Climate Mobility Research Symposium
Schedule
| Date: Feb 24, 2026 Time: 10:00 am – 4.00 pm PST UNC Ballroom 200, UBCO. | |
| 9:45 am – 10:00 am | Registration and Coffee |
| Welcome Session | |
| 10:00 am – 10:20 am | Introductions |
| Session 1: Presentation Session 1 (15 min presentation, and 5 min Q & A) | |
| 10:20 am – 10:40 am | Developing a Next Generation Travel Demand Model for Climate-resilient Policy Testing Speaker: Dr. Mahmudur Fatmi Abstract/Presentation |
| 10:40 am – 11:00 am | An agent-based Integrated Land Use, Vehicle Ownership, and Transportation Model for Okanagan and Metro Vancouver Speaker: Md Shahadat Hossain Abstract/Presentation |
| 11:00 am – 11:20 am | A Mobile Platform for User-Augmented Travel Behavior Data Collection Speaker: Dr. Khalad Hasan Abstract/Presentation |
| 11:20 am – 11:35 am | Coffee Break |
| Session 2: Presentation (15 min presentation, and 5 min Q & A) | |
| 11:35 am – 11:55 am | A Flexible Framework for High-Resolution Vehicle Emission Inventories in Data-Rich and Data-Limited Canadian Cities Speaker: Mina Jamshidi Kalajahi Abstract/Presentation |
| 11:55 am – 12:15 pm | Life-cycle thinking-based housing development optimization: Integrating building and vehicle emissions Speaker: Dr. Kasun Hewage Abstract/Presentation |
| 12:15 pm – 12:30 pm | Geospatial Visualization: Creating Interactive Tools to Better Understand Complex Climate and Mobility Research Data Speaker: Dr. Jon Corbett Abstract/Presentation |
| 12:30 pm – 1:30 pm | Lunch Break |
| Session 3: Poster Session | |
| 1:30 pm – 2:30 pm | Posters by Students Abstracts/Posters |
| Session 4: Round Table Discussions | |
| 2:30 pm – 3:45 pm | World Café |
| 3:45 pm – 4:00 pm | Closing Remarks |
| More information: Manoj (manoj.sangameshwar@ubc.ca) | |
Gallery
Presentations
Developing a Next Generation Travel Demand Model for Climate-resilient Policy Testing
Presenter: Mahmudur Fatmi Ph.D., P.Eng.
Abstract:
This presentation will briefly outline the scope of this overall research project which includes, transportation modelling, land use and vehicle ownership modelling, data collection, emissions analysis and Geoportal. Then, I will focus on the innovation in the transportation modelling and data component of this project. Specifically, I will introduce a next generation travel demand model. Why we call this a next generation model? Because, we are adding fundamental capacities to this model to tackle the limitation of the existing models: 1) extending the modelling paradigm from travel activities to modelling how individuals spend their time at home, out-of-home and online, 2) extending the modelling of vehicular travel to adding an explicit bike simulation module, and 3) extending the model from a typical weekday to a weeklong investigation. This is an agent-based model – i.e., all individuals and households in the study area are represented in the simulation. The model has been developed, calibrated, validated, and used for policy testing for Okanagan and Metro Vancouver regions. I will also discuss about the data for this modelling which comes from two longitudinal survey (2023, 2024 and 2025) sources: 1) British Columbia Activity Time Use Survey which provides information on how British Columbians spend time on virtual and physical spaces in a typical weekday, and 2) a Smartphone app-based weeklong survey which provides information on 7-day travel pattern of British Columbians.
An agent-based Integrated Land Use, Vehicle Ownership, and Transportation Model for Okanagan and Metro Vancouver
Presenter: Md Shahadat Hossain
Abstract
Traditional travel demand models treat land use patterns and vehicle ownership as external factors, overlooking their dynamic interactions with transportation choices over time. This limits their ability to evaluate integrated transportation and land use policies, such as transit-oriented development and electric vehicle incentives. With this motivation, we developed the Simulator for Transportation, Energy, LAnd use for Regional System (STELARS), an integrated, agent-based hybrid (continuous–discrete) simulation model that simulates population demographics, residential location, vehicle ownership, and travel behavior across time and space. The model is implemented and validated for Okanagan and Metro Vancouver. This presentation highlights the vehicle ownership component of STELARS, which simulates: (1) the timing of vehicle purchase, sale, or disposal, and (2) vehicle type choice by size, age, fuel, and technology. VOSim has been deployed and validated for 2011–2021 in the study regions, providing a behaviorally realistic and policy-sensitive framework for forecasting vehicle ownership under alternative scenarios.
