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Matt’s Schedule. Headway Variation. Estimated Load vs. Passenger Movement. Weather. Interesting to note the below average passenger boardings in the summer and x-mas week Need to calculate the average by quarter or by month, since the summer is a distinct season.

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Matt’s Schedule

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Matt s schedule l.jpg

Matt’s Schedule


Headway variation l.jpg

Headway Variation


Estimated load vs passenger movement l.jpg

Estimated Load vs. Passenger Movement


Weather l.jpg

Weather


Slide8 l.jpg

  • Interesting to note the below average passenger boardings in the summer and x-mas week

  • Need to calculate the average by quarter or by month, since the summer is a distinct season


Slide9 l.jpg

  • I tried to normalize the data, creating a summer and non-summer period to account for the lower ridership over the summer…not sure if the dates I picked for the normalization are the best. In this chart, summer is June, July or August. I could probably be more precise to match the school year.


Boardings vs ave temp am average direction 1 l.jpg

Boardings vs Ave TempAM Average, Direction = 1


Dwell vs ave temp am average direction 1 l.jpg

Dwell vs. Ave Temp AM Average, Direction = 1


Trip time vs ave temp am average direction 1 l.jpg

Trip Time vs. Ave Temp AM Average, Direction = 1


Boardings vs precipitation am average direction 1 l.jpg

Boardings vs. Precipitation AM Average, Direction = 1


Boardings vs precipitation am average direction 114 l.jpg

Boardings vs. Precipitation AM Average, Direction = 1


Boardings vs ave temp am average direction 115 l.jpg

Boardings vs Ave TempAM Average, Direction = 1


Trip time vs precipitation am average direction 1 l.jpg

Trip Time vs. Precipitation AM Average, Direction = 1


Trip time vs ave temp am average direction 117 l.jpg

Trip Time vs. Ave Temp AM Average, Direction = 1


Dwell vs precipitation am average direction 1 l.jpg

Dwell vs. Precipitation AM Average, Direction = 1


Dwell vs ave temp am average direction 119 l.jpg

Dwell vs. Ave Temp AM Average, Direction = 1


Boardings vs precipitation deviation from mean l.jpg

Boardings vs. PrecipitationDeviation from Mean


Boardings vs ave temp deviation from mean l.jpg

Boardings vs. Ave TempDeviation from Mean


Trip time vs precipitation deviation from mean l.jpg

Trip Time vs. PrecipitationDeviation from Mean


Trip time vs ave temp deviation from mean l.jpg

Trip Time vs. Ave TempDeviation from Mean


Dwell time scatter plots l.jpg

Dwell Time Scatter Plots


Dwell 3 d l.jpg

Dwell 3-D


Dwell 3 d axes reversed l.jpg

Dwell 3-D Axes Reversed


Dwell regression dwell 1 min boardings only l.jpg

Dwell Regression Dwell <= 1 min, Boardings Only

X1 = Boardings

X2 = Alightings

X3 = Late (> 3 minutes)

X4 = Timepoint (dummy)

X5 = Precipitation

X6 = Ave Temp


Dwell regression dwell 1 min boardings only28 l.jpg

Dwell Regression Dwell <= 1 min, Boardings Only

X1 = Boardings

X2 = Alightings

X3 = Late (> 3 minutes)

X4 = Timepoint (dummy)

X5 = Precipitation

X6 = Ave Temp

X7 = Boardings2

X8 = Alightings2


Dwell regression dwell 1 min alightings only l.jpg

Dwell RegressionDwell <= 1 min, Alightings Only

X1 = Boardings

X2 = Alightings

X3 = Late (> 3 minutes)

X4 = Timepoint (dummy)

X5 = Precipitation

X6 = Ave Temp


Dwell regression dwell 1 min alightings only30 l.jpg

Dwell RegressionDwell <= 1 min, Alightings Only

X1 = Boardings

X2 = Alightings

X3 = Late (> 3 minutes)

X4 = Timepoint (dummy)

X5 = Precipitation

X6 = Ave Temp

X7 = Boardings2

X8 = Alightings2


Dwell regression dwell 1 min both boardings alightings l.jpg

Dwell RegressionDwell <= 1 min, Both Boardings & Alightings

X1 = Boardings

X2 = Alightings

X3 = Late (> 3 minutes)

X4 = Timepoint (dummy)

