This panel will explore the definition of "productive" people mobility as well as what are the emerging trends in personal mobility: Again, will technology present new opportunities and what challenges will arise in the future? And what new enabling policies, regulations and mindsets will we need to maximize the productive movement of passengers?
Panelists will include representatives from Housing, Infrastructure and Communities Canada,lthe City of Ottawa, Motor Coach Canada, and the Centre for Living Standards.
Director General, Housing Infrastructure and Communities Canada
Sean Keenan is the Director General, Economic Analysis and Results at Housing, Infrastructure and Communities Canada. Sean is responsible for overseeing the economic analysis, research, data and analytics and results reporting done by the department. Prior to joining Infrastructure... Read More →
City Councillor & Chair, Planning & Housing Committee, City of Ottawa
Jeff Leiper, first elected in 2014, is the City Councillor for Kitchissippi Ward. In this term of Council, he serves as Chair of the Planning and Housing Committee and is a member of Built Heritage Committee, Transit Committee, and Finance and Corporate Services Committee.Jeff studied... Read More →
President, Motor Coach Canada, Ontario Motor Coach Association
Vince's career has been spent working with like-minded professionals who are passionate about building a competitive and vibrant tourism and transportation sector in Canada. He is an accomplished tourism and transportation industry professional with comprehensive experience in association... Read More →
Executive Director, Centre for the Study of Living Standards
Andrew Sharpe is founder and Executive Director of the Ottawa-based Centre for the Study of Living Standards (CSLS). Established in 1995, CSLS is a national, independent, non-profit research organization whose main objective is to study trends and determinants of productivity, living... Read More →
Wednesday May 28, 2025 8:15am - 10:00am EDT Desmarais 116055 Laurier Ave E, Ottawa ON K1N 6N5
Understanding the route choice behavior of truck drivers in urban transportation delivery networks is essential for enhancing freight mobility and optimizing route planning strategies. This study introduces a data-driven method that integrates route choice set generation with discrete choice modeling (DCM) to identify the key factors influencing truck drivers' route selection. Based on the truck GPS trajectory data in the Amsterdam metropolitan area, route choice sets are generated using Monte Carlo Labeling (MCL) and Accelerated Monte Carlo (AMC) methods. By using the generated choice sets as inputs and considering the influencing factors of road grade, route distance, number of turns, and route size, a Path Size Logit (PSL) model is established to estimate the impacts of different factors. The findings contribute to a deeper understanding of truck route choice behavior and offer practical insights for the development of smart route recommendation systems for logistics operators.
As personal mobility devices (PMDs) gain popularity, their coexistence with other path-users in off-street shared spaces is becoming a concern. Past studies show that path-users perceive lower comfort towards motorized types of PMDs. However, the underlying factors affecting the perceived comfort of sharing the path with PMDs require further investigation.
The objective of this study is to identify the primary considerations of non-automobile travelers when sharing a path with PMDs. We analyzed 1232 open-ended comments from a survey conducted on non-automobile paths in Vancouver, Canada, in which travelers rated their comfort sharing the path with different types of PMDs. Structural topic modeling was used to identify topics spontaneously discussed by participants when explaining their comfort ratings and investigate the underlying factors affecting the topic prevalence.
Results show that the primary overall considerations affecting comfort when sharing paths are facility design (e.g., pathway width), PMD characteristics (e.g., motorization and speed), and rider behavior (e.g., rule compliance). The topic most distinctly associated with motorized devices is "Safety risks associated with PMD design and speed attributes". Efforts to integrate PMDs into urban transportation systems without degrading the non-motorized travel experience should focus on riders' cautious behavior, riding skills, and compliance.
Associate Professor, University of British Columbia
Alex Bigazzi is an Associate Professor in the Department of Civil Engineering at the University of British Columbia. His research focuses on non-motorized and lightly-motorized travel – in particular, the intersection of physics, physiology, and behaviour for active travellers... Read More →
On-street parking can have considerable impacts on traffic congestion and road safety within cities. In order to manage on-street parking, an in-depth understanding of on-street parking behaviour is required. This paper examines how land-use impacts two critical components of on-street parking: parking location occupancy and parking duration. This paper uses parking transaction data from paid on-street parking locations throughout Toronto to examine the influence of the following five land-uses: low-density residential, high-density residential, hospitals, offices, and universities. The results show that for on-street parking occupancies, locations adjacent to universities generally have the highest occupancies while locations adjacent to hospitals have the lowest occupancies. Contrary to the differences observed in parking location occupancy, parking duration is similar for all the land-uses during weekdays and Saturdays. Further examination of each land-use's impact is discussed within the paper. In addition, it is observed that on-street parking occupancies are significantly lower during weekdays versus weekends but parking duration is similar throughout the week. The results show the importance of location and time dependent parking pricing.
Advances in battery and charging technology have made heavy-duty battery-electric vehicles (HDBEVs) a viable pathway for decarbonizing heavy-duty vehicles (HDV). Predicting electrical charging profiles for HDBEV fleets is critical to supporting Canadian energy system reliability. This study leverages high-resolution telematics from the American Transportation Research Institute for Ontario HDVs in 2019 to produce annual HDBEV fleet charging profiles under various technology and operator charging scenarios. _x000D_ _x000D_ The project has two phases: data processing and charging demand modelling. First, converting real-world HDV travel data into schedules, identifying driving and charging periods and summarizing travel statistics. Second, estimating the charging demand for randomly sampled HDBEV fleets using government-reported HDBEV battery sizes, charging rates, and selected charging strategy. Strategies include immediate charging (start charging once stationary), delayed charging (fully charge just before next departure), or minimum-power (charge at lowest constant power)._x000D_ _x000D_ Preliminary findings using August 8-14 data generated 1960 HDV schedules and highlighted the impact of charging strategy. Immediate charging increases afternoon peak electrical demand by over 30% compared to delayed and minimum-power charging, while minimum-power charging minimizes daily electrical demand variation. These results offer energy system decision makers valuable insights into HDBEV load profiles and power demand variations across operator charging behaviours.
