Use of Passenger Count Data to provide Cost-Benefit Analysis of Fixed-Route Cluster Operations Helping Agencies Do More with Less Dennis Fletcher M.E.S., director, transit solutions Gera Taubkin, M.S.,senior transit planner GENIVAR, Markham, ON
PASSENGER GLOBAL SOLUTIONS IN ENGINEERING COUNTING ANALYSIS Buildings Municipal Infrastructure Transportation Industrial Energy Environment
3 PC DATA. MAIN PURPOSES to check and clean How PC Data Quality to maintain and keep Readiness for PC Data use PC Data to use and analyze Transit Operation Service and Efficiency
4 PRESENTATION HIGHLIGHTS -Developed set of parameters for diagnostic analysis of transit operations and identification of appropriate potential solutions without manual drill-down into stop level (passenger density, crowding factor, weight focuses of passenger s route activity, load characteristics, route pattern similarity) - Procedure for Route Correspondence Matrix creation to provide IF-WHAT comparative Cost-Benefit Analysis for proposed solutions Matrix Parameters - Computer EXCEL-based tools incorporating these methodologies and presentation of examples Tools Process
5 PLACE OF PC DATA USAGE IN TRANSIT PLANNING PROCESS PC Analysis
6 TRANSIT ANALYTICAL PROCESS Auto - Diagnostic Computer procedure analyzing PC Data to classify found GAPs Manual-Diagnostic PC Data Analysis by planner. Drill-down methodology Operational GAPs Identification Auto - Proposing Computer procedure proposing appropriate variants of solutions according to GAP type Proposing required solutions by result of PC Analysis and professional knowledge of planner Proposing of directions/solutions to fix GAPs Auto-Manual Choice Manual - Proposing Interactive computer application to choice preferable solution in IF-WHAT mode Choice of preferable solution Key Meanings Similarity
7 AUTO DIAGNOSTIC AND PROPOSING / SELECTED ROUTE 3 4 Back
8 AUTO DIAGNOSTIC AND PROPOSING / SELECTED ROUTE/ SELECTED PERIOD stops? Back
1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 9 COMPARATIVE COST-BENEFIT ANALYSIS/ SELECTED ROUTE/ SELECTED PERIOD 1 2 3 4 5 6 7 LOAD 1 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 spare 1.2 1 72 68 65 61 58 54 50 47 43 40 36 32 29 25 22 18 14 11 7 4 No branching, frequency increase Branching, frequency variation = * Base Short-1 Short-2 Short-3 Back Next
10 COMPARATIVE COST-BENEFIT ANALYSIS/ IF-WHAT ANALYSIS AND CRITERIAS PC usage Options comparison Cost assessment Buses, Hours/KM, Riders per Cost unit $! LOS assessment Classification and Quantification of existing riders by groups according to impact from proposed solutions : - No significant travel pattern change -Service Improvement (frequency, travel time, transfer ) - Service worsening (frequency, travel time, transfer ) - Service cancelation Back Similarity
