---
title: Optimizing Bus Schedules to Best Serve Changing Commuting Patterns
description: SamTrans used Streetlight’s Origin-Destination Metrics to optimize bus schedules by shedding light on shifting travel patterns, improving ridership by 30%.
---

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COMMUTE PLANNING CASE STUDY

# Optimizing Bus Schedules to Best Serve Changing Commute Patterns

##### Bay Area public transit agency SamTrans needed to respond to shifts in commuting patterns as a result of COVID. They sought to find out why ridership on a previously popular express bus route to San Francisco had dropped disproportionately versus other modes. Streetlight’s Origin-Destination Metrics helped SamTrans:

- Understand commuter behavior, including shorter stays downtown
- Analyze vehicle demand to see how the pandemic affected commutes overall
- Boost ridership by 30% after making adjustments to the schedule

 

##### Learn how, like SamTrans, you can apply StreetLight Metrics to any transit or transportation demand management project seeking to reorient services and programming to fit the new commute landscape.

### Download the Case Study

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![Case Study Optimizing Bus Schedules](https://learn.streetlightdata.com/hubfs/Case%20Studies/Optimizing%20Bus%20Schedules%20to%20Best%20Serve%20Changing%20Commuting%20Patterns/Case%20Study%20Optimizing%20Bus%20Schedules.png)

##### “We can now keep track of travel behavior trends in a way that hasn’t been possible before. Accessing accurate and timely trip origins and destinations allows us to quickly plan better service”

![](https://learn.streetlightdata.com/hubfs/Case%20Studies/Optimizing%20Bus%20Schedules%20to%20Best%20Serve%20Changing%20Commuting%20Patterns/bus%20icon.png)

**Jonathan Steketee**

 Manager of Operations Planning at SamTrans

## Your biggest transportation challenges require better analytics

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Origin-Destination for multiple modes

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Granular, on-demand Metrics segmented by time of day and day of week

![metrics-3](https://learn.streetlightdata.com/hubfs/Icons/metrics-3.svg)

Layer on demographics, trip attributes, and more

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### Optimizing Bus Schedules to Best Serve Changing Commute Patterns

[Download the Case Study](https://learn.streetlightdata.com/bus-schedule-optimization-bay-area#form-section)