Promoting viable alternatives to motorized trips is crucial in moving away from car dependency and reducing the number of vehicle-kilometers travelled. Among these alternatives, cycling has proven to be an effective mode of transport to replace motorized vehicles for certain trip types, provided that adequate bicycle infrastructure is in place to support this modal shift._x000D_ _x000D_ However, many bicycle networks are either too sparse or poorly connected, resulting in unsafe or inefficient routes that deter potential users. Budgetary constraints also limit the amount of new infrastructure that can be built to improve existing networks._x000D_ _x000D_ This study addresses these challenges by proposing an algorithmic approach to cycling investments prioritization, aiming to maximize network productivity. The methodology focuses on identifying currently infeasible trips on a given network due to safety concerns or excessive detours. The network is then strategically expanded such that it minimizes these downsides and enhances overall connectivity and usability. Montreal's bicycle network is used as a case study, leveraging publicly available network data and trip data from the region's origin-destination survey. By systematically optimizing infrastructure investments, this research offers a practical framework for improving bicycle networks that can be used by city planners to support a modal shift towards cycling.
This paper aims to define a methodology to infer off-street parking at the scale of a municipality in the province of Quebec. Firstly, a database structure is proposed which allows the storage of estimates coming from multiple inference methods for a given lot, at multiple points in time_x000D_ A first estimation method using the parking requirements laid out in municipal zoning codes is proposed. A database structure is put forward to represent the variety of parking requirement formulations (based on square footage, seating capacity, etc.) present in zoning codes. Then an inference method using Quebec's municipal tax assessment database is tested. The results are discussed within the context of Quebec City._x000D_ Additionally, a web interface is presented allowing practitioners to complete the calculations, visualize the results and to override the proposed estimate manually or through other automatic estimation methods._x000D_ Finally, an Application Programming Interface (API) is proposed to access the results as part of other travel behaviour studies. The proposed API would allow the extraction of parking capacity within a geopolitical boundary or within a given isochrone of a point of interest.
Poor hazard anticipation skills play a main role in truck collisions, and Canadian truck drivers have identified a need for more exposure to hazardous scenarios as part of their mandatory entry level training. The aim of this study is to develop an evidence-based truck driver VRU hazard anticipation training module and to test its effectiveness on novice truck driver hazard anticipation skills in a simulated environment._x000D_ A video-based training was developed and truck driver trainees and novices (less than 5 years of truck driving experience) were recruited through invitations to several Ontario truck driving schools. A quarter cab truck simulator and a head-mounted eye tracker were used. The experiment consisted of 4 simulator drives including 8 hazardous scenarios, half of which were completed by participants before taking the hazard anticipation training (or "placebo" training for the control group) and half were completed after training. 26 novice truck drivers' glance and driving behaviour was recorded throughout the drives. Results are expected to highlight drivers' improved scanning of the environment, earlier detection and reaction to hazards, and overall improved safety after training for the experimental group, compared to the experimental group's performance before training and to the performance of the control group.
Advanced Air Mobility (AAM) systems are expected to operate in high-tempo, high-density urban environments. AAM airframes, made of primarily composite materials, are susceptible to impact damage. In addition to hail, dropped tools, and bird strike, AAMs are also subject to other sharp and blunt impact sources in busy urban environments, such as drones, ground vehicles, golf balls, and other objects which previously were not considered as threats to conventional commercial aircraft. It is well-known that impact damage in composites materials may not be readily detectable due to viscoelastic behaviour. This work provides a preliminary examination of impact damage scenarios with a focus on damage threat types from the perspective of damage severity and damage detectability. The study features a combined experimental and numerical investigation of impact damage from a range of impactors, from sharp to blunt, and the post-damage load-carrying capabilities of composite laminates. High-fidelity impact modelling and compressive residual strength modelling provided a physics-based understanding of damage evolution and residual strength performance with excellent experimental agreement.
Trucks' illegal parking results from parking shortage and policies that do not consider the parking requirements of trucks. Understanding trucks' parking behaviour is needed for the design of adequate infrastructure and the development of effective policies. For truck parking, data is limited, incomplete, and of variable quality. This results in decision models with unreliable predictability and transferability, yet these models are needed to inform policy questions. In this study, we synthesize the attributes of truck activity and parking, including attributes of the tour, parking location, industry sector, and commodity type for the purpose of developing a parking location choice model. This is done through the fusion of four data sources to construct a record of observed parking behaviours of trucks, mainly location choices and corresponding attributes. GPS data are used to construct truck trip diaries across the City of Toronto, including stop location, duration, frequency, and trip time of day and length. Business establishment data are used to infer the industry sectors associated with each tour. Data from the Ontario Commercial Vehicle Survey are used to predict the commodity types associated with each tour. Lastly, parking characteristics are inferred from spatial data representing the features of parking infrastructure.
This paper introduces a novel framework for optimizing delivery systems incorporating remotely piloted aircraft (RPAS), integrating advanced task allocation and routing loops to address key operational challenges in urban logistics. Inspired by studies on RPAS integration with public transportation networks for dynamic resource optimization, this work builds on a dual-loop structure: one dedicated to the spatiotemporal allocation of delivery tasks and the other to identifying optimal routes under complex urban conditions. Using public transit systems extends RPAS range, reduces energy consumption, and minimizes operational costs by utilizing existing infrastructure. The framework incorporates two independent optimization approaches, Monte Carlo simulations are employed to account for transit time variability, providing robust data for a multi-objective genetic algorithm that optimizes cost, time, and reliability, the cost model considers diverse components, including operational expenses, infrastructural investments for RPAS charging stations, and the potential economic impact on public transportation revenue. By comparing the results of the two approaches, the study evaluates their relative effectiveness in achieving significant delivery cost reductions and improving logistical performance. These findings underscore the potential of the dual-loop design to support practical decision-making in large-scale delivery network design.