1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 11 COMPARATIVE COST-BENEFIT ANALYSIS/ COST 1 2 3 4 5 6 7 LOAD 1 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 spare 1.2 1 72 68 65 61 58 54 50 47 43 40 36 32 29 25 22 18 14 11 7 4 Hours Buses = * Base Short-1 Short-2 Back LOS
1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 12 COMPARATIVE COST-BENEFIT ANALYSIS/ LOS 1 2 3 4 5 6 7 LOAD 1 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 spare 1.2 1 72 68 65 61 58 54 50 47 43 40 36 32 29 25 22 18 14 11 7 4 Crowding Factor Load Density, pass/sq m Acceptable level = * Base Short-1 Short-2 Cost Similarity
13 AUTO DIAGNOSTIC AND PROPOSING / SELECTED ROUTE / SIMILARITY Riders number, Max Load Is it enough to recognize ridership pattern? Process NEXT
14 AUTO DIAGNOSTIC AND PROPOSING / SELECTED ROUTE / SIMILARITY Two Trips/Day Periods may be considered as SIMILAR if their pattern accommodate the same planning solution, based on 3 ingredients : - Branch structure - Frequency - Vehicle Type Headway Bus Type minutes Branch 1 Base 10 Regular Branch 2 Short 10 Regular Branch 3 Express 20 Small Departure Headway betwee bus departure Branch1 7:00 Branch2 7:05 0:05 0:05 Branch 1 Branch1 7:10 0:05 0:05 0:10 0:10 Branch 2 Branch2 7:15 0:05 0:05 Branch3 7:18 0:03 0:08 Branch 3 Branch1 7:20 0:02 0:05 0:02 0:10 Branch2 7:25 0:05 0:05 Branch1 7:30 0:05 0:05 0:10 0:10 Branch2 7:35 0:05 0:05 Branch3 7:38 0:03 0:08 Branch1 7:40 0:02 0:05 0:02 0:10 Branch2 7:45 0:05 0:05 Branch1 7:50 0:05 0:05 0:10 0:10 Branch3 7:53 0:03 0:08 Branch1 7:55 0:02 0:05 0:02 0:10 Base Short Express Back Key Meanings
1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 15 COMPARATIVE COST-BENEFIT ANALYSIS/ COST 1 2 3 4 5 6 7 LOAD 1 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 spare 1.2 1 72 68 65 61 58 54 50 47 43 40 36 32 29 25 22 18 14 11 7 4 Hours Buses = * Base Short-1 Short-2 Back Key Meanings
16 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS Passenger Density on Bus Crowding factor Load - Characteristics Weight Centers of riders Correspondence Matrix BRT DESIGN Agency Macro Analysis HIGHLIGHTS START PROCESS
17 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS / DENSITY Key Meanings Next
18 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS / DENSITY Level 1 : Just Seats Level 2 : Low density Level 3 : Medium density 1 2 3 4 5 6 7 8 9 10 Dencity Levels pass/sq.m Seats Standing Area 1 0 0 + - 2 0 1 + low 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 3 1 2 + medium Level 4 : High density Level 5: Very High density 4 2 4 + high 5 4 + very high 1 2 3 1 2 3 4 5 6 7 8 9 10 1 2 3 1 2 3 4 5 6 7 8 9 10 4 4 5 5 6 6 7 7 8 8 9 9 10 10 Bus Seats Square Capacity based on 4 pass/sq.m Dencity in case of ON-BOARD=35 Dencity in case of ON-BOARD=55 Dencity in case of ON-BOARD=75 35 55 75 Small 20 5.0 40 3.0 7.0 11.0 Regular 40 8.0 72 1.9 4.4 Articulated 50 10.0 90 0.5 2.5 Back
