TECHNOLOGY SCANNING Foresight Study on Urban Mobility in Singapore 2040 November 2016
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Foresight Study on Urban Mobility in Singapore 2040 TECHNOLOGY SCANNING Foresight Study on Urban Mobility in Singapore 2040 November 2016 Lee Kuan Yew Centre for Innovative Cities 1 Singapore University of Technology & Design
Foresight Study on Urban Mobility in Singapore 2040
When it comes to our perception of technologies, we often underestimate how much a certain
technology can evolve in medium to long term period, such as in a decade or 25 years. In order to
develop a more concrete perspective of what technologies can have the most game-changing influence
on the future, especially in the mobility sector, we first need to develop the right frame of thinking. One
way to do this is to reflect back on the last 25 years and think of what technologies that we take for
granted today, that did not exist in 1990. It is eye-opening to realise that smartphones, dynamic maps,
social media, and even the Internet hardly existed then. Today, using these technologies are a norm in
our routines. In this section, we discuss in detail nine technologies that were identified from our expert
interviews, focus group discussions and an environmental scan of professional, academic, and mass
media sources.
The nine technologies discussed are data analytics, mobile technology (including applications
for shared mobility), connected vehicles (V2X) and the Internet of Things (IoT), autonomous vehicles,
electric and alternative fuel vehicles, personal mobility devices, shared city cars, drones and freight
robotics, and virtual reality and telecommuting. The intention of this technology scanning is to describe
technologies, their current state and role in Singapore’s mobility system, and detail challenges to their
development and future expectations in the next 25 years. Lastly, we have provided essential reading
material at the end of each technology description for interested readers.
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DATA ANALYTICS
As we become increasingly connected, smartphones, online services, pervasive sensing, payment
systems and even personal vehicles produce massive amounts of data. This data accumulates and adds
complexity to IT operations, but the analysis of this Big Data can also provide insights into user needs
and behaviour patterns.
There is growing demand for scaling up data analytics in terms of speed and capacity as real-
time information sources increase. Data analytics can help advise policy makers and provide clear and
usable information on real-time happenings to users. For example, crowd analysis is used to understand
citizen behaviour and evaluate the efficiency of different public transportation routes (DFRC, 2016).
Predictive analytics may be used to improve asset utilisation and keep vehicles and roads in good
working order through proactive maintenance. For freight transport, automated fuel management
systems and vehicle location data can be used to improve operational efficiency.
Artificial Intelligence (AI) is in some ways an extension of data analytics, in which a system draws
inference from a large set of unstructured data through some kind of “common-sense” framework,
which may be based on machine learning that then executes what it has been designed to do. Examples
include route-finders like Google Maps to interactive robots. AI is also an umbrella term for when a
machine is able to do what previously only human intelligence was able to.
CURRENT STATE AND ROLE IN SINGAPORE’S MOBILITY SYSTEM
Data analytics is used extensively in Singapore’s mobility system. Planners and service
operators use the location data of trains, buses, and taxis as well as travel patterns determined by the
Transit Link transaction system and the Electronic Road Pricing (ERP) system to optimise the
deployment of buses and trains. Additionally, the Land Transport Authority (LTA) is working on
developing systems to understand and use commuter paths to encourage the use of public
transportation instead of personal vehicles (Kwang, 2015). Crowd-sourced and real-time data is used
in the development of efficient ride-sharing applications, such as BeeLine (iDA, 2015).
Singapore’s open data platform shares a variety of datasets with the public to create a
participatory environment for people and businesses to formulate innovative ideas and solutions
contributing to the Smart Nation initiative. This data includes real-time taxi availability, and average
daily transport utilisation over time (Data.gov.sg, 2016). There is also an increasing number of university
courses and education in data analytics and big data analysis as it becomes more important in the
workforce. Additionally, the “open source revolution” provides access to the tools required to perform
big data mining (Fan et al., 2012).
Most businesses and organisations report medium to high investment in big data analytics and
consider it an important way to gain and maintain competitive advantage. While aggregated data
services providing insights for longer term decisions are well established, this is not the case for shorter
term scenarios. Real-time data management and analytics require evolving technology to improve
immediate decision-making.
Location data is currently the most used type of data (Press, 2015). Efficient and accurate data
analytics underlie most transportation innovations and continue to play a major role in improvements
to user experience.
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CHALLENGES AND EXPECTATIONS FOR THE FUTURE
Data management is a major challenge (SAS, 2013). Storing data, determining what data is
useful and organising this data is an ongoing challenge as data gets “bigger”. Additionally, processes to
combine raw data from different systems to get meaningful information are limited (Rosado, 2014).
Typically, statistical analysis, simulation and predictive analytics are used to gain insights.
There are ethical issues pertaining to the increased reliance on and usage of personal data. In
the wake of several high-profile hacking scandals and data leaks around the world, people are
concerned about being analysed without their knowledge or permission as well as the security of their
data. Some estimate that individuals’ discomfort about the detail and personal value of big data from
automated technologies will slow their adoption (Neagle, 2013).
Finally, real-time data compounds these challenges, since faster algorithms must be used and
require an automated or human decision-maker (Davis, 2015).
As data analytics systems become more sophisticated and the above challenges are mitigated,
several types of data may be processed at once to glean insights from disparate sources. Real-time data
management will improve and decisions can be made faster and more judiciously. Through improved
data mining and management, data can be visualised in real-time for users, government and
businesses.
Multi-modal route planning will be able to tailor public transportation options to individual
needs such as avoiding polluted areas, maximising active mobility and minimising time and/or cost.
Transport systems will be able to continuously learn and use vast quantities of information to
make immediate decisions, leading to autonomous systems that increase safety and potentially save
millions of lives (Goodall. et al., 2015). Andrew Ng, associate professor at Stanford University, describes
AI as “the new electricity” which will transform many industries and embed itself in most aspects of
living (Eckert, 2016). Improved data analytics services will enable and work with nearly all other game-
changing technologies in the transportation system.
