Based on initial literature review our group decided to analyze if inclement weather impacts New Jersey Transit train delays. Additionally, we would like to look at how inclement weather affects commuters with respect to their neighborhood demographics and if train delays disproportionately affect disadvantaged neighborhoods.
To achieve this, we will look at several data sets. First, we will look at GTFS transit feeds for the New Jersey Transit Northeast Corridor Line, specifically looking at the transit delays between station pairs along the line during the evening commute. The time frame we will be analyzing is March 2018 due to varied weather patterns in New Jersey during that month. The weather data sets will be sourced from the National Center for Environmental Information. Weather stations along the route will be used to gain an understanding of differences in precipitation and temperature and how they impact travel times and delays.
Lastly, we will use census data to compare travel time delays between high income and low-income neighborhoods. Some additional points we would like to consider during our analysis include census data for annual real estate property taxes, and race.
To analyze these data sets we will use the statistical computing open-source platform, R. Within R, we will use different packages to help aid our statistical modeling and data visualization. These packages include, tidycensus, tidytransit, tmap, ggplot, tidyverse, and dplyr. Since we are looking at more than two variables, we expect to estimate the relationship between transit delays, weather, and impacted commuters (based neighborhood demographics) by regression modeling and ANOVA statistical analysis. At the conclusion of this project, we hope to be able to determine if weather plays a key role in train delays and if lower income neighborhoods are adversely impacted. We will present our findings in an HTML format through RPUBS.
Elora Lee Raymond (2018) Race, uneven recovery and persistent negative equity in the southeastern United States, Journal of Urban Affairs, 40:6, 824-837, DOI: 10.1080/07352166.2017.1392828 (https:/www.tandfonline.com/doi/full/10.1080/07352166.2017.1392828)
Karner, Alex. (2018). Assessing public transit service equity using route-level accessibility measures and public data. Journal of Transport Geography. 67. 10.1016/j.jtrangeo.2018.01.005. (https:/www.sciencedirect.com/science/article/pii/S0966692317303794?casa_token=u5ystJxKU8sAAAAA:EW3L6ZODX0eq0yVXYl-FWcphYRzcbyD71KEVu9uRWL8PxaL79ebuNKS12KDB_tyfeRrtcbhWuQ)
GTFS: (https:/gtfs.org/schedule/)
NOAA: (https:/www.ncei.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:USC00286055/detail)