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BusMezzo

Dynamic Modeling of Bus and Car Traffic



                     Oded Cats

          Centre for Traffic Research (CTR)
            Kungliga Tekniska Högskolan


    2010-01-14        Transportforum 2010 Linköping
                                                      1
Outline

•   Dynamic transit model
•   Mezzo simulation
•   Supply side: transit operations
•   Case study
    – Design
    – Results
    – Control strategies
• Demand side: passenger path choice




                                       2
Transit model components




                           3
Motivation
• Modeling sources of uncertainties
   •   Departure time from origin terminal
   •   Traffic conditions
   •   Passenger arrival process
   •   Dwell time

• Planning and operations dynamic tool
   ▫ Evaluation
     ▫ System scenarios
     ▫ Policies and strategies
   ▫ Measures of service
     ▫ Service regularity
     ▫ Crowding levels
     ▫ On-time performance
                                             4
Mezzo
•   Mesoscopic traffic simulation
•   Event-based
•   Stochastic
•   Traffic dynamics
    ▫ Running part: speed-density relationship
    ▫ Queuing part: turn specific queue servers



       Running part     Queue part


• Open source:
   http://mezzo_dev.blogspot.com

                                                  5
Transit operations
• Transit entities
  ▫ Bus stop, bus line, bus route, bus trip, bus vehicle and bus type


• Transit mechanisms
  ▫   Boarding and alighting rates
  ▫   Dwell time
  ▫   Travel time
  ▫   Trip chaining
  ▫   Time point control strategies




                                                                        6
Case study - background
•   Line 51, Tel-Aviv metropolitan
•   High-demand bus line
•   Heavily congested urban corridor
•   14km long route
•   Max. frequency: 10 buses/hour




                                       7
Case study – background (Cont.)
• Static information at stops
• No control strategies




                                  8
Case study results
Trajectory
                    11000




                    9000
   Time (seconds)




                    7000




                    5000




                    3000




                    1000
                            0         2000         4000          6000            8000             10000         12000        14000
                                                                    Distance (meters)

                                bus 12 simulated      bus 13 simulated         bus 12 scheduled           bus 13 scheduled
                                                                                                                                     9
Case study results
Service reliability




                      10
11

Case study results
Load profiles
                    80

                    70

                    60
   Passenger load




                    50

                    40

                    30

                    20

                    10

                    0
                         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 26 27 28 29 30
                                                           Stop number
                                     Short headway     Long headway       Planned headway

                                                                                                       11
12

Case study results
Recovery time scenarios
 Recovery                       On-time     Schedule       Late
time policy      Fleet size   performance   deviation   departures
(percentile of
travel time)
                                  (%)         (sec)        (%)


    55%             15           78.5         196         13.0

    70%             16           84.0         169          7.3

    85%             17           90.4         131          0.9




                                                                      12
Case study design
Holding control strategies
• Setting a criteria for departing from selected locations
• Decisions
   – How many?
   – Where?
   – Which criteria?
• Schedule-based vs. Headway-based
   – Not before the scheduled time
   – Not before a minimum headway from the preceding bus




                                                             13
Case study design
Time points location




                       14
Case study results
Effects along the route
                                  100

                                            90
     Headway standard deviation [seconds]

                                            80

                                            70

                                            60

                                            50

                                            40

                                            30
                                                                                                     TP #3
                                            20
                                                                 TP #1             TP #2
                                            10

                                                       No control        Headway-based control        Schedule-based control
                                            0
                                                 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 26 27 28 29 30
                                                                                      Stop
                                                                                                                                    15
Case study results
System measures comparison

     120%

     100%

      80%

      60%

      40%

      20%

      0%
                 SD(H)        On-time      Schedule deviation    Bunching
                            performance
            No control   Headway-based control     Schedule-based control

                                                                            16
Applications
• The capabilities of Mezzo as an evaluation tool of
  transit operations had been demonstrated through
  real-world case study.

• Examples of potential applications
  ▫ Frequency determination
  ▫ Restoration from major disruptions
  ▫ Transit link segregation assessment


• Future developments
  ▫ Realistic network validation
  ▫ Car-bus interaction
  ▫ Detailed passenger demand modeling
                                                       17
Transit loading framework




                            18

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Session 55 Oded Cats

  • 1. BusMezzo Dynamic Modeling of Bus and Car Traffic Oded Cats Centre for Traffic Research (CTR) Kungliga Tekniska Högskolan 2010-01-14 Transportforum 2010 Linköping 1
  • 2. Outline • Dynamic transit model • Mezzo simulation • Supply side: transit operations • Case study – Design – Results – Control strategies • Demand side: passenger path choice 2
  • 4. Motivation • Modeling sources of uncertainties • Departure time from origin terminal • Traffic conditions • Passenger arrival process • Dwell time • Planning and operations dynamic tool ▫ Evaluation ▫ System scenarios ▫ Policies and strategies ▫ Measures of service ▫ Service regularity ▫ Crowding levels ▫ On-time performance 4
  • 5. Mezzo • Mesoscopic traffic simulation • Event-based • Stochastic • Traffic dynamics ▫ Running part: speed-density relationship ▫ Queuing part: turn specific queue servers Running part Queue part • Open source: http://mezzo_dev.blogspot.com 5
  • 6. Transit operations • Transit entities ▫ Bus stop, bus line, bus route, bus trip, bus vehicle and bus type • Transit mechanisms ▫ Boarding and alighting rates ▫ Dwell time ▫ Travel time ▫ Trip chaining ▫ Time point control strategies 6
  • 7. Case study - background • Line 51, Tel-Aviv metropolitan • High-demand bus line • Heavily congested urban corridor • 14km long route • Max. frequency: 10 buses/hour 7
  • 8. Case study – background (Cont.) • Static information at stops • No control strategies 8
  • 9. Case study results Trajectory 11000 9000 Time (seconds) 7000 5000 3000 1000 0 2000 4000 6000 8000 10000 12000 14000 Distance (meters) bus 12 simulated bus 13 simulated bus 12 scheduled bus 13 scheduled 9
  • 10. Case study results Service reliability 10
  • 11. 11 Case study results Load profiles 80 70 60 Passenger load 50 40 30 20 10 0 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 26 27 28 29 30 Stop number Short headway Long headway Planned headway 11
  • 12. 12 Case study results Recovery time scenarios Recovery On-time Schedule Late time policy Fleet size performance deviation departures (percentile of travel time) (%) (sec) (%) 55% 15 78.5 196 13.0 70% 16 84.0 169 7.3 85% 17 90.4 131 0.9 12
  • 13. Case study design Holding control strategies • Setting a criteria for departing from selected locations • Decisions – How many? – Where? – Which criteria? • Schedule-based vs. Headway-based – Not before the scheduled time – Not before a minimum headway from the preceding bus 13
  • 14. Case study design Time points location 14
  • 15. Case study results Effects along the route 100 90 Headway standard deviation [seconds] 80 70 60 50 40 30 TP #3 20 TP #1 TP #2 10 No control Headway-based control Schedule-based control 0 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 26 27 28 29 30 Stop 15
  • 16. Case study results System measures comparison 120% 100% 80% 60% 40% 20% 0% SD(H) On-time Schedule deviation Bunching performance No control Headway-based control Schedule-based control 16
  • 17. Applications • The capabilities of Mezzo as an evaluation tool of transit operations had been demonstrated through real-world case study. • Examples of potential applications ▫ Frequency determination ▫ Restoration from major disruptions ▫ Transit link segregation assessment • Future developments ▫ Realistic network validation ▫ Car-bus interaction ▫ Detailed passenger demand modeling 17