Small Bus Regular Bus Articulated Bus = * = * = * = * = * = * Density 19 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS / CROWDING FACTOR LOAD 1 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 LOAD 1 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 spare 1.2 60 spare 1.2 72 # 72 68 # 68 65 # 65 61 # 61 58 # 58 54 # 54 50 # 50 47 # 47 43 # 43 40 # 40 36 # 36 32 9 32 29 8 29 25 7 25 22 6 22 18 5 18 1 14 4 14 1 11 3 11 1 7 2 7 1 4 1 4 1 1 1.0 3.9 LOAD 1 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 LOAD 1 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 60 spare 1.2 60 spare 1.2 72 # 72 68 # 68 65 # 65 61 # 61 58 0.1 # 58 0.4 54 # 54 50 # 50 47 # 47 43 # 43 40 # 40 36 # 36 32 9 32 29 8 29 25 7 25 22 6 22 18 5 18 1 14 4 14 1 11 3 11 1 7 2 7 1 4 1 4 1 1 5 4 3 2 1 LOAD 1 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 LOAD 1 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 60 spare 1.2 60 spare 1.2 72 # 72 68 # 68 65 # 65 61 # 61 58 0.0 # 58 0.1 54 # 54 50 # 50 47 # 47 43 # 43 40 # 40 36 # 36 32 9 32 29 8 29 25 7 25 22 6 22 18 5 18 1 14 4 14 1 11 3 11 1 7 2 7 1 4 1 4 1 1 Back Next
Articulated Bus Regular Bus Small Bus 20 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS / CROWDING FACTOR 7.8% 13.8% Density Distribution 17.2% 33.6% 27.6% 1.0 0.34*0.0 0.28*0.1 0.14*0.5 0.08*1.0 75.9% Density Distribution 9.5% 1.7% 5.2% 7.8% 3.9 0.05*0.0 0.02*0.1 0.08*0.5 0.10*1.0 Seats Low Mid High Very High 0.17*5.0 Seats Low Mid High Very High 0.76*5.0 3.4% Density Distribution 11.2% 2.6% 0.0% 82.8% Seats Low Mid High Very High 0.1 0.83*0.0 0.11*0.1 0.03*0.5 0.03*1.0 0.00*5.0 Density Distribution 0.0% 19.8% 24.1% 18.1% 37.9% Seats Low Mid High Very High 0.4 0.24*0.0 0.18*0.1 0.38*0.5 0.20*1.0 0.00*5.0 Density Distribution 0.0% 0.0% 6.0% 94.0% 0.0 0.94*0.0 0.06*0.1 0.00*0.5 0.00*1.0 4.3% 0.0% Density Distribution 0.0% 49.1% 46.6% 0.1 0.47*0.0 0.49*0.1 0.04*0.5 0.00*1.0 Seats Low Mid High Very High 0.00*5.0 Seats Low Mid High Very High 0.00*5.0 Back
21 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS /LOAD CHARACTERISTICS = * 75 71 68 64 60 56 53 49 45 41 38 34 30 26 1 23 1 19 15 11 8 4 Max ON-BOARD Square of : -Total Polygon : PKM (Passenger-KM) -Polygon of black color : Load factor closed to MAX(>80% from MAX) -Polygon of dark gray color : Load factor in range (50%-80% from MAX) -Polygon of light gray color : Load factor in range (20%-50% from MAX) -Polygon of very light gray color : Load factor closed to MIN (<20% from MAX) Average ON-BOARD LOAD # 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 Max Load Stop Key Meanings Next