Essential Reading
SAS. (2013). Big data analytics: What it is and why it matters. Retrieved from
http://www.sas.com/en_us/insights/analytics/big-data-analytics.html
Rosado, W. (2014). Data Detour: Analytics Will Move Transportation Forward. Retrieved from
http://www.wired.com/insights/2014/07/data-detour-analytics-will-move-transportation-
forward/
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MOBILE TECHNOLOGY (INCLUDING APPLICATIONS FOR SHARED MOBILITY)
Singapore has the highest levels of smartphone penetration globally: exceeding 100%, and with at least
9 out of 10 citizens having ready access to a smartphone (Telecomasia, 2016), (Deloitte Southeast Asia,
2015). This creates a huge demand for content and provides a platform for many types of mobile
applications. Information is easily disseminated in real time and responses are immediate. Apps can
change users’ behaviours and modes of interacting with the world, becoming an interface for
socialising, shopping, commuting and other aspects of life.
People are changing the way they travel due to transportation-related apps and technology
underlying mobile payments or mPayments. Mobile wallets and mobile banking are common, allowing
users to instantly access finances and use their smartphones to make payments. In addition to banking
apps, near field communication (NFC), a short range standard which enables two electronic devices in
close range to communicate with each other, is commonly used in ticketing and payment systems. Such
mobile payment technology has enabled convenient and quick payments. Figure 1 shows NFC
communication to pay fare through mobile. On-demand transport services like Uber have taken
advantage of this, and bike-sharing stations often use such apps to identify and allow users to pay.
Figure 1. Mobile payments. (source: IBTimes UK)
CURRENT STATE AND ROLE IN SINGAPORE’S MOBILITY SYSTEM
Around the world, on-demand shared ride services are gaining popularity. Apps like Uber, Grab
and Didi which connect passengers and drivers are now ubiquitous, and several continuously invest in
technology to compete (Russell, 2016).
Singapore has several examples of shared mobility which use mobile technologies. Beeline is
an app that harnesses crowd-sourced data to provide direct shuttle buses based on demand, and a step
towards a shared mobility system. Additionally, Courier Network Services (CNS), in which individuals
use personal vehicles (such as cars, scooters and bikes) to make on-demand deliveries, have emerged.
Apps such as GoGoVan and Rocket Uncle connect customers to drivers for freight transport. Finally,
carpooling apps (like RYDE) aim to ease city congestion and a driver’s financial burden by filling empty
seats.
In addition, mobile applications collect data from a variety of sensors that add to the scope of
big data analytics and provide real-time information. For example, they have been used as an interface
for low-definition mobile air quality sensors to alert asthmatic commuters of locations to avoid (Metz,
2014). Another application is crowd management and control using built-in sensors.
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Mobile apps are also commonly used to plan trips using public transportation, or to provide
walking or driving directions that optimise for real-time traffic conditions. To reduce congestion, some
route planning apps use gamification to influence commuter behaviour (Shaheen et al., 2015). In some
ways, the entertainment value of other mobile apps encourages public transportation use by lessening
irritation with wait times, particularly if users can pinpoint exactly when their transport is supposed to
arrive using real-time information. In Singapore, a government produced app, myTransport.sg, includes
journey planning, bus arrival times and a “snap and send” feature to send instant feedback to the
government regarding maintenance issues. Additionally, NFC-enabled EZlink or other Contactless e-
Purse Application (CEPAS) approved cards are used for all public transportation journeys, and the
technology is now starting to be integrated into mobile devices to further ease the use of public
transport.
CHALLENGES AND EXPECTATIONS FOR THE FUTURE
Experts we spoke to cited cultural shifts in Europe and the United States towards on-demand
travel and noted falling rates of driver’s license registrations. These developments, should they take
root in Singapore, are likely to encourage people to adopt a more car-lite lifestyle. Moving forward into
2040, we can expect increasingly seamless matching of supply and demand for both passenger trips
and goods deliveries.
Shared mobility is enabled by mobile applications, whether it’s sharing cars, bikes, scooters, or
shuttle buses. Mobility apps may also be able to collect and use data such as air quality, weather or
crowds to determine the optimal time and method for travel depending on users’ preferences. In
addition, mobile technologies make multi-modal transport easier. Some route planning apps include
multi-modal options, though there is currently no dedicated app to pay for an entire trip utilising
multiple modes because it may be prohibitively expensive to upgrade and unify payment methods for
all modes of transportation (for instance, through a smartphone ticket) (Barry, 2014). Future mobility
apps should be able to handle a combination of walking, personal mobility devices, ride sharing, and
public transportation. Singapore has a unique opportunity to integrate several modes of transportation
since the main transportation infrastructure is not shared between multiple agencies.
Mobile technology continues to face challenges in security and privacy. As mobile banking
becomes more popular and mobile apps collect massive amounts of personal information, mobile
devices and their data are subject to interception or theft. Additionally, hackers can access a phone’s
sensors, microphone and location data remotely, and some mobile devices have payment capabilities
that can be accessed as well (Veracode, 2011).
The uptake of mobile technology has already transformed mobility systems and new
developments can build on the prevalence of smartphones. They will continue to be an interface
between users and the world around them for some time, but some predict that the form factor for
mobile technology could be entirely different, transitioning to wearable technology or mobile
technology used mainly for supporting virtual and augmented reality instead (Rettinger, 2016).
Essential Reading
Shaheen, S., Chan, N., Bansal, A., & Cohen, A. (2015). Shared Mobility: A sustainability & technologies
workshop: Transportation Sustainability Research Center, University of California Berkeley.
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CONNECTED VEHICLES (V2X) AND THE INTERNET OF THINGS
Connected vehicles use wireless technology to communicate with infrastructure (V2I), other vehicles
(V2V) as shown in Figure 2, or other objects such as pedestrians or personal devices (V2X). The
connection may be through wi-fi or other dedicated short-range communication (DSRC) technology, or
through cellular telematics.
