Level (household) and to have lower average (personal) incomes
  • more likely to only have a high school level education or some college
  • more likely to be a racial or ethnic minority


The city’s transportation information infrastructure must correct the inequities in information access as part of its efforts to address inequities in transportation access and outcomes. Lack of access to information directly impacts a household or residents ability to use all the available transportation options in the city and therefore limits their access to opportunities and amenities.

Safety and security

While it’s paramount that users of the transportation system be protected from misuse of their personal information (financial information, origin-destination data, etc.), system users also need protections from issues that stem from how information is managed at the system level. For example, a well-designed geofencing scheme provided to ride-share providers may encourage the drop-off of passengers in safer locations. Similarly, requiring service operators to provide real-time incident and condition information can allow for system-level routing of travelers away from potentially dangerous incidents.

Providing strategic information to the right system actors at the right time is essential to ensuring these protections now and into the future. In the near term, well-managed information can help us identify safer flight paths for delivery drones, provide real-time asset condition information, and vary speed limits according to current traffic conditions–all of which help improve safety.

For long-term, intergenerational safety, we need to know what types of information may help protect against threats such as climate change. For example, requiring that system actors provide information on the carbon emissions associated with various travel modes may shift travel behavior to more sustainable modes. Ideally, we will also be able to collect information on near-misses which would allow system managers to identify and target unsafe locations before an incident occurs and build the necessary physical changes to the infrastructure.

Of course, travelers can also face safety issues if the information system itself fails, whether through malfunction or malicious hacking. For example, a system failure could result in traffic signal outages that may endanger travelers. SDOT should build redundancy into any transportation information system and should address system security issues at the level of each specific technology.



100 Resilient Cities defines a resilient transportation system as

“one that promotes safe, equitable, and inclusive accessibility by providing sustainable, integrated, flexible, and robust mobility options – during normal times and times of crisis.”[39] 

Information systems, from street signs to online traffic maps, are an essential part of any transportation system. But physical and technological disruptions can cause these systems to function poorly or, in some cases, cause them to cease functioning all together. These failures may undercut safety and equity and exacerbate exclusion (e.g., if a disruption means only travelers with smartphones can navigate the system safely).

As new technologies are introduced to our aging transportation system, the number and severity of potential disruptions increase exponentially. We should design our information infrastructure to provide for:

  • The ability of SDOT and other system managers to continue to provide essential information in the face of acute system shocks and chronic stressors, both physical and technological
  • The ability of users of the transportation system to access transportation information in the face of acute system shocks and chronic stressors, both physical and technological


To address potential failures, our transportation information infrastructure system should both be flexible and incorporate redundancy, meaning if one information system is unavailable, operations can continue using another. SDOT needs to address this with every technology that it considers as it implements the policies, projects, initiatives, and technology investments under this plan.


[13] “Car sharing’s time comes.” CNN Money, July 19, 2000.

[14] There were exclusive car clubs starting back in the 1940s and there were several car-share services operating in Europe.

[15] RFID technology allows information to be stored digitally in miniature “tags” that can be captured by an electronic reader.

[16] Brian McCullough. “How the Internet Happened: From Netscape to the iPhone.” (New York: Livewright/Norton, 2018.)

[17] General transit feed specification is a common data format for digital sharing of public transportation schedules and associated geographic information

[18] Rampton, John. “The Evolution of the Mobile Payment.” Techcrunch, 17 June 2016, 7:00 AM, techcrunch.com/2016/06/17/the-evolution-of-the-mobile payment/

[19] As well as the competing mobile OS platforms from Windows, Nokia, and a host of other companies

[20] In the US, car-share memberships grew from 200,000 in 2007 to nearly a million by 2012, just five years later.

[21] S. Shaheen, N. Chan, A. Bansal, and A. Cohen, “Definitions, Industry Developments, and Early Understanding.” Shared Mobility: A Sustainability & Technologies Workshop. Transportation Sustainability Research Center, University of California Berkeley, November 2015.

[22] By 2018, the price would drop to $200,000. (See “Episode 643: The Taxi King.” https://www.npr.org/sections/money/2018/05/23/613776997/episode-643-the-taxiking. Planet Money, NPR, 23 May 2018.

[23] “Chinese Startups Saddle Up for Bike-Sharing Battle.” https://www.wsj.com/articles/chinese-startups-saddle-up-for-bike-sharing-battle-1477392508 Wall Street Journal, 25 October 2016.

[24] Now called Waymo.

[25] One prediction says human drivers will be prohibited from roads by 2040 http://www.dot.state.mn.us/research/TS/2016/201602.pdf

[26] Garrett-Glaser, Brian. “Will the Global Urban Air Mobility Market Justify the Investment?” Avionics Today, 22 August 2019. Retrieved via https://www.aviationtoday.com/2019/08/22/will-global-urban-air-mobility-market-justify-investment/

[27] Outside the names known in the U.S. are the operators emerging in China (Didi Chuxing), South East Asia (Grab and GoJek), Latin America (99), North Africa (Careem), South Africa (Taxify), India (Ola), and others.

[28] https://phys.org/news/2019-03-ipo-due-uber-aims-amazon.html

[29] Uber lost over $5 billion in one quarter, but don’t worry, it gets worse.” By Andrew J. Hawkins https://www.theverge.com/2019/8/8/20793793/uber-5-billion-quarterloss-profit-lyft-traffic-2019

[30] Nickelsburg, Monica. Inside the abrupt shutdown of BMW’s ReachNow car-sharing service in Seattle and Portland. Geekwire, 5 August 2019. Retrieved from https://www.geekwire.com/2019/inside-abrupt-shutdown-bmws-reachnow-car-sharing-service-seattle-portland/

[31] From the City of Seattle Privacy Principles, available via: https://www.seattle.gov/Documents/Departments/InformationTechnology/ City-of-Seattle-Privacy-Principles-FINAL.pdf

[32] The Public Records Act also makes it difficult to protect data once we have collected it or had it collected on our behalf by a third party: http://apps.leg.wa.gov/rcw/default.aspx?cite=42.56

[33] See the Surveillance Ordinance and technologies under review at: http://www.seattle.gov/tech/initiatives/privacy/surveillance-technologies

[34] Byrne, Ciara. Trading privacy for survival is another tax on the poor. Fast Company, 18 March 2019. Retrieved via https:// www.fastcompany.com/90317495/another-tax-on-the-poor-surrendering privacy-for-survival

[35] Available via: http://murray.seattle.gov/wp content/uploads/2016/11/Executive-Order-2016-08_Welcoming-City.pdf

[36] https://www.nytimes.com/2019/07/23/health/data-privacy-protection.html

[37] Angwin, Julia, et. al. “Machine Bias” ProPublica, 23 May 2016, www.propublica.org/article/machine-bias-risk-assessments-in-criminal sentencing.

[38] Available via: www.seattle.gov/tech/initiatives/digital-equity/technology access-and-adoption-study

[39] Attributed to Mariane Jang, Associate Director, Solutions Development & Innovation – Mobility and Urban Development, 100 Resilient Cities

Need More Information?

This is a draft plan. It was developed by Benjamin de la Pena, Mary Alyce Eugene, Alex Hagenah, and Sam Marshall along with their colleagues from across the Seattle Department of Transportation (SDOT).

If you have questions about this plan, please send us email via draft_tiip@seattle.gov.

If you have questions about SDOT, please visit our website at www.seattle.gov/transporation.

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