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Do ‘normal’ traffic conditions really exist?
  Why modelling variation & uncertainty is not a choice


  S.C. Calvert MSc




TU Delft Masterclass                                                        May 2012



                                                          Challenge the future   1
Who am I?

Simeon Calvert, MSc, 28 yrs

•   Traffic researcher at TNO & PhD-candidate at TU Delft
•   Graduated at TU Delft, Transport & Planning, 2010.
•   Specialisation in Traffic flow theory and traffic modelling
•   PhD-subject is on probabilistic traffic flow modelling.




                                                        Challenge the future   2
Contents for today

•   Is considering ‘normal’ traffic conditions good enough?
•   Demonstration of variation in traffic flow
•   Focus of my research
•   Modelling variation using probability
•   Supervision




                                                      Challenge the future   3
Is ‘normal’ traffic flow good enough?


• Traffic is affected by day-to-day variations in traffic demand,
  weather conditions, road works, etc.
• Normal practice: take an average/representative situation

• Is it sufficient to consider normal traffic conditions
  when modelling traffic?       And why?




                                                      Challenge the future   4
Is ‘normal’ traffic flow good enough?


• Demonstration of variations present on roads
         8000


       7000


         7000



       6000                       Traffic demand:
         6000



       5000

         5000




       4000

         4000
                                   Congestion:
       3000
         3000




       2000
         2000




       1000
         1000




         0 0
                0             1             2                3          4                 5                    6
                                                                                                           5
                                                                                                        x 10
                    1.46   1.47      1.48       1.49   1.5       1.51       1.52   1.53       1.54             1.55
                                                                                                                             5
                                                                                                                      x 10




                                                                                                     Challenge the future        5
Is ‘normal’ traffic flow good enough?


• Capacity varied due to different weather conditions
• Two scenarios with same input, but one varied and one the
  ‘average’ situation
                                                            1

                                                           0.9

                                                           0.8

                                                           0.7




                                         Capacity factor
                                                           0.6

                                                           0.5

                                                           0.4

                                                           0.3

                                                           0.2

                                                           0.1

                                                            0
                                                                 0   0.1   0.2   0.3    0.4     0.5    0.6      0.7   0.8   0.9   1
                                                                                       Cumulative probability




                               source: Calvert, Taale, Snelder & Hoogendoorn (2012)


                                                                                               Challenge the future               6
Is ‘normal’ traffic flow good enough?


• Results:
         Scenario                Median Travel times   Average Travel times
                                     (minutes)              (minutes)
         Variation in input             20.23                 23.98
         No variation in input          18.16                 18.16

                                               source: Calvert, Taale, Snelder & Hoogendoorn (2012)


• Varied capacity leads to a (much) higher travel time!
• Non-varied capacity does not sufficiently consider delays

• NB: This is often the case, but not always! -Calvert & Taale (2012)




                                                                              Challenge the future   7
Focus of my research

• Effects of (external) events on traffic flow
   • Such as weather, daily demand variation, incidents, …
   • Data analysis
• Modelling variation in traffic
   • Models used for planning/forecasting & evaluation
• Presentation of probabilistic model results
   • Especially for policy-makers


                                                                                ?

                                                         Challenge the future   8
Modelling variation using probability


• Traffic modelling -> macroscopic / microscopic




                                                   Challenge the future   9
Modelling variation using probability


• Advanced Monte Carlo
   • Many simulations, with a different combination of input values
     for each simulation
   • ‘Advanced’ refers to clever ways of selecting the input values
                                                                                                                                       Histogram of network delay (Systemtic sampling)
                              1                                                                                               12


   • INPUT:                  0.9
                                                                                                        OUTPUT:               10
                             0.8

                             0.7
                                                                                                                              8
           Capacity factor




                             0.6




                                                                                                                  Frequency
                             0.5                                                                                              6

                             0.4
                                                                                                                              4
                             0.3

                             0.2
                                                                                                                              2
                             0.1

                              0                                                                                               0
                                   0   0.1   0.2   0.3    0.4     0.5    0.6      0.7   0.8   0.9   1                              0   1         2           3            4          5          6
                                                         Cumulative probability                                                                 Network delay (vehicle hours)               4
                                                                                                                                                                                         x 10




                                                                                                                                                     Challenge the future                 10
Modelling variation using probability

• Core probability
   • Variation is calculated in the core of the model as sets of
     probability distributions
   • Faster, completer, ☺ … but harder to implement




                                                       Congestion if:

                                                       K > Kcritical = 25 veh/km




                                                            Challenge the future   11
Supervision

• MSc:
   • 1 or 2 daily supervisors & professor
• PhD:
   • 1 or 2 daily supervisors & promoter
• High degree of independence expected




                                            Challenge the future   12
Supervision

• Important for dealing with supervisors:
   •   Make clear arrangements (about meetings, input, reporting, …)
   •   Be independent, but keep regular contact with supervisor(s)
   •   Remember: supervisors have been there before!
   •   …but you do have a say how you progress.
   •   Serving two masters (conflicting interests)*
   •   Sort out problems quickly, don’t ignore them!




