World Conference on Transport Research Society

WCTRS Y-II PhD student grants

Grants to support PhD students to conduct and present research at the WCTR-16 Montreal

The WCTRS-Y Initiative is delighted to announce the results of the WCTRS-Y II. The calibre of submissions was incredibly high, and the successful PhD scholars, and details of their projects, are listed below. They will each present a paper based on their research as part of a Special Session at the WCTR-16 Montreal in July 2023.

Karyn Scerri portrait photo  Innovation Grant– Karyn Scerri (University of Malta: Contact Email)

Project Title: Understanding the Impact of Pedestrian Intervention on Laziness and Car Dependency Reduction in a European Island.

Sedentary behaviour, including sitting in motorised vehicles, has been linked with negative physical and psychological health repercussions, even in sufficiently physically active individuals. It is therefore pivotal to identify factors and potential determinants associated with this sedentary behaviour, including the role of the urban environment. Within the plethora of studies analysing habits and experiences as psychological determinants, few have delved into the concept of laziness and car use. This research will explore the phenomenon of laziness by measuring people’s perceived physical exertion to walk instead of drive for short-distance trips and apply the ‘Lazy User Theory’ to examine the constructs of people’s lazy user behaviour in modal choice. Using a living lab approach and questionnaire surveys, pedestrian-focused intervention will be used as a tool to analyse laziness as a behavioural determinant for short-distance trips to better understand and assess the potential impact of pedestrian interventions to encourage active travel.

Vaibhav Puri portrait photo   Prestige Grant– Vaibhav Puri (University of Dehli: Contact Email)

Project Title: Effects of Mass Rapid Transit Systems (MRTS) on Changing Urban Landscape: A Remote Sensing-Based Study of Delhi Metro

With more than two-thirds of the world population projected to reside in the urban areas by 2050, Delhi is set to become the most populous city in the world by 2028 as per the United Nations. Urbanisation presses the need for a more effective and sustainable form of transportation network. In light of the ongoing of Metro Rail expansion across the megacity-Delhi, the objective of the current study is to analyse the interplay between urban land-use change and the growth of transit system over time using spatial techniques. Satellite data pertaining to night-light activity and land cover change will be used for analysis. The spatio-temporal variability in urban growth studied through lens of Mass Rapid Transit Systems (MRTS) will prove instrumental in evaluating the potential of resilient transport infrastructures in shaping the future of global cities.

  Prestige Grant-Mohamed Khachman (Polytechnique Montréal: Contact Email)

Project Title: Application of Machine Learning to Spatialized Population Synthesis

Simulations of mobility behaviours require rich datasets describing the population. These datasets, generally unavailable due to privacy issues, are generated through population synthesis. Population synthesis is a process that uses census summary tables and disaggregate samples to create a fully enumerated population with economic and sociodemographic characteristics assigned. To guarantee the simulation’s accuracy, synthetic populations used should be spatialized, ideally, at the housing unit scale. In Quebec, the data recorded as part of the cyclically conducted Origin-Destination (O-D) surveys can be used as disaggregate inputs for population synthesis. The O-D sample’s households are precisely located and assigned to clusters where each cluster reflects a different mobility behaviour. Hence, it is suggested to make use of spatially disaggregated O-D samples to estimate the type of household in each housing unit through various machine learning models, and consequently distribute the synthetic households by correspondence of household type and geographic zone.

Elodie Deschaintres portrait photo   Prestige Grant– Elodie Deschaintres (Polytechnique Montréal: Contact Email)

Project Title: Assessing complementarity between modes of transport in an urban and multimodal context

Despite increasingly diversified urban transport services, little research has been conducted to understand how the modes interact: questions about their complementarity (or competitiveness) are still raised. Therefore, this project aims at giving some insights into relations between transit and other modes (namely bikesharing, carsharing and taxi) using various passive datasets. First, an algorithm will be developed to identify different types of interactions (first-mile/last-mile intermodal connections, complementarity situations in space, time, service quality/efficiency, or substitutions). An indicator will then be defined to assess an aggregated level of complementarity per spatial-temporal unit (per zone per day for instance) based on the probability of each type of interactions. Finally, the correlation of this complementarity with various factors will be analysed, and the causal impact of this complementarity on the level of use of the modes will be modelled. The results will help clarify the role of each mode in urban multimodal mobility.

Debarshee Bhardwaj portrait photo   Prestige Grant– Debarshee Bhardwaj (Universität Bremen: Contact Email: Institutional Profile)

Project Title: How managers evaluate country logistics performance for global supply chain decision making

Global supply chain design decision (GSCDD) processes such as country selection for locating facilities are extremely complex. Decision-makers must scan large amount of logistics-related country-specific attribute information, such as infrastructure and logistics service quality and demonstrate varying levels of rationality. The standpoint on how managers cognitively use this information for the decision-making is largely missing both in academia and practicality.  As a result, our research, which is based on a case study, offers the first experiences of managers making a country selection decision through exploratory experiments. Our research specifically demonstrates the various issues managers face while going through this process, and what role attribute information plays within the process which can be very useful for a better managerial understanding of the decision process. All in all, we demonstrate how much information or rationality is enough for the managers for different organisational cases in terms of the structure of decision process.