A scoring index is developed to analyze the attractiveness of bike routes in urban areas for last-mile logistics using electric cargo cycles (ECCs). Existing bikeability scores tend to focus on infrastructure and operations-based attributes of a route. Comfort and safety attributes become more critical for ECCs due to the increased weight of a conventional bicycle when transporting goods. This report develops the ECC scoring index using a survey with participants riding on four routes within the York University Keele Campus. A literature review is conducted to identify twelve variables for the score. Data is collected using devices such as a GPS-connected smartphone, a Gyroscope, and a GoPro camera. Participants are asked to rate specified variables on infrastructure, safety and behaviour. The analytical hierarchy process is used to compute the weights for each factor using pairwise comparisons. It was found that cyclists prioritized collision risk, cyclist visibility and pavement condition the most when choosing a cycling route. Variables with the highest weights out of 100% include collision risk (24.3%-25.5%), visibility (11.1%-13.0%) and pavement condition (9.9%-12.4%). A simplified scoring index is derived using variables that could easily be applied to other routes to test its transferability.
Talk to me about public transit, rail transit, active transportation, transportation planning and freight transportationI would also like to learn about Marine Transportation and High-Speed Rail more.
Enhancing shared mobility can enable carsharing companies to optimise their services, improve user experiences, and increase adoption rates. Research on carsharing also informs urban planning and policy development. The adoption of carsharing services can help alleviate traffic congestion, reduce greenhouse gas emissions, and address the challenges of limited parking in urban areas by providing viable alternatives to personal vehicle use. This research, which primarily focuses on station-based system, aims to understand how people use carsharing reservation systems. These insights are essential for improving carsharing services. Communauto, Canada's largest carsharing company, has users who frequently modify their reservations, occasionally causing logistical challenges. Using the company's reservation database and R software, statistical analyses link social and temporal variables"”such as modification dates, number of modifications, age, gender, day of the week, and time of day"”to observed behaviours. One notable finding is the phenomenon of "fake cancellations," where 41% of cancelled reservations lead to another honoured reservation on the same day. To identify the key variables that determine whether a reservation will be cancelled or honoured, a decision tree has been constructed. Based on these findings, recommendations will be developed to minimise reservation modifications.
Full Professor, Polytechnique Montréal and CIRRELT
Martin Trépanier is a civil engineer and professor at the department of mathematics and industrial engineering of École Polytechnique de Montréal, an engineering school affiliated to the Université de Montréal. He is the titular of the Chair in the transformation of transportation... Read More →
Julien Lépine is an Associate Professor at the Department of Operations and Decision Systems at Université Laval in Québec City and a member of the Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT). Formerly, he was a Research Associate... Read More →
Emeritus Associate Professor, Sauder School of Business at UBC
Garland Chow is Emeritus Associate Professor in the Sauder School of Business at the University of British Columbia. He has published over 200 articles and reports in the supply chain and transportation field. In 2012, Garland was awarded the Queen Elizabeth II’s Diamond Jubilee... Read More →
Assistant Professor, University of British Columbia - Okanagan
Dr. Mahmudur Fatmi is a transportation professor at UBCO. He has started as an assistant professor at UBCO since July 2018. Dr. Fatmi contributes by developing advanced econometric modelling methods and agent-based microsimulation modelling techniques to assist in making effective... Read More →
The rapid expansion of remotely piloted aircraft systems (RPAS) operated over densely populated urban areas necessitates structured airspace management to ensure safety and efficiency. This study addresses the limitations of free-routing and proposes risk-based RPAS corridors as a solution to enhance operational control in congested urban environments. The main objective is to evaluate the capacity and safety implications of both static and dynamic RPAS corridors using a simulation model incorporating parameters like failure rates, navigation accuracy, and environmental conditions. Through this model, we assess the ground and air risks associated with RPAS operations, considering factors such as ground population density and weather variations. The results indicate that under optimal conditions, RPAS corridors can accommodate up to 92 flights per hour while maintaining the Target Level of Safety (TLS). However, increased traffic density or adverse weather can elevate collision risks, underscoring the need for dynamic capacity adjustments. The findings suggest that implementing adaptable separation standards and integrating real-time monitoring could effectively mitigate risks, enhancing safety and public acceptance. This study offers a detailed framework for designing RPAS corridors that balances safety and efficiency. Predictive analytics and risk-based methods enable safe RPAS integration, advancing sustainable urban air mobility.
Municipalities increasingly use GPS and IoT data to enhance freight analytics and inform policy. E-commerce activities, driven by connected vehicles, improve visibility yet complicate distinguishing e-commerce vehicles from other freight. Freight impacts the neighborhood's emissions, safety, noise, and traffic, underscoring the need to precisely identify e-commerce activities. Current traffic flow modeling and data lack granularity for neighborhood-level vehicle movements. As such, this study proposes a predictive framework to classify e-commerce vehicle trajectories using integrated datasets such as vehicle configuration, customer metadata, GPS trajectories, and duty cycle data. Capitalizing on Artificial Intelligence (AI), we first developed a large language model (LLM) to filter e-commerce fleets from non-e-commerce vehicles with similar configurations. Second, feature engineering on duty cycles and trajectories supports training machine learning models, including XGBoost, logistic regression, k-nearest neighbors (KNN), support vector machines (SVM), and random forests (RF). The proposed AI-driven model is tuned through cross-validation and oversampling to address class imbalance. Our AI model achieves nearly 80% precision, effectively distinguishing e-commerce vehicles with similar configurations. These results enable huge potential for municipal freight analytics across multiple domains.
