Session 74 Fredrik Johansson

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Mikrosimulering av fotgängare - effekter av att personer stannar upp eller står och väntar
Transportforum 2013

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Session 74 Fredrik Johansson

  1. 1. Mikrosimulering av fotgängare - effekter av att personer stannar upp eller står och väntar Fredrik Johansson12 Anders Peterson1 Andreas Tapani12 1 Linköping Universitet 2 VTI January 10, 2013
  2. 2. Background Waiting Pedestrians Results and ConclusionsOutline 1 Background Project Motivation Method 2 Waiting Pedestrians Motivation and Goal Models 3 Results and Conclusions Simulation results Conclusions Johansson et. al. Transportforum 2013 2/ 22
  3. 3. Background Project Waiting Pedestrians Motivation Results and Conclusions MethodOutline 1 Background Project Motivation Method 2 Waiting Pedestrians Motivation and Goal Models 3 Results and Conclusions Simulation results Conclusions Johansson et. al. Transportforum 2013 3/ 22
  4. 4. Background Project Waiting Pedestrians Motivation Results and Conclusions MethodProject: “Simulation of interchange stations” Goal: Evaluate a proposed design of a multi modal public transport interchange station using microscopic simulation. Initiators: Peterson and Tapani (LiU and VTI). Financier: Trafikverket. Beneficiaries: Linköping municipality and Östgötatrafiken. Performed by: LiU and VTI. Johansson et. al. Transportforum 2013 4/ 22
  5. 5. Background Project Waiting Pedestrians Motivation Results and Conclusions MethodMotivation Why study interchange stations? Stations are important for system performance. An increasing number of people travel by public transport. For efficient transfers small stations are needed. The Problem Small station + lots of people ⇒ congestion. Congestion causes Delay Discomfort Johansson et. al. Transportforum 2013 5/ 22
  6. 6. Background Project Waiting Pedestrians Motivation Results and Conclusions MethodMotivation Why study interchange stations? Stations are important for system performance. An increasing number of people travel by public transport. For efficient transfers small stations are needed. The Problem Small station + lots of people ⇒ congestion. Congestion causes Delay Discomfort Johansson et. al. Transportforum 2013 5/ 22
  7. 7. Background Project Waiting Pedestrians Motivation Results and Conclusions MethodMotivation Why study interchange stations? Stations are important for system performance. An increasing number of people travel by public transport. For efficient transfers small stations are needed. The Problem Small station + lots of people ⇒ congestion. Congestion causes Delay Discomfort Johansson et. al. Transportforum 2013 5/ 22
  8. 8. Background Project Waiting Pedestrians Motivation Results and Conclusions MethodMethod: Microscopic Simulation What? Modeling of the individual microscopic entities. Macroscopic flow structures are not explicitly modeled, but emerges from the interaction. Why? Congested pedestrian traffic is highly dynamic. The pedestrian traffic volumes in a station varies much both in space and time. Walkable areas can have almost arbitrary shape. The pedestrian population is diverse. Johansson et. al. Transportforum 2013 6/ 22
  9. 9. Background Project Waiting Pedestrians Motivation Results and Conclusions MethodMethod: Microscopic Simulation What? Modeling of the individual microscopic entities. Macroscopic flow structures are not explicitly modeled, but emerges from the interaction. Why? Congested pedestrian traffic is highly dynamic. The pedestrian traffic volumes in a station varies much both in space and time. Walkable areas can have almost arbitrary shape. The pedestrian population is diverse. Johansson et. al. Transportforum 2013 6/ 22
  10. 10. Background Project Waiting Pedestrians Motivation Results and Conclusions MethodGeneral model structure Behavior Model Activity Not Strategical planning modeled Shortest Tactical Route choice path Evasive Social force Operational maneuvers model Johansson et. al. Transportforum 2013 7/ 22
  11. 11. Background Project Waiting Pedestrians Motivation Results and Conclusions MethodGeneral model structure Behavior Model Activity Not Strategical planning modeled O-D Shortest Tactical Route choice path Evasive Social force Operational maneuvers model Johansson et. al. Transportforum 2013 7/ 22
  12. 12. Background Project Waiting Pedestrians Motivation Results and Conclusions MethodGeneral model structure Behavior Model Activity Not Strategical planning modeled O-D Shortest Tactical Route choice path vp (x) Evasive Social force Operational maneuvers model Johansson et. al. Transportforum 2013 7/ 22
  13. 13. Background Motivation and Goal Waiting Pedestrians Models Results and ConclusionsOutline 1 Background Project Motivation Method 2 Waiting Pedestrians Motivation and Goal Models 3 Results and Conclusions Simulation results Conclusions Johansson et. al. Transportforum 2013 8/ 22