A Mobile Platform for User-Augmented Travel Behavior Data Collection
Presenter: Dr. Khalad Hasan Ph.D.
Abstract
Understanding users’ mobility behaviors and trip purposes is essential for advancing research in transportation planning, urban analytics, and sustainable mobility design. This project introduces a mobile application designed to capture high‑resolution, app‑based travel survey data from participants across British Columbia. Once installed, the application passively records users’ movement patterns, detecting individual trips and visualizing them both as list entries and mapped trajectories. It also allows users to annotate each trip with its purpose (e.g., work, dining at restaurants or cafés) and transportation mode. By incorporating user feedback into algorithmically detected trips, the system enhances the reliability, accuracy, and contextual depth of collected mobility data, further supporting robust analyses of travel behavior and activity patterns.
A Flexible Framework for High-Resolution Vehicle Emission Inventories in Data-Rich and Data-Limited Canadian Cities
Presenter: Mina Jamshidi Kalajahi
Abstract:
Developing high-resolution, bottom-up vehicle emission inventories (EIs) in Canadian cities is complicated by large differences in local data availability. Many municipalities lack detailed traffic activity, fleet composition, or driving pattern information, limiting their ability to produce inventories that support air quality management and transportation planning. This study presents a flexible framework that integrates agent-based activity-based model (ABM) with the MOVES emissions model to generate spatiotemporally-resolved EIs in both data-rich and data-limited contexts. The framework includes procedures for extracting road segment-level traffic activity from MATSim, mapping these outputs to MOVES inputs, and incorporating local fleet characteristics and driving behaviour using either existing databases or estimation and scaling approaches suitable for data-sparse regions. We demonstrate the framework’s adaptability through two contrasting applications: Metro Vancouver, representing a data-rich urban environment, and the Okanagan Region, representing a mid-sized region with limited traffic and fleet data. Across both regions, we generated high-resolution inventories for traffic-related air pollutants and greenhouse gases.
Life-cycle thinking-based housing development optimization: Integrating building and vehicle emissions
Presenter: Dr. Kasun Hewage Ph.D., P.Eng.
Abstract
Life-cycle thinking is a concept that views products and systems as a whole, offering a comprehensive framework for evaluation by examining environmental impacts across all stages of their existence, rather than focusing on isolated components or phases. In this project, adopting a life-cycle perspective uncovers emissions and impacts that are often hidden by traditional assessments of land use and vehicle ownership. In addition, this research focuses on developing an integrated life-cycle framework that links residential development to transportation systems to examine their interrelationships. To achieve this, the framework combines a life-cycle-based housing-starts model with a regional model of light-duty vehicle commuting emissions. Commuting emissions are further analyzed using a regional model that extends the system boundary beyond tailpipe emissions to include impacts from vehicle manufacturing, fuel supply chains, operation, maintenance, and end-of-life disposal. In addition to environmental assessment, the framework considers multiple stakeholder perspectives by aiming to maximize developer profitability and minimize household user costs. The resulting optimization model incorporates housing demand, land availability, and zoning constraints to predict the best location, type, and timing of residential developments, while mitigating overall life-cycle impacts.
Geospatial Visualization: Creating Interactive Tools to Better Understand Complex Climate and Mobility Research Data
Presenter: Dr. Jon Corbett Ph.D.