Accurate predictions of on-street parking availability are vital for enhancing parking guidance systems, reducing drivers' search times, and alleviating traffic congestion and CO2 emissions. Traditional methods for predicting parking occupancy often fail to account for both the spatial dependencies between parking blocks and the impact of exogenous factors such as weather, nearby amenities, and traffic conditions._x000D_ This paper presents a novel simplified spatio-temporal graph neural network (SST-GNN) model that addresses these limitations by integrating exogenous data and leveraging a graph-based representation to capture spatial relationships between parking locations. The model also incorporates a temporal mechanism to account for the dynamic evolution of parking demand. By combining intrinsic and contextual factors, the proposed approach significantly improves prediction accuracy._x000D_ Experimental results on a real-world dataset demonstrate that the (SST-GNN) model outperforms traditional benchmarks in forecasting on-street parking occupancy, showcasing its potential to revolutionize smart parking systems.
Full Professor, Polytechnique Montréal and CIRRELT
Martin Trépanier is a civil engineer and professor at the department of mathematics and industrial engineering of École Polytechnique de Montréal, an engineering school affiliated to the Université de Montréal. He is the titular of the Chair in the transformation of transportation... Read More →
This paper examines Canada's new national Origin-Destination Survey, an initiative led by Housing, Infrastructure, and Communities Canada in collaboration with Statistics Canada. The survey is designed to address a long-standing gap in Canada's understanding of transportation and mobility patterns, providing critical data to inform policy and infrastructure planning.
The paper outlines the methodological framework and design considerations underpinning the survey, including sampling strategies, key metrics, and approaches to capturing data on transit behaviors, modal choices, vehicle-kilometers traveled, and travel patterns at household and individual levels. It discusses the inclusion of demographic data to understand the mobility challenges faced by equity-deserving populations, ensuring the survey addresses issues of accessibility and inclusivity.
Furthermore, it explores the anticipated utility of the survey findings in addressing national priorities, such as reducing greenhouse gas emissions, enhancing public transit access, and supporting evidence-based initiatives like Canada's Permanent Public Transit Fund.
Additionally, the paper highlights the timeline for data collection (scheduled for late 2025 or early 2026) and discusses the implications of the expected 2027 data release. The survey aims to drive transformative advancements in transportation planning by providing a comprehensive framework for leveraging large-scale data to inform sustainable, equitable mobility solutions and infrastructure policy across Canada.
Director of Data and Analytics, Housing, Infrastructure and Communities Canada
Eiad El Fateh is currently the Director of Data and Analytics within the Policy and Results Branch at Infrastructure Canada. Prior to Infrastructure Canada, Eiad held a variety of positions in economic policy across the federal government, most recently at Environment and Climate... Read More →
The transition to electric vehicles (EVs) remains in its early stages and the electric vehicle market share has become significant only recently. As a result, assessments of vehicle energy usage-influenced by everything from economic activity to fleet composition to charging behaviour-have relied on assumptions that are undergirded by limited empirical evidence. However, these assessments are crucial for electricity system operators, investors, and policy makers as they make long-term investments in electricity system supply. Here, we develop an analytical framework that integrates publicly available data and makes few assumptions to generate hourly load profiles of electric vehicle charging loads across the power system. The model is developed for the Canadian province of Alberta but employs economic and transportation data that are compiled routinely by other jurisdictions, making it broadly applicable to other locations. Results show that electric vehicles (EVs) will represent 16% of the current Alberta electricity consumption on an annual basis, with peaks that reach as high as 2.5 times the current demand peaks. With the growth in electric vehicles accelerating, the generalizable framework proposed here can be used by analysts in other jurisdictions to investigate the impact of light duty electrification on the electricity system, including to prioritize investments.
Understanding cyclists' route preferences is crucial for designing equitable and accessible urban cycling infrastructure. While previous research has examined the influence of network, contextual, and individual factors, energy expenditure remains an underexplored but critical determinant. Despite its recognized importance, energy costs are typically inferred rather than directly quantified in utilitarian cycling analyses. This study introduces the marginal rate of substitution between energy and time (MRS_{et}) to measure cyclists' willingness to exert physical effort to save travel time. Using a Mixed Path-Size Logit (MPSL) model with latent segmentation, this research empirically demonstrates that energy preferences significantly shape route choices. High-MRS cyclists"”more sensitive to exertion"”experience greater disutility from distance and steep grades but prioritize minimizing travel time over explicitly conserving energy. Low-MRS cyclists"”more willing to exert effort"”strongly avoid disruptions such as intersections and high-crash areas, favoring a smoother ride. These findings highlight behavioral heterogeneity in energy sensitivity and its impact on route selection. Designing infrastructure that accommodates diverse energy preferences"”through flatter, more direct routes, expanded e-bike access, and energy-efficient wayfinding"”can improve cycling inclusivity. Future research should refine energy expenditure quantification and develop integrated models that jointly consider route, speed, and mode choices, advancing sustainable urban mobility solutions.
Associate Professor, University of British Columbia
Alex Bigazzi is an Associate Professor in the Department of Civil Engineering at the University of British Columbia. His research focuses on non-motorized and lightly-motorized travel – in particular, the intersection of physics, physiology, and behaviour for active travellers... Read More →
Labour disruptions are a recurring theme in Canada's supply chains. In 2023, more than 230,000 days of work were lost to work stoppages in the transportation sector. In 2024, this number increased to more than 1.3 million._x000D_ _x000D_ Modern supply chains are complex. When a work stoppage occurs at any transportation link, the effects are felt widely by workers, consumers, and businesses alike. Each work stoppage affects Canada's economy, workers' earnings, and the country's reputation as a reliable trading partner. _x000D_ _x000D_ Over the past several decades, Canada has experienced more than five times the OECD average for work days lost from stoppages. Opinion surveys demonstrate that most Canadians want governments to proactively step in and act to prevent the devastating impacts of work stoppages. Canada needs a solution._x000D_ _x000D_ This paper models the macroeconomic impacts of work stoppages in Canada's transportation sector. Whether it's rail, ports, truck, or air, transportation industries provide essential supply chain services that keep the economy moving. It is critical that policy makers recognize the impacts of labour disruptions on the country's economy to develop effective legislative solutions._x000D_
Encouraging parents to adopt more sustainable commuting modes remains a persistent challenge for transportation planners. A critical yet often overlooked barrier is the impact of "service trips", such as driving children to school, on parental mobility choices. These trips, driven by time constraints and logistical demands, frequently lead to increased car ownership. This, in turn, reinforces car use for commuting and other daily activities, creating a self-perpetuating cycle of car dependency.
