evaluating station facilities through...

Presented at PTV Innovation day & User Group Meeting, New Delhi on 25th Nov 2015

Evaluating StationFacilities through

SimulationPresented by: Rohan ModiGuide: Prof. H.M. Shivanand Swamy

o Background

o Literature review

o Data collection

o Base Model

development & Output

o Scenario development

o Findings and

recommendations

Presentation Overview

2Evaluating Station Facilities Through SimulationC E P T University, Ahmedabad

BackgroundIntroductionResearch ObjectiveScope & LimitationsResearch Methodology


o Develop a methodology to assess transit station capacity using

microsimulation model

o To demonstrate physical constraints of Maninagar railway station

4

Introduction

Research Objective

o Rail based transit system are one of most Efficient and Economic, offers

Shorter Travel Time and expected to enhance PT share.

o Attempts are to build passenger friendly stations

o Density, Walking Distance and Transfer Time as performance

assessment tool

o Assessment through Manual Method and Simulation

o Simulation represents Effective Visualization and Detailed Analysis

Evaluating Station Facilities Through SimulationC E P T University, Ahmedabad

Scope & Limitations

5

o The model created in PTV VISSIM is applicable to Maninagar railwaystation only. It is created for the paid areas of the station only.

o There are certain loop holes in infrastructure that can’t be incorporatedin model.

Research MethodologyIntroduction

Literature study

Case study

Data collection

Base modeldevelopment

Modelcalibration

Analysis

Aim andObjective

Scope andLimitation

LOSidentification

Evaluationstandards

Data needed

Process

Surveymethodology

Scenariodevelopment

Conclusion andrecommendation


Literature ReviewIntroduction toperformance AssessmentSummary of case studies


7

Introduction to Performance Assessmento A qualitative measure, Level of Service is generally used for the

performance assessment.o Density criteria by John J. Fruin in 1971

LOS Walkway ( ) Queuing area/Platforms( ) Stairway ( )

LOS A <0.27 <0.85 <0.52

LOS B 0.27 to 0.43 0.85 to 1.11 0.52 to 0.71

LOS C 0.43 to 0.71 1.11 to 1.58 0.71 to 1.11

LOS D 0.71 to 1.07 1.58 to 3.70 1.11 to 1.42

LOS E 1.07 to 2.17 3.70 to 5.55 1.42 to 2.5

LOS F >2.17 >5.55 >2.5Source: Pedestrian Planning and Design, J.J.Fruin, 1971

o The same criteria has been adopted by HCM, TCQSM.o The Manual for standards and specifications for railway station by

Ministry of Railways, India also follows the same criteria.o The Manual suggest that operational LOS should be LOS C for all the

infrastructure.


8

Introduction to Performance Assessment

LOS BFree circulation,occasional needto adjust path

LOS AFree circulation,

Ability to move indesired path

LOS CSlightly restricted

circulation,Frequent need to

adjust path

LOS DCirculation without

touching isimpossible,

overpassing slowerpedestrian is

restricted

LOS ERestricted

circulation for allpedestrians,

Limited abilitypass slowerpedestrian

LOS FComplete

breakdown incirculation, Can’t

pass slowerpedestrian

Source: Author


9

Summary of case studiesMetrotown

station,Burnaby

Railway stationin South Africa

North Melbournestation, Victoria

o Data needed for the study such as station layout, trainschedule, passenger volume, speed has been identified

o Methodology has been finalised


Data CollectionWhy Maninagar?Introduction to MRSData CollectionMethodologyObservation from DataCollection


11

Why Maninagar?

SabarmatiRailwaystation

AhmedabadRailway Station

ManinagarRailway Station

o Train frequency fromAhmedabad railway stationtowards South direction ishigher compare to Northdirection

o Well connected by urbantransport

o Due to thesecharacteristics, ManinagarRailway station has higherpassenger load thanSabarmati Railway station


12

Introduction to Maninagar Railway Station

PF 2 (Towards Mumbai)

PF 1 (Towards Ahmedabad) 1 2

3N

BRTS

AMTS Terminal

AMTS

AMTS


13

Data Collection Methodology

Trainschedule

Defining peakperiod

Passengercount

Speedsurvey

Classified Inand out countat entrances

and FOB

Speed ofpedestrian withrespect to age,gender, Group,

Luggage

Data collection

Secondarydata Primary data

Stationlayout



14

Defining Peak

0

1

2

3

4

Trai

ns

Time

Daily trains2 Local and2 Express

trains3 Local and3 Express

trains



14

Speed Survey

o Speed varies with, Group behaviour, Luggage characteristics Gender Age

Videography Survey Location

PF 2

PF 1 1 2

43

N

1 2

3


16

Observation from Survey

Train Name Platformnumber

Type oftrain

Remarks

Surat Jamnagar Intercity1 Express

Train is not schedule to stop but due tosome reason stopped during surveyperiod

Gujarat Queen Express 2 ExpressGorakhpur – OkhaExpress

1 Express

This is weekly train which is scheduled toarrive at 5:20 p.m. but due to somereason it was delayed and arrived duringsurvey period.

