A Data Framework to Correct Underperforming Transit Lines

Client: Charlotte Area Transit System

In 2021, the Charlotte Area Transit System (CATS) initiated 'The Bus Priority Study' as part of the city's broader Strategic Mobility Plan, aiming to enhance the speed, reliability, and convenience of bus trips for passengers. CATS seeks to gain insights into recent developments in local bus transit and the potential financial and equity implications of hypothetical changes to the network. To achieve this, CATS identified three primary objectives:

1. Understanding recent dynamics in bus ridership.
2. Evaluating current bus accessibility, taking into account ridership patterns and demographic distributions.
3. Assessing network efficiencies and potential improvements. 

To address these objectives, our project helps CATS planners in:

1. Identification of underperforming bus stops.
2. Analysis of demographic, spatial, and economic factors in the Charlotte area that may impact bus ridership and performance.
3. Optimization of the current bus network, including stops and routes, to enhance transit services.

The goal of this project was to develop a proof-of-concept analytical and informational system to identify underperforming stops or routes within Charlotte’s bus transit network. These insights were then presented visually so they can be leveraged by CATS' transportation planners to make data-driven planning decisions for the city of Charlotte.

Purpose & Use Case

The team assists CATS transportation planners in enhancing bus line efficiency by analyzing historical ridership trends at individual bus stops to identify and forecast underperforming stops and routes. The team studied the dynamics of the bus system in Charlotte to develop a model that predicts demand and performance for every bus stop that is currently in use. Using Automated Passenger Counter (APC) data, capturing boarding and alighting counts, students modeled monthly bus demand by line and stop.

Subsequently, the team proposed alternative network options through a web-based dashboard that presents predictions within the context of demographic and spatial factors influencing bus transit.

Learn More

Website
Presentation