Vehicles that communicate through cellular telematics are part of the Internet of Things (IoT),
a vast network of smart connected objects ranging from internet-enabled home thermostats to running
shoes. IoT objects use sensors to gather information and communicate with other objects, mobile
devices or the cloud (Carter, 2016). IoT also includes wearables, such as health monitoring wristbands
like the FitBit, which aim to influence people’s mobility choices, or smart textiles like the Navigate
Jacket, which taps the wearer on the shoulder to indicate a left or right turn (Entis, 2015).
Figure 2. V2V illustration (source: GM)
CURRENT STATE AND ROLE IN SINGAPORE’S MOBILITY SYSTEM
Governments and companies around the world are investing heavily in the Internet of Things
(IoT). They are also trying to use open platforms that allow individuals to create their own interoperable
system of IoT technologies, such as Google’s Open Web of Things (Hsu, 2015). IBM is investing 3 billion
dollars over the next four years in its Internet of Things Foundation. However, there are different
standards being developed by several consortia in the IoT space, which must be carefully managed to
ensure sufficient security across products (M. Anderson, 2014a).
In the mobility sector, V2V promises improved safety and efficiency. The USA National Highway
Traffic Safety Administration (NHTSA) announced in 2014 that they would begin working on a
regulatory proposal that would require V2V devices in all new vehicles (NHTSA, 2014). The US
Department of Transportation has been testing connected vehicles using DRSC technology with a focus
on V2V communications for safety, such as intersection movement assist and V2I safety applications
such as red light warnings as well as real-time data capture and management. From this, dynamic
mobility applications are expected to arise (Jin et al., 2015).
A DSRC system boasts fast network acquisition, low latency, high reliability, and interoperability
even at high vehicle speeds and under extreme weather conditions. Connected Vehicle DSRC may also
act as a moving-sensor network and address up to 82% of crash types for unimpaired drivers. However,
DSRC requires significant back end support. Another challenge for DSRC technology is that it runs on
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the 5.9 GHz band, which may be open to unlicensed users as data traffic increases, causing congestion
and confusion for DSRC technologies. Additionally, DSRC equipped cars must reach a critical mass to
see a safety effects, which may take years. In the meantime, several companies are already using DRSC
technologies in fleet vehicles. (Jin et al., 2015)
An alternative to DSRC, cellular networks already provide off-the-shelf vehicle connectivity and
may incorporate cloud data to lower costs. In several markets, using cellular telematics to provide
vehicle connectivity bypasses government intervention and there is great market potential in the
development of these technologies.
Vehicular Ad-Hoc Networks (VANET) essentially turn vehicles into wireless routers and can be
employed with either of the abovementioned technologies. Vehicles within 100-300 metres of each
other connect to create a vast network by information “hopping” through multiple intermediate
vehicles. (Jin et al., 2015)
Singapore already has significant smart road infrastructure for V2I connectivity. The Express
Monitoring Advisory System (EMAS) does not currently use V2I communication, but employs video
surveillance to monitor traffic and communicates information about upcoming roads in real-time to
drivers. This functionality might be boosted by V2V and V2I communications; this information complete
with alternative routes could be delivered to drivers at any point instead of just at a particular junction.
The current Electronic Road Pricing (ERP) system uses short range communication between a
vehicle add-on and a stationary gantry to reduce congestion in the city center and discourage car usage.
In February 2016, LTA announced the development of a new ERP system (ERP2) based on Global
Navigation Satellite System Technology and cellular telematics (designed for 4G LTE) with cameras to
enforce traffic rules (The Straits Times, 2016). Figure 3 illustrates the ERP2 concept. The new system
will be able to charge drivers’ congestion taxes as well as parking fees automatically. It will also be able
to alert drivers about congestion through the vehicle add-on. The government is considering using ERP2
to charge users based on distance driven, though not in its immediate rollout in 2020. While other cities
have implemented ERP and automatic parking charges by using Automatic Number Plate Recognition
(ANPR), Singapore’s ERP2 system is able to provide much more data and functionality, making it a large
step forward in V2I technology.
Figure 3. ERP2 Concept. (source: The Straits Times, LTA)
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CHALLENGES AND EXPECTATIONS FOR THE FUTURE
In a Pew survey of 1,606 experts, 83% responded that they expected the Internet of Things to
“have widespread and beneficial effects on the everyday lives of the public by 2025” (J. Anderson et al.,
2014). For example, if wearables were adopted into Singapore’s smart mobility system as a way to
promote and track active mobility - through, for example, schemes which reward those who spend
more time walking, biking, or using personal mobility devices - that may reduce congestion and
encourage healthy behaviour. However, there are many concerns about the trade-off between
convenience and privacy. If every activity is monitored, and hundreds of other smart objects are able
to make decisions, they can also manipulate people’s behaviours and choices, leading to potential social
ills. Additionally, it is challenging to ensure the security of many connected objects. They may be
vulnerable to hacking, and there is also the issue of installing new firmware on each object as updates
are released, which people are already reluctant to do with their current devices. (M. Anderson, 2014b)
The challenges of connected vehicles include privacy, security, data ownership and liability. The
cost of adoption is also an issue: if initial V2X applications are a value-add for the driver, the consumer
may pay a monthly fee or a higher price for the vehicle. Otherwise, the government may need to
provide subsidies to encourage uptake. Finally, connected devices that interact with drivers can lead to
distraction and unexpected errors.
5G cellular networks are expected to arrive in 2020, with 1000 times the system capacity, a
100-fold increase in data rates and device connectivity, and significantly reduced latency to enable
tactile Internet, augmented reality and real-time and dynamic control of machine-to-machine
communication. (NTT Docomo, 2014) Connected vehicles may employ some kind of combined
connectivity using DSRC for basic safety applications and 5G or other next-generation cellular networks.
