TRANSPORTATION SYSTEMS ANALYSIS IN MONTRÉAL-NORD

ALIREZA AZADI AHMAD ABADI 40013878MOHAMAD BOLBOL 27591071HOSSEIN KHODAVERDIPOUSARBANDI 40003814WONYEEL HWANGBO 27684886MARZIEH OSTADSHARIF MEMAR 40012648 INSTRUCTOR: PHD. TIM SPURR URBAN TRANSPORTATION PLANNING CIVI 6411 WINTER2016

OUTLINEIntroductionData CollectionData Analysis by Excel (Demand)o Regression Modelo OD Tableo Mode ShareData Analysis by QGIS (Supply)o Bus lineso Trip analysis in Morning peako Trip analysis in Afternoon peakConclusionReferences 2

http://www.venturaxllc.com/transportation/

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INTRODUCTION• 5.1% population of Montreal• 3% of Montreal area.• Demanding problems: - Low income - Difficulty in getting to spaces of inclusion by transit

Number Borough Population Area(Km

²)1 Ahuntsic-Cartierville 126,891.00 24.22 Anjou 41,928 13.7

3 Côte-des-Neiges–Notre-Dame-de-Grâce 165,031 21.4

4 Lachine 41,616 17.75 LaSalle 74,276 16.36 Le Plateau-Mont-Royal 100,390 8.17 Le Sud-Ouest 71,546 15.78 L'Île-Bizard–Sainte-Geneviève 18,097 23.6

9 Mercier–Hochelaga-Maisonneuve 131,483 25.4

10 Montréal-Nord 83,868 11.111 Outremont 23,566 3.912 Pierrefonds-Roxboro 68,410 27.1

13 Rivière-des-Prairies–Pointe-aux-Trembles 106,437 42.3

14 Rosemont–La Petite-Patrie 134,038 15.915 Saint-Laurent 93,842 42.816 Saint-Léonard 75,707 13.517 Verdun 66,158 9.718 Ville-Marie 84,013 16.5

19 Villeray–Saint-Michel–Parc-Extension 142,222 16.5

  Total 1,649,519 365.4

https://en.wikipedia.org/wiki/Montreal

DATA COLLECTIONMontréal-Nord Values

The population  83,868Number of households in the survey area  34985Number of census tract in the area 18Average income in the study area  43846People belong to the responding households  3368Number of households responding to the survey  1475The sampling rate of this survey  0.42Number of trips made by the surveyed households  7659The average household size  2.4The average number of vehicles per household  0.97Total trips are made during the morning peak period  45680Total trips are made during the Afternoon peak period 56977 

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DATA ANALYSIS BY EXCEL

Regression StatisticsMultiple R 0.974242708R Square 0.949148854

Adjusted R Square 0.948674718

Standard Error 323.6603926Observations 434

  CoefficientsStandard

Error t Stat P-value

Intercept 115.258346115.8425115

87.27525717

41.65744E

-12 Fulltime worker 4.198475755

0.262780007

15.97715062

2.01268E-45

Part time worker

-5.163515046 1.20838664

-4.27306532

22.37711E

-05Sum of

Students 0.9546422190.34026209

92.80560844

80.005250

642

Sum of Retired 1.0715437140.25413668

54.21640706

23.02927E

-05

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• Four independent variables considered to analyze a regression model.

• The highest R²• Coefficient • T-Stat• P-value• Standard Error

DATA ANALYSIS (cont’d)

Regression StatisticsMultiple R 0.973131301R Square 0.946984529

Adjusted R Square 0.946614654

Standard Error 330.0919364Observations 434

  CoefficientsStandard

Error t Stat P-value

Intercept 113.71380916.1531164

87.03974425

57.66241E

-12

Fulltime Worker 3.815795714 0.25195774 15.14458627.88797E

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Sum of Retired 0.932936970.25706679

53.62916171

60.000318

541Sum of

Students 0.7221332330.34255767

32.10806322

40.035603

598

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• Three independent variables considered to analyze a regression model.

