Data Challenge 2020

DOTS Campus Traffic Counts - Problem Overview

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Problem Overview

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    Problem Statement

         Over the summer in 2019, DOTS installed Numina sensors at 5 intersections on campus to count bikes, pedestrians, cars, buses, trucks, and identify path of travel.

         The goals outlined for us to explore were outlined as follows:

  • Summarize (visualize) the time trend for traffic by each mode. What is the temporal dynamic of traffic at each location?
  • Explain the dynamic you observe: What factors may affect the traffic on campus? We think it’s worth exploring the impact of weather conditions, class schedules, noticeable events on campus (e.g. Game Day), and other factors that may cause traffic to fluctuate.
  • After the initial explorations, you can choose either one of the following three topics to continue developing your story:
    1. > As part of the Campus Climate Plan, DOTS aims to reduce the number of single-occupancy vehicles. Using data analysis and visualization, come up with a few ideas to improve transportation planning and traffic management on campus
      > Build a traffic count predictive model using data science techniques and explain the usefulness of your model.
      > Use traffic and count data to measure the campus’ social, economic, and health benefits to walking, biking, and taking transit.