Activity-Based Demand Modeling for a Future Urban District

Delhoum, Younes; Belaroussi, Rachid; Dupin, Francis; Zargayouna, Mahdi

doi:10.3390/su12145821

Cited by 16 publications

(20 citation statements)

References 18 publications

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“…An activity-based model requires generating a set of activity-plans, which refer to the daily chain of activity planned by each resident of the study-area [16]. Once the activityplans are generated, the time-choice process is applied to adjust the time settings of the different activities of the plan.…”

Section: Proposed Methodology To Set Time-choices From Travel Surveymentioning

confidence: 99%

“…In our case study, we do not use a utility function to estimate the activity time or duration. Activity-choice and their locations were previously addressed in [16], and we use MATSim (Multi-Agent Transport Simulation [17]) framework for demand-modeling and agent-based mobility-simulation: it is open-source and widely used to implement large-scale activity-based modeling.…”

Section: Related Workmentioning

confidence: 99%

“…This work is the continuation of the work started in [16], where we modeled travel behaviors of the population of the catchment area of a rather large future district (real estate development LaVallée, due in 2024). This area of study is shown in Figure 25 along with home locations.…”

Section: Urban Experimentsmentioning

confidence: 99%

“…The algorithm is a sequential approach that starts with generating the sequence of activities, then location-choice and mode-choice (detailed in [16]), and finally, the proposed time-choice process. At this level, the time-choice process cannot modify the activity-chain.…”

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confidence: 99%

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Modeling Activity-Time to Build Realistic Plannings in Population Synthesis in a Suburban Area

et al. 2021

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In their daily activity planning, travelers always considers time and space constraints such as working or education hours and distances to facilities that can restrict the location and time-of-day choices of other activities. In the field of population synthesis, current demand models lack dynamic consistency and often fail to capture the angle of activity choices at different times of the day. This article presents a method for synthetic population generation with a focus on activity-time choice. Activity-time choice consists mainly in the activity’s starting time and its duration, and we consider daily planning with some mandatory home-based activity: the chain of other subsequent activities a traveler can participate in depends on their possible end-time and duration as well as the travel distance from one another and opening hours of commodities. We are interested in a suburban area with sparse data available on population, where a discrete choice model based on utilities cannot be implemented due to the lack of microeconomic data. Our method applies activity-hours distributions extracted from the public census, with a limited corpus, to draw the time of a potential next activity based on the end-time of the previous one, predicted travel times, and the successor activities the agent wants to participate in during the day. We show that our method is able to construct plannings for 126k agents over five municipalities, with chains of activity made of work, education, shopping, leisure, restaurant and kindergarten, which fit adequately real-world time distributions.

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Section: Proposed Methodology To Set Time-choices From Travel Surveymentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Urban Experimentsmentioning

confidence: 99%

mentioning

confidence: 99%

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Modeling Activity-Time to Build Realistic Plannings in Population Synthesis in a Suburban Area

et al. 2021

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“…The current situation data, plus the population data based on a survey of the real-estate developer (see Figure 3). The detailed process of population synthesis, together with all the used data can be found in [21].…”

Section: Input Datamentioning

confidence: 99%

Multi-Agent Activity-Based Simulation of a Future Neighborhood

Delhoum

Belaroussi

Dupin

et al. 2021

Agents and Multi-Agent Systems: Technologies and Applications 2021

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Mobility simulations are an effective tool to forecast the effects of transportation policies. They are a useful part of decision support systems for policy makers. Big real-estate projects, aiming at creating whole new neighborhoods for instance, need this kind of applications to estimate their impacts on the surrounding environment. The potential visits of the various equipments and the public spaces of the new neighborhood can also be estimated with this kind of tools. In this context, agent-based simulation is a relevant model for the design and implementation of transportation applications, that represents travelers individually, together with their perception model of the environment and their internal decision processes. In this paper, we propose a multi-agent activity-based simulation to represent current and future mobility patterns in a city, with or without a new neighborhood. We describe the inputs of the simulation, in terms of networks and travel demand, the behaviors of the agents and the outputs on the laVallée project (France). The first series of experiments demonstrate the potential of the simulation and its benefits for the project managers and the decision-makers in the concerned territories.

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