  14. 14. Background Motivation and Goal Waiting Pedestrians Models Results and ConclusionsModeling waiting pedestrians Why? At interchange stations a significant fraction of the population are waiting. The location of waiting areas can to some extent be controlled. Goal Develop different extensions to the model to include waiting pedestrians. Characterize and compare the predictions of the different extensions. Johansson et. al. Transportforum 2013 9/ 22
  15. 15. Background Motivation and Goal Waiting Pedestrians Models Results and ConclusionsModeling waiting pedestrians Why? At interchange stations a significant fraction of the population are waiting. The location of waiting areas can to some extent be controlled. Goal Develop different extensions to the model to include waiting pedestrians. Characterize and compare the predictions of the different extensions. Johansson et. al. Transportforum 2013 9/ 22
  16. 16. Background Motivation and Goal Waiting Pedestrians Models Results and ConclusionsA naive waiting model Model 0: Stop and stay vi = 0. Problem: Only a few waiting pedestrians may cause almost complete stop. Johansson et. al. Transportforum 2013 10/ 22
  17. 17. Background Motivation and Goal Waiting Pedestrians Models Results and ConclusionsA naive waiting model Model 0: Stop and stay vi = 0. Problem: Only a few waiting pedestrians may cause almost complete stop. Johansson et. al. Transportforum 2013 10/ 22
  18. 18. Background Motivation and Goal Waiting Pedestrians Models Results and ConclusionsStructureAt what level should waiting be modeled? Waiting Behavior Model model Activity Not Waiting area planning modeled O-D Shortest Placement in Route choice waiting area path vp (x) Evasive Social force Interactions maneuvers model while waiting Johansson et. al. Transportforum 2013 11/ 22
  19. 19. Background Motivation and Goal Waiting Pedestrians Models Results and ConclusionsThree waiting models Model A: Stop vp = 0. i Model B: Choose a spot vp = (xp − xi )/4τ, |xp − xi | < 4τvip0 . i i i Model C: Choose a spot, adjust it vp = (xp − xi )/4τ, |xp − xi | < 4τvip0 . i i i Max p = −Fp − Ffriction i i Johansson et. al. Transportforum 2013 12/ 22
  20. 20. Background Motivation and Goal Waiting Pedestrians Models Results and ConclusionsThree waiting models Model A: Stop vp = 0. i Model B: Choose a spot vp = (xp − xi )/4τ, |xp − xi | < 4τvip0 . i i i Model C: Choose a spot, adjust it vp = (xp − xi )/4τ, |xp − xi | < 4τvip0 . i i i Max p = −Fp − Ffriction i i Johansson et. al. Transportforum 2013 12/ 22
  21. 21. Background Motivation and Goal Waiting Pedestrians Models Results and ConclusionsThree waiting models Model A: Stop vp = 0. i Model B: Choose a spot vp = (xp − xi )/4τ, |xp − xi | < 4τvip0 . i i i Model C: Choose a spot, adjust it vp = (xp − xi )/4τ, |xp − xi | < 4τvip0 . i i i Max p = −Fp − Ffriction i i Johansson et. al. Transportforum 2013 12/ 22
  22. 22. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsOutline 1 Background Project Motivation Method 2 Waiting Pedestrians Motivation and Goal Models 3 Results and Conclusions Simulation results Conclusions Johansson et. al. Transportforum 2013 13/ 22
  23. 23. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsTotal delay distribution 800 Model B Model A Model C 600 400 200 0 −2 0 2 4 6 8 10 Mean total positive delays: Model A:1.4, Model B: 2.2, Model C:1.8 Johansson et. al. Transportforum 2013 14/ 22
  24. 24. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsDensity, model A Johansson et. al. Transportforum 2013 15/ 22
  25. 25. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsDensity, model B Johansson et. al. Transportforum 2013 16/ 22
  26. 26. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsDensity, model C Johansson et. al. Transportforum 2013 17/ 22
  27. 27. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsDelay rate density, model A Johansson et. al. Transportforum 2013 18/ 22
  28. 28. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsDelay rate density, model B Johansson et. al. Transportforum 2013 19/ 22
  29. 29. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsDelay rate density, model C Johansson et. al. Transportforum 2013 20/ 22
  30. 30. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsAdjust SFM for waiters Waiting Behavior Model model Activity Not Waiting area planning modeled O-D Shortest Placement in Route choice waiting area path vp (x) Evasive Social force Interactions maneuvers model while waiting Johansson et. al. Transportforum 2013 21/ 22
  31. 31. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsConclusions The models produce reasonable behavior. Probably necessary to interfere with the SFM. Significant differences in the traffic resulting from the different models. Outlook Data Calibration Johansson et. al. Transportforum 2013 22/ 22
  32. 32. Background Simulation results Waiting Pedestrians Conclusions Results and ConclusionsConclusions The models produce reasonable behavior. Probably necessary to interfere with the SFM. Significant differences in the traffic resulting from the different models. Outlook Data Calibration Johansson et. al. Transportforum 2013 22/ 22

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