These communications will contribute to a safer driving experience and potentially usher in
autonomous vehicles. With improved V2V and V2I technology, it should be possible to have both AVs
and human-driven vehicles on the road at the same time. In Singapore, the implementation of ERP2
and 5G cellular networks creates an opportunity for connected vehicles to catch on even before 2040,
catalysing a shift towards AVs.
Essential Reading
Jin, P., Fangnat, D., Hall, A., & Walton, C. (2015). Emerging Transportation Technologies White Papers
Volume 2: Connected Vehicle Technologies (Tech. No. 0-6803-P2): University of Texas Austin
Center for Transportation Research.
The Straits Times, S. (2016). ERP 2.0 goes the distance with new tech. : Straits Times.
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AUTONOMOUS VEHICLES
SAE International defines 6 different levels of driving automation for on-road vehicles. These levels
range from Level 0 for no automation to Level 5 for full automation as shown in the Figure 4 (SAE
International, 2014).
In this report, autonomous vehicles (AVs), which are also popularly known as self-driving or
driverless vehicles, are considered to be at Level 5 of this scale. Such vehicles are capable of handling
all aspects of driving on all types of roads and in all environmental conditions. AVs may be personally
owned, fleet vehicles, or part of a larger public transportation system such as shuttle buses.
AVs are expected to increase convenience and address manpower and land constraints as well
as safety concerns. Human error is often the last failure in a chain of events leading to each road
accident (NHTSA, 2008). Sophisticated on-board systems of AVs can navigate without human
intervention and have the potential to reduce road accidents substantially. In addition, AVs free up time
for passengers for the duration of their commute since no human drivers are needed.
CURRENT STATE AND ROLE IN SINGAPORE’S MOBILITY SYSTEM
Many vehicles today already possess some degree of automation using a variety of driver-
assistance tools that aid in steering, acceleration and deceleration. These vehicles typically fall under
SAE Levels 1 and 2, and human drivers are still in charge of monitoring the driving environment.
Google’s dome-shaped two-seater, which is still under development, is considered a SAE Level 4
vehicle. At this level, automated driving systems monitor the driving environment, minimising human
intervention because the system has complete control of the car.
Research is ongoing to develop vehicles that can achieve full autonomy. Challenges like getting
such vehicles to operate in adverse weather conditions like thunderstorms and on different types of
roadways are still works-in-progress.
Automation features such as lane-keeping assistance, parking-assist, collision avoidance, and
adaptive cruise control are already widely available, and vehicle manufacturers such as Ford, Renault,
Nissan, and Toyota anticipate the launch of the first commercially-ready AVs by 2020 (Naughton, 2015)
(Turvil, 2016) (D. Lee, 2015). Figure 5 shows Olli, an autonomous shuttle designed by Local Motors.
Trials are in progress around the world. For instance, Delphi Automotive completed a coast-to-coast
drive in the United States in April 2015, with 99% of the journey in automated mode (Delphi
Automotive, 2015). In the United Kingdom, the UK Autodrive consortium consisting of companies such
as JLR, Tata Motors, Ford, and Thales are preparing for trials of autonomous passenger cars in Coventry
and Milton Keynes that will last until 2018 (Matthews, 2015). However, a number of technical
challenges remain, and recent deaths in Tesla AVs pose further challenges to implementation and
adoption (NTSB, 2016).
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Figure 4. SAE International J3016 Levels of Driving Automation. (SAE International, 2014)
According to the LTA and Ministry of Transport, AVs can potentially address Singapore’s land
and manpower constraints (LTA, 2015; LTA & MOT, 2015), and self-driving vehicle trials are ongoing in
the one-north region and Gardens by the Bay. AVs such as the Alphard built by A*STAR (A*STAR, 2015)
and SCOT by SMART-NUS (SMART, 2015), and the Vehicle-to-Infrastructure NTU-NXP Smart Mobility
Test Bed (NTU, 2015) are examples of existing initiatives. In addition, several stakeholders are jointly
developing technologies such as autonomous truck platooning. For instance, the Ministry of Transport,
Maritime and Port Authority, and PSA Singapore are researching automated guided vehicles (Aggarwal,
2015), and the Sentosa Development Corporation and ST Engineering are developing self-driving
shuttle services (Ong, 2015).
Figure 5. Autonomous Bus (source: Olli)
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CHALLENGES AND EXPECTATIONS FOR THE FUTURE
There are a number of ways in which AVs may benefit the transport ecosystem in Singapore.
AVs may be used to move packages from point-to-point during off-peak hours, reducing the number of
vehicles on roads during peak periods. AVs may also be employed as feeder bus services or on-demand
transport, alleviating manpower shortages in the transportation sector.
Moreover, AVs may become commonplace in Singapore faster than elsewhere in the world due
to V2I technologies already implemented for ERP2. Such technologies would assist both semi-
autonomous and fully-autonomous vehicles with automated navigation while easing congestion
through real-time traffic planning and routing. This would also enhance road safety as vehicles will be
more aware of their surroundings and can reduce accidents caused by human error.
Policies will have to address issues of regulation, insurance, liability and social acceptance.
Given that vehicles have useful lives of at least 10 to 20 years, the government should prepare for a
long transition period in which vehicles of many different levels of autonomy operate on the same
roads. Additionally, some benefits may not be as great as expected. Freight deliveries may still require
physical hand-offs to customers, meaning that autonomous freight vehicles may not reduce manpower
requirements. Also, although truck platooning is useful for highway driving, individual vehicles will
eventually diverge to reach their respective destinations. As for passenger services, even though AVs
could be useful for senior citizens who may need assistance to travel, it is unclear whether they would
be receptive to AVs, especially if there is still a possibility of accidents. In addition, the ease and comfort
of travelling in AVs may result in more trips being made.
