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Matt’s Schedule

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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  1. Matt’s Schedule

  2. Headway Variation

  3. Estimated Load vs. Passenger Movement

  4. Weather

  5. 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

  6. 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.

  7. Boardings vs Ave TempAM Average, Direction = 1

  8. Dwell vs. Ave Temp AM Average, Direction = 1

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

  10. Boardings vs. Precipitation AM Average, Direction = 1

  11. Boardings vs. Precipitation AM Average, Direction = 1

  12. Boardings vs Ave TempAM Average, Direction = 1

  13. Trip Time vs. Precipitation AM Average, Direction = 1

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

  15. Dwell vs. Precipitation AM Average, Direction = 1

  16. Dwell vs. Ave Temp AM Average, Direction = 1

  17. Boardings vs. PrecipitationDeviation from Mean

  18. Boardings vs. Ave TempDeviation from Mean

  19. Trip Time vs. PrecipitationDeviation from Mean

  20. Trip Time vs. Ave TempDeviation from Mean

  21. Dwell Time Scatter Plots

  22. Dwell 3-D

  23. Dwell 3-D Axes Reversed

  24. Dwell Regression Dwell <= 1 min, Boardings Only X1 = Boardings X2 = Alightings X3 = Late (> 3 minutes) X4 = Timepoint (dummy) X5 = Precipitation X6 = Ave Temp

  25. 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

  26. Dwell RegressionDwell <= 1 min, Alightings Only X1 = Boardings X2 = Alightings X3 = Late (> 3 minutes) X4 = Timepoint (dummy) X5 = Precipitation X6 = Ave Temp

  27. 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

  28. Dwell RegressionDwell <= 1 min, Both Boardings & Alightings X1 = Boardings X2 = Alightings X3 = Late (> 3 minutes) X4 = Timepoint (dummy) X5 = Precipitation X6 = Ave Temp

  29. 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

  30. 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)

  31. 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)

  32. 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)

  33. 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)

  34. 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)

  35. 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)

  36. 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

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

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

  39. 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

  40. 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

  41. 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

  42. 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

  43. 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

  44. 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.

  45. 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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