Using data from Origin-Destination travel surveys conducted in the Montreal and Quebec regions, this presentation examines the complex relationship between school-related service trips and parental transportation behaviors. It highlights the potential of improving transportation options for children to travel independently to school as a lever to reduce car dependency among parents. The analysis estimates the positive impacts of such changes, including shifts in mode share, reductions in kilometers traveled by car, energy consumption, and greenhouse gas emissions. Additionally, the study explores the broader benefits, such as improved health outcomes for children and enhanced family mobility flexibility.
This research underscores the need for integrated planning approaches that address the role of school trips in shaping mobility patterns, paving the way for more sustainable urban transportation systems.
Artificial intelligence (AI) has surprised and delighted many professionals for its potential to revolutionize the way we work and live. There are many AI applications in the transportation sector, and many of these help us learn at an accelerated rate. This accelerated learning helps us more accurately predict futures such as people and goods movements and asset condition, under new climate, social, and technology scenarios. Our ability to better predict helps us make decisions that better prepare us for the future. But there is also great awareness of the risks AI can pose and the computing power it requires. Further, each AI application requires substantial data governance efforts and other risk mitigation measures. It can therefore be difficult to know where to start. This paper will review the criteria necessary to evaluate AI initiatives, and provide practical guidance to urban and provincial transportation professionals on where to start with their AI journey, and how to prioritise and set a roadmap for their AI applications.
Executive Director, Research & Innovation, WSP Canada
Passionate about designing a built environment that creates wealth and improves quality of life for all.Civil Engineer and Economist with a Asset Management backgroundMentor in the IBET program (Indigenous Black Engineering Technology)Adjunct Professor at UNB
To increase the productivity of public transit networks, we need a comprehensive way to study it from various perspectives, particularly in conjunction with the built environment of cities. Traditionally, the approach toward public transport interventions is to study ridership data without unpacking the underlying urban form and context of the transit network. We present the concept of didactic cartography-an approach to teach complex systems through clear and engaging spatial data-in relation to public transit and their built environments. We propose a transdisciplinary and interactive platform - CAMMM Atlas web application - that aggregates data and disseminates information in an accessible manner. The Atlas points to areas of opportunity to increase the productivity of the transit system and improve spatial equity in the urban space. Through this tool, understanding the gaps in public transit systems will enable local transit authorities, decision makers, and other stakeholders to collaborate on spatial equity issues like multimodality, connectivity, safety, accessibility, proximity to services and amenities, etc. The multidisciplinary approach of the Atlas allows policy makers and transportation professionals to obtain concrete recommendations to improve the productivity of public transit.
Developing an optimal on-route charging network for long-haul electric vehicles (LHEVs) is a complex task. The varying nature of LHEV driving ranges further complicates this challenge. Using current LHEV operational ranges may produce misleading results especially when planning the future of the charging infrastructure. This is likely to be the case as newer LHEV models with longer ranges become available in the future, while older models remain in use. This study simulates various scenarios to optimize on-route charging locations in Ontario, Canada for 2040. The scenarios account for advancements in battery technology, long-term battery degradation, ancillary energy use, and seasonal variations. Results suggest that summer and winter seasons reduce ranges by approximately 3% and 8%, respectively, necessitating more charging during these seasons. Other factors like varying utilization rates and maximum space capacity constraints are found to have noticeable effects on the number of required charging locations in the province. Lastly, estimated energy demands suggest the need for substantial infrastructure upgrades, particularly during winter season, with a projected daily demand reaching about 67 GW.
The British Columbia Ministry of Transportation and Infrastructure launched an e-bike purchase rebate program in June 2023, with income-conditioned incentives of $350, $1,000, and $1,400. The objective of this study was to determine how rebate recipients' travel behaviour changed following their e-bike purchase, and up to a year later. We recruited 1,069 rebate recipients to participate in a 3-wave panel survey. The study participants answered a range of questions related to their sociodemographic attributes, e-bike purchase decisions, typical travel behavior before and after the purchase, and experience using the e-bike. We find that 12 months after purchase most participants still regularly use their e-bike, with 37% of e-bike trips substituting for auto travel. Average e-bike usage increased by around 50 km/week, while auto usage decreased by half that amount. We also examine the impacts of socio-economic, demographic, and contextual factors on usage of and experience with the purchased e-bikes. The study findings provide insights on the benefits and design of future e-bike incentive programs.
Associate Professor, University of British Columbia
Alex Bigazzi is an Associate Professor in the Department of Civil Engineering at the University of British Columbia. His research focuses on non-motorized and lightly-motorized travel – in particular, the intersection of physics, physiology, and behaviour for active travellers... Read More →
Since most COVID-19 restrictions were eased in early 2022, labour disruptions in the transportation sector have come in "waves", beginning with a two-day lock-out by CP._x000D_ _x000D_ Despite government interventions, there seems to be no enduring labour peace. For example, the unions are challenging the Minister's referrals and the CIRB's decisions that led to binding arbitration being imposed on rail and port workers._x000D_ _x000D_ This paper will track the major labour disruptions in the past 2 years, reviewing the issues, developments and key impacts on the nation's goods movement, trade, supply chain and economy, It will include references to the existing Canada Labour Code (CLC) and the Canada Industrial Relations Board which is an independent administrative tribunal responsible for resolving workplace disputes and certain appeals that arise under the CLC, for federally regulated sectors including transportation._x000D_ _x000D_ In looking for potential solutions, the paper will consider the broader picture and some upcoming key developments including the federal transportation supply chain strategy under develo(to be released end of 2024) and the federal Industrial Inquiry Commission on longshoring disputes at Canada's West Coast ports, which is expected to present its findings and recommendations in a report to the Minister in Spring 2025.