Given such limitations, the adoption of AVs may take longer than expected. A report from the
Victoria Transport Policy Institute expects that the impacts of AV technology will not be felt until the
2050s or 2060s. This projection was based on the implementation time of past vehicle technologies
and the technological infrastructure required for AVs (Litman, 2015). Nonetheless, we expect that AVs
will have a high impact on the transport ecosystem, but the full benefits of a fully autonomous network
of vehicles may only be realised in a few decades.
Essential Reading
Litman, T. (2015). Autonomous Vehicle Implementation Predictions: Victoria Transport Policy Institute.
Jin, P., Fangnat, D., Hall, A., & Walton, C. (2015). Emerging Transportation Technologies White Papers
Volume 2: Connected Vehicle Technologies (Tech. No. 0-6803-P2): University of Texas Austin Center
for Transportation Research.
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ELECTRIC AND ALTERNATIVE FUEL VEHICLES
Electric vehicles (EV) rely on batteries and significantly reduce noise and air pollution. Hybrid electric
vehicles (HEV) have both an electric motor and traditional engine that are either coupled to use
regenerative braking and motor assistance, or independently use either petrol or electricity. Alternative
fuel vehicles on the other hand simply run on fuels other than petrol or diesel - this category includes
EVs that also run on solar power, biofuels, compressed or liquid natural gas, or hydrogen).
There have been numerous attempts worldwide to invest in alternative fuels and electric
vehicles as environmental consciousness has risen. Figure 6 shows Tesla's concept of electric car and
charging stations. However, EVs have higher upfront costs than traditional vehicles and Singapore’s
vehicle tax reduces their life cycle cost competitiveness.
Figure 6. Electric Vehicle (source: Tesla)
Furthermore, Singapore’s available energy sources are limited, such that the electricity used
by EVs produces carbon emissions on the overall, and the ostensibly “zero-carbon” EVs are still subject
to emissions taxes (Tan, 2016). Additionally, the accessibility of alternatives such as compressed natural
gas fuels is limited. Compressed natural gas (CNG) vehicles experienced a short boom in popularity that
diminished rapidly when users found very few locations (with short operating hours) for refuelling their
cars. Many have reverted to using the petrol engine almost exclusively (Tan, 2010). Consumers are
now turning to diesel cars (Cuellar, 2015) as a semi-alternative fuel source, drawn by low prices, better
mileage and reduced CO2 emissions albeit higher particle emissions.
CURRENT STATE AND ROLE IN SINGAPORE’S MOBILITY SYSTEM
In LTA’s investigation of EVs in 2011-2013, EVs were deemed economically unfeasible at that
time, although the interagency Electro-Mobility Singapore (EMS) Taskforce found them to be
technically feasible in Singapore. The lifetime cost of an EV is still significantly higher than that of an
internal combustion engine vehicle (LTA, 2014), and in addition to the high upfront costs of owning an
EV, there is little public charging infrastructure. However, it is also noted that the test bed laid the
groundwork for an EV ecosystem based on electric vehicle sharing (1,000 shared electric cars would be
deployed by 2020) and investigating the use of electric fleet vehicles (HDT Singapore Taxi applied for
an operator license for 100 electric taxis) (Channel News Asia, 2016), (A. Lim, 2016).
Costs will only go down once battery technology improves and when a certain critical mass of
vehicles is on the road, and buy in will only occur once there are many public charging stations and
several EV types for consumers to choose from, which results in a chicken-and-egg problem.
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Bloomberg’s New Energy Finance research predicts that battery technology will become economically
feasible around 2025 and that 35% of new car sales will be EVs by 2040. Some businesses are adopting
HEVs in the meantime as it allows for faster growth than fully EVs given the current lack of infrastructure
(K. Lim, 2016). Plug-in HEVs went on the market in Singapore in 2008 and as of Mar 2016, there are two
pure EVs and 112 Plug-in Petrol Electric Vehicles registered (Energy Research Institute, 2016). This is a
very small percentage of Singapore’s total personal vehicles on the road, though it is expected that
HEVs are most likely to grow before full EVs in most markets (The Economist, 2004).
CHALLENGES AND EXPECTATIONS FOR THE FUTURE
Experts we spoke to were pessimistic that EVs would form an important part of the transport
ecosystem in Singapore by 2040. However, they agreed that if there was strong political will backing a
widespread rollout, EVs could be viable within only a few years. The LTA acknowledges that this rollout
is technically feasible, but challenges to implementation remain. Currently, EVs in Singapore are used
mostly in car sharing schemes or for research, though the government is supportive of further
development and expansion. EV technology may also play a significant role in mobility modes in the
future, whether in cars or other devices taking advantage of potential future charging station
infrastructure across Singapore. For now, companies must install their own charging infrastructure
instead of using public resources; standardised charging must eventually be developed to enable EV
interoperability between networks and countries (Energy Research Institute, 2016).
Electrification of buses, or at least hybridisation, will likely occur by 2050 according to the LTA’s
E-mobility Technology Roadmap. Buses in Singapore produce the highest amount of emissions per
vehicle, and the Energy Research Institute at Nanyang Institute of Technology estimates that
electrification of 50% of buses and hybridisation of 10% can lead to a 56% decrease in bus emissions,
compared to a 25% decrease in personal vehicle emissions if EVs are adopted (Energy Research
Institute, 2016).
A technical risk of EVs becoming commonplace is grid overload, though some estimates suggest
that EVs in Singapore will only increase daily grid load by 4.8% (LTA, 2014). However, if a significant
number of EVs are charging at once (for example, overnight) then that could cause grid issues which
may need to be addressed by battery swapping and charging in off-peak hours (Bullis, 2013). The public
may not adopt these vehicles if they are both expensive and limited to off-peak travel, as it significantly
reduces the convenience of owning a car. Finally, there are some safety risks with EVs: for instance they
are usually very quiet, which can be dangerous for pedestrians who do not hear them approaching.
