Driverless vehicles are ideal for shared use.

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Digitalisation is rapidly changing the transport sector. Already today, it influences which modes of transport are used and combined, which routes are taken and which mobility services are on offer. For all that, the digital transformation of the transport sector is still in its infancy. Automation, connectivity, and a rising number of collaborative mobility services will set in motion far-reaching changes in how people get around. These trends offer not only the chance to bring about a safe, efficient and climate-friendly transport sector. They also provide an important foundation for innovative technologies and new business models (figure 5.1).87



A closer look at the possible effects of digitisation on the transport sector, however, shows that this process must be understood as an organisational task. It does not necessarily lead to positive effects; it is also associated with risks. Indeed, it could even jeopardise the transport transformation.

To be sure, digitalisation extends well beyond the transport sector. It has initiated a far-reaching, structural transformation that spans numerous domains. This transformation is impacting jobs in the industrial and service sectors (Insight 11) as well as data security and the resilience of technical systems, to name just a few effects. Clearly, such effects will play a role in determining public acceptance of digitalisation and its influence on the transport system.

87 Canzler, W.; Knie, A. (2016)

  • Even a small number of driverless cars can increase traffic

    Over the past few years, vehicle-automation technology has taken major strides (figure 5.2). With the first fully automated vehicles (level 5) vehicles slated to enter the market in 2018, attention has mainly turned to safety, reliability, liability and ethics.88 The German government has already taken note of these developments. Draft bills recently introduced by the German parliament to reform the Vienna Convention and Germany’s road traffic laws spell out technical regulations for driverless vehicles and define the scope of driver responsibility.89



    So far, there’s been little discussion about how fully automated cars will affect vehicle use, mobility behaviour and, by extension, the environment. But these issues are decisive in whether driverless vehicles will help render the transport transformation a success – or not.

    Thanks to automation, driverless cars are expected to operate more efficiently, travel closer to other cars, and make traffic more fluid.90 While this could reduce fuel and energy consumption, other more disruptive effects are conceivable as well. A fleet of driverless vehicles, available on demand everywhere and at short notice, could lead to a fundamental reassessment of private vehicle ownership. Collaborative mobility services operated with fully automated vehicles could help shared vehicle use generate wider public support and gain growing importance. As a result, the integration of driverless vehicles into the mobility network is likely to blur the line between private and public transport (see Insight 3).

    Preliminary studies of such scenarios in Lisbon, Pittsburgh, Singapore and other places have found that, were all road private and public vehicles fully automated, only 10 to 30% of the existing vehicle stock would be needed to cover current transport needs without restricting mobility – provided that automated vehicles are used collectively, either serially (carsharing) or in parallel (ridesharing).91 A vehicle reduction of that magnitude would not only sink energy use in the transport sector; it would also give municipalities more room to determine land use and urban development (Insight 3). Automation is likely to have similar effects on transport in rural areas. Driverless vehicles have the potential to bring new transport options and improve mobility in the less densely populated areas (Insight 4).

    The outcome of vehicle automation may not necessarily be positive, however. For instance, it might inadvertently generate more traffic. Owners could program their automated vehicles to circulate in cities without any passengers in order to avoid parking fees. Or people unburdened of driving might be more willing to commute longer distances as the time inside the vehicle can be used more productively. It is also possible that individuals will shift from traditional forms of ecomobility to affordable door-to-door services provided by fully automated fleets.

    If today’s mobility structures and ownership rates remain the same, then, vehicle ownership and mileage is likely to increase (figure 5.3). Even a drastic reduction of the vehicle stock of up to 90% could generate more traffic if, as previous scenarios have found, many people opt for shared driverless cars and small buses instead of high-capacity public transport.92



    Hence, even in a future with fully automated vehicles, high-capacity rail- and road-based public transport will be needed to bundle demand and maximise efficiency. When combined with collaborative mobility services, driverless vehicles can provide an important, flexible supplement to fixed-route public transport, and can thus have a positive effect on vehicle demand and output. But strategies will still be needed to minimise the risk of rising distances travelled by private driverless vehicles. Such strategies might need to consider regulatory and fiscal policies, as well.

    Despite uncertainty about the effects of automated driving, decision-makers and experts need to consider potential positive and negative effects early on. The general outlook is promising, though. Should a multimodal integration of driverless vehicles within a high-performance transport system succeed, the quality of mobility can be maintained or even increased without motorised private transport – not least because public transit will also benefit from increasing vehicle automation, becoming more efficient and comfortable.

