Simulating transport and societal effects of automated
vehicles
Astrid Gihnemann ‘i 2s
Paul Pfaffenbichler Simon Shepherd Gunter Emberger
Institute for Transport Studies is s a 3
a Institute for Transport Studies, Institute of Transportation, TU
University of Natural Resources and University of Leeds, UK Wien, AT
Life Sciences, AT
astrid.quehnemann@ boku.ac.at s.p.shepherd@ its.leeds.ac.uk tuwien.ac.at
paul.pfaffenbichlen@ boku.ac.at
Keywords: automated vehicles, private cars, public transport, transport demand, cause-effect-
diagram, dynamic land use and transport interaction modelling
Background: Not long ago self-driving cars were nothing more than an unrealistic (boyhood)
dream in science fiction movies and books. The most famous examples of autonomous, intelligent
vehicles are probably the VW Beetle “Herbie”, from the 1970s Disney movie series, and K.I.T.T.
(Knight Industries Two Thousand), from the television series Knight Rider produced in the 1980s.
In 1990 Amold Schwarzenegger's sci-fi movie "Total Recall", directed by Dutch director Paul
Verhoeven, starred automated taxis which were branded as "Johnny Cab". Today, technological
progress made in recent decades brings the dream of fully automated vehicles more and more into
the realm of possibility.
Two potential paths may lead towards fully automated vehicles. Car manufacturers favour a
stepwise, evolutionary approach from driver assistance systems towards fully automated vehicles.
New players particularly from the field of information technology, such as Google or Apple,
favour a revolutionary aiming directly at driverless operation (Glotz-Richter, 2017). The latter
attempt to develop automated vehicles (SAE levels 4 and 5) from scratch, while the former think
in typical product development cycles and successively added innovations. Recently, several car
makers announced dates for the market entrance of their first "eyes off vehicles" (SAE level 3)
and level 4 and 5 prototypes (Auto Bild, 2017) , (Kleine Zeitung, 2017a).
Automated vehicles can either substitute private cars, car sharing or taxi fleets or be part of public
transport. In the United States ride hailing company Uber is experimenting with automated
driving (Kleine Zeitung, 2017b). Pilot studies with automated busses are undertaken e.g. in the
Austrian municipality Koppl (Lagler, 2017) or the Swiss city Neuhausen (Miller, 2017). The
International Association of Public Transport (UITP) defines three different potential future
scenarios of automated driving: automated vehicles replacing private cars, automated vehicles
used in shared fleets, which compete with public transport or are integrated into public transport
(UITP, 2017).
Early simulation results: The project CityMobil (Towards Advanced Road Transport for the
Urban Environment) funded by the European Commission in the 6" Framework Program was one
of first testing automated vehicles on al large scale. The overall objective was to achieve a more
effective organisation of urban transport, resulting in a more rational use of motorised traffic with
less congestion and pollution, safer driving, a higher quality of living and an enhanced integration
with spatial development. As part of this, the System Dynamics based model MARS
(Metropolitan Activity Relocation Simulator) was used to investigate long-term impacts of local
and city-wide implementation of new automated technologies in four European cities (Shepherd,
et al., 2008). Information about MARS different case studies and example models in the formats
Vensim® Packaged A pplication (.vpa) and Vensim® Packaged Model (.vpm) could be found at
http://www. fvv.tuwien.ac.at/forschung/mars-metropolitan-activity-relocation-simulator/.
In total five different scenarios of private and shared automated vehicles have been tested. In two
of them automated vehicles are used to enhance inner city public transport. In one scenario
automated vehicles act as feeder system for public transport. Another scenario deals with busses
running automated on specially equipped tracks and finally one scenarios deals with automated
private cars. The simulations show that automated vehicles integrated into the public transport
system have a potential for strengthening public transport and improving the carbon footprint of
European cities. Although depending on the size of the scheme city wide effects can be relatively
small. On the contrary, privately owned automated vehicles lead to an increase in car mileage
travelled.
Ongoing research and revision of MARS: Currently a revised and actualised version of the
model MARS is developed in the project SAFiP (System Scenarios Automated Driving in
Personal Mobility), funded by the Austrian Ministry of Transport, Innovation and Technology.
The first step was the development of detailed causal loop diagrams identifying the connection
between automated vehicles and attractiveness and use of different means of transport. Results of
this analysis concerning private and shared cars are shown in the figure below and have so far
been programmed into a prototype MARS model of the city of Leeds, UK. First preliminary
results show a significant increase in car-km travelled in both scenarios. Peak speed decreases
with low fleet shares of automated vehicles, but recovers to higher speeds when fleet shares of
automated vehicles reach about 40-50%.
a =
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/ patting Pace senreniog He operating costs private —_—e
° weighting Xe ds = S prsatcr
accessfegress time a
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weighting in hee af ie \
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Bo du % fig SS gurersin pate car automated cr
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Summary and conclusions: An accelerating development and market maturity of highly and
fully automated vehicles can be observed. Expectations of policy makers and the public
concerning positive transport and societal effects of vehicle automation are very high. There is
still no consensus whether automated driving will happen in form of private cars, shared fleets
(car sharing, taxis) or integrated into public transport. This leads to uncertainty about
transformation paths and future ownership models. First results using qualitative and quantitative
models demonstrate that it is likely that automation of private as well as shared car fleets will
significantly increase mileage travelled.
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