It is expected that EV technology will play a large role in concert with other technologies such
as AVs and be an influencing factor in new designs for mobility systems. Accenture identified seven
success factors for EV adoption in 2014, which include integrating EVs into the eMobility value chain –
for instance, through car sharing or other value propositions to consumers. The impact of EVs in
Singapore will not be so much an environmental one (due to upstream energy sources) as a symbolic
and technological stepping stone into the future of transportation.
Essential Reading
Accenture. (2014). The Electric Vehicle Challenge: Electric Vehicle Growth in an Evolving Market
Dependent on Seven Success Factors Accenture.
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PERSONAL MOBILITY DEVICES
Personal Mobility Devices (PMDs) are relatively lightweight, can travel up to 25 km/h, and typically carry
a single person. Electric scooters (eMicro One, e-Twow), hoverboards (Powerboard, IOHawk),
skateboards (Boostboard, Onewheel) and electric unicycles (Ninebot One) all fall into this category and
have become popular in Singapore in recent years. Figure 7 shows two common forms of PMDs in
Singapore.
Figure 7. Personal Mobility Devices (source: James Martin/CNET)
Bicycles are also personal mobility devices, and folding bikes are becoming a popular choice for first
and last mile travel. Electric bicycles are also used widely, but many are too heavy and move at faster
speeds than typical PMDs.
Personal mobility assistants include wheelchairs and other assistive technologies for limited-
mobility users and are not subject to the same weight limits as PMDs. Much of the research on electric
PMDs pertains to the use of Segways, which are significantly larger than the PMDs allowed in Singapore,
but have applicable lessons with regard to the use of PMDs for first and last mile travel (Dowling et al.,
2015).
CURRENT STATE AND ROLE IN SINGAPORE’S MOBILITY SYSTEM
The battery-powered PMDs of today use various approaches to mobility. Some use “intuitive”
technology or a gyroscope, relying on the rider’s shifting weight to accelerate or change direction;
examples include hoverboards and Segways. Some skateboards are steered by shifting weight and
accelerated or stopped using a hand held device. Scooters may accelerate and brake using handlebar
controls or by manually kicking off, and turning using the steering bar (Hollister, 2016).
In April 2016, the LTA released official rules on the use of PMDs and bicycles, allowing them on
both foot and cycle paths if they meet certain weight and speed limits. This allows for the integration
of PMDs into Singapore’s mobility system for first and last mile travel, between home and the MRT or
bus station. Singapore’s footpaths are also well-kept and easier to ride on than in other cities. However,
some are concerned by the limited enforcement and unclear rules about fines or other punishment for
speeding or reckless behaviour on narrow footpaths (A. Lee, 2016). Insurance policies for PMD users
and cyclists are now available to protect against personal harm or damage caused to others, further
encouraging use of PMDs (NTUC Income).
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CHALLENGES AND EXPECTATIONS FOR THE FUTURE
Due to the safety concerns about hoverboards and other electric PMDs, some predict that such
technology is already on its way out, with bans in the US catalysing withdrawal. Amazon has recalled
several brands of hoverboards due to fires occurring from malfunctioning lithium ion batteries, and the
production of these PMDs is not well regulated. Studies in cities in the US and Australia have shown
that crash rates per mile for active mobility modes are higher than in passenger vehicles. However, as
active mobility increases in a community, both traffic and pedestrian casualty rates decline (ABW, 2010-
2016). Acceptance rates notwithstanding, there are still concerns about sidewalk congestion and
mixed-speed users sharing the same small walkways, and falls from these relatively high speed vehicles
can prove fatal (Cheong, 2016). As Singapore moves towards allowing them on footpaths and
promoting PMDs as a form of active mobility, they may increase in popularity instead of disappearing
quickly as they have in other parts of the world, especially if PMDs can become safer for both users and
pedestrians without increasing substantially in price.
While electric PMDs solve some of the criticisms of conventional bikes, such as not requiring
too much effort and being smaller and more readily carried onto public transportation, they are still
heavy to carry over long distances and seen as unprofessional. Reducing the physical exertion required
in last mile travel does not completely combat the issue of sweating due to Singapore’s climate.
Additionally, adverse weather hinders their use, and PMD’s often cannot handle steep gradients.
Moreover, they are more expensive than conventional bicycles.
There are two ways PMDs might be utilised in the coming few years. Firstly, they may continue
to serve in the same way as bicycles as a form of last-mile transportation, sharing the same lanes as
pedestrians and encouraged through government and workplace policies. A sharing model, much like
bike shares such as Hubway or Barclay Bikes, could be developed. Alternatively, they may advance with
technology, becoming faster and more “pod-like” and requiring separate lanes, being neither cars nor
small PMDs – much like the ambiguous space e-bikes currently occupy. This has been the evolution of
Toyota’s PMDs, with the i-Swing and i-Real as electric wheelchairs that can navigate pedestrian spaces
with ease to the newest model, the i-Road, which resembles an enclosed motor bike and uses intuitive
motions of the passenger to move quickly on roads, though not as quickly as a traditional car.
Essential Reading
Dowling, R., Irwin, J., Faulks, I., & Howitt, R. (2015). Use of personal mobility devices for first-and-last
mile travel: The Macquarie-Ryde trial. Paper presented at the 2015 Australasian Road Safety
Conference, GoldCoast.
Panel., A. M. A. (2016). Recommendations on Rules and Code of Conduct For Cycling and the Use of
Personal Mobility Devices LTA.
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SHARED CITY CARS
City Cars are “right-sized” vehicles for use in urban areas, meaning that they are usually sized for 1-3
people. Vehicle occupancy rates in Singapore stand at less than two people per vehicle (Menon et al.,
2006), creating an opportunity to ease congestion and parking issues through more compact vehicles.
City cars are also more fuel efficient, lightweight, and require fewer materials in construction, making
them economical to buy and use.
