Understanding, Modeling and Presenting the Impact of Various Endogenous & Exogenous Factors on Mobility in New York City
Overview
The multi-modal nature of transportation in NYC presents choices to users such as fixed-route public transit systems (e.g., subway and bus), on-demand taxi, and bike-sharing (e.g., Citibike). However, the usage of each of these modes depends on several endogenous factors such as socio-economic and demographic characteristics, availability, affordability and convenience of use. Furthermore, the usage also depends on extraneous conditions such as roadway incidents, construction activities, transit disruptions and delays, weather, special events, etc. All the extraneous factors that affect each mode of transport have an impact that is Spatio-temporal in nature within the mode. An incident on a transit line can affect the next train but may also delay other lines depending on the type of incident and where it has occurred.
Furthermore, the influence of events can spillover to other modes that can result in crossing over of demands due to reduced supply in a particular mode. E.g., inclement weather can result in a reduction in bike ridership and see an increase in transit ridership. There were several studies performing visualization of Spatio-temporal movement data. However, visualizing NYC subway has been performed, to the team’s knowledge, by only two studies (Palomo et al. (2015) and Sukhov et al. (2015)). These studies do not identify commonalities and correlations between delays and how they can spread to different lines. This pattern analysis is important and helps in estimating delays for similar future events. Similarly, Citibike data has been used to visualize (Keler et al. (2020)) as well as forecast demands (Yang et al. (2016)). Pattern analysis on correlation with other events and modes will provide critical inputs for detecting and locating abnormal patterns, which is the objective of this project.
Research Objectives & Deliverables
Various tasks involved in the successful completion of the proposed project will include the following:
- Project Management
- Meetings: The PI shall hold a Mid-Point Meeting to review progress to date, discuss difficulties encountered and proposed solutions for overcoming them, and to outline then-current plans for completing the scope of work; and a Wrap-Up Meeting at the end of the project.
- Progress Reports: The PI shall provide CSMART written progress reports quarterly. These reports shall describe any difficulties encountered and the cost of the work performed during the reporting period.
- Final Report: The PI shall provide a final report detailing all project findings. The PI shall make this report available via C2SMART Web site.
- Literature Review: This task entails a review of literature of past studies that study multimodal performance measures in time and space, factors influencing the performance of transportation modes such as fixed-route transit and bikes, and modal inter-dependencies.
- Collect & process transit data
- This task is to collect and analyze the real-time transit data to analyze baseline performance measures, define and detect abnormal conditions.
- Extraneous and systemic factor data collection
- Data for the key extraneous factors identified in task 2 from literature and others from research team’s understanding will be collected as a part of this task. These data may include weather observations, special events, bike lane incidents or any disruption due to maintenance, signal failures on subways.Combined analysis of abnormal metrics for transit and bikes
- Dashboard construction: A dashboard that will represent and summarize statistics on various abnormalities analyzed in task 6 will be prepared as a part of this task. We plan to segment the metrics as before and after COVID to distinguish any shifts that have happened due to the pandemic. The visualization will be based on the maps of NYC transit subway lines, stops, and Citibike stations. E.g., subway lines and stops within a line impacted by a certain kind of delay will be visualized. Specific trends in metrics will be included in the form of other charts that will be included in the dashboard.
- Final report preparation: The final report will present all the findings of all the tasks on data collection, processing, and analysis.
| Principal Investigator | Camille Kamga |
| Funding Source | C2SMART Center ($65,000) CCNY ($37,076) |
| Total Project Cost | $102,076 |
| USDOT Award # | 69A3551747124 |
| Implementation of Research Outcomes | The research results include a mobility analysis framework that will be able to gauge the impact caused by various kinds of the impact of extraneous and systemic factors on modes, across spatial and temporal scales. The ongoing disruption due to the COVID-19 pandemic has clearly shown that mobility impacts different populations differently. Furthermore, some of the impacts to mobility before the pandemic may not apply in the future. Thus, the city-wide mobility framework will help NYC agencies and mobility providers assess the impacts of various exogenous factors on mode usage and forecast supply. |
| Impacts/Benefits of Implementation | The proposed project will improve the understanding of the impact of exogenous factors across transportation modes in space and time and will illustrate potential correlations between modes. The developed city-wide mobility framework will help agencies and mobility providers to prepare, estimate the supply required and provide appropriate advisories. This framework can, thus, act as a platform that can adapt and help match transportation demand to supply. |