Bias d'agrégation spatiale dans les modèles d'affectation des déplacements

Cities are complex systems that urban models can help to comprehend. From simplistic models to more sophisticated ones, urban models have pushed forward our understanding the urban phenomenon and its intricacies. In this context, models can be of great value to policy makers providing that these tools become practical. In this regard, research has put little emphasis on the practicality of urban models and their use under operational conditions.To date, urban models which rely on spatial aggregation are the closest possibility to come to practical models. For this reason, the spatially aggregated modeling framework is widely used. This framework is relatively practical when compared to other modeling frameworks like microsimulation. Nevertheless, spatial aggregation is a serious source of bias in these models. This is especially the case of Land-Use and Transport Interaction (LUTI) models and more particularly of Four Step Models.The current PhD is committed to the study of spatial aggregation issues in traffic assignment models. Traffic assignment is responsable for the computation of travel times and travel conditions of present and future travel demand. Accessibility measurement, which is at the core of LUTI models, is tightly dependent on traffic assignment modeling and outcomes. Any bias in traffic assignment is likely to corrupt the overall modeling framework. In this context, a special attention is to be paid to spatial aggregation in traffic assignment models.In traffic assignment, spatial aggregation consists in grouping observations using zones or traffic analysis zones instead of using a continuous representation of space. By design, aggregation bears an implicit omission in data variability and thus a potential bias if this omission is not random. This is the case with the definition of centroid connectors and the omission of intrazonal demand in traffic assignment. With the use of zones as the basic spatial units, transport models require the use of centroid connectors to attach zones to the transportation network. Centroid connectors are introduced to model average access and egress conditions to and from the network. Nevertheless, average accessibility conditions are found to be too crude to render accurately accessibility conditions as encountered by trip makers. The current PhD explores the extent of the impact of this spatial aggregation bias in the case of transit models and suggests a new modeling strategy to overcome such modeling errors.The use of zones as spatial units induces a loss of intrazonal data. The omission of intrazonal trips in traffic assignment models is an example of such omission. This research introduces an uncertainty framework to study the statistical impact of ignoring intrazonal trips in traffic assignment models. Findings from this research are used to design new assignment strategies that are more robust towards the omission bias and more generally towards the spatial aggregation bias.Les villes sont des systèmes complexes que les modèles urbains peuvent aider à comprendre. Des modèles les plus simplistes aux modèles les plus sophistiqués, la modélisation urbaine a permis de mieux comprendre la question urbaine et ses implications sociétales. Dans ce contexte, les modèles peuvent avoir une valeur-ajoutée appréciable dans le processus de décision publique. Encore faut-il que ces modèles deviennent pratiques et répondent aux contraintes opérationnelles de la chaîne de décision. Dans ce sens, peu de recherches s’est intéressée à la question de praticité des modèles urbains et leur utilisation en situation opérationnelle. À ce jour, les modèles urbains standard qui reposent sur une description agrégée de l’espace sont parmi les approches de modélisation les plus opérationnelles et aussi les plus répandues. De par sa relative praticité, cette approche standard est attractive et simple à mettre en oeuvre. Toutefois, l’agrégation spatiale peut aussi être une source de biais statistiques préjudiciables à la qualité de la modélisation. C’est en particulier, le cas des modèles intégrés Transport-Urbanisme ou des modèles de transport à quatre étapes.La présente thèse a pour objectif d’étudier la question de l’agrégation spatiale dans les modèles transport et plus particulièrement dans les modèles d’affectation des déplacements. Les modèles d’affectation servent à calculer les temps de parcours et les conditions de déplacement sous congestion, présents et futurs, des personnes et des marchandises. Ils servent aussi à calculer les accessibilités nécessaires aux modèles d’usage des sols dont les modèles de choix de localisation des ménages et des entreprises. Toute erreur ou biais dans l’affectation des déplacements peut compromettre la validité et la qualité globales de la modélisation. Dans ce cadre, une attention particulière doit être allouée au problème d’agrégation spatiale dans les modèles d’affectation. Dans ces modèles, l’agrégation spatiale consiste à regrouper les observations individuelles enutilisant une description agrégée de l’espace, i.e. des zones. Par nature, l’utilisation d’une description agrégée à la place d’une représentation continue engendre une omission de l’information et de sa variabilité et donc un biais statistique dans la modélisation. C’est le cas par exemple avec l’utilisation des connecteurs de zones ou avec l’omission des trafics intrazones dans les modèles d’affectation.En reposant sur les zones comme unité spatiale de base, les modèles de transport recourent à l’utilisation des connecteurs de zones pour relier les centroïdes de zones au réseau de transport. Les connecteurs sont des liens fictifs qui modélisent les conditions moyennes d’entrée et de sortie du réseau de transport. Pour ce faire, la majorité des modèles de transport reposent sur une méthode simpliste sujette au problème d’agrégation spatiale. La présente thèse examine en détail l’impact de cette description simpliste sur les résultats et la qualité d’un modèle d’affectation des déplacements en transports en commun. Cette thèse propose aussi une nouvelle méthode de modélisation des connecteurs de zones afin de s’affranchir partiellement du biaisd’agrégation spatiale dans la modélisation des conditions d’accès au réseau des transports en commun.L’utilisation des zones comme unité spatiale de base a aussi pour conséquence l’omission des trafics intrazones de l’affectation des déplacements. Les trafics intrazones ont pour origine et pour destination la même zone et de ce fait ne sont pas pris en compte par les modèles standard d’affectation. Cette omission a souvent été ignorée et son impact sur la qualité de la modélisation demeure non évalué. Cette thèse développe une méthode stochastique pour l’évaluation de cet impact..