    88. See Driverless Car Market Watch (2016). Tesla’s driverless model will appear in 2018; Volkswagen’s, in 2019; Daimler’s, in 2020; Honda’s, in 2020; Nissan’s, in 2020; and BMW’s, in 2021.
    89. See BMVI (2015).
    90. See BMVI (2015), p. 10.
    91. See ITF (2016); Spieser, K. et al. (2014); and Zachariah, G; Kornhauser, M. (2013).
    92. See ITF (2016).

  • An interlinked transport system ­contributes to the mobility transition

    A transport system of the future must include road and rail transport with intelligent infrastructure and traffic control systems (for road signs, parking spaces, light signals and the like). Such a system will pave the way for vehicle automation and lay the groundwork for transport that is safer, more efficient and more climate friendly. Combined with big data applications, it can guide traffic proactively and seamlessly link multi- and intermodal trips. In this way, existing transport infrastructures can be used more efficiently.  

    Moreover, it can contribute to sustainable mobility behaviour and reduce traffic-related CO2 emissions, and it can decrease the need for traffic infrastructure. An as yet undervalued benefit of a connected transport system is the added potential for shaping traffic policy. Dynamically priced low emission zones and toll systems (Insight 10) that vary based on traffic levels, time of day, CO2 emissions, air quality, and other factors could be used to steer climate friendly transport.

    In a connected system like this, however, every non-connected vehicle could be a source of interference. The question of how to organise a transitional phase containing both connected and non-connected traffic without loss of efficiency and safety remains an open one. But it urgently requires answering in view of the increasing automation of vehicles. Points of discussion include whether cyclists and pedestrians can and should be included in a connected transport system, whether separate infrastructures are needed for interlinked and fully automated modes of transport, and whether automated driving modes should only be allowed in special areas, such as rural roads or highways.

    Automation is easier to implement with rail transport than with its road-based counterparts. Urban rail systems that use a single mode of transport offer more favourable conditions for connected and automated transport. Driverless trains can improve punctuality, timing and energy efficiency through, say, shorter safety gaps and more economical operation.

  • Smartphones are key for connected mobility

    Smartphones are a key technology for the digitalisation of the transport sector. They are enabling and driving the development of collaborative mobility services, in part because of their GPS functionality. Moreover, they are increasingly important for the analysis of changes in mobility behaviour, and thus provide important information for multimodal, integrated transport planning. Smartphones allow people to access a variety of mobility services – including station-based and free-floating carsharing vehicles – quickly and whenever they need them (figure 5.4). At the same time, smartphones are increasingly used to plan trips with single and multiple modes of transport.



    With smartphone apps, users can enter preferences such as time, costs and CO2 emission levels to calculate optimal routes and in many cases reserve and purchase tickets for inter- and multimodal journeys ahead of time. Smartphones make users part of a connected transport system that provides pertinent information about their mobility choices in real time. They make inter- and multimodal mobility simple, comfortable and economically transparent.

    In cities, smartphones are already shaping the shift to intermodal and multimodal mobility – and it will continue to influence the organisation of mobility in the future. For smartphones to achieve their potential, it is crucial for start-ups to develop new, innovative mobility solutions. Yet traditional companies in the transport sector must also embrace digital technology. Smartphones can be used to link public transit to new mobility services – carsharing, bikesharing, ridesharing and so forth – and in this way promote the nationwide availability of integrated mobility with electronic ticketing.

    It is important, however, that smartphone-centred mobility does not create a digital divide; comparable information, booking and payment systems must exist for people without smartphone as well. One example is the planned elimination of paper tickets and their replacement with eTickets by the end of 2018. With the new system, tickets can be purchased via smartphones or, if they are unavailable, with electronic chip cards.93

    Many still underestimate the potential of smartphones for research and planning. Traditional methods of collecting data such as traffic censuses, questionnaires and travel diaries can barely keep up with the increasing variety of mobility services on offer. The use of mobile devices enables detailed analysis of mobility behaviour while reducing the effort people must make to share data. Mobile devices can significantly improve the detail, scope and reliability of data used in long-term studies and traffic simulations. The need for establishing digital methods of data collection in transport research and planning is plain. The potential of smartphones is not restricted to individual benefits.
     