X5 = Precipitation

X6 = Ave Temp


Dwell regression dwell 1 min both boardings alightings32 l.jpg

Dwell RegressionDwell <= 1 min, Both Boardings & Alightings

X1 = Boardings

X2 = Alightings

X3 = Late (> 3 minutes)

X4 = Timepoint (dummy)

X5 = Precipitation

X6 = Ave Temp

X7 = Boardings2

X8 = Alightings2


Trip time model modified ahmed version l.jpg

Trip Time ModelModified Ahmed Version

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Total Boardings

  • X8 = Boardings Squared

  • X9 = Total Alightings

  • X10 = Alightings Squared

  • X11 = Lift

  • X12 = Average Passenger Load

  • X13 = Total Dwell Time

  • X14 = Precipitation

  • X15 = Average Temperature

  • X16 = Summer (dummy variable if month = June thru August)

  • X17 = Friday (dummy)


Trip time model modified ahmed version34 l.jpg

Trip Time ModelModified Ahmed Version

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Total Boardings

  • X8 = Boardings Squared

  • X9 = Total Alightings

  • X10 = Alightings Squared

  • X11 = Lift

  • X12 = Average Passenger Load

  • X13 = Total Dwell Time

  • X14 = Precipitation

  • X15 = Average Temperature

  • X16 = Summer (dummy variable if month = June thru August)

  • X17 = Friday (dummy)


Trip time model modified ahmed version35 l.jpg

Trip Time ModelModified Ahmed Version

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Total Boardings

  • X8 = Boardings Squared

  • X9 = Total Alightings

  • X10 = Alightings Squared

  • X11 = Lift

  • X12 = Average Passenger Load

  • X13 = Total Dwell Time

  • X14 = Precipitation

  • X15 = Average Temperature

  • X16 = Summer (dummy variable if month = June thru August)

  • X17 = Friday (dummy)


Trip time model modified ahmed version outliers removed tripmiles 0 tripmiles 25 total dwell 100 60 l.jpg

Trip Time ModelModified Ahmed Version – outliers removed tripmiles > 0 & tripmiles < 25 & total_dwell < 100*60

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Total Boardings

  • X8 = Boardings Squared

  • X9 = Total Alightings

  • X10 = Alightings Squared

  • X11 = Lift

  • X12 = Average Passenger Load

  • X13 = Total Dwell Time

  • X14 = Precipitation

  • X15 = Average Temperature

  • X16 = Summer (dummy variable if month = June thru August)

  • X17 = Friday (dummy)


Trip time model modified ahmed version outliers removed tripmiles 0 tripmiles 25 total dwell 100 6037 l.jpg

Trip Time ModelModified Ahmed Version – outliers removed tripmiles > 0 & tripmiles < 25 & total_dwell < 100*60

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Total Boardings

  • X8 = Boardings Squared

  • X9 = Total Alightings

  • X10 = Alightings Squared

  • X11 = Lift

  • X12 = Average Passenger Load

  • X13 = Total Dwell Time

  • X14 = Precipitation

  • X15 = Average Temperature

  • X16 = Summer (dummy variable if month = June thru August)


Trip time model modified ahmed version outliers removed tripmiles 0 tripmiles 25 total dwell 100 6038 l.jpg

Trip Time ModelModified Ahmed Version – outliers removed tripmiles > 0 & tripmiles < 25 & total_dwell < 100*60

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Total Boardings

  • X8 = Boardings Squared

  • X9 = Total Alightings

  • X10 = Alightings Squared

  • X11 = Lift

  • X12 = Average Passenger Load

  • X13 = Total Dwell Time

  • X14 = Precipitation

  • X15 = Average Temperature

  • X16 = Summer (dummy variable if month = June thru August)


Trip time model modified ahmed version outliers removed tripmiles 0 tripmiles 25 total dwell 100 6039 l.jpg

Trip Time ModelModified Ahmed Version – outliers removed tripmiles > 0 & tripmiles < 25 & total_dwell < 100*60

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Total Boardings

  • X8 = Boardings Squared

  • X9 = Total Alightings

  • X10 = Alightings Squared

  • X11 = Lift

  • X12 = Average Passenger Load

  • X13 = Total Dwell Time

  • X14 = Precipitation

  • X15 = Average Temperature

  • X16 = Summer (dummy variable if month = June thru August)

  • X17 = (Boardings + Alightings)2


Histogram of total boardings blue and total alightings red l.jpg

Histogram of total boardings(blue) and total alightings(red)


