Patrícia Lavieri

University of Melbourne | MSD · Department of Infrastructure Engineering

Current applications of Graph Neural Networks in citywide short-term crash risk prediction have been limited by a gridded representation of space, which restricts the network's capability to effectively capture the spatial and temporal dependency of crash occurrences. In addition, a grided representation does not match most geographic units used fo...

The subject of this research is to model the probability of accepting package delivery tasks in Crowd-Shipping (CS) systems focusing on shipping packages by Public Transportation (PT) passengers. Real-world implementation of such a PT-based CS initiative requires a proper grasp of the behavior of crowd shippers, package receivers, and senders, amon...

Electric vehicles (EVs) can help decarbonise transport as long as the energy sector successfully balances the electricity supply with the demand and maximises the use of renewable resources. For that, demand-side management strategies are necessary to encourage users to charge at certain times through time-of-use (ToU) tariffs or to control the loa...

The objectives of the study are to (A) explore the use of metabolic equivalent of task (MET) as an accessibility measure for active travel (compared to travel time separation measures), (B) investigate the potential impacts of e-bikes on the older adult population level of access to opportunities, and (C) analyze the potential for substitution of m...

The efficacy of electric vehicles (EVs) in reducing emissions is contingent on the source of energy used for charging. Australia is a leading country in residential rooftop photovoltaic (PV) installations per capita, which already results in a mid-day electricity surplus. While using solar energy resources for EV charging seems to be an imminent op...

Bikesharing systems have gained popularity over the years and now face the challenge of being responsive and of meeting the growing demand. Thus, understanding the temporal pattern of bikesharing trips is paramount. This study examined data from Bikesampa (a fixed-station system operating in the Brazilian city of São Paulo) and applied k-means clus...

The mass deployment of electric vehicles (EVs) may bring significant challenges to the electricity sector. However, many of these challenges can be converted into opportunities depending on how and when consumers decide to charge their vehicles. While there are currently multiple efforts worldwide investigating EV charging behaviour, these efforts...

The mass deployment of electric vehicles (EVs) may bring significant challenges to the electricity sector. However, many of these challenges can be converted into opportunities depending on how and when consumers decide to charge their vehicles. While there are currently multiple efforts worldwide investigating EV charging behaviour, these efforts...

Surging electric vehicle (EV) adoption concerns the energy sector due to challenges in balancing the supply with electricity demand. In this context, electricity demand management strategies can be used to reduce potential grid strains posed by EV charging. This study investigates consumer preferences for smart charging technology and control (user...

We investigate the variation in location and time allocated to work during the COVID-19 pandemic. Data from the American Time Use Survey (2019-2020) was modeled using a latent-class multiple discrete-continuous model. Two main segments of individuals who suffered different impacts from the pandemic on their work arrangements were identified. Men, y...

To better understand the role of generational technology savviness in telework uptake, the current study compares digital immigrants' and digital natives’ engagement in at-home work activities. Generational differences are analysed using longitudinal data extracted from the HILDA survey (DSS 2019). HILDA is a household-based panel survey that recor...

The study simultaneously and jointly analyzes the influence of socioeconomic and attitudinal characteristics on travelling using ridehailing and transit services. Ordered probit bivariate hybrid models were estimated to consider unobserved factors that directly affect people's tendency to travel and are valid for all the transport modes. The use of...

As electric vehicle (EV) uptake increases worldwide, a major concern is how consumer charging behavior will impact electrical networks. This project addresses this concern through the investigation of consumer behaviour, network modelling, and techno-economic modelling. As part of the behavioural investigation, this report complements the literatur...

As EV uptake increases worldwide, a main area of research focuses on understanding the characteristics of current EV owners and consumers most interested in transitioning to EV technology. The findings and evidence provided by such studies generate insights on the behaviour, socio-demographic characteristics, and location of these consumers, allowi...

The virtual (online) and physical (in-person) worlds are increasingly inter-connected. Although there is considerable research into the effects of information and communication technologies (ICT) on activity-travel choices, there is little understanding of the inter-relationships between online and in-person activity participation and the extent to...

This study presents a survey and a series of analyses performed to better understand the use of private and shared bicycles in a city where bicycle infrastructure and bicycle-sharing systems are recent and still limited. Using descriptive analysis, a multivariate ordinal model and a binary choice model, we (1) explore the profile of bicyclists befo...

Even as ride-hailing has become ubiquitous in most urban areas, its impacts on individual travel are still unclear. This includes limited knowledge of demand characteristics (especially for pooled rides), travel modes being substituted, types of activities being accessed, as well as possible trip induction effects. The current study contributes to...