Abstract:
This presentation explores the critical role of data visualization and geospatial representation in transforming complex climate and mobility research into accessible, actionable insights. Beginning with foundational principles of why visualization matters (from revealing hidden spatial patterns to enabling diverse stakeholder collaboration), the talk examines the unique challenges of working with large-scale, synthetic datasets in web-based environments. The presentation showcases the development of the CliMR (Climate Mobility Research Network) Geoportal. Using examples in real-time, this initiative demonstrates innovative approaches to making modelled synthetic data accessible to multiple audiences, from academic researchers requiring direct data access to public users seeking engaging, exploratory visualizations. Key technical and collaborative challenges are addressed, including managing massive population agent model outputs through strategic data aggregation, presenting modeled data responsibly without misleading users, coordinating parallel development workflows with evolving datasets, and creating cohesion across multidisciplinary research teams. The presentation emphasizes that effective geospatial visualization serves not only as a communication tool but also as a validation mechanism for complex research outputs.
Posters
Please note that a few of the poster materials presented at the symposium are currently part of manuscripts that are under review for publication. Those materials have not yet been made publicly available. If you are interested to get access to these materials, please reach out to Manoj (manoj.sangameshwar@ubc.ca).
5. How British Columbians Spend Time at Home, Online, and Outside
Student: Mostaq Ahmed
Principal Investigator: Dr.Mahmudur Fatmi
Abstract
Activity-based travel demand modeling begins with a simple premise: people do not travel for its own sake—they travel to participate in activities. Yet most conventional travel surveys record trips and broad purposes, providing too little detail to study how at-home and online activities substitute for, or complement, out-of-home participation. The British Columbia Activity-Time Use Survey (BC ATUS) addresses this gap through a 24-hour diary that captures in-home, online, and out-of-home activities with granular categories, timing, and locations, and records mode and trip context for out-of-home episodes. BC ATUS is a three-wave longitudinal survey, which is crucial in a rapidly changing post-COVID world for assessing whether behaviors rebound toward pre-COVID norms or whether remote and online patterns persist as a new baseline. This Wave 2 poster synthesizes findings from the BC ATUS in Metro Vancouver and the Okanagan, based on 2,391 individuals (1,594 households) surveyed in Oct–Dec 2024 and Feb–Mar 2025. we document substantial regional differences in mode choice and carbon impacts, and clear contrasts between commuters, remote workers, and non-workers in daily travel distance and GHG emissions.
6. A Mobile Platform for User-Augmented Travel Behavior Data Collection
Student: Qingyun Qian
Principal Investigator: Khalad Hasan
Abstract
Understanding users’ mobility behaviors and trip purposes is essential for advancing research in transportation planning, urban analytics, and sustainable mobility design. This project introduces a mobile application designed to capture high‑resolution, app‑based travel survey data from participants across British Columbia. Once installed, the application passively records users’ movement patterns, detecting individual trips and visualizing them both as list entries and mapped trajectories. It also allows users to annotate each trip with its purpose (e.g., work, dining at restaurants or cafés) and transportation mode. By incorporating user feedback into algorithmically detected trips, the system enhances the reliability, accuracy, and contextual depth of collected mobility data, further supporting robust analyses of travel behavior and activity patterns.
8. Microsimulating Vehicle Ownership for Okanagan and Metro Vancouver using an Agent-based Model
Student: Md Shahadat Hossain
Principal Investigator: Mahmudur Fatmi, Ph.D., P.Eng.
This study presents a large-scale agent-based vehicle ownership simulation (VOSim) model to microsimulate vehicle ownership in the Okanagan and MetroVancouver regions. VOSim operates as an event-based decision process adopting a hybrid of continuous-discrete time simulation techniques. Each household agent in the model becomes active to adjust their vehicle fleet following a list of events (e.g., child-birth) and make two interconnected decisions- vehicle transaction and type choices. The transaction stage models the timing of first vehicle purchases, additions, disposals, or replacements in continuous time, while the type choice stage simulates selections by vehicle body, vintage, fuel, and technology in discrete time steps. Multi-year validation confirms the model’s satisfactory accuracy. VOSim is deployed to predict vehicle ownership for a 10-year period (2011-2021) in the study regions, revealing spatio-temporal patterns and variations across socio-economic groups. Overall, VOSim has the capacity to enhance urban simulation tools by integrating realistic, policy-sensitive vehicle ownership behavior.
