The Oslo study: How will
MaaS defeat traffic?
Modeller, we
simulated around
60 different
forecasts. The busiest
scenario includes existing
car drivers, their passengers
and public transport riders on
tram and bus. This equates to
over 600,000 trip makers using
shared mobility in the
simulated time period
between 6am and 10am.”
The most optimistic scenario
regarding the reduction of
kilometers driven is achieved
when all car users share their
rides and public transport riders
continue to use the services. All
scenarios show a significant
drop in the number of cars
needed to cover all trips,
indicating between 7-16% of the
current privately owned vehicle
fleet could serve the demand in
the morning rush hours.
Measuring results
“The study’s detailed results are
based on modeling up to 600,000
simultaneous trip requests over
are an essential part of
Oslo’s mobility system.
In a recently published
report, consulting firm COWI
and software company PTV
Group analyzed what shared
autonomous transport and
passenger uptake would look
like in the region in four
different scenarios. The
scenarios consider both car
and ride sharing, examining
the mobility services during
morning rush hour on a
working day in Oslo and the
neighboring county Akershus.
Reducing cars, not service
The report considers the impacts
that fleets of autonomous
vehicles can have on the region’s
network through an increase or
decrease of total vehicle
kilometers travelled, the number
of cars needed to cover the
demand and the level of service
provided to the customers.
Paul Speirs, modeling expert
at PTV Group, says, “With our
software tool, PTV MaaS
Technology Profile |
How do you forecast and
| Need to know
Just 7-16% of the
current privately
owned vehicle fleet in
Oslo would be enough
to serve the demand in
morning rush hours
Traffic Technology International September/October 2019
www.TrafficTechnologyToday.com
076
predict future
technological
developments, consumer needs
and the potential uptake of new
solutions? Experts agree that
Mobility as a Service (MaaS)
is a key concept that sets the
framework for other
developments. MaaS is based on
a transportation system where
different services are integrated
into a single mobility service that
is on-demand and able to meet
individual customer requests.
As the development of
autonomous vehicle technology
is gaining momentum, selfdriving
vehicles will be the norm
in future mobility scenarios, not
the exception. In Oslo, Norway’s
capital, the future is now. Selfdriving
buses have been on trial
since May this year and the city’s
public transport company, Ruter,
is already looking further into
the future of transport where
MaaS and autonomous driving
a four hour period
served by a fleet of
up to 56,000 vehicles
travelling close to 1 million
journey legs,” says Speirs.
“Planning for the right
infrastructure investment with
the uncertainty autonomous
vehicles bring is challenging.
The Oslo study serves as a
fundamental basis for
sustainable policy decisions
regarding future mobility
investment and risk
management.”
PTV’s MaaS Modeller
calculates many combinations
of shared mobility operation
assumptions. These can include
– among many variables – the
total shared mobility traveler
demand, the catchment area,
pre-booking time, the available
vehicle fleet size, the maximum
wait time for the traveler and
the acceptable journey detour
time for ride sharing.
The combination of these
variables, in turn, produces a
distribution of possible future
> PTV MaaS Modeller
calculates variables
including the total shared
mobility traveler demand,
the catchment area and
pre-booking time
> PTV MaaS Modeller also
identifies benign variables
that have little or no
impact on the business
model and those that are
subject to change
/www.TrafficTechnologyToday.com
