1) The presentation discusses how disruptive technologies will impact urban mobility and deliver innovative solutions to support smart cities. 2) It outlines challenges like increasing traffic, costs of congestion, and emissions, and opportunities from technologies like mobile internet, IoT, cloud computing and autonomous vehicles. 3) The presentation argues that integrating data from networked infrastructure can optimize operations through predictive analytics and transform conventional approaches to mobility.

1. CRICOS Provider
00111D
A/Prof Hussein Dia
Centre for Sustainable Infrastructure
@HusseinDia
Intelligent Mobility for
Smart Cities
Presentation to the IRF & Roads Australia Regional Conference (Asia and Australasia)
Sydney, Australia
May 4-6, 2015

2. Explore the complexity of urban
mobility and how the convergence
of disruptive technologies will
deliver innovative solutions that
support smart, connected and
liveable cities.
Outline

3. The Urban Millennium Ambition
“The age of nations is over. The new
urban age has begun.” Parag Khanna
Beyond City Limits
www.paragkhanna.com
New York & London represent 40% of the global market
capitalisation
100 cities account for 30% of the global economy and
innovation
21st century appears likely to be dominated by global
cities, which will become the magnets of economy and
engines of globalisation

5. The Urban Challenge
2 . 50 . 75 . 80

6. The Mobility Challenge
1 Billion
Vehicles in
Operation

7. The Cost Problem
Traffic Congestion
Road Safety
Costs around 1% - 3% of a country’s GDP
Global annual fatalities: 1.2 million
Economic Cost: $100 billion per year

8. The Cost Problem
2013: 440ppmEmissions

9. New approaches are needed to fund, manage,
operate and optimise utilisation of transport
infrastructure
The Funding Challenge

10. The Opportunities

11. The Opportunities

12. Internet-Connected Devices

14. Principles
• Increase the amount of data
collected from assets
• Share, integrate and filter real-time
data from networked infrastructure
• Optimise operations using predictive
analytics, data mining and modelling
• Enhanced information flow to citizens
and service providers
Transformation to Smart Cities
Instrument
to Manage
Integrate to
Innovate
Optimise to
Transform
Path to
Transformation

15. Conventional Approaches Trends and Targets
Building additional infrastructure
capacity (focus on supply)
Maximising efficiency, resilience,
and sweating of assets (focus on
managing demand)
Vehicle-oriented People-oriented
Customer-centric
Focus on reacting to congestion Focus on positive business and
operational outcomes
Emphasis on “knowing and
seeing”
Emphasis on “predicting and
anticipating in order to avoid”
Spending on physical
infrastructure
Spending on data fusion,
predictive analytics, Artificial
Intelligence and adaptive tools
Smart Mobility ‘Knowledge Gaps’

16. Disruptive Technologies
Technology Trends
Mobile Internet Increasingly inexpensive and capable
mobile computing devices and Internet
Connectivity
The Internet of Things Networks of low-cost sensors for data
collection, monitoring, decision making,
and process optimisation
Cloud Technology Use of computer hardware and software
resources delivered over a network or
the Internet, often as a service
Energy Storage Devices or systems that store energy
for later use, including batteries
Autonomous & Near
Autonomous Vehicles
Vehicles that can navigate and operate
with reduced or no human intervention

17. Real-time mobility monitoring using
smartphones
Large-scale sensing data from sensor-rich smart mobile
devices deliver information that can be used to provide
users with more travel options depending on time of
travel, weather, price and destination
Data fusion methods to sanitise and filter the data, and
derive mobility patterns, origins-destinations, travel
times, and other mobility information
Reduces reliance on data from fixed sensors
Participatory Sensing

18. New Business Models
What if …?
Automakers subsidise car purchases by working with technology companies
to capitalise on the lifetime revenue opportunity of connected drivers?

19. What if …?
Consumers replace traditional car ownership models
with on-demand access to the vehicles they want?
New Business Models

20. Leap Buses
$6.00 vs $2.20
Market Forces

21. The “Autonomes” are here:
How will they impact urban mobility?

22. Nearly the same mobility can be delivered with 35% of
the cars – Peak hours scenario
Modelling using MATSim
Vehicle capacity: up to 8 passengers
Maximum 5 minutes wait time
Source: International Transport Forum, Urban Mobility System Upgrade

23. Nearly the same mobility can be delivered with
10% of the cars – 24 hours scenario
Source: International Transport Forum, Urban Mobility System Upgrade
Complex mathematical model typically solved using LP
“Dynamic pickup and delivery problem with defined time windows

24. The overall volume of car travel will likely increase
Source: International Transport Forum, Urban Mobility System Upgrade

25. Impacts on emissions, air quality and utilisation
Austin, Texas MATSim Study
Emissions
• Average 26 trips per day (versus 3)
• Average in use 8 hours per day (versus 1)
• Fewer cold starts and dynamic ridesharing could
offset part of higher VKT
Utilisation
• 300 km per day (110,000 km per year)
• Need replacement every 3-5 years
Source: Fagnant, D. et al (2015). Operations of a Shared Autonomous Vehicle Fleet for the Austin, Texas Market

26. Disruptive Technologies
The technology is rapidly advancing
or experiencing breakthroughs
The potential scope of impact is
broad
Significant economic value could be
affected
Economic impact is potentially
disruptive
Doing nothing is not an option!
The smart mobility vision

27. Connected and
Cooperative Mobility
Traffic Demand
Profiling
Traffic Forecasting
and Predictive
Modelling
Network Performance
Analysis
New Generation Traffic
Management and
Control Systems
Impact Assessment
Tools
Smart Mobility Research Facility
Smart
Mobility

28. Modelling and Evaluation of Smart
Mobility Options
Travel
Behaviour
Behavioural modelling
and prediction
Simulation and
Modelling
Multi-modal transport modelling
Emissions modelling

29. Concluding Remarks
Technology will play a major
role in delivering
sustainable mobility
solutions but must be part
of a holistic vision