12. A Flexible Framework for High-Resolution Vehicle Emission Inventories in Canadian Cities: Methodological Design and Initial Insights
Student: Mina Jamshidi Kalajahi
Principal Investigator: Naomi Zimmerman
Abstract
Developing high-resolution, bottom-up vehicle emission inventories (EIs) in Canadian cities is complicated by large differences in local data availability. Many municipalities lack detailed traffic activity, fleet composition, or driving pattern information, limiting their ability to produce inventories that support air quality management and transportation planning. This study presents the methodological details of a flexible framework that integrates an agent-based activity-based model (ABM) with the MOVES emissions model to generate EIs with high spatial and temporal resolution in both data-rich and data-limited contexts. Metro Vancouver and the Okanagan Region, two contrasting application areas, have been chosen for this purpose. Building on this approach, the framework leverages detailed agent-based model outputs while remaining computationally efficient for large urban areas, and incorporates locally collected driving cycles and fleet characteristics to reflect region-specific driving behaviour. The resulting inventories reveal how emissions vary across fuel types, road classes, and vehicle processes, as well as their spatial and temporal distributions across each study area, highlighting the critical role of local data in accurately capturing urban emission patterns.
13. Beyond Tailpipe Accounting: Quantifying Regional Light-Duty Vehicle GHG Emissions from a Life-Cycle Perspective
Principal Investigator: Dr. Kasun Hewage
Student: Nipun Kumarage
Abstract
Light-duty vehicles (LDVs) generally account for a substantial share of regional greenhouse gas (GHG) emissions due to relatively high vehicle ownership rates across Canada. Traditional emission accounting methods for LDVs mainly focus on tailpipe emissions. However, as the adoption of zero-emission vehicles increases, tailpipe emissions decrease, and emissions shift to other stages of the vehicle life cycle, such as manufacturing, battery production, upstream fuel processing (well-to-pump), and end-of-life disposal. This shift emphasizes the need for a regional life cycle emissions modelling framework to quantify and interpret these changes accurately. To address this need, the poster presents a method for estimating regional LDV-related GHG emissions by combining life cycle assessment with travel-demand projections derived from agent-based vehicle-ownership models. Furthermore, the approach is demonstrated with a case study of the Metro Vancouver area, offering insights into how future shifts in vehicle technology and ownership patterns could influence regional transportation emissions from a life cycle perspective.
14. The Geoportal Emissions Storytelling – Interactive Maps for Transportation Understanding in the North Okanagan and Metro Vancouver
Student: Leandro Meneguelli Biondo / Stuart Mcgorman
Principal Investigator: Jon Corbett
Abstract
This paper explores “The Geoportal Emissions Storytelling” as a framework to translate complex transportation data into accessible public knowledge. Using agent-based model outputs for Metro Vancouver and the North Okanagan, the Geoportal serves as an interactive hub for disseminating insights on vehicular emissions and travel behaviour. We analyze five geovisualization models—including 3D extruded road networks and hexagonal activity grids—to evaluate how spatial storytelling enhances user understanding of transportation impacts. Leveraging a technical foundation of PostgreSQL, PostGIS, and H3 hierarchical aggregation, the tool processes data for millions of simulated agents to ensure high-performance browser interactivity. Findings suggest that personalized features, such as origin-destination of carbon footprint assessments, allow users to ground abstract data in their daily routines. By integrating intuitive 3D maps with coordinated charts, the Geoportal bridges the gap between scientific modelling and public participation in the co-development of regional climate mitigation strategies
1. AI-Driven Activity-Based Model to Simulate Activities in Physical and Virtual Spaces
Student: Mostaq Ahmed
Principal Investigator: Dr. Mahmudur Fatmi
Abstract
Activity-based travel demand models depend on realistic daily schedules, yet many existing systems generate activity participation and timing in separate steps and under-represent in-home and virtual behaviour. This study proposes an AI-driven activity-based model that simulates a person’s activity sequence across physical and virtual spaces and embeds it within an agent-based microsimulation. The activity scheduler, ASTRA, combines a Transformer encoder to capture long-range temporal dependencies with an LSTM decoder to enforce sequential coherence, producing conflict-free 24-hour schedules from socio-demographic and time-of-day inputs. It represents the day in 15-minute intervals and aggregates labels into activity episodes. The framework is implemented for Metro Vancouver using a census-consistent synthetic population and British Columbia Activity Time Use Survey diaries to train the scheduler. Schedules feed destination and mode choice components, and trips are executed in MATSim for network loading and policy testing. A telecommuting scenario illustrates how behavioural shifts propagate through downstream travel patterns.
