delays and performance: king county metro rapidride c & d lines

Delays and Performance:King County METRORapidRide C & D Lines

University of WashingtonURBDP 422 Geospatial Analysis, Winter 2014Debmalya 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 day

and 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 WashingtonURBDP 422 Geospatial Analysis, Winter 2014Debmalya Sinha, Austin Bell, Riley Smith, Andrew Brick