• The highest R²• Coefficient • T-Stat• P-value• Standard Error

OD TABLE-PUBLIC TRIPS

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Sum of d_fexp Column LabelsRow Labels 4620610.01 4620610.02 4620610.03 4620610.04 4620610.05 4620610.06 4620610.07 4620611.01 4620611.02 4620612 4620613 4620614 4620615 4620616 4620617.01 4620617.02 4620618 4620619 Grand Total4620610.01 165.48 67.76 17.24 87.63 60.9 40.27 146.78 81.1 54.14 62.12 110.25 51.75 103.8 22.88 86.55 23.45 73.78 1255.884620610.02 76.94 24.95 219.48 54.24 46.24 27.88 49.98 26.21 525.924620610.03 17.24 24.95 28.52 53.39 19.44 167.83 170.67 132.03 44.97 92.38 91.93 100.39 13.93 88.53 1046.24620610.04 66.01 28.52 15.24 29.23 25.9 58.98 223.884620610.05 54.42 225.52 15.57 89.44 72.9 457.854620610.06 17.2 54.24 38.84 23.07 44.7 100.51 24.89 303.454620610.07 146.78 46.24 19.44 15.57 86.18 15.32 36.57 27.19 13.41 17.12 23.84 19.82 467.484620611.01 81.1 27.88 197.57 15.32 80.54 402.414620611.02 54.14 210.77 44.47 67.52 22.96 21.33 140.36 52.41 39.65 75.77 22.16 38.68 47.74 837.964620612 43.38 29.61 132.03 73.48 35.24 26.47 85.28 35.16 17.17 46.53 44.78 569.134620613 44.97 27.19 39.65 70.48 292.29 144.55 76.45 101.84 797.424620614 80.82 22.64 73.27 19.39 196.124620615 51.75 92.38 13.41 13.46 26.47 21.72 28.72 58.11 25.62 331.644620616 140.03 55.38 100.51 17.12 75.77 42 144.55 73.27 45.66 30.59 63.51 31.42 819.814620617.01 22.88 34.89 44.27 35.16 30.59 22.16 22.16 22.16 234.274620617.02 70.29 136.94 22.16 17.17 76.45 19.39 58.11 61.53 22.16 22.16 506.364620618 39.68 16.16 29.49 29.49 23.84 38.68 59.79 22.16 259.294620619 73.78 88.53 24.89 19.82 47.74 51.32 101.84 42.11 31.42 481.45Grand Total 1201.92 476.2 1103.72 190.11 450.92 296.26 467.48 305.59 929.5 598.93 762.18 224.63 364.77 890.15 253.91 514.26 227.57 458.42 9716.52

MODE SHARE

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12 AM1 AM

2 AM3 AM

4 AM5 AM

6 AM7 AM

8 AM9 AM

10 AM11 AM

1 PM2 PM

3 PM4 PM

5 PM6 PM

7 PM8 PM

9 PM10 PM

11 PM12 PM

0%10%20%30%40%50%60%70%80%90%

100%All trips Mode share

MixedUnknownPara-transitOn footBicycleMotorcycleTaxiOther busSchool busCIT busSTL busRTL BusMetroSTM busauto pas-sengerAuto-driver

SUPPLY

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•  The capacity of transportation infrastructures and modes, generally over a geographically defined transport system and for a specific period of time.• Supply is expressed in terms of infrastructures (capacity),

services (frequency) and networks (coverage)• Applying QGIS to GTFS files in order to demonstrate supply

of our sector

QUANTUM GIS ANALYSIS (BUS LINES IN THE SECTOR)

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MORNING AND AFTERNOON PEAK LOADS

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OD DEMAND-CARS (MORNING PEAK)

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Car-morningSum of p_fexp Column LabelsRow Labels 4620610.01 4620610.02 4620610.03 4620610.04 4620610.05 4620610.06 4620610.07 4620611.01 4620611.02 4620612 4620613 4620614 4620615 4620616 4620617.01 4620617.02 4620618 4620619 Grand Total4620610.01 102.92 28.02 17.72 72.9 28.74 250.3

4620610.02 36.81 16.26 63.68 28.15 35.06 34.82 25.88 15 255.66

4620610.03 68.27 36.54 28.02 42.29 49.23 17.3 24.7 30.31 33.15 51.61 381.42

4620610.04 14.62 24.04 12.98 46.18 30.6 14.24 34.1 176.76

4620610.05 53.74 153.17 55.2 262.11

4620610.06 73.43 93.18 166.61

4620610.07 17.72 167.13 57.71 242.56

4620611.01 16.4 24.95 16.66 16.16 13.46 87.63

4620611.02 51.48 22.37 25.96 27.81 159.94 49.4 47.78 17.72 49.38 58.31 510.15

4620612 23.41 16.66 35.24 30.77 192.19 16.27 61.62 376.16

4620613 38.03 46.98 132.25 24.04 95.52 30.64 56.04 67.76 491.26

4620614 36.75 34.82 131.66 63.95 267.18

4620615 14.64 43.27 26.63 17.66 21.18 59.28 136.9 31.56 75.5 61.3 487.92

4620616 67.42 40.95 46.11 17.35 36.58 54.72 16.86 26.95 98.57 405.514620617.01 28.26 26.34 22.77 23.73 30.43 16.27 19.85 21.75 29.62 219.024620617.02 50.55 13.46 24.54 50.61 139.164620618 70.75 33.15 30.62 72.72 73.66 280.94620619 49.04 19.06 55.05 86.48 48.43 13.46 271.52Grand Total 395.25 555.98 405.82 17.66 86.05 66.91 111.14 223.74 456.58 233.83 576.59 173.49 417.79 535.93 193.92 264.86 193.34 362.95 5271.83

ANALYZING 13 CRITICAL PATHS (MORNING PEAK)

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Ecole Marie-Clarac

Cegep Marie-Victorin

Shopping center (place bourassa)

RESULTS (MORNING PEAK-CARS VS STM)

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Analysing the paths with the highest number of trips by car in the morning peak period

No. origin destinationDemand

available bus line for this path supply-STM joint Reason of trip attractionloads-car >50 loads-STM

1 4620610.06 4620611.02 93.18 22.96 469-O 69-O 43-O 40-O 65 Ecole Jean Nicolat-Shopping center (place bourassa)-Gase station

2 4620610.07 4620613 159.94 27.19 469-O 48-O 67-O 439-O 140-S 58 1 Cegep Marie-Victorin

3 4620613 4620611.02 132.25 0 440-O 140-O 22 Ecole Jean Nicolat-Shopping center (place bourassa)-Gase station

4 4620618 4620610.01 70.75 0 469-O 69-O 51 Shopping center (place bourassa)5 4620616 4620610.01 67.42 34.57 469-O 69-O 51 Shopping center (place bourassa)6 4620617.02 4620610.02 50.55 0 469-O 69-O 49-O 80 7 4620610.07 4620614 57.71 0 469-O 48-O 58 8 4620613 4620617.01 56.04 0 469-O 48-O 380-O 49-O 439-S 67-S 87 1 9 4620612 4620618 61.62 0 439-S 22

10 4620610.03 4620619 51.61 0 469-O 48-O 380-O 49-O 87 Ecole Marie-Clarac11 4620611.02 4620619 58.31 0 469-O 48-O 49-O 69-O 43-O 380-O 124 Ecole Marie-Clarac12 4620613 4620619 67.76 0 439-S 67-S 34 Ecole Marie-Clarac13 4620617.02 4620619 50.61 0 469-O 49-O 69-O 380-O 118 Ecole Marie-Clarac

OD DEMAND-CARS (AFTERNOON PEAK)

