Delays and Performance:

King County METRORapidRide C & D Lines

University of Washington

URBDP 422 Geospatial Analysis, Winter 2014

Debmalya Sinha, Austin Bell, Riley Smith, Andrew Brick

Overview

• Primary task: identify delays• Where• When• Magnitude

• Secondary tasks:• Identify priorities for remediation• Recommend delay reduction strategies

• Future research:• Relationship between delays and socioeconomic status

Data

• Onboard System (OBS) for October 2013 (245,826 entries)• Records real-time information of bus activity• No weekend data was included in data file

• General Transit Feed Specification (GTFS)• Provides scheduled arrival times for all routes

• Shapefiles• C & D Line stop locations (point)• C & D Line routes, manually segmented (line)

• Field Data• Physical attributes of stops and route segments

Methods

• Raw OBS and GTFS data imported into R• All times converted to seconds after midnight where

required• Trips categorized by start time:• 0000 – 0600: pre-peak• 0600 – 0900: am-peak• 0900 – 1500: midday• 1500 – 1800: pm-peak• 1800 – 0000: post-peak

Data Preparation

Methods

• Delays• scheduled arrival time – actual arrival time (in seconds after

midnight)

• Stop performance• “Marginal” doors open time: number of seconds it takes for

each passenger to board or alight (over the amount of time it takes only one passenger to do so)• Averaged for each stop

• Segment performance• Seconds per foot: number of seconds between sequential

stops divided by the segment length, converted to speed• Averaged for each segment

Computations

Methods

• Raw OBS data imported into GIS• X,Y data extracted from GPS entries (generated point

shapefile)• Data screen: retained only those stops which did not

occur at bus stops (retained only entries where STOP_ID = 0)• Computed kernel density with DWELL_SEC as value field• Reclassified output raster from 1 to 9, with 1

representing shortest stops / lowest number of stops

Unplanned Stops

• Worst Delays• Southbound in West Seattle• Southbound and

Northbound Downtown

ResultsDelays

Results

• Marginal on/off time consistently higher in D than C• Correlated with

passengers embarking and alighting• Off board payment

generally unused

Relative Stop Performance

Results

• Worst performance:• Northern and

Southern endpoints of Rapid Ride• Downtown

segments• Alaska Junction

Relative Segment Performance

Results

• Averaged data reveals differences by time of dayand by ridership

Stops & Segments

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 480

1

2

3

4

5

6

7

8

0

2000

4000

6000

8000

10000

12000

14000

Number of “Doors Open” Seconds per Passenger by Ridership

Per-passenger Doors Open Time Observations (Secondary Axis)

Number of Passengers Boarding and Alighting

Seco

nds

Obs

erva

tions

Conclusions and Questions

• No correlation between physical attributes of stops and performance• Ridership explains only 26% of doors open time• More complex phenomena (traffic flows, signals)

account for most variation

• Why does C Southbound accumulate large delays in West Seattle?

Questions

University of Washington

URBDP 422 Geospatial Analysis, Winter 2014

Debmalya Sinha, Austin Bell, Riley Smith, Andrew Brick