Fast forward a decade to a time when there are predicted to be nearly 50 billion internet-connected Machine-to-Machine (M2M) devices. ITS America predicts a billion or more of these so-called "internet-of-things" devices will be either "smart" cars or "intelligent" transportation devices. But for "Big Data" to fulfill its promise in transportation, cultivating data will not be enough - it must be harvested, stored, processed and brought to market to be of value. The market for such data is just beginning to emerge.
The world’s seed stock of digital data is increasing on an exponential scale. IBM estimates that 2.5 quintillion bytes are created every day. The future clearly belongs to organizations and enterprises that can grow and successfully harvest data. Companies like Google have already answered an important question - that is, how does one make ordered sense of the fastest ever expanding crop of data, the World Wide Web, as it has grown beyond a trillion unique addresses? Google, Amazon, Twitter, and others have all tilled data and tapped into their stores to make "big data" analytics - such as profiles, rankings, and recommendations - core to their success. Observing these trends among internet companies are various car makers, fleet operators, and road agencies, who are in the seedling stage as they begin to envision how to reap the benefits of their unique crop of data.
Data-centric industries, such as finance, utilities, or telecommunications, have always cultivated subscriber data to provider service to their customers, but road transportation has been different. In transportation, the data situation has been either data feast or data famine. The feast has been a few large courier delivery services and freight carriers, which collect and process large amounts of data to keep industry supply chains buzzing and logistics running just-in-time. For decades, highway agencies were just not able to tap deep, reliable wells that could sustain the data cultivation needed to manage operations or sustain many traveler information services. Many agencies were subsistence data farmers, living day-to-day on only the modest crop they were able to grow themselves. Uncultivated information deserts existed in many places -- frontier geographies devoid of easily accessible or timely data.
In the 2000s, trucking fleets, logistics firms, and even some state agencies began to share traffic "speed data" with third parties on a nation-wide or regional basis. In this phase, a new breed of data farming cooperative - the "transportation data aggregator" - brokered and bartered data. Furthermore, new species of mobile computing devices such as smart phones, tablets, and personal navigation devices lowered the barriers for pioneer smallholder startups to seed and grow traffic and other data to produce greater varieties of mobility information services. The location of traffic bottlenecks, dangerous weather conditions, or the presence of destination amenities such as fuel stations suddenly became available to any traveler, not just a select few fleet managers or traffic management centers. The information desert began to recede, bringing an end to the era of subsistence data farming.
As a result, road users became ever more accustomed to viewing navigation, traffic, weather, tolling, and parking information as a necessity, rather than a luxury. In a fashion similar to what Google did for web searching, new transportation data aggregators and their distribution channel partners (e.g. internet and mobile app developers, radio, TV) began alleviating the traveler's burden of browsing for information relevant to their trip. Such "new mobility" information services reduce traveler uncertainty - that is, uncertainty regarding to trip routes, travel times, costs, payment options, fuel availability, and other needs.
Beyond data aggregators, larger data warehouses emerged, like the University of Maryland Center for Advanced Transportation Technology (CATT) Laboratory in the United States. Such warehouses amass harvested data and make it ready-for-market, nicely packaged and easily consumable. Transportation data market intermediaries continue to refine, clean, and present the data, bartering for information and other considerations in the growing data marketplace with various transportation communities such as transit, freight, personal vehicle, road, and parking operators.
Lastly, cars themselves are getting smarter. Vehicle-oriented services are often designed to preserve and maintain vehicle assets from wear and damage through remote monitoring, predictive diagnostics, and safe driver incentives such as discounts from pay-as-you drive insurance. Better data means safer cars. Next-generation vehicles, equipped with dedicated short range Vehicle-to-Vehicle communications, will exchange standardized data on scales unimaginable until just a few years ago. Self-driving cars and other robotic marvels will cultivate enormous stocks of data and computing power to intelligently navigate roads.
The transportation data market has been a great story of success and progress. However, the impediments for transportation to exploit "big data" are still many, and they range from the technical to the institutional. Many public transportation authorities have little ambition to move beyond subsistence data farming. Agencies still are worried about the costs or risks of more data collection and sharing. Of particular concern are the stresses placed on their mission in tight budgetary times, and the potential impact of liability and privacy. ITS America is looking forward to working with its members and the International Transport Forum to address some these problems, and to establish sustainable data farming practices and communities.
About Steven Bayless and Sean Murphy of ITS America
Steven H. Bayless is Senior Director for Telecommunications and Telematics, focusing on Connected Vehicle crash avoidance and applications. Sean Murphy is a Transportation Specialist working in the field of fleet and traveler information.