Encouraging greater public transport usage and reducing automobile dependency requires making public transport systems more competitive and appealing. To achieve this, transit networks must address the mobility needs of diverse population segments with varying travel needs throughout the day. Providing a high-quality transit system requires an in-depth understanding of users, their habits, and their route-choice decision-making process.
This presentation focuses on the various types of travelers among public transit users when it comes to choosing which route to use to travel between two points. Decisions regarding route choice are closely tied to factors such as age, gender, occupation, and household characteristics. Additionally, some users may prioritize minimizing walking distance, while others may seek to reduce the number of transfers or minimise total travel time. Using observed transit routes from an Origin-Destination travel survey of Montreal, we develop a typology of traveler based on transit route choice strategy.
This approach sheds light on user preferences and travel habits, enabling transit planners to design systems that better align with the needs and expectations of diverse traveler groups.
There is growing need for human-centered geographical methods to understand how urban systems, like transportation, are differently experienced by different urban inhabitants and how those differences are imprinted in the territory. Under this premise, this paper presents a method for a human-centered classification of urban transport flows, focused on gender. The objective is to unveil if men and women produce distinct spatial patterns to inform gender-equity aware transport planning. Using an origin-destination survey for the metropolitan area of Montreal, it applies a Hierarchical Link Clustering algorithm to produce communities of flows with similar characteristics based on geography, distance and number of trips. Then a K-means classification is applied to the resulting communities to derive movement types. Results show a distinct geographical pattern between genders, where women move predominantly in round, local types of communities, whereas men tend to move in elongated, movement types of communities. These results can be used to introduce more targeted interventions to transport systems, and further, it can be applied to other dimensions of equity beyond gender.
Full Professor, Polytechnique Montréal and CIRRELT
Martin Trépanier is a civil engineer and professor at the department of mathematics and industrial engineering of École Polytechnique de Montréal, an engineering school affiliated to the Université de Montréal. He is the titular of the Chair in the transformation of transportation... Read More →
Canada's transportation sector is rapidly transitioning to electrification, raising concerns about the strain on electricity grids during peak electric vehicle (EV) charging times. This increase in electricity demand has raised concerns about heightened peak demand, fluctuations in wattage and frequencies, increased transmission loss, compromised grid reliability, and the risk of power line overloads. Mitigating these concerns can be accomplished through demand management programs. As an initial exploration into understanding charging demand patterns this research aims to study the demand behavior patterns at electrical charging stations within the City of Ottawa. The research develops a multiple variable regression model using publicly available data from the City of Ottawa to model the gap times between charging events. The regression model aims to identify temporal/seasonality variations in EV charging behavior and the significance of the presence of rapid transit, and arterial roads. The regression model will also utilize data from the 2020 census to study the impact of site-specific dissemination area characteristics such as median income, median household sizes, and average travel times. The findings provide foundational knowledge to develop more resilient and efficient integration of EV charging infrastructure into urban grids.
The COVID-19 pandemic had a serious impact on residents' work and travel around the world. China and Canada, as two typical countries with two social systems, have imposed different restrictions on travel and social interactions in the face of COVID-19. This paper conducted a questionnaire survey on travelers in China and Canada, recording personal travel and social and family attributes. The survey content included life satisfaction, travel satisfaction indicators, sociodemographics, travel patterns before, during, and after the COVID-19 pandemic, and social interaction patterns during the pandemic. Latent class analysis was used to analyze travel choice behavior dynamics before, during, and after the pandemic, and to compare the travel choice behaviors of residents in China and Canada. Finally, a comparison was made to explore which factors and how much they contribute to the well-being of residents in different countries. These findings help formulate appropriate travel and social strategies to improve residents' well-being in response to similar public health emergencies such as COVID-19.
Grain elevators are a crucial part of the agricultural supply chain of Manitoba, and they have played a historic role in the economic success of the province. Motivated by a desire for enhanced efficiency and productivity, grain companies have been consolidating elevators in Canada, and this has resulted in the closure of less viable grain elevators located in rural parts of the country. This shift has presented significant challenges for farmers, who are now required to transport their grains over longer distances. This study investigates the economic and environmental impacts of these closures from a supply chain sustainability perspective. Economically, farmers are burdened by rising transportation costs, while environmentally, the increased travel distances contribute to higher greenhouse gas emissions and accelerate infrastructure degradation. A conceptual framework is proposed to examine the interconnections between economic and environmental sustainability within agricultural supply chains, drawing on principles of Sustainable Supply Chain Management (SSCM) and the Triple Bottom Line (TBL). The study emphasizes the need for policy interventions, community-driven solutions, and sustainable practices to balance economic viability with environmental stewardship, fostering resilience in Manitoba's agricultural supply chains.
In most metropolitan areas, a diverse array of transportation modes is available to travelers, each serving specific travel needs and shaping distinctive usage patterns. This research focuses on analyzing these patterns across a wide spectrum of transportation options in the Greater Montreal Area. While traditional transport surveys are valuable for modeling individual behaviors during an average weekday, they fail to capture the variability in the use of different transportation modes over time.
This study addresses this gap by leveraging a diverse set of operational data from transportation systems and services. Clustering approaches are applied to identify typical daily and weekly usage patterns. Six relatively independent data streams are analyzed: vehicle road counts, bicycle counters, transit validation records for subway and bus, GPS data for taxis, BIXI bikesharing usage data, and Communauto carsharing data. These datasets collectively cover a common area in the central part of the Island of Montreal for the years 2019 to 2023.
The four years of continuous data enable an analysis of how usage patterns have evolved over time, offering insights into shifts in mobility trends. Additionally, this research highlights the methodological challenges of integrating multiple data streams to model usage at varying spatial and temporal resolutions.