The rise of ride-hailing services has presented a number of challenges and opportunities in the urban mobility sphere. On the one hand, they allow travelers to summon and pay for a ride through their smartphones while tracking the vehicle’s location. This helps provide mobility for many who are traditionally transportation disadvantaged and not wel...

With the era of fully automated vehicles (AVs) quickly approaching, ridesharing services could have an important role in increasing vehicle occupancy, reducing vehicle miles traveled, and improving traffic conditions. However, the extent to which these potentials can be achieved depends on consumers’ disposition to sharing rides. From a travel beha...

This chapter provides a discussion of the important research topics for understanding behavioral responses to highly automated vehicles (AVs) as discussed at a breakout session at the Automated Vehicle Symposium (AVS) 2018. The session, and thus this chapter, highlights the need for valid behavioral data on which to base assumptions, models, foreca...

Though RGB Cameras, Radar and LIDARs are popular sensors for intelligent vehicle systems, real-time joint inference on their sensory outputs remains challenging. Moreover, high-resolution LIDAR is expensive both in terms of cost and computation. This paper presents a deep learning-based pedestrian detection algorithm that takes both RGB image and l...

In this study, we propose a conceptual and analytic framework anchored on the concepts of physical and virtual accessibility (the “ease” with which opportunities or activities can be reached in the physical and in the virtual space, respectively) to investigate the rich interplay between virtual and physical activity engagements in multiple activit...

Ridesourcing has experienced exponential growth in recent years, yet its impact on individual travel are unclear and have not been adequately examined. Recently, an Austin-based ridesourcing company released a large dataset containing disaggregate trip-level information. In this research, we use this new dataset in tandem with several publicly avai...

In this paper, we propose a general copula approach to accommodate non-normal continuous mixing distributions in multinomial probit (MNP) models. In particular, we specify a multivariate mixing distribution that allows different marginal continuous parametric distributions for different coefficients. A new hybrid estimation technique is proposed to...

We propose in this paper a spatial random coefficients flexible multivariate count model to examine, at the spatial level of a census tract, the number of pedestrian injuries by injury severity level. Our model, unlike many other macro-level pedestrian injury studies in the literature, explicitly acknowledges that risk factors for different types o...

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing...

There is considerable interest in modeling and forecasting the impacts of autonomous vehicles on travel behavior and transportation network performance. In an autonomous vehicle future, individuals may privately own such vehicles, or use mobility-on-demand services provided by transportation network companies that operate shared autonomous vehicle...

Smartphone ownership and use are becoming increasingly prevalent around the world. However, little is known about the impacts of this technology on activity travel choices. The objective of this study was to determine the extent to which smartphone ownership and use influence activity travel demand, after controlling for other lifestyle and demogra...

This paper explores differences in activity-travel behavior within the millennial generation with a view to better understand how their choices might shape transportation systems of the future. Through the estimation of a Generalized Heterogeneous Data Model on a special millennial mobility attitudes survey data set, this study investigates heterog...

The objective of this paper is to evaluate the effectiveness of a dedicated short-range communication (DSRC)-based wireless vehicle-to-vehicle (V2V) communication system, called the overtaking assistant, devised for improving safety during overtaking (also referred to as passing) maneuvers on two-lane rural highways. Specifically, the paper examine...

This paper presents a comprehensive model of injury severity that accounts for unmeasured driver behavior attributes. The results of the model have important implications for the design of safety interventions and advanced vehicular features and technologies. Engineering designs that accommodate the diminished capabilities of older drivers, that in...

O artigo analisa a qualidade das informações sobre previsões de chegada de veículos a pontos de ônibus (disponibilizadas nas paradas através de painéis de mensagem variável), bem como os determinantes do uso destas informações por parte dos passageiros. Os dados foram coletados em duas paradas no corredor Campo Limpo/Rebouças/Centro em São Paulo. F...

O teletrabalho é uma prática que pode ser utilizada como medida de gerenciamento da demanda por transporte urbano, uma vez que tem o potencial de reduzir a necessidade de realização de viagens através da substituição de atividades presenciais, que exigem deslocamentos, pelas virtuais, realizadas com auxílio de tecnologias da informação e comunicaçã...

Telework has been adopted and studied in some countries for over 30 years; in Brazil, the phenomenon is in its early stages but rapidly advancing. This paper investigates how companies are shaping their telework policies: what the goals, benefits and limitations being experienced are. The results show that while the major barriers to telework adopt...