Stefanie Peer
stefanie.peer@wu.ac.at Asjad Naqvi Funded by the:
naqvi@iiasa.ac.at
Gerald Richter
gerald.richter@ait.ac.at
Christian Rudolf
christian.rudolf@ait.ac.at
Markus Straub
markus.straub@ait.ac.at
Simulating the Socio-economic and Environmental Effects of Shared Autonomous Electric Vehicles
A Case Study of Vienna
Background and motivation
Soci o-economi I c mpacts i mpact s are ? uncl Envi ear ronment al i mpact s Three devel opments i n mobi l i ty
Electric vehicles Shared
vehicles Self-driving SAEVs Autonomous
vehicles
+ + =
rel at ed emi ssi ons have gone
I n Austri a by
si 67% nce 1990
Project-related Sustainable Development Goals (SGDs)
● To identify environmentaland socioeconomiceffects ofSAEVs,as wells as synergiesand trade-offsbetween them.
● To extend an agent-based model(ABM)ofVienna’s transportsystemwith a module thatallows forthe simulationofscenarios related to SAEVs.
● To supportthe formation oftransportpoliciesthatlead to a reductionin transport-related emissions,while maintaining an efficientand inclusive transportsystem
Objectives
Working papers
● Peer,S.,Naqvi,A.,Schöggl,A.(2019).Shared,autonomous,electric vehicles (SAEVs):Solving urban challenges?
● Adler,M.,Peer,S.,Sinozic,T.(2019).Autonomous,Connected,Electric Shared vehicles (ACES)and public finance:an explorative analysis.
Presentations
● Richte
● Richter,G.,Rudloff,C.,Straub,M.(2019).Enriching the features ofa
synthesised population – using generative neuralnetworks forpopulation synthesis.Presented atStochastic Models,Statistics and theirApplication (SMSA),Dresden,6.– 8.3.2019.
Public outreach
● Website: www.SimSAEV.eu
● Twitter: @SimSAEV
Dissemination
● SAEVs have importantimplicationsforthe environment,the transport system,public space,public finance,and inequality(in particular
regarding accessibility)
● WhetherSAEVs exacerbateorsolve existing urban challengesis largely dependenton km drivenby SAEVs and the overallnumber ofcarspresent
● Withoutappropriate policy interventions,both the km drivenby SAEVs and the overallnumber ofcarspresentwillbe higher than socially
optimal
● The introduction ofroad tollsin line with “user pays”and “polluter pays” principles willbecome more attractive
Work Package 2 - Literature Review
Work Package 4 - Policy Scenarios
● Price structures ofSAEVs and preference structure ofindividuals ● distance- vs traveltime-based pricing
● income distributions,locations,and preference structures
● Enviromentalimpacts ofSAEVs
● Heatislands (parking lots) versus emptry rides ● Energy use ofSAEVs
● Socioeconomic implications for
● Socioeconomic implications for
● Non-car owners,poorly connected neighhborhoods ● Differentage and income groups
● Meso and Macro implications ofSAEVs
● Ownership structures,public finance and regulation ● Impacts on urban sprawland infrastructure
Vienna facilities data
Population Synthesis
The goalofthe population synthesis is to generate an artificialbutrealistic population for the simulation which matches the realpopulation (öu data),e.g.has the same age distri- bution or modalsplit.
Baseline synthesis methods
● Randomized sub-sampling from Österreich Unterwegsdata
● For realistic performance tests on the multi-agentsimulation ● For comparison with more refined synthesis approaches
● Iterative proportionalfitting Advanced synthesis methods
● Artificialneuralnetworks applying variationalautoencoders Nextsteps
● Use alternate data sources to check regionaldata setfor possible
corrections regarding demography
● Refine advanced synthesis methods and comparisons
Simulations:
The goalofthe traffic simulation is to evaluate the impactofdifferentpolicies and impactfac- tors (e.g.pricing scheme ofSAEVs) for the creation ofpolicy scenarios in WP4
● Multi-agenttransportsimulation based on the open-source framework MATSim*
● Builtupon MATSim core + AV module
● Directsimulation ofcar + SAEV traffic
● AIT Ariadne routing framework for intermodal routing (foot,bicycle,public transport)
● Integration ofintermodalmode choice model
* Widely used transport simulation in the research context, intitally developed at ETH Zurich.
Work Package 3 - Transport Simulation
Routing Data
●OpenStreetMapsstreet network
●OGD PublicTransport timetables
MatSIM simulation interface
CoverageArea
● MetropolitanareaofVienna
● ~30km radiusaroundcenter
● ~2.3m inhabitants Mobility Data
●Österreichunterwegs(öu) mobilitysurvey
●Containsstatistical
populationcharacteristics FacilityData
●OpenStreetMap
●POIs
●GEOSTATpopulation