    For instance, Germany’s national cycling plan for 2020 (Radverkehrsplan 2020) has shown that smartphone-based data collection provides a valuable contribution to demand-oriented planning of transport hubs and junctures for intermodal mobility.94

    93. See Mobilität21 (2016).
    94. See Nationaler Radverkehrsplan 2020 (2016).

  • Connected mobility and data privacy do not conflict

    Each day, smartphones and modern cars collect enormous amounts of transport data – from apps for route planning, from the use of new mobility services or from navigation devices in private cars. As transport systems have been more automated and connected, questions of availability, ownership, use and privacy of this data have become increasingly relevant. The answers to these questions will mainly decide on the trust and acceptance of users andthe innovation potential of new technologies and mobility services.

    Hence, the main objective must be to provide clear information to passengers, manufacturers and operators about how personal data will be used. For instance, users must be informed about the scope and use of collected data and allowed to decide whether to share it. A “privacy by default” design can guarantee users the control of own personal data and for the most part avoid privacy disputes.95 To avoid the restriction of data usage, personal data can be processed by being anonymised or pseudonymised.96 In this way, large amounts of information can be recorded for, say, big-data applications, without violating the principle of data minimisation enshrined in Germany’s data privacy laws.97

    Another requirement alongside data privacy is the nationwide availability of public mobility and infrastructure data. Providing source maps, timetables, price information, real-time weather data and accident alerts creates a level playing field and promotes new, innovative mobility services. The availability of public information and the use of big datasets could, in Europe alone, prevent 629 million hours of traffic jams. This could reduce energy use in motorised private transport by around 16%, and generate economic savings of around 28 billion euros.98 To unlock the potential of transport data applications, national open data regulation can govern the disclosure of data in a uniform standard and safeguard its availability on an online portal.99

    95. See von Schönfeld, M. (2015).
    96. The Federal Data Protection Act (Bundesdatenschutzgesetz, BDSG) defines anonymisation as “means the modification of personal data so that the information concerning personal or material circumstances can no longer or only with a disproportionate amount of time, expense and labour be attributed to an identified or identifiable individual” (Sec. 3, para. 6). It defines pseudonymisation (also called aliaising) as “replacing a person’s name and other identifying characteristics with a label, in order to preclude identification of the data subject or to render such identification substantially difficult” (Sec. 3, para. 6a).
    97. See von Schönfeld, M. (2015).
    98. See EU COM (2015).
    99. In Germany, the Mobilitäts Daten Marktplatz (MDM) has already started doing this. See MDM-Portal (2016).

  • Field testing paves the way for innovation

    Though the digital revolution has arrived in the transport sector, little reliable empirical data exists on the climate effects of new mobility services. Indeed, more experience is needed with real-life operation to prepare technology for series production and to investigate the effects of innovative mobility services on mobility patterns and travel behaviour.

    Germany has already begun to try out new approaches in the transport sector. These include an incentive program to encourage the use of electric vehicles (Schaufenster Elektromobilität)100 and digital testing areas for automated and connected mobility.101 But much of this testing is focused strongly or almost exclusively on technology. Only in a few cases has the integration of innovative mobility services with the transport system been the focal point. But experimentation in this area could generate valuableinformation about the potential of digitalisation. Among other things, policymakers should discuss the promotion of new mobility services such as ridesharing by loosening or temporally repealing the Public Transport Act. This will encourage ridesharing and allow information about its public support and influence on travel behaviour to be collected for designing innovative regulation (such as widening the scope of the experimentation clause of Art. 2, para. 7 of German Public Transport Act).102

    To better promote experimental approaches like these in Germany, politicians must understand that they play a vital role in pioneering transport sector innovations. Following examples abroad, they must discuss how best to create more room for experimentation.103 For instance, field testing could be carried out for fiscal policy instruments such as the introduction of low emission zones and new parking management strategies and for the promotion of cooperation between, say, traditional transport sector companies and new mobility services.

    In any case, it’s important to coordinate planning authorities at the regional and municipal levels, accompanied by transparent, systematic study of experiences in the field. This ensures that insights gained can be applied elsewhere – for example, to uncover shortcomings in common approaches to transport management. At the same time, field testing can deliver reliable knowledge about the validity of traffic models and strategies for decarbonising the transport sector.

    100. See Schaufenster Elektromobilität (2015).
    101. See BMVI (2016b).
    102. A passage from that clause reads: “For trying out new types or means of transport in the field, the approval authority can, when requested in special cases, approve exemptions from provisions in this act or enacted on the basis of this act for the duration of up to four years, provided that it does not conflict with public transport interests.”
    103. One example is the loosening of taxi legislation in the Swiss canton of Geneva to allow the testing of ridesharing services in real-life operation. See Tages-Anzeiger für Stadt und Kanton Zürich (2016).

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