22 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS /LOAD CHARACTERISTICS = * 75 71 68 64 60 56 53 49 45 41 38 34 30 26 1 23 1 19 15 11 8 4 LOAD # 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 Max Load 56.8 Max Segment 5 distance: % 14.7% Average Load 2 24.6 PassKM 285.5 Variation 64.3% Variation Factor 2.31 Average Rider Distance km 2.49 from Distance % 21.5% Chanchebility 4.7 = * 72 68 65 61 58 54 50 47 1 43 1 40 36 32 29 25 22 18 2 14 2 11 2 7 2 4 2 Max Load 60.0 Max Segment 12 distance: % 44.0% Average Load 47 PassKM 541.25 Variation 34.6% Variation Factor 1.29 Average Rider Distance km 4.73 from Distance % 40.8% Chanchebility 2.5 LOAD # 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 Back Focuses
= * = * 23 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS 75 71 68 64 60 56 53 49 45 41 38 34 30 26 1 23 1 19 15 11 8 4 LOAD # 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 72 68 65 61 58 54 50 47 1 43 1 40 36 32 29 25 22 18 2 14 2 11 2 7 2 4 2 LOAD # 1 1 1 1 2 2 2 3 3 4 5 5 6 6 7 8 8 8 8 9 10 10 11 11 11 12 12 13 14 14 15 15 16 16 16 17 18 18 18 19 19 20 20 20 21 21 22 23 24 24 25 Key Meanings Back
24 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS / CORRESPONDENCE MATRIX Boarding Alighting Matrix Algorithm Correspondence between each pair of stops Key Meanings Examples
25 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS / CORRESPONDENCE MATRIX Stops Distance ON OFF 1 0.8 125 2 0.7 0.8 85 3 0.5 1.5 130 4 0.3 2.0 124 22 5 0.4 2.3 30 18 6 0.6 2.7 29 100 7 0.2 3.3 20 45 8 0.9 3.5 12 99 9 0.3 4.4 14 106 10 0.4 4.7 25 42 11 0.6 5.1 40 26 12 0.5 5.7 46 49 13 0.3 6.2 56 39 14 0.4 6.5 50 20 15 0.5 6.9 40 46 16 0.8 7.4 20 42 17 0.3 8.2 30 47 18 0.5 8.5 10 37 19 0.6 9.0 10 14 20 0.7 9.6 1 30 21 0.4 10.3 10 46 22 0.3 10.7 9 48 23 0.2 11.0 34 24 0.4 11.2 3 25 11.6 3 11.6 916 916 Example 1 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Correspondence Matrix Boarding 1 1 10.5 7.7 29.9 9.6 19.8 18.7 7.2 4.0 5.8 3.1 1.4 2.1 1.2 0.9 0.7 0.2 0.4 0.6 0.6 0.3 0.0 0.0 125.0 125.0 2 2 7.1 5.2 20.4 6.5 13.5 12.7 4.9 2.7 4.0 2.1 1.0 1.5 0.8 0.6 0.5 0.2 0.3 0.4 0.4 0.2 0.0 0.0 85.0 85.0 3 3 4.4 3.4 34.3 11.0 22.6 21.4 8.2 4.6 6.7 3.6 1.7 2.5 1.3 1.1 0.8 0.3 0.5 0.7 0.6 0.4 0.0 0.0 130.0 130.0 4 4 1.7 13.7 13.6 28.0 26.5 10.2 5.7 8.2 4.4 2.0 3.0 1.6 1.3 1.0 0.3 0.6 0.9 0.8 0.5 0.0 0.0 124.0 124.0 5 5 1.7 2.8 7.5 7.1 2.7 1.5 2.2 1.2 0.5 0.8 0.4 0.4 0.3 0.1 0.2 0.2 0.2 0.1 0.0 0.0 30.0 30.0 6 6 1.5 6.5 8.3 3.2 1.8 2.6 1.4 0.6 1.0 0.5 0.4 0.3 0.1 0.2 0.3 0.2 0.1 0.0 0.0 29.0 29.0 7 7 1.2 7.4 2.9 1.6 2.3 1.2 0.6 0.9 0.5 0.4 0.3 0.1 0.2 0.2 0.2 0.1 0.0 0.0 20.0 20.0 8 8 3.8 2.1 1.2 1.7 0.9 0.4 0.6 0.3 0.3 0.2 0.1 0.1 0.2 0.2 0.1 0.0 0.0 12.0 12.0 9 9 0.7 1.0 4.1 2.2 1.0 1.5 0.8 0.7 0.5 0.2 0.3 0.4 0.4 0.2 0.0 0.0 14.0 14.0 10 10 1.9 6.2 4.6 2.1 3.1 1.7 1.4 1.0 0.3 0.6 0.9 0.8 0.5 0.0 0.0 25.0 