                                                        Challenge the future   13
Opportunities / Interested?

• MSc-thesis project internship
• @TNO (or @ITS Edulab)
• Email: simeon.calvert@tno.nl




                                  Challenge the future   14
Challenge the future   15

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Calvert, Do ‘normal’ traffic conditions really exist? Why modelling variation & uncertainty is not a choice

  • 1. Do ‘normal’ traffic conditions really exist? Why modelling variation & uncertainty is not a choice S.C. Calvert MSc TU Delft Masterclass May 2012 Challenge the future 1
  • 2. Who am I? Simeon Calvert, MSc, 28 yrs • Traffic researcher at TNO & PhD-candidate at TU Delft • Graduated at TU Delft, Transport & Planning, 2010. • Specialisation in Traffic flow theory and traffic modelling • PhD-subject is on probabilistic traffic flow modelling. Challenge the future 2
  • 3. Contents for today • Is considering ‘normal’ traffic conditions good enough? • Demonstration of variation in traffic flow • Focus of my research • Modelling variation using probability • Supervision Challenge the future 3
  • 4. Is ‘normal’ traffic flow good enough? • Traffic is affected by day-to-day variations in traffic demand, weather conditions, road works, etc. • Normal practice: take an average/representative situation • Is it sufficient to consider normal traffic conditions when modelling traffic? And why? Challenge the future 4
  • 5. Is ‘normal’ traffic flow good enough? • Demonstration of variations present on roads 8000 7000 7000 6000 Traffic demand: 6000 5000 5000 4000 4000 Congestion: 3000 3000 2000 2000 1000 1000 0 0 0 1 2 3 4 5 6 5 x 10 1.46 1.47 1.48 1.49 1.5 1.51 1.52 1.53 1.54 1.55 5 x 10 Challenge the future 5
  • 6. Is ‘normal’ traffic flow good enough? • Capacity varied due to different weather conditions • Two scenarios with same input, but one varied and one the ‘average’ situation 1 0.9 0.8 0.7 Capacity factor 0.6 0.5 0.4 0.3 0.2 0.1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Cumulative probability source: Calvert, Taale, Snelder & Hoogendoorn (2012) Challenge the future 6
  • 7. Is ‘normal’ traffic flow good enough? • Results: Scenario Median Travel times Average Travel times (minutes) (minutes) Variation in input 20.23 23.98 No variation in input 18.16 18.16 source: Calvert, Taale, Snelder & Hoogendoorn (2012) • Varied capacity leads to a (much) higher travel time! • Non-varied capacity does not sufficiently consider delays • NB: This is often the case, but not always! -Calvert & Taale (2012) Challenge the future 7
  • 8. Focus of my research • Effects of (external) events on traffic flow • Such as weather, daily demand variation, incidents, … • Data analysis • Modelling variation in traffic • Models used for planning/forecasting & evaluation • Presentation of probabilistic model results • Especially for policy-makers ? Challenge the future 8
  • 9. Modelling variation using probability • Traffic modelling -> macroscopic / microscopic Challenge the future 9
  • 10. Modelling variation using probability • Advanced Monte Carlo • Many simulations, with a different combination of input values for each simulation • ‘Advanced’ refers to clever ways of selecting the input values Histogram of network delay (Systemtic sampling) 1 12 • INPUT: 0.9 OUTPUT: 10 0.8 0.7 8 Capacity factor 0.6 Frequency 0.5 6 0.4 4 0.3 0.2 2 0.1 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 Cumulative probability Network delay (vehicle hours) 4 x 10 Challenge the future 10
  • 11. Modelling variation using probability • Core probability • Variation is calculated in the core of the model as sets of probability distributions • Faster, completer, ☺ … but harder to implement Congestion if: K > Kcritical = 25 veh/km Challenge the future 11
  • 12. Supervision • MSc: • 1 or 2 daily supervisors & professor • PhD: • 1 or 2 daily supervisors & promoter • High degree of independence expected Challenge the future 12
  • 13. Supervision • Important for dealing with supervisors: • Make clear arrangements (about meetings, input, reporting, …) • Be independent, but keep regular contact with supervisor(s) • Remember: supervisors have been there before! • …but you do have a say how you progress. • Serving two masters (conflicting interests)* • Sort out problems quickly, don’t ignore them! Challenge the future 13
  • 14. Opportunities / Interested? • MSc-thesis project internship • @TNO (or @ITS Edulab) • Email: simeon.calvert@tno.nl Challenge the future 14