Codification des connecteurs de zones pour les transports en commun

La plupart des méthodologies de codification des connecteurs reposent sur la position géographique des centroïdes de zones. Cette pratique est, certes, simple à implémenter, mais elle semble être inadaptée aux connecteurs des transports en commun, d’autant plus que son impact sur les résultats de modélisation n’est pas négligeable. Le présent mémoire a pour objectif l’élaboration d’une nouvelle méthodologie de codification plus adaptée aux transports collectifs. Cette nouvelle codification doit s’affranchir du biais d’agrégation imposé par le zonage et rendre compte, à un niveau désagrégé, des pratiques de marche à pied vers et depuis les arrêts

Assessing the Role of Daily Activities and Mobility in the Spread of COVID-19 in Montreal With an Agent-Based Approach

International audienceDaily activities and mobility dynamics play a central role in the spread of COVID-19. Close physical interactions involved by certain daily activities help transmit the virus. Travel required by the spatial distribution of activities contributes to the propagation of the virus. In order to control and limit this propagation, it is critical to understand the contribution of daily activities to the dynamics of COVID-19. This paper investigates the connection between daily activities, their distribution in space and time, the characteristics of the individuals performing them, and the transmission of the virus. A business-as-usual agent-based simulation scenario of Montreal, Canada is used. To address this research question, we use two agent-based models: MATSIM and EPISIM. MATSIM simulates daily activities and mobility dynamics of the population. EPISIM simulates the spread of the virus in the population using contact networks computed by MATSIM. A synthetic population of Montreal is defined to replicate the main observed sociodemographic characteristics of Montrealers as well as their activity and mobility patterns. The definition of the synthetic population relies on various data sources: household travel survey, census, real estate, car ownership, and housing data. In the business-as-usual scenario, findings underline the significant role of home, work, and school activities in community transmission of COVID-19. Secondary activities, including leisure and shopping, also help spread the virus, but to a lesser degree in comparison with primary activities. The risk of infection in the workplace depends on the economic sector. Healthcare workers are, by far, the most exposed workers to the virus. Workplace infections mirror the gender-biased job market of Montreal. Most infections in the healthcare and educational services are among women. Most infections in the manufacturing, construction, transportation, and warehousing industries are among men. In the business-as-usual scenario where community transmission is high, primary and secondary school-aged children are found to be a major transmission vector of the virus. Finally, simulation results suggest that the risk of infection in the public transportation system is low

On how COVID-19 mitigation measures can reshuffle the risk of infection: a case study from Montreal, Canada

