Ifsttar PhD subject

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Title : Predicting urban vitality of a district with an activity-based model of transportation at two scales

Main host Laboratory - Referent Advisor   -

Director of the main host Laboratory   -

PhD Speciality Informatique

Axis of the performance contract 3 - COP2017 - Planning and protecting regions

Main location Marne-la-Vallée

Doctoral affiliation UNIVERSITE PARIS-EST

PhD school MATHEMATIQUES ET SCIENCES ET TECHNOLOGIES DE L'INFORMATION ET DE LA COMMUNICATION (MSTIC)

Planned PhD supervisor ZARGAYOUNA Mahdi  -  Université Gustave Eiffel  -  COSYS - GRETTIA

Planned financing Contrat doctoral  - UPE

Abstract

Identifying the spatio-temporal patterns of people activities in urban areas is key to effective urban planning; it can be used in real-estate projects to predict their future impacts on behavior in surrounding accessible areas. LaVallée is a large construction project recently started in Paris's suburb; it is a new district due in 2024.
The work presented aims at developing a method making it possible to model the potential visits of the various equipment and public spaces of the district, by mobilizing data from census at the regional level, and the layout of shops and activities as defined by the real-estate project. This model takes into account the flow of external visitors, estimated realistically based on the pre-project movements in the areas of influence of LaVallée. To perform this evaluation, we implemented a multiagent based simulation model (MATSim) at the regional scale and at the scale of the future district.

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. We present a method for synthetic population generation with a focus on activity-time choice, at a regional scale. 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.

In its design, the LaVallée district is physically open to the outside and will offer services that will be of interest to other residents or users of the surrounding area. To know the effect of this opening on a potential transit of visitors in the district, as well as the places of interest for the inhabitants, it is necessary to predict the flows of micro-trips within the district once it is built. We propose a gravitation model to estimate the daily activities and trips of the future residents. This transportation model is articulated in conjunction with the regional model in order to establish the flow of outgoing and incoming visitors. The impacts of LaVallée district on the mobility of its surrounding area is deduced by implementing a simulation in the projection situation.

Once the activity plannings for the whole population is generated, we apply the simulated flows for urban characterization. We first propose a study of the Visit Potential Model, an integrated model to evaluate public space characteristics that combines a universal law of visit frequencies in cities with a gravity measure of accessibility.
Population objects represent the places where people are going in and out for their primary activities: houses, offices and schools. Attractor objects include the destinations that people visit, for instance, leisure parks and shopping malls or restaurant. The visit potential of a public space can be defined as its proximity to people, its connection to other attractors or an aggregate pedestrian movement reflecting the people moving through or staying in it. In the case study of LaVallée district, the reported outcomes of this model is analyzed to provide us with a first insight of the visit potential of public spaces within LaVallée during a typical day. Originally, the model was defined for one single time-frame: by explicitly taking into account the time component, we derived a dynamic model. It enables us to extend the analysis of the future hotspots of LaVallée during the morning, midday and evening periods.

Visit Potential Model was estimated, based on the theoretically generated aggregate flows, without taking into account constraints, such as congestion, furthermore, unrealistic trip chains were observed. To overcome the limitations of previous models, in which vitality is estimated statistically and mainly based on the build-environment, the proposed indicator estimates vitality dynamically, based on human activity and results, of a simulated scenario. It requires a road network, counting results and vitality potential of the places of activity, the latter corresponds to the level of user satisfaction, it combines metrics of movement and presence of travelers in the area of interest. Vitality itself is estimated at three levels: user, activity location and lot. We then apply the model to LaVallée, with a detailed analysis of the results provided, following a set of measures, they will be reported mainly in the form of hotspots and heatmaps.

Keywords : Population synthesis,MATSim,activity-based model,micro-mobility,visit frequencies,urban vitality

Main host Laboratory - Referent Advisor	-
Director of the main host Laboratory	-
PhD Speciality	Informatique
Axis of the performance contract	3 - COP2017 - Planning and protecting regions
Main location	Marne-la-Vallée
Doctoral affiliation	UNIVERSITE PARIS-EST
PhD school	MATHEMATIQUES ET SCIENCES ET TECHNOLOGIES DE L'INFORMATION ET DE LA COMMUNICATION (MSTIC)
Planned PhD supervisor	ZARGAYOUNA Mahdi - Université Gustave Eiffel - COSYS - GRETTIA
Planned financing	Contrat doctoral - UPE
Abstract Identifying the spatio-temporal patterns of people activities in urban areas is key to effective urban planning; it can be used in real-estate projects to predict their future impacts on behavior in surrounding accessible areas. LaVallée is a large construction project recently started in Paris's suburb; it is a new district due in 2024. The work presented aims at developing a method making it possible to model the potential visits of the various equipment and public spaces of the district, by mobilizing data from census at the regional level, and the layout of shops and activities as defined by the real-estate project. This model takes into account the flow of external visitors, estimated realistically based on the pre-project movements in the areas of influence of LaVallée. To perform this evaluation, we implemented a multiagent based simulation model (MATSim) at the regional scale and at the scale of the future district. 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. We present a method for synthetic population generation with a focus on activity-time choice, at a regional scale. 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. In its design, the LaVallée district is physically open to the outside and will offer services that will be of interest to other residents or users of the surrounding area. To know the effect of this opening on a potential transit of visitors in the district, as well as the places of interest for the inhabitants, it is necessary to predict the flows of micro-trips within the district once it is built. We propose a gravitation model to estimate the daily activities and trips of the future residents. This transportation model is articulated in conjunction with the regional model in order to establish the flow of outgoing and incoming visitors. The impacts of LaVallée district on the mobility of its surrounding area is deduced by implementing a simulation in the projection situation. Once the activity plannings for the whole population is generated, we apply the simulated flows for urban characterization. We first propose a study of the Visit Potential Model, an integrated model to evaluate public space characteristics that combines a universal law of visit frequencies in cities with a gravity measure of accessibility. Population objects represent the places where people are going in and out for their primary activities: houses, offices and schools. Attractor objects include the destinations that people visit, for instance, leisure parks and shopping malls or restaurant. The visit potential of a public space can be defined as its proximity to people, its connection to other attractors or an aggregate pedestrian movement reflecting the people moving through or staying in it. In the case study of LaVallée district, the reported outcomes of this model is analyzed to provide us with a first insight of the visit potential of public spaces within LaVallée during a typical day. Originally, the model was defined for one single time-frame: by explicitly taking into account the time component, we derived a dynamic model. It enables us to extend the analysis of the future hotspots of LaVallée during the morning, midday and evening periods. Visit Potential Model was estimated, based on the theoretically generated aggregate flows, without taking into account constraints, such as congestion, furthermore, unrealistic trip chains were observed. To overcome the limitations of previous models, in which vitality is estimated statistically and mainly based on the build-environment, the proposed indicator estimates vitality dynamically, based on human activity and results, of a simulated scenario. It requires a road network, counting results and vitality potential of the places of activity, the latter corresponds to the level of user satisfaction, it combines metrics of movement and presence of travelers in the area of interest. Vitality itself is estimated at three levels: user, activity location and lot. We then apply the model to LaVallée, with a detailed analysis of the results provided, following a set of measures, they will be reported mainly in the form of hotspots and heatmaps.
Keywords :	Population synthesis,MATSim,activity-based model,micro-mobility,visit frequencies,urban vitality

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