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List of datasets to model mobility of cities (Paris region in particular)

Authors:
  • Institut Polytechnique de Paris

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MuTAS - Coordinated by Andrea ARALDO
CES 22 - Sociétés urbaines, territoires, constructions et mobilité JCJC; 48 months;
AAPG ANR 2021
List of datasets to model mobility of cities (Paris
region in particular)
Name Organization /Authors Source Description
European population per
Km2
The European Commission link
Population at each cell of 1 Km2 of all the Euro-
pean surface
World population per
Km2
Columbia Univ. and NASA [2]
Population at each cell of 1Km2 of the entire
world, with age and sex specification
Urban Population United Nations link
Population of urban conurbations around the
world
Urban typology frame-
work
M. Ben-Akiva [4]
69 indicators of mobility, economic, demographic,
land-use and behavioral data of 331 cities.
GTFS data Transportation operators
Operator web-
sites
Transit schedules.
GTFS data collection
MobilityData (non-profit
org.)
transitfeeds.com
Collection of GTFS data from cities around the
world.
Table 1. Tentative list of open data sources for the targeted cities
Name Organization
Source
Description Usage
GTFS data Île de France Mobilité link Transit schedules for Île de France SU
Road network of Île de France
Open Street Map (OSM)
Foundation
link Open street map of the entire Île de France SU
Households Préfet Île de France link
Population of different ages, size of households,
household revenue, all per 200m-squares
PO
Employment in ÎdF Institut Paris Region link
Employment status and type of employment at
the municipality level.
PO
Education locations Ministry of the Education link
Geolocalization of all education institution in
France
PO
Base Sirene INSEE link
Geolocalized list of businesses and firms in ÎdF,
type of activity, number of employees
PO
Enqête Globale Transport
(EGT)
Île de France Mobilité link
Number and types of daily trips, divided by orign
and destination macro-zones, length and duration
of trips, time of departure, modal shares for each
activity purpose, origin-destination macro-zone,
employment type
CA
National Travel survey
Commissariat Général au
Développement Durable
[1]Simular to (EGT) CA
Traffic Counts in Paris City of Paris link
Traffic counts of 3000 points from sensors de-
ployed in Paris every 1h.
CA
Traffic counts in Île de France
Direction des routes d’Île de
France
link
Traffic counts from loop-based counters every 1h
CA
Ticketing information Île de France mobilité link
Historical number of tickets validated in each line
at different times
CA
High-detail data ETH Zurich [3]
Data and procedures to build agent-based simu-
lation of Île de France
SU,
CA,PO
Table 2. Tentative list of open data sources for Île de France and our usage: SU (to build and calibrate the supply
network), PO (to build the synthetic population), CA (to calibrate the demand and supply models)
References
[1] Enquête nationale transports et déplacements: Île de France. Tech. rep. Commissariat Développement Durable, 2010.
[2] Gridded Population of the World, v4, rev 11. Columbia University. 2018.
[3] Hörl, S. “Reproducible scenarios for agent-based transport simulation A case study for Paris and Île-de-France”. 2020.
[4]
J. B. Oke, M. Ben-Akiva, et al. “Evaluating the systemic effects of automated mobility-on-demand services via large-scale
agent-based simulation of auto-dependent prototype cities”. In: Transp. Res. Part A (2020).
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Article
The growing demand for urban mobility highlights the need for relevant and sustainable solutions in cities worldwide. Thus, we develop and implement a framework to analyze the systemic impacts of future urban mobility trends and policies. We build on prior work in classifying the world’s cities into 12 urban typologies that represent distinct land-use and behavioral characteristics by introducing a generalized approach for creating a detailed, simulatable prototype city that is representative of a given typology. We then generate and simulate two auto-dependent (largely US-specific) prototype cities via a state-of-the-art agent-based platform, SimMobility, for integrated demand microsimulation and supply mesoscopic simulation. We demonstrate the framework by analyzing the impacts of automated mobility on-demand (AMoD) implementation strategies in the cities based on demand, congestion, energy consumption and emissions outcomes. Our results show that the introduction of AMoD cannibalizes mass transit while increasing vehicle kilometers traveled (VKT) and congestion. In sprawling auto-dependent cities with low transit penetration, the congestion and energy consumption effects under best-case assumptions are similar regardless of whether AMoD competes with or complements mass transit. In dense auto-dependent cities with moderate transit modeshare, the integration of AMoD with transit yields better outcomes in terms of VKT and congestion. Such cities cannot afford to disinvest in mass transit, as this would result in unsustainable outcomes. Overall, this framework can provide insights into how AMoD can be sustainably harnessed not only in low-density and high-density auto-dependent cities, but also in other typologies.
Reproducible scenarios for agent-based transport simulation A case study for Paris and Île-de-France
  • S Hörl
Hörl, S. "Reproducible scenarios for agent-based transport simulation A case study for Paris and Île-de-France". 2020.