2. Deploying an Activity-Based Simulator (ASIM) to Predict Travel Demand up to 2050 in the Okanagan
Student: Bijoy Saha, Ph.D. Candidate
Principal Investigator: Mahmudur Rahman Fatmi, Associate Professor
Abstract
Increased exposure to ICT has changed how people travel, introducing significant challenges for developing and deploying travel demand models (TDMs) to evaluate future policies. Predicting traffic with TDMs refers to the temporal transferability of the model. This study develops and estimates a temporal transferability methodology and applies it within an activity-based travel demand and network simulation framework. Specifically, statistical models for activity participation and the number of activity episodes are estimated using travel survey data from 2013, 2018, and 2023. The models estimate scale parameters that capture changes in behavior over time, such as which activities individuals participate in and how frequently they engage in them. Results indicate that travel behavior remained stable from 2013 to 2018 but shifted significantly from 2018 to 2023. Specifically, individuals moved from multiple activity episodes toward single episodes. The models are deployed in the Activity-Based Simulator (ASIM) to predict traffic up to 2050.
3. Building Faster and Accurate Agent-Based Travel Demand Models: Why Input Resolution Matters
Student: Madhawa Premasiri, Ph.D. Student
Principal Investigator: Mahmudur Rahman Fatmi, Associate Professor
Abstract
Large-scale agent-based network simulations provide detailed insights into network performance but are often constrained by long runtimes and high computational cost. While most efforts to address this problem focus on faster hardware or improved algorithms, less attention has been paid to how network and spatial input resolution influence simulation efficiency. This study shows that carefully selecting road network resolution and the spatial aggregation of demand locations can substantially improve the performance of agent-based network simulations without compromising accuracy. Using ASIM, an activity-based agent-based model for Metro Vancouver with 2.7 million agents, we evaluate over 130 combinations of network detail and spatial aggregation. Results show that moderate network simplification yields the largest runtime reductions, whereas spatial aggregation alone offers limited gains. A mid-resolution network (without access roads) combined with neighbourhood-scale aggregation (300-400m) reduces runtimes by approximately 22.5-25.5% while keeping key system and link-level outputs within ±5% of the highest-resolution reference. These findings offer practical guidance for building faster, more scalable agent-based network simulations.
4. Adding Bike Simulation Capacity to Travel Demand Model and Testing for Policy Interventions
Student: Bijoy Saha, Ph.D. Candidate
Principal Investigator: Mahmudur Rahman Fatmi, Associate Professor
Abstract
Existing activity-based models (ABMs) have limited to no capacity to explicitly accommodate bike users’ behavior. This study extends an existing ABM to simulate bike users’ travel. Specifically, a bike destination choice sub-module is integrated within the ABM. This sub-module simulates bike users’ destination choices, accounting for the spatial, temporal, and physical strength constraints they experience while biking. Finally, bike traffic is simulated on the road network. The model is developed, calibrated, and validated for Okanagan. The validated model is used to evaluate three scenarios: (1) reduced car ownership, (2) increased bike ownership, and (3) both occurring simultaneously. Results show that with increased bike ownership, the share of bike trips increases significantly; however, this is less effective in reducing car use. The highest reduction in car share occurs when both car and bike ownership are regulated. This also leads to higher bike network utilization and greater reduction in GHG emissions.