Regional fare integration is critical for the growth of robust and attractive urban transit systems, allowing for seamless travel and improving accessibility for urban populations where municipal boundaries are increasingly blurred or irrelevant in public perception. Examples of fare integration approaches globally provide insight into success factors and commonalities between successful regional fare integration models. This paper considers global best practices in fare integration, focusing on governance models, pricing schemes and operational strategies that facilitate effective implementation. Case studies from Canada including ARTM in Montréal and TransLink in Metro Vancouver, Europe including Switzerland's nationwide fare network and the Berlin-Brandenburg public transport association, and Sydney (Australia) Metro are analyzed to identify key drivers of success. _x000D_ _x000D_ This paper incorporates findings from a detailed desktop review of publicly available reports, academic sources, and transit agency websites, supplemented with interviews with individuals at transit agencies and consultations with a panel of transit industry professionals. This multifaceted approach aims to provide a thorough understanding of the governance structures, technology, fare schemes and operational strategies conducive to successful fare integration._x000D_ _x000D_ The analysis underscores the potential for Canadian regions to increase transit ridership, reduce congestion, and support sustainable, equitable, and user-friendly transit through effective fare integration strategies.
A productive public transit system is one that serves everyone's access to places that matter. Access to grocery stores is an essential destination that matters to all, and accessibility measures can be used to quantify this idea. However, how the public transit system provides access to destinations is a question of equity: what populations are better-off, from before- and within the COVID years, and how does accessibility compare across urban regions is an important task in benchmarking public transit service and identifying areas that fall short. In this study, we apply balancing factors (similar to those used in trip gravity modelling) to calculate public transit spatial accessibility in the 12 most populous CMAs in Canada and benchmark how accessibility has changed between 2019 and 2023. This work is done using an open and reproducible database, with methods based in R. Additionally, the methods applied are more interpretable than conventional accessibility measures, making them better suited for temporal and spatial interpretation. Our hope is that this approach will facilitate the mainstreaming of open and reproducible practices and accessibility analysis in transportation planning practice in Canada.
Transportation is estimated to account for roughly one-quarter of Canada's annual greenhouse gas emissions. As Canada transitions toward a greener future, zero-emission vehicles (ZEVs) are being promoted in support of the 2030 climate reduction targets. Indeed, Canada's accelerated ZEV target is 100% for new light-duty car and passenger truck sales by 2035. Therefore, understanding how public charging infrastructure aligns with ZEV adoption is critical to inform policymakers and industry stakeholders. Moreover, there is some evidence to suggest that geographic disparities in ZEV ownership and charging infrastructure are potential obstacles to achieving the target. _x000D_ _x000D_ This research examines the factors driving ZEV adoption across Canada, including public charging infrastructure, incentive programs, and other factors such as income and location. Drawing on data from Statistics Canada and other agencies, the study examines patterns of ZEV adoption, charging infrastructure provision, and disparities in coverage. Public charging infrastructure is assessed by forecasting ZEV adoption rates under three scenarios. Next, Canada is divided into urban, and rural & small-town areas to quantify any geographic disparities that may be emerging. The study concludes by discussing next steps including related work involving the heavy-duty vehicle fleet.
Cities are facing growing issues related to the effects of GHG emissions, air pollution and congestion. To induce mode shift towards more sustainable transportation modes, planners need to provide highly attractive transit networks. One way to do this is to improve their accessibility.
Enhancing walking accessibility to public transportation starts with something crucial: assessing the current level of walking accessibility. This study introduces a walking accessibility assessment using GIS functions and open-source data. It also proposes new accessibility indicators of the quality of access to transit. The Montreal metro network is used as a case study. We generate walking catchment areas and test indicators of accessibility by studying their geometric properties and by comparing them with ideal ones. We use census data to further develop indicators accounting for the population
This methodology identifies stations with low accessibility and estimates potential accessibility gains. In Montreal, some 406,375 people could benefit from accessibility improvements, representing a 46.5% increase.
Based on the diagnostic, scenarios were developed to address specific barriers such as infrastructure and land-use constraints. These scenarios involve bridging physical barriers to maximize accessibility gains. These measures aim to improve walking access equitably and enhance transit network attractiveness.
The decline of grain elevators in Canada has increased reliance on local truck-based grain transportation, raising concerns over economic costs, environmental impacts, and rural sustainability. This study explores the potential of shortline rail as a sustainable alternative for grain transportation from farms to elevators, adopting the triple-bottom-line sustainability framework"”economic, environmental, and social sustainability. The research aims to develop a comprehensive sustainability assessment framework tailored to shortline rail networks, integrating quantitative sustainability indicators and qualitative stakeholder feedback. The proposed framework includes indicator forecasting, stakeholder analysis, engagement strategies, and case studies to evaluate the current grain transportation system and the viability of shortline rail networks in improving sustainability. By assessing cost efficiency, carbon footprint reduction, logistical feasibility, and socio-economic benefits, this study highlights shortline rail's potential to enhance rural economic development, reduce transportation bottlenecks, and strengthen community resilience. Findings will contribute to evidence-based policy recommendations for optimizing Canada's grain supply chains while fostering long-term sustainability in the agricultural transportation sector.
The urban street sits at the centre of policy attention looking to redress the injustice of the car domination of the urban landscape, which contributes to unhealthy cities, pollution, high rates of fatal crashes between automobiles and other travellers, and other maladies. Much of the contestation around the street focuses on the space allocated to different transport infrastructures, which overwhelmingly is dedicated to cars. While some recent research has begun to closely examine the distribution of street space to transport infrastructures, another under-explored angle is dynamic street space consumption: how much space does a trip occupy in the city, over time, considering movement dynamics. In this paper, we use mobility survey data to analyze how the street space used by different travellers and households varies according to trip, personal, and household characteristics. In this way, we examine inequities in how people use city space according to travel mode, gender, race, income, and household composition. In addition to the spatial dimension, we also consider the carbon emissions of trips, to understand how space consumption and carbon emissions are related, and how different personal and household characteristics relate to the environmental cost of travel.
It's well known that the cost of flying through Canadian airports remains relatively high. This paper will examine the influence of government policies on airfare affordability, delve into how airlines navigate these regulations and explore potential collaborative solutions for achieving more affordable air travel.
