August 2019
    Disruptive technology 
    and innovation  
    in transport
    Policy paper on sustainable infrastructure
            Executive summary
            A key objective of the European Bank for               key challenge in the development of the identified 
            Reconstruction and Development (EBRD),                 disruptive technologies and their applications will 
            especially in the transport sector, is to support      be their successful integration into new business 
            the promotion of innovative new technology in the      and governance models, maximising their combined 
            economies where the Bank operates to improve           benefits to support the end goal.
            competitiveness and provide demonstration 
            effects. The purpose of this paper is to provide an    The four applications of the disruptive technologies 
            overview of the current state of the market and        that Section 3 reviews in detail are as follows:
            opportunities for the implementation of a range 
            of (disruptive) digital technologies capable of        • Traffic management using intelligent transport 
            revolutionising the transport sector in the EBRD         systems (ITS) – using new technologies to predict 
            regions. These technologies include:                     future traffic demand more accurately and optimise 
                                                                     road networks accordingly, providing a wide range 
            • the internet of things (IoT) – a system of objects,    of social and economic benefits, including reduced 
              processes, data and people connected with each         congestion and pollution, improved safety and 
              other via sensors, and controlled remotely using       travel experiences for all road users.
              the internet
                                                                   • Personal travel planning and public transport – 
            • big data – complex data characterised by high          analysing available information on travel demand 
              volume and requiring the use of advanced               and travel patterns of the population, to facilitate 
              analytics for processing                               the optimisation of planning, programming and 
                                                                     operation of public transport systems, as well as 
            • artificial intelligence (AI) – computer science        improving personal journey planning for the public.
              which enables machines to function like  
              a human brain                                        • Autonomous and connected vehicles for 
                                                                     mobility – developing applications for AVs which 
            • drones – unmanned aerial vehicles (UAVs) or            can contribute to increased safety, a better user 
              flying robots.                                         experience, economic savings and reductions 
                                                                     in congestion, by facilitating car sharing and 
            The paper outlines a range of digital technologies       “mobility as a service” (MaaS).
            and concepts (Section 2), introduces various 
            technology application areas with supporting case      • Unmanned aerial vehicles/drones for 
            studies and cost-benefit analysis (Section 3) and        monitoring - using technology to revolutionise 
            discusses a policy roadmap for their successful          the way we undertake asset management, 
            implementation (Section 4).                              maintenance and inspections (bridges, tunnels 
                                                                     and construction sites) and providing an efficient 
            The summary of the technologies presented in             means to deliver packages (logistics).
            Section 2 demonstrates that IoT, big data and AI 
            do not operate in isolation but instead represent      These technology application areas were reviewed 
            highly complementary technologies. Big data is         in the context of their contribution to the following 
            collected most effectively using IoT systems and       policy objectives: (1) transport efficiency, (2) safety and 
            drones and then processed most efficiently using       security, (3) environment and climate change and 
            AI algorithms and optimisation techniques. The         (4) socio-economics. From the analysis of these policy 
            main applications of these particular technologies     objectives we concluded that the technology application 
            in transportation focus around demand forecasting      areas which have the most profound (disruption) 
            and traffic optimisation resulting in better traffic   potential impact were new smart mobility (AVs/MaaS 
            management, asset management, travel planning          and drones) and intelligent transport systems (ITS), each 
            and operation of autonomous vehicles (AVs). The        requiring and leveraging different digital technologies.
            Policy paper on sustainable infrastructure                                                 August 2019    1
            The key challenge in the development of the             • Identifying requirements for facilitating necessary 
            identified digital technologies and their applications    enabling “public” infrastructure and forms of 
            will be to integrate the business and governance          economic regulation to enable widespread 
            models for new mobility technologies, services and        adoption.
            systems successfully. The following challenges are 
            critical to this process:                               • Developing cost-benefit analysis methodologies 
                                                                      and the supporting evidence base to promote 
            • Harmonising existing and new policies related to        adoption.
              the legal framework for use and operationalisation 
              of such technologies.                                 • Launching analytical work and developing 
                                                                      innovative operating models.
            • Facilitating interoperability and data sharing.
                                                                    • Developing integrated mobility systems.
            • Promoting vehicle-to-infrastructure (V2I) and 
              vehicle-to-vehicle (V2V) communication.               • Sharing data and digital infrastructure.
            • Ensuring data security and addressing risk-           • Supporting capacity-building, education and 
              sharing/liability concerns.                             awareness-raising.
                                                                     
            2    August 2019                                               Disruptive technology and innovation in transport