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Transport and Climate
Change Week
Digital mobility, new business
models and innovative planning
24 – 28 September 2018
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Beyond Mobility as a Service – The Age of
Data in Urban MobilityDr. Christian Mettke, Melissa Cruz
Transport and Climate Change Week2018
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For the
better
For the
worse
The “Age of Data” in Transport has the potential to
transform mobility as we know...
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Why decarbonising the Transport Sector?
• Almost all (95%) of the world transportation energy comes from petroleum based fuels, largely gasoline and diesel
• Transport accounts for almost 60% of global oil use
2 Degree Target not reachable without the transport sector
Need for increasing ambitions and speed up implementation of NDCs
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Hype!? Justified?
Artificial Intelligence is the new electricity. (Andrew Ng)
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AI enables performance improvement of any given task
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Seite 7
So far, AI is not yet widespread in the transport sector, but is
gaining momentum.
Mostly „narrow AI“ applications are being used to perform specific tasks.
AI will unlock new business models and require the cooperation of a variety of stakeholders
from different branches and Government to ensure sustainability of AI transformation in transport sector.
Currently,
approximately 500
companies are
working with AI in
transport and over
52 billion USDhave been invested in
since 2010.
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Reality
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Road transport is a major contributor to air pollution and climate change.
Transport contributes to 23% of energy-related CO2 emissions and is still
growing!
Challenges
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Worldwide, 1.3 Million road deaths and up to 50 Million
people injured per year
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10-25% of urban areas are taken by road transportation
infrastructure
Challenges
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Insufficient public
transport provision
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What do we want to achieve today?
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Excite your
curiosity
14
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Understanding
basic
fundamental
technologies
15
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Learn about
real-life
applications
16
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Explore
possible
government
actions
17
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18
Guiding Questions1. What are fundamental technologies
that are changing the mobility sector
in the near future?
2. In the context of the digital
transformation of the mobility sector,
what are new, emerging business
ideas and models?
3. How can governments proactively
engage with the digital transformation
towards a more climate-friendly,
sustainable transport sector?
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1 2 3
Fundamentals
and
Technologies
10.30 -12.30
Applications and
Business Models
14.00-15.30
Towards
Sustainability:
Government
Actions
16.00-17.30
Our agenda
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1 2 3
ThirdSpaceAuto Blockchain Lab POLIS
4
Door2Door
Our guests
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Thank you!email:
skype: christian.mettke
twitter: christianCIOW
web: changingtransport.org
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Additional
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AI Applications in Transport: End-Users
Mobility as a Service (MaaS)
Courier Network
Services (CNS)
Vehicle Connectivity & Smart Parking
Autonomous Vehicles
- Flexible routing, booking, payment of single & multimodal trips
- Apps: shared mobility (i.e., B2C and P2P sharing), public transit, real-time info, hailing, multimodal aggregators
- For-hire paid delivery services using online app
- Connect couriers using private vehicles, bicycles, scooters, etc., with light cargo
- Vehicle diagnostic info, remote access, and emergency services (e.g., roadside assistance or vehicle unlocking)
- Info on parking costs, availability through IoT
- Input integration & info computation towards full automation
- Will most likely change travel patterns and need for vehicle usage tax
- Socio-economic implications on jobs (freight, taxi, PT)
Source of icons: https://www.flaticon.com/authors/zlatko-najdenovski
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AI Applications in Transport: “Back-End”
Predictive Auto-mated planning
Traffic Management
& Enforcement
AutomatedSupply Chains
Drones for Maint. & Road Safety,
logistics- Sensors, machine learning to analyze current situation
- Predictive analytics to forecast and responds to demand
- Using anonymized mobile location data
- IoT & machine learning used to automate traffic management & enforcement
- Will significantly improve traffic flow & enforcement
- Improved operational responses to hazards
- Advanced Algorithms for merchant & providers to optimize supply & delivery chain
- Automated order fulfillment
- Identification of most economic or fast delivery route
- Automated inspection of: traffic, parking, road & bridge state of repair, accidents
- Improved accessibility of (critical) goods
Source of icons: https://www.flaticon.com/authors/zlatko-najdenovski
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Data Privacy in Transport
Privacy is “the claim by individuals, groups or
institutions to determine for themselves when,
how and to what extent information about
them is communicated to others, and the right
to control information about oneself even after
divulgating it” Alan F. Westin. (Westin, 1967)
Geo-spatial privacy is “the ability of
individuals to move in public space with the
expectation that under normal circumstances
their location will not be systematically and
secretly monitored for later use” Geospatial
Privacy and Risk Management Guide, Natural
Resources, Canada. (Natural Resources Canada,
2010)
https://www.itf-
oecd.org/sites/default/files/docs/15cpb_bigdata_0.pdf
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• Regulate data recording/sharing
• Adjust policy frameworks (incl. non-and quasi
regulatory approaches) for vehicle and safety
standards, assurance and liability regime,
taxation, privacy and cyber security, …
• Define experimental use cases and spaces
• R&D, consumer education, ethical considerations
Benefits&Challenges of AVs – Regulatory Options
Markets don’t
control externalities
Fiscal Regime Change
Data/ Cyber
SecurityJob Displacement
Increased car use
Challenges
Improved road
safety
Increased mobility
Increased efficiency
Reduced emissions
Reduced congestion
Expected Benefits
https://www.itf-oecd.org/sites/default/files/docs/cooperative-mobility-systems-automated-driving-roundtable-summary.pdf
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Icon-set
27
Arrows and charactersGeneral
Digital, Energy and Transport