Ahmedabad Memu 1 LocalNavjivan Express 1 ExpressSaurashtra Express 1 ExpressGaribrath

1 ExpressTrain is not schedule to stop but due tosome reason stopped during surveyperiod

Anand Memu 2 LocalGandhinagar Memu 1 Local


17


0

50

100

150

200

250

300

350

400

05:4

5

05:5

0

05:5

5

06:0

0

06:0

5

06:1

0

06:1

5

06:2

0

06:2

5

06:3

0

06:3

5

06:4

0

06:4

5

06:5

0

06:5

5

07:0

0

07:0

5

07:1

0

07:1

5

07:2

0

07:2

5

07:3

0

07:3

5

07:4

0

07:4

5

07:5

0

07:5

5

08:0

0

PASS

ENGE

RS

TIME

Passenger count

Entry Exit Trains on PF2Trains on PF1

o Total passenger volume is 5483.o Higher alighting volume than boarding volumeEvaluating Station Facilities Through SimulationC E P T University, Ahmedabad

18



o Gate 2 is predominant entry-exit point.o The passengers are daily commuters.

Base Model Development & OutputIntroduction to SocialForce ModelModel LimitationsMethodology for ModelDevelopmentModel CalibrationModel ValidationOutput


20

Introduction to Social Force Modelo Through Viswalk as an add-on module in Vissim, it is possible to simulate

high volume of pedestrian traffic and analyse only pedestrian situation orinteraction of pedestrian traffic with vehicular traffic.

o In Vissim, vehicular traffic behaviour is based on Wiedemann’s phycho-physical car-following model while pedestrian traffic is based on SocialForce Model by Helbing & Molnar.

o The model considers pedestrian motion is subjected to forces and due tothis forces, pedestrian move in certain direction.

Source: http://futurict.blogspot.in/2014/12/social-forces-revealing-causes-of.html

F= + + +


21

Model Limitationso Uniform alighting-boarding has been from each coach.

o Passenger input is just outside of the station area. If locationchanged then it may affect density at bottlenecks.

o It is not possible to visualise passengers travelling withluggage and with family or group with exact composition.

o The passengers waiting at station by occupying seatingarrangements are not possible to visualise.

o The passengers in waiting area tend to move if and whencongestion increases however the same is not true in themodel.


22

Methodology for Model Development

Modelling PTinfrastructure

Modellingboardingpassenger

volume

Modellingalighting

passengervolume

Calibrationand validation

Passengerroutingdecision

Passenger O-D andcomposition

Train schedule

Static potential, dynamicpotential and partial

routes

Behavior parameters,GEH Statistics,

Speed,Screen line check

Station layout


23


Modelling PT Infrastructure

o Railway Track, PT Lines & PT Stops Different stops & PT lines for different trains

o Waiting Area & Platform Edge Physically it is a single unit but in model it differs Waiting area behaviour such as Wait at Fixed Location & Wait if held

up

o Stairs Access to Station area FOB

o Supporting Infrastructure Seating arrangements, water hut, commercial outlets and columns of

station building platform sheds, traction line & pedestrian RoB Obstacle distance of 0.5m


24


Modelling Boarding-Alighting Volumes

o Passenger Input Passenger input at 5 min interval as counted from each gate. Stochastic variation

o Passenger Composition Relative Flow for each category is modelled for passenger entering

from each gate and Alighting from each traino Speed

Desired speed for each category in from of S- shaped curve Maximum & Minimum speed for each category

o Boarding Volumes Interaction between platforms calculated using passenger count at

entry-exit and FOB for 5 min time interval Boarding volume assigned to only trains which are coming from

Ahmedabad railway station or going beyond Ahmedabad railwaystation

o Alighting Volumes Passenger going out from each gate within 10 mins from train arrival

is considered as alighting volume


25


Passenger Routing Decisions

o It is human tendency to minimize travel time to their decision.

o Shortest path may not be quickest path

o Thus static route with dynamic potential is considered which is function ofgeneral strength “g” and directional impact “h”


26

Model Calibration

o The calibration is a process by which one tries to fit the accuracyof the model with existing situation.

o Two type of calibration process System Calibration Operation Calibration

o Model calibrated by adjusting behaviour parameters.

o These parameters governs passengers characteristics such asreaction time, distance from obstacles and passengers, strengthbetween passengers, directions, evading distance and randomforce.

o There is no study available for relationship between change inparameter value and change in behaviour.


27

Model Calibration

Walkingbehaviourparameter

Explanation Change Effect Defaultvalue

Adjustedvalue

Tau (τ) Tau can be interpreted asreaction time which can berelated to inertia or relaxationtime. It relates the differencebetween desired speed anddesired direction withcurrent speed and direction.It can be consider as thedriving force.

Increase Increases pedestrianacceleration, decreasedensity at the bottleneck,increases radius nearobjects

0.4 0.6

React to