A Strategy Analytics report for Intel puts the global social and economic value of intelligent, driverless vehicle use at US$7 trillion by 2050. The majority of this “passenger economy”, some 55%, will be derived from a shift away from vehicle ownership towards personalized, on-demand transportation, known as Mobility-as-a-Service (Maas). For example, ride-hailing, car-sharing or concierge services.
Business use will account for 43% as haulage, distribution and delivery services leverage new opportunities and benefit from expanded working hours (trucks don’t need a vacation) and savings on driver salaries. Other businesses could also reinvent themselves, transitioning from costly physical premises to on-demand home delivery or on-the-go mobile stores and services.
US$200 billion is also predicted to come from the development of innovative onboard services and products like in-vehicle apps, accessories or dedicated service and “experience” pods. When we become passengers rather than drivers, we are free to eat, sleep, work, shop, enjoy entertainment or even be pampered in the beauty salon. Driverless vehicles have game-changing applications across the board, from tourism to hospitality to healthcare. And as new players enter the market, MaaS providers will increasingly need to differentiate themselves through complementary services and features.
The passenger economy also promises indirect savings in terms of productivity (commute time can be used for last-minute work or study), recovered work hours when congestion is eliminated and public health savings from reduced traffic accidents.
The potential is such that everyone from industry-disrupting mobility startups to tech giants to traditional car manufacturers has, quite literally, a car in the race.
Healthy competition is essential for the evolution of sophisticated services. Therefore, a heavy regulatory hand is undesirable as it can stifle market development. However, governments and transport authorities must work to ensure the impacts of the passenger economy are neither detrimental nor unevenly distributed. For example, the cost of MaaS to the user is likely to be quite low. Therefore, restricting the number of licenses and/or vehicle speeds should ensure the continued competitiveness of mass-occupancy public transport.
Government intervention can also prevent gentrification and disparities in mobility services between different neighborhoods. If city planners invest in certain areas and provide public transport, this attracts people to the area and stimulates further demand for transit services. And where there are customers and demand, private companies will follow.
The authorities must, therefore, focus on creating the conditions for the passenger economy to flourish. This allows established industry players like car manufacturers–which are important to national economies–to reinvent themselves and enter new markets, for example as service providers or transport operators. However, while these giants are past masters at reinvention, they can be slow to evolve, hampered by size, fixed costs, legacy systems, inflexible partnership models or regulatory compliance.
This is where small startups–with the flexibility and freedom to collaborate, experiment and reinvent themselves–come in. Shotl is working with diverse public and private international partners, providing the technology to enable dynamically-routed, demand-responsive transit. From self-driving minibuses to digitizing school journeys to shared corporate shuttles, we’re bridging the gap and helping drive the development of the passenger economy.
Machine Learning (ML) is a field of Artificial Intelligence (AI) which focuses on the development of techniques that allow computers to learn how to perform a specific task.