Car Sharing systems allow people to own and rent cars, or collectively own cars, and some
predict a future of shared city cars. Newer iterations are based off mobile technologies to facilitate
sharing. Arthur D. Little’s Future of Urban Mobility Report predicts that car sharing will become mass
market in the next few years, and proffers several car sharing business models (Van Audenhove et al.,
2014). In urban environments, shared city cars offer a possible avenue for optimising land use through
fewer and smaller cars in addition to reducing emissions.
CURRENT STATE AND ROLE IN SINGAPORE’S MOBILITY SYSTEM
There are different models of implementation for city cars and car sharing around the world.
Japan has regulated city cars, called kei cars, which were popularised in the post-war era to encourage
motorisation. Now there are several electric versions as well, and all kei cars have reduced taxes
compared to full size cars, but are personally owned vehicles. Seoul has a car sharing network has been
growing rapidly since 2013 (SMG, 2015). By using a public-private partnership model and mostly small
domestic city cars or EVs, in the last three years Seoul has deployed over 4,000 vehicles (Hong, 2016),
been used by over 1.9 million people, and estimated that 1 shared vehicle removes 8.5 vehicles from
the road (Seoul Metropolitan Government, 2015). Finally, car2go is the largest car sharing company in
the world, located in 29 cities in Europe and the USA as well as China. It exclusively uses city cars:
conventional or electric Smart For-two cars. Their model allows one-way trips and does not strictly
require reservations, addressing two complaints users have about traditional car sharing programmes
(Car2go, 2016).
Major companies and research groups parade concept ‘city cars of the future’ every few years.
However, few gain traction. MIT’s 2007 CityCar (Figure 8), pitched as an eco-friendly solution to
transportation woes, was extremely small, electric, designed for car sharing programmes, and could
fold itself to stack upon other city cars and consume less space when immobile. However, due to slow
commercial production, the project leader declared the technology obsolete and said AVs would fill the
niche instead (Frayer et al., 2015).
Figure 8. MIT CityCar (source: Yahoo News)
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Traditional car sharing in Singapore exists but is not very popular, likely due to the
inconvenience of several small companies spread out across the island, strict regulations, and lack of
availability of options. However, experts have pointed out that when ERP2 becomes operational, there
will be an opportunity to overhaul the vehicle tax regime and improve it such that the population of
city cars increases and congestion decreases.
CHALLENGES AND EXPECTATIONS FOR THE FUTURE
Both car sharing services and smaller city cars encourage users to think of cars as a utility, as
opposed to a status symbol (Wall, 2014). Several car manufacturers continue to try to make similar
extremely small cars work – Nissan and Renault have piloted a city-car sharing programme with Scoot
in San Francisco, and Toyota’s i-Roads are shared on the streets of Grenoble, France. In visions of the
future, city cars, EVs, and mobile technology all work together to provide a seamless and sustainable
transportation experience.
Some challenges to car sharing in Singapore include complex tax structures and ERP charges,
as well as expensive parking. The question of ownership and responsibility for damage is another
barrier. It is also expensive and inconvenient to use traditional car rentals. Moreover, on-demand
services Uber and Grab are already popular, with ride-sharing apps like Ryde aiming to fill the gap, so
driving within Singapore looks even less attractive.
There are also some concerns as to whether car sharing and ride-sharing are in direct
competition with one another or if they can coexist, and which option users will prefer in the future.
Ride-sharing is currently based on personal ownership of a vehicle, and may become too costly or
burdensome if a car sharing plan is adopted. Car and ride-sharing could work together in the case of
entirely autonomous vehicles on the road that optimise routes and pick up multiple passengers, though
it would be a fundamentally different model to today’s car sharing.
Many predict that AVs will also effectively be right-sized city cars, which will be able to trail
each other and work cooperatively. In fact, the replacement of MIT’s CityCar is their Persuasive Electric
Vehicle (PEV) that is intended to act as a combination of EV, PMD, city car and autonomous human and
freight transporter (Barr, 2015).
Essential Reading
Van Audenhove, F., Korniichuck, O., Dauby, L., & Pourbaix, J. (2014). The Future of Urban Mobility 2.0:
Arthur D. Little Future Lab, UITP.
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DRONES AND FREIGHT ROBOTICS
A drone is any type of Unmanned Aerial Vehicle (UAV). Typically seen as a last-mile delivery solution,
drones run on battery power and use a variety of sensors and multiple rotors to stay aloft, control their
position, manage inclement weather, and land safely (Pullen, 2015). Gyroscopes, pressure sensors,
accelerometers and GPS provide thousands of data inputs per minute, and may use several processors
in parallel.
An Automated Ground Vehicle (AGV) is an unmanned ground vehicle that is quite common in
factories and warehouses, but not typically used for last-mile deliveries. They use similar sensors to
drones to receive information and navigate a warehouse or loading dock, or follow a predictable path.
Several types of AGVs are used, from automated forklifts to unit-load AGVs that might handle pallets
(MHI, 2016). These are also commonly used in ports to transition from sea to land safely and efficiently
as supersized ships become more common (Phillips, 2016), and as the demand for more sustainable or
environmentally friendly technology increases (Wieschemann, 2016). These innovations indirectly
impact Singapore’s mobility system through the way goods may be handled in the future, as well as
land-use impacts and keeping up with increasing demand for global goods.
CURRENT STATE AND ROLE IN SINGAPORE’S MOBILITY SYSTEM
Despite many predicting drones to be pervasive by now, they have yet to be deployed en masse
due to regulatory challenges. Drones as goods transport solutions have been gaining popularity since
big players like Amazon (PrimeAir, as shown in Figure 9) and Google (Project Wing) announced plans in
2014 to deliver packages to customers via drone. However, this use case may be years away from
release, due to both technological and legal limitations.