Incorporating in-motion charging into Battery Electric Bus (BEB) transit systems offers a practical approach to overcoming key challenges of stationary charging, including limited resources, long charging times, and higher battery costs. This study introduces a comprehensive optimization framework that combines conductive Overhead Catenary Charging (OCC) technology with overnight depot charging to minimize overall BEB system costs, both capital and operational. Capital costs are effectively reduced by strategically determining the optimal placement of OCC segments, battery capacity, and depot charging configurations. Simultaneously, operational costs are optimized through refined charging schedules that account for electricity time-of-use (ToU) pricing, greenhouse gas (GHG) emissions intensity (measured in tCo2e), and BEB battery degradation costs. _x000D_ Applying this optimization framework to a real-world transit network reveals significant findings, including a 56% reduction in peak electricity demand, a 13% drop in GHG emissions, and a 27% decrease in overall charging costs. Furthermore, sensitivity analysis underscores the influence of OCC infrastructure costs on total system costs while increasing OCC charging power further enhances cost savings by up to 28%.
I received a B.Sc. degree in the Electrical Power and Machines Department from Tanta University, Egypt, in 2014 with distinction (honors). In January 2021, I received a master's degree in engineering mathematics from Tanta University. My research areas of interest include optimization... Read More →
Canada relies heavily on international trade for its economic growth and success. The total trade in 2024 was worth 1.52 trillion dollars, 64% of which was with the U.S. Around 58% of total trade between the two countries took place by trucks through key Ontario land borders. The COVID-19 pandemic led to unexpected supply-chain interruptions and that included the health care sector. Part of these interruptions included the inability to move pharmaceuticals to Ontario across the border. Shortage of certain medicine supplies can have detrimental impacts on the Canadian health Care sector. To date, studies on the cross-border movements of pharmaceuticals between the U.S. and Canada are lacking. The work in this paper will fill the existing gap by characterizing these movements to understand where in the U.S. pharmaceuticals originate, and which routes and land borders are normally used to bring them into Ontario. The analysis will be based on a variety of data sources to provide a clear picture of the key U.S. markets that Ontario trades with. Scenario analysis will examine the impacts of land border closures which will cause diversion in the truck flows through alternative land border crossings to ensure uninterrupted supply-chain of pharmaceuticals to Ontario.
In a previous study, we identified eight distinct carsharing reservation types in Montreal, characterizing a wide range of usage patterns. Among them, the ""20-minute Trips'' cluster represents nearly 50% of all reservations but accounts for only 10% of the total distance traveled and 4% of the total duration. This cluster consists exclusively of one-way single-stop trips with an average duration of 20 minutes and average distance of 7 km. In this study, we document the context in which users chose carsharing for these short free-floating trips. To assess alternatives, we calculate public transit travel times, evaluate bike-share availability at trip origins and destinations, estimate the cost of an equivalent taxi ride, and calculate walking times. We further incorporate historical weather data to refine our evaluation of bike-sharing and walking feasibility and our understanding of the spatial-temporal context. Finally, we conduct spatial analyses to identify problematic blind spots in public transit and areas with limited access to bike-sharing infrastructure. Based on findings from previous research, we anticipate that these trips predominantly occur in areas with limited access to public transit and bike-sharing infrastructure. This work aims to provide insights into improving transportation equity and enhancing sustainable mobility options in urban areas.
Full Professor, Polytechnique Montréal and CIRRELT
Martin Trépanier is a civil engineer and professor at the department of mathematics and industrial engineering of École Polytechnique de Montréal, an engineering school affiliated to the Université de Montréal. He is the titular of the Chair in the transformation of transportation... Read More →
Electric bicycles (e-bikes) are a growing component of sustainable urban mobility, but their reliance on grid-based charging and logistical inefficiencies, such as rebalancing, contribute to operational emissions. This study evaluates the feasibility of solar-powered charging stations in Vancouver, Canada, analyzing energy production, emissions reduction, and economic viability. Using bike-share data, e-bike energy demand was found to be 538 kWh annually per station, met by a 4 m² photovoltaic (PV) system with 2 kWh of battery storage._x000D_ _x000D_ The proposed system can fully replace grid-based charging while eliminating rebalancing-related emissions (23.38 kg CO₂e per station annually). Despite solar PV having a higher lifecycle carbon intensity (40 g CO₂e/kWh vs. BC Hydro's 14 g CO₂e/kWh), cumulative emissions are lower over a 25-year lifespan due to improved operational efficiency. However, economic analysis indicates a payback period of 26 years, exceeding the system's lifespan, highlighting the need for financial incentives._x000D_ _x000D_ This study considers a worst-case scenario, yet the system proved sufficient, suggesting scalability across a bike-share network. Findings provide insights for city planners and policymakers seeking to integrate renewable energy into urban transportation, improving sustainability while addressing practical deployment challenges.
The relative importance of cross-border trade in Canada has been changing for quite a long time, particularly in Ontario which borders the five U.S. states in the south: Minnesota, Michigan, Ohio, Pennsylvania and New York. With the growth of e-commerce, there has been a tremendous increase in products that cross the 5,500-mile border between Canada and the U.S.
According to some experts in transportation research, "cross-border transportation involves the activities, infrastructures, and flows that ensure the passage of passengers and freight across an international border". As a result, "cross-border transportation can be facilitated, monitored, controlled, and even prevented".
As such, this paper will present a descriptive account of Canada-US cross-border freight transportation along those lines, with relevant background, details or examples (e.g. regulatory and operating requirements, border crossings and infrastructure, customs and trade facilitation, developments and data including technological advances and commodity flows) and with particular reference to land freight transportation and trucking services.
The intent is for the paper to provide an overall picture of shipping goods between Canada to the U.S. via cross-border freight transportation especially trucking, which is required for considering the current situation as well as issues and challenges facing the industry involved in cross-border trade.
