MATSim Destination Choice for Shopping and Leisure Activities 1 MATSim Destination Choice for Shopping and Leisure Activities MATSim User Meeting 2012, Berlin

Topics: Destination Choice in MATSim … 2 now: future: filling the gaps between small-scale choice models and large-scale microsimulations → how fancy can the models be? → which data are required?

MATSim Destination Choice + eexplicit V + eimplicit

eij Repeated Draws: Quenched vs. Annealed Randomness destinations e00 fixed initial random seed freezing the generating order of eij e10 eij one additional random number can destroy «quench» i storing all eij i,j ~ O(106) -> 4x1012Byte (4TByte) enn persons personi alternativej store seed ki store seed kj regenerate eij on the fly with random seed f(ki,kj)

Search Space Optimum tdeparture tarrival work shopping home Dijkstra forwards 1-n Dijkstra backwards 1-n approximation probabilistic choice

Filling the Gaps future study (IATBR, STRC) 6 future study (IATBR, STRC) crux of matter in practice → study will be exemplified for specific microsimulation and data (MATSim and Swiss data) triumvirate of sources for gap: I. lack of necessary data II: computational issues III: lack of recent progress in implementation/application

State-of-Art Theoretical Destination Choice Models 7 7 broad range of disciplines such as transport and urban planning, marketing and retailing science, economics, geography, psychology. attributes/choice determinants: examples: standard attributes: prices & incomes no comprehensive literature review yet

State-of-Art Microsimulation Destination Choice Models 8 8 person age, gender, mobility tools, occupancy, home loc (ha), work loc (municipality) act chain randomly assigned from microcensus destination location (ha), open times, rough type (h, w, s, l, e) validation counts → relatively limited set of attributes other microsims → similar but no comprehensive literature review yet available

I. Lack of Data: Available Data Switzerland 9 9 main data sets, complete Switzerland: census of population (full survey) -> population / person attributes microcensus (person sample) -> demand business census (hectare) -> supply (infrastructure) miv counts (lane) -> validation only locally available (canton, municipality, city) pt schedules and lines (*) parking supply (*) green times (*) open times (*) (*) ZH scenario only

I. Lack of Data: “Missing” 10 10 “missing” attributes in MATSim incomes vot activity / shop subtypes size categories (shop) education number of employees store price level store hours (complete CH) parking prices Evt. Tabelle erstellen, mit Auflösung und Umfang des Datensatzes.

I. Lack of Data: “Missing” 11 11 Should a manual data collection effort be undertaken? local sim quality collection costs Evt. Tabelle erstellen, mit Auflösung und Umfang des Datensatzes. transferability / flexibility detail level of data

II. Computational Issues: Choice Sets … Variability 12 12 huge destination choice sets, in particular routing very expensive (for assessing an alternative) microsimulation stochasticity: no data → sophisticated rolling of a dice + correlations → model is not restrained → large variability → many runs required Temporal, spatial resolution -> averaging, smoothing

Closing Gaps: Destination Choice Research Avenues Research Avenues 13 13 further heterogeneity of agents and alternatives, in particular, prices, income, vot (household budget survey) finer activity classification available in microcensus and business census spatial correlations agglomeration terms + correlated error terms choice dimensions interrelation e.g., mode – destination etc.

Closing Gaps: Destination Choice Research Avenues 14 14 interaction effects at destinations (e.g., at parking lots) similar to space-time competition on roads reduces number of implausibly overloaded facilities Load category 1: 0 – 33 % 2: 33 - 66 % 3: 66 - 100 % 4: > 100% 10 % ZH Scenario: 60K agents destination choice equilibration e.g., approximate calculation of travel times errtot = wb errb + we erre + wtt errtt if (wtt = small) -> tt can be approximated equilibrium concept is approximate itself