Figure 9. Amazon PrimeAir (source: Amazon)
Drones are more commonly used in military applications such as attacks and surveillance or for
filming (BBC News, 2012) rather than for transportation, although some companies are able to use
drones to transport high-value/low-weight goods in areas without flight regulations and limited road
infrastructure. Matternet uses drones to deliver medicines and blood samples in developing areas like
Haiti and Lesotho, where road networks are scarce and regulations lax, averaging 24 cents per journey
(Raptopoulos, 2013). They hope to make use of drones in congested cities by effectively having a layer
of airspace dedicated to a drone postal system. Drones are also being assessed for potential use in
organ donation/transplants between hospitals (Kumarl, 2016).
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AGVs continue to be instated, particularly in ports, but due to the high cost of replacing an
entire system, implementation is rolled out over several years. A smaller and nimbler type of AGV is
beginning to appear in industrial settings, and can easily move from industrial to commercial settings.
Some new industrial robots carry small loads or work collaboratively with humans (sometimes called
cobots). Amazon’s picking robots are an example of these cobots which speed up warehouse activities
and are accurate about 98% of the time (Heath, 2016). Amazon’s robots have several competitors
which work as “fast mechanical pack mules,” following a human picker around and carrying a load until
an order is complete, then taking it to a packing station or recharging itself (Soper, 2015). Figure 10
shows such robots by Fetch.
Figure 10. Fetch Robotics (source: Evan Ackerman/IEEE)
Drones are not currently a major part of Singapore’s mobility system, but a hobbyist’s item.
However, an agreement was recently made to test drones for last-mile delivery in a collaboration
between NUS and Airbus, and several other inter-agency uses are currently being tested (Aircargo
News, 2016). SingPost has also done a test flight with a drone between the mainland and Pulau Ubin
(SingPost, 2015). Singapore’s ports have moved towards freight automation, investing heavily in the
Pasir Panjiang Terminal and Tuas ports.
CHALLENGES AND EXPECTATIONS FOR THE FUTURE
The challenge with drones, AGVs, and cobots are that they are currently expensive, but as the
price of sensors and computers drops, they become more economically feasible. Common concerns
include privacy and possible job reduction as the transportation and manufacturing sectors move
towards automation. However, for cities with labour shortages, this may instead be helpful.
Drone technology itself may continue to improve and even carry humans, as E-hang’s human
sized drone (which is still under testing) is purported to do (Rundle, 2016). In the next 25 years, city
airspace may be regulated to allow and manage drones for last-mile goods travel or even to replace the
current postal system. As more items are delivered on-demand, travel patterns may change as people
need to make fewer trips. At the very least, drones will continue to be used for monitoring and safety
purposes. Communication between UAVs and cars may reroute traffic as V2X technology becomes
more widespread. For example, as proposed in the Siemens 2015 Mobility IDEA competition, drones
could communicate with cars to lead them to an open parking space (ITS International, 2015). Drones
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may also monitor infrastructure quality and deploy workers only when a fix is required, avoiding
accidents, costly repairs and shut-downs (Chant, 2014).
AGVs may be deployed in an underground freight network to reduce congestion and improve
efficiency. Switzerland is already planning the Cargo Sous Terrain, an autonomous underground
logistics system for pallet-loaded AGVs running along electromagnetic tracks (Cargo Sous Terrain).
These pallets may then be unloaded at delivery centres throughout the city and run for 24 hours a day.
Robots and other automated assistive devices have huge potential for business, government,
and individuals, with the market expected to increase ten-fold in the next five years (Tobe, 2015). They
will no longer be used almost exclusively in manufacturing, but may also be deployed alongside humans
for any number of tasks. They may work together with AGVs and drones as e-commerce grows, picking
packages or buying items and then sending them to consumers via an underground network of AGVs
or via drone. Alternatively, they may become so cheap that citizens can own them, as has happened
with the Roomba, a robotic vacuum cleaner. Future cobots can assist with shopping, cleaning, and even
providing care for the elderly to promote aging-in-place. Developments will have to be made in robot-
human interaction and in increasing comfort levels with smart machines for such a reality to manifest.
Essential Reading
Tobe, F. (2015). Why Co-Bots Will Be a Huge Innovation and Growth Driver for Robotics Industry. : IEEE.
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VIRTUAL REALITY AND TELECOMMUTING
Telecommuting, or working outside a central office and transferring information remotely, is an idea
which existed even before mobile technology became commonplace. In 1973, Jack Nilles wrote The
Telecommunications-Transportation Tradeoff, proposing telecommuting as an alternative to driving
into central business districts and recommending the use of satellite offices (Gan, 2015). Several studies
have noted that telecommuting reduced overall person-miles per day. However, there is limited
research on how this impacts overall mobility patterns (Kitamura et al., 1991). With the rise of the
Internet, faster connection speeds, and near-instant information transfer, telecommuting is much
easier now than in the 1970s but can further be improved using artificial reality technologies.
Augmented Reality (AR) overlays existing reality with virtual enhancements that can be
distinguished from reality. This is frequently used in mobile devices. Virtual Reality (VR), on the other
hand, is an immersive artificial simulation or recreation of real-life situations, often experienced
through a headset (Augment, 2015). This may influence transportation patterns, as certain activities
people might travel for (e.g. movies, meeting venues) may take place in a virtual world instead (see
Table 1 for details).
Table 1: Scope of Augmented Reality and Virtual Reality (Adapted from PWC)
Augmented Virtual
Reality (AR) Reality (VR)
Presence
Refers to whether the user is physically present at the location of the Yes No
experience.
Movement
Refers to whether the user can physically navigate through the Yes No
environment
Real-time
Refers to whether the user can interact in real-time with the Yes Depends
environment he/she is in
See-through Capability
Refers to whether the user can see past the environment he/she is to Yes No
see the physical space around them
CURRENT STATE AND ROLE IN SINGAPORE’S MOBILITY SYSTEM
Both AR and VR have a variety of products associated with them. Microsoft HoloLens, Magic
Leap (Figure 11), and the Oculus Rift are all on the verge of going to market, with smartphone enabled
“headsets” such as Google Cardboard already in the market, albeit not yet used for telecommuting.
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