7. Weeklong Travel Pattern in British Columbia: Evidence from the BC ATUS GPS Survey
Student: Imrul Kayes Shafie
Principal Investigator: Dr. Mahmudur Fatmi
Abstract
This poster summarizes evidence from the first wave of the weeklong GPS smartphone survey collected as part of the British Columbia Activity Time Use Survey (BC ATUS) in 2023. Using weeklong GPS data from Metro Vancouver and the Okanagan region, we quantify how mobility changes across the week; from early-week routines to midweek adjustments and the transition into weekend travel. We will share differences in trip frequency, timing, and purpose to reveal day-to-day variation that single-day data often miss. The results highlight how travel behavior in British Columbia is shifting from predictable daily routines toward more flexible weekly patterns. Growth in telework, online services, and hybrid schedules suggests that the traditional “typical weekday” may no longer exist, yet many planning models and datasets still rely on single-day surveys. Findings provide a clear picture of how travel is distributed across the week and where weekday and weekend patterns differ.
9. How Changes in Electric Vehicle Incentives Changes Vehicle Purchase Decisions in British Columbia, Canada?
Student: Imrul Kayes Shafie
Principal Investigator: Dr. Mahmudur Fatmi
Abstract
This poster describes how electric vehicle (EV) purchase preferences in British Columbia (BC) change under different incentive policies. Federal and provincial subsidies have significantly influenced EV uptake in BC; however, the recent pause of both incentive programs raises important questions about consumer preferences and BC’s achieving emission reduction target. Using stated-preference data from 921 BC residents, we compare household’s responses to following availability scenarios: (1) provincial incentives only, (2) combined federal and provincial incentives, and (3) no incentives. We examine shifts across vehicle types (plug-in electric, hybrid, and gasoline) and purchase condition (new or, old). Findings show that incentives strongly support new EV adoption, with the largest benefits for lower-income households. When incentives are removed, EV preference declines sharply and many consumers shift toward used gasoline vehicles. The response to incentive withdrawal is larger than the gains observed when incentives are added, suggesting a risk of losing market momentum without continued policy support.
10. From Price to Perception: Unpacking Why Some British Columbians Still Say No to Zero-Emission Vehicles (ZEVs)
Student: Shoumic Shahid Chowdhury, Md Shahadat Hossain
Principal Investigator: Dr. Mahmudur Fatmi
Abstract
Canada’s transportation decarbonization strategy relies on mass adoption of Zero-Emission Vehicles (ZEVs), targeting 100% new ZEV sales by 2035. Most of the current investigations focus on motivators for EV purchase, while far less attention is paid to understanding what deters individuals from it. Understanding this resistance is crucial for designing equitable and effective policy interventions. Using data from the British Columbia (BC) Electric Vehicle Market Research Survey, this study investigates why individuals resist adoption, grouping barriers into cost, charging and range limitations, model availability, environmental perceptions, and broader contextual constraints. A statistical model (multinomial logit) has been used to explore the effects of sociodemographic, household, residential location, and attitudinal profiles. The MNL model has been extended to explore the behavioral heterogeneity across groups. The findings of this study unpack who resists ZEV adoption and why and informs socially attuned deployment strategies to accelerate British Columbia’s transition.
11. Multi-objective and multi-period optimization of housing starts for sustainable urban development
Student: Oshadhi Weerasinghe
Principal Investigator: Dr. Kasun Hewage
Abstract
This research develops a multi-objective housing development model that overcomes limitations in previous work by considering multi-periods and life-cycle thinking. The model optimizes housing location, type, and development timing. A genetic algorithm-based method is employed in model development to balance trade-offs among developer profit, household user costs, and greenhouse gas emissions, considering various objective weighting scenarios. In addition, the uncertainty arising from the stochastic nature of population generation was evaluated to assess the robustness of the results. The result indicated that the proportion of single-family housing in the total new housing stock is projected to range from 26% to 33%, while the percentage of apartment units is expected to increase to 64% to 71% at the 95% confidence level, reflecting the trend toward high-density development. Moreover, the findings identify the neighborhoods with higher development potential by the end of the planning period. Beyond forecasting housing developments, the model serves as a testing platform for different zoning regulation scenarios, thereby determining their impact on objective functions and development potentials.