International audienceTo control the spread of COVID-19, various non-pharmaceutical interventions (NPIs) were introduced. Restrictions on mobility and activities were among the widely adopted NPIs. The introduction of these NPIs was often based on their global positive effect, with little regard to their micro-level implications. In this paper, we investigate the macro and micro implications of three NPIs: work from home, school opening and university closure, and leisure and shopping restrictions. Two hypothetical scenarios from Montreal are compared: with and without NPIs. An agent-based simulation is used to investigate the impacts of these scenarios. Results show that the three NPIs can significantly reduce the incidence rate of COVID-19 in the population. However, the benefit of this reduction is unequally distributed in the population. Some citizens benefit more from these interventions than others depending on their socio-demographic and economic characteristics or residential location. Findings suggest that these NPIs can exacerbate existing disparities in terms of exposure to COVID-19 and give less benefit to those who are most exposed to the virus. These findings can be informative to decision-makers in the design of efficient and fair COVID-19 mitigation strategies

Assessing the Role of Daily Activities and Mobility in the Spread of COVID-19 in Montreal With an Agent-Based Approach

Daily activities and mobility dynamics play a central role in the spread of COVID-19. Close physical interactions involved by certain daily activities help transmit the virus. Travel required by the spatial distribution of activities contributes to the propagation of the virus. In order to control and limit this propagation, it is critical to understand the contribution of daily activities to the dynamics of COVID-19. This paper investigates the connection between daily activities, their distribution in space and time, the characteristics of the individuals performing them, and the transmission of the virus. A business-as-usual agent-based simulation scenario of Montreal, Canada is used. To address this research question, we use two agent-based models: MATSIM and EPISIM. MATSIM simulates daily activities and mobility dynamics of the population. EPISIM simulates the spread of the virus in the population using contact networks computed by MATSIM. A synthetic population of Montreal is defined to replicate the main observed sociodemographic characteristics of Montrealers as well as their activity and mobility patterns. The definition of the synthetic population relies on various data sources: household travel survey, census, real estate, car ownership, and housing data. In the business-as-usual scenario, findings underline the significant role of home, work, and school activities in community transmission of COVID-19. Secondary activities, including leisure and shopping, also help spread the virus, but to a lesser degree in comparison with primary activities. The risk of infection in the workplace depends on the economic sector. Healthcare workers are, by far, the most exposed workers to the virus. Workplace infections mirror the gender-biased job market of Montreal. Most infections in the healthcare and educational services are among women. Most infections in the manufacturing, construction, transportation, and warehousing industries are among men. In the business-as-usual scenario where community transmission is high, primary and secondary school-aged children are found to be a major transmission vector of the virus. Finally, simulation results suggest that the risk of infection in the public transportation system is low.</jats:p

The impact of ignoring intrazonal trips in assignment models: a stochastic approach

International audienceIn transportation modeling, intrazonal trips are frequently omitted during trip assignment. These trips are not assigned to the network because their origin and destination are in the same zone. However, in reality, intrazonal trips use the network and take up some of its capacity. This omission is due to the spatial aggregation problem. Omitting these short trips from assignment models affects the level of service of the network and biases the estimation of main assignment outcomes. The issue of intrazonal trips omission has received limited attention in transportation research. In this paper, we address the problem of ignoring intrazonal trips in traffic assignment models by applying a stochastic approach in order to characterize the statistical impact of their omission. Our results show that the omission of intrazonal trips has a significant impact on main assignment results. Network speeds, volumes and congestion levels vary significantly with the omission of intrazonal trips. The extent of this impact depends on the road’s category in the network hierarchy. As regards level of service, local streets are more sensitive to the omission of intrazonal trips than the primary network. These findings reveal the existence of a bias due to the omission of intrazonal trips in assignment models and raise doubts about the accuracy and reliability of assignment results from standard four step transport models especially when the spatial zoning is coarse

Better be private, shared, or pooled? Implications of three autonomous mobility scenarios in Lyon, France

International audienceAutonomous vehicles will be one of the most disruptive technologies of the automative industry. Their wider implications on society are expected to be considerable, even if these implications are still under debate. Meanwhile, various stakeholders, including cities and tech companies, are launching different AV pilot projects to test and help boost the technology readiness level. This research assesses some of the impacts of three AV mobility scenarios: private, shared, and pooled AVs in Lyon, France. An agent-based simulation framework is used (MATSim). Results suggest that AV services can reshuffle existing transportation dynamics by attracting a significant share of travel demand, especially from public transport and walking. If not regulated, these services can produce substantial excess travel distances and increase energy consumption and emissions of the transportation system. In this regard, pooled robotaxis are the least impactful introduction scenario of AVs compared to non-pooled robotaxis or private AVs