Boxplot of total boardings 1 and total alightings 2 l.jpg

Boxplot of total boardings(1) and total alightings(2)


Slide42 l.jpg

Trip Time ModelModified Ahmed Version – outliers removed tripmiles > 0 & tripmiles < 25 & total_dwell < 100*60 & total_ons > 0 & total_offs > 0

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Total Boardings

  • X8 = Boardings Squared

  • X9 = Total Alightings

  • X10 = Alightings Squared

  • X11 = Lift

  • X12 = Average Passenger Load

  • X13 = Total Dwell Time

  • X14 = Precipitation

  • X15 = Average Temperature

  • X16 = Summer (dummy variable if month = June thru August)

  • X17 = (Boardings + Alightings)2


Slide43 l.jpg

Trip Time ModelModified Ahmed Version – outliers removed tripmiles > 0 & tripmiles < 25 & total_dwell < 100*60 & total_dwell > 0

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Boardings + Alightings

  • X8 = Lift

  • X9 = Average Passenger Load

  • X10 = Total Dwell Time

  • X11 = Precipitation

  • X12 = Average Temperature

  • X13 = Summer (dummy variable if month = June thru August)

  • X14 = (Boardings + Alightings)2


Slide44 l.jpg

Trip Time ModelModified Ahmed Version – outliers removed tripmiles > 0 & tripmiles < 25 & total_dwell < 100*60 & total_dwell > 0

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Total Boardings

  • X8 = Boardings Squared

  • X9 = Total Alightings

  • X10 = Alightings Squared

  • X11 = Lift

  • X12 = Average Passenger Load

  • X13 = Total Dwell Time

  • X14 = Precipitation

  • X15 = Average Temperature

  • X16 = Summer (dummy variable if month = June thru August)

  • X17 = (Boardings + Alightings)2


Slide45 l.jpg

Trip Time ModelModified Ahmed Version – outliers removed tripmiles > 0 & tripmiles < 25 & total_dwell < 100*60 & total_dwell > 0

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Boardings + Alightings

  • X8 = Lift

  • X9 = Average Passenger Load

  • X10 = Total Dwell Time

  • X11 = Precipitation

  • X12 = Average Temperature

  • X13 = Summer (dummy variable if month = June thru August)

  • X14 = (Boardings + Alightings)2

Ahmed says use this version


Slide46 l.jpg

Trip Time ModelModified Ahmed Version – outliers removed tripmiles > 0 & tripmiles < 25 & total_dwell < 100*60 & total_dwell > 0

  • X1 = Distance (in miles)

  • X2 = Scheduled Number of Stops

  • X3 = Direction or Southbound

  • X4 = AM Peak

  • X5 = PM Peak

  • X6 = Actual Number of Stops

  • X7 = Boardings + Alightings

  • X8 = Lift

  • X9 = Average Passenger Load

  • X10 = Total Dwell Time

  • X11 = Precipitation

  • X12 = Average Temperature

  • X13 = Summer (dummy variable if month = June thru August)

  • X14 = (Boardings + Alightings)2


Regression l.jpg

Regression

  • Dwell Regression Model

    I have run several of these..here is an example

    Dwell = 6.09 + 3.54*No. Boardings + 1.97*No. Alightings

    R squared = .291

    There are interesting differences in the dwells for timepoint stop locations versus regular stops.

  • Travel Time Regression Model

    I am still experimenting with this. The thought was that we can explain as much variation as possible with the bus data…what we can’t explain would be road conditions/congestion. It would be interesting to compare routes (low and high congestion routes) to test this assumption. I have achieved an R squared of about .19 Most of the variation is explained by passenger movement and dwell.


Notes l.jpg

Notes

  • Headway variance

    • Subplots of headway variance and estimated load

    • Subplots of headway variance and boardings/alightings

    • Table of summary statistics to re-plot in excel

      • See if what I did worked…

      • Also experiment w/different ways of displaying the timepoint names (i.e. a legend)

  • Dwell regression model

    • With stop locations

    • W/O stop locations

  • Dwell Circle

    • Running time: arrive time(x) – leave time(x-1)

    • Layover time: hmmm…

    • Dwell time: dwell, less layover (?)

    • Stop circle time: leave_time - arrive_time, less dwell (?)

  • Travel time regression model

  • Plottools function in Matlab, which you call from the command line, is very handy for manipulating figure formats…


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