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Sum of p_fexpColumn LabelsRow Labels 4620610.01 4620610.02 4620610.03 4620610.04 4620610.05 4620610.06 4620610.07 4620611 4620611 4620612 4620613 4620614 4620615 4620616 4620617 4620617 4620618 4620619 Grand Total4620610.01 106.54 95 53.74 19.67 78.51 57.9 48.75 32.3 218.7 48.99 43.99 36.37 840.464620610.02 107.03 64.63 48.68 73.43 57.62 122.31 48.28 20.73 542.714620610.03 87.24 26.44 25.46 146.94 46.52 121.26 46.98 26.63 50.22 37.94 24.7 640.334620610.04 17.66 28.33 45.994620610.05 28.02 26.47 34.82 85.43 25.72 200.464620610.06 16.49 25.96 30.16 43.12 115.734620610.07 19.82 32.44 30.3 25.03 48.29 52.3 23.73 26.06 257.974620611.01 42.12 28.15 47.69 21.18 46.11 32.4 47.31 264.964620611.02 147.5 71.43 29.36 67.56 92.94 121.52 119.61 29.36 29.23 75.1 102.42 71.63 135.35 1093.014620612 171.22 26.33 83.25 49.51 16.27 52.43 24.82 61.3 485.134620613 66.69 17.12 63.87 30.6 48.29 37.53 70.48 72.19 231.69 25.03 60.59 724.084620614 34.82 74.6 72.66 36.33 30.43 248.844620615 87.74 55.31 58.78 29.43 78.19 72.28 67.23 39.24 86.48 574.684620616 142.03 17.3 45.62 24.04 40.61 30.43 160.19 154.88 73.16 66.73 13.46 59.63 32.13 860.214620617.01 34.89 37.3 59.52 14.24 32.4 16.27 19.85 175.14 23.45 413.064620617.02 23.45 20.73 28.33 37.53 13.46 57.45 28.06 63.95 24.82 24.54 23.45 345.774620618 50.32 20.2 56.54 30.62 19.85 177.534620619 48.71 15 88.02 58.31 38.75 20.57 115.9 26.44 15.36 19.85 446.91Grand Total 852.9 333.06 525.59 222.92 207.89 199.77 367.56 263.46 735.91 518.67 643.34 285.09 821.19 695.95 373.98 451.86 246.69 532 8277.83

Car-Afternoon

ANALYZING 9 CRITICAL PATHS (AFTERNOON PEAK)

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Ecole Jean Nicolat-Shopping center (place bourassa)-Gase station

RESULTS (AFTERNOON PEAK-CARS VS STM)

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Analysing the paths with the highest number of trips by car in the afternoon peak period

No. origin destination

Demand

available bus line for this path supply-STM Reason of trip attraction

loads-car>100 loads-STM

20 4620610.01 4620616 218.7 29.08 469-O               8

21 4620610.02 4620615 122.31 0 469-O 43-O 49-O 69-O         51

22 4620610.03 4620611.02 121.26 107.27 252-O 32-S 353-O380-O432-S439-S469-O 69-O 75Ecole Jean Nicolat-Shopping center (place bourassa)-Gase station

23 4620611.02 4620612 121.52 20.37 140-O439-S440-O           15Ecole Jean Nicolat-Shopping center (place bourassa)-Gase station

24 4620611.02 4620613 119.61 0 140-O440-O             15Ecole Jean Nicolat-Shopping center (place bourassa)-Gase station

25 4620611.02 4620619 135.35 34.33 469-O 48-O 49-O 69-O 43-O 380-O     124Ecole Jean Nicolat-Shopping center (place bourassa)-Gase station

26 4620612 4620611.02 171.22 0 469-O380-O 69-O           45Ecole Jean Nicolat-Shopping center (place bourassa)-Gase station

27 4620616 4620610.01 142.03 21.14 469-E               21

28 4620616 4620613 154.88 144.55 140-O355-S439-S           8

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Morning peak

https://www.google.ca/maps?hl=en&tab=wl

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Afternoon peak

https://www.google.ca/maps?hl=en&tab=wl

CONCLUSION

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• Analyzing and comparing the demand and supply in the study area shows that the number of trips by cars during the morning and af-ternoon peak are considerable and needs improvement in the pub-lic transit.• According to study ‘The Transportation Systems Analysis in Mon-

treal North’, there should be several improvement ways in this zone-congestion during peak-time.• STM bus Improvement: Decreasing the impedance function of STM

like access time, travel time, and vehicle time in our sector, particu-larly in the mentioned areas which are critical in the morning and afternoon peak period.• Metro Improvement:Providing metro system in the area would im-

prove transit.

REFRENCES• Retrieved from AMT: https://amt.qc.ca/en• Retrieved from STM: http://www.stm.info/en• Retrieved from Statistics Canada: http://www.statcan.gc.ca/start-debut-eng.html• Retrieved from Wikipedia: https://en.wikipedia.org/wiki/Montr%C3%A9al-Nord• . Retrieved from MTQ: https://www.mtq.gouv.qc.ca/en/Pages/default.aspx• Retrieved from CMM: http://cmm.qc.ca/accueil/• Retrieved from Google Map: www.googlemap.com• Retrieved from QGIS: http://www.qgis.org/en/site/• Spurr, T. Urban Transportation Planning Lecture.

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THANK YOU!

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