25.0 11 11 5.3 9.3 4.3 6.4 3.4 2.8 2.1 0.7 1.2 1.8 1.6 1.0 0.1 0.0 40.0 40.0 12 12 4.9 2.8 11.6 6.2 5.1 3.8 1.2 2.3 3.3 3.0 1.7 0.1 0.0 46.0 46.0 13 13 1.5 6.2 11.3 9.2 6.8 2.2 4.1 5.9 5.4 3.2 0.2 0.1 56.0 56.0 14 14 5.0 8.3 9.1 6.7 2.1 4.0 5.9 5.3 3.1 0.2 0.1 50.0 50.0 15 15 3.6 9.1 6.7 2.1 4.0 5.8 5.3 3.1 0.2 0.1 40.0 40.0 16 16 4.1 3.9 1.2 2.3 3.4 3.1 1.8 0.1 0.0 20.0 20.0 17 17 1.6 2.3 5.7 8.2 7.5 4.4 0.3 0.1 30.0 30.0 18 18 0.4 2.1 3.0 2.7 1.6 0.1 0.0 10.0 10.0 19 19 1.0 3.6 3.3 1.9 0.1 0.1 10.0 10.0 20 20 0.2 0.5 0.3 0.0 0.0 1.0 1.0 21 21 5.8 3.4 0.5 0.3 10.0 10.0 22 22 5.9 1.0 2.1 9.0 9.0 23 23 24 24 25 25 Matrix Total 22.0 18.0 100.0 45.0 99.0 106.0 42.0 26.0 49.0 39.0 20.0 46.0 42.0 47.0 37.0 14.0 30.0 46.0 48.0 34.0 3.0 3.0 916.0 Alighting 22.0 18.0 100.0 45.0 99.0 106.0 42.0 26.0 49.0 39.0 20.0 46.0 42.0 47.0 37.0 14.0 30.0 46.0 48.0 34.0 3.0 3.0 916.0 1 2 3 4 5 6 22 23 24 25 Matrix Boarding 0.6 0.3 0.0 0.0 125.0 125.0 0.4 0.2 0.0 0.0 85.0 85.0 0.6 0.4 0.0 0.0 130.0 130.0 0.8 0.5 0.0 0.0 124.0 124.0 0.2 0.1 0.0 0.0 30.0 30.0 0.2 0.1 0.0 0.0 29.0 29.0 Key Meanings Back Next
new 26 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS / CORRESPONDENCE MATRIX 77% 1 4 7 10 15 18 23 3 6 9 14 17 22 25 1 2 3 4 5 6 7 2% 17% 77% 17% 2% 2% 2% 2% 2% Key Meanings Back Next
27 AUTO DIAGNOSTIC AND PROPOSING / KEY MEANINGS / CORRESPONDENCE MATRIX 100% LOS change by riders percentage 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Key Meanings Back
28 PC DATA USAGE-EXAMPLES / BRT-ZUM / VEHICLE FLEET STRUCTURE Run Key Meanings
29 PC DATA USAGE-EXAMPLES / BRT-ZUM / VEHICLE FLEET STRUCTURE Graph Key Meanings Back
30 PC DATA USAGE-EXAMPLES / BRT-ZUM / VEHICLE FLEET STRUCTURE Key Meanings Back Fleet
31 PC DATA USAGE-EXAMPLES / BRT-ZUM / VEHICLE FLEET STRUCTURE Headway, minutes Queen Corridor. Option1.1 Regular Artic Regular Artic Regular Artic Regular Artic Regular Artic Regular Artic Regular Artic Regular Artic Regular Artic Regular Artic Regular Artic Regular Artic Regular Artic Key Meanings Back
32 PC DATA USAGE-EXAMPLES / MACRO ANALYSIS / TRIPS Key Meanings Bus Type Route Efficiency
33 PC DATA USAGE-EXAMPLES / MACRO ANALYSIS /TRIPS / CROWDING Artic Regular Short Trips
34 PC DATA USAGE-EXAMPLES / MACRO ANALYSIS /TRIPS / CROWDING Artic Regular Short Trips
35 PC DATA USAGE-EXAMPLES / MACRO ANALYSIS /TRIPS / CROWDING Artic Regular Short Trips
36 PC DATA USAGE-EXAMPLES / MACRO ANALYSIS /ROUTES/ CROWDING Artic Regular Short Trips Load
37 PC DATA USAGE-EXAMPLES / MACRO ANALYSIS /ROUTES/ CROWDING Artic Regular Short Trips Load
38 PC DATA USAGE-EXAMPLES / MACRO ANALYSIS /ROUTES/ CROWDING Artic Regular Short Trips Load
39 PC DATA USAGE-EXAMPLES / MACRO ANALYSIS /ROUTES/ PREDICT Trips Routes
40 PC DATA USAGE-EXAMPLES / MACRO ANALYSIS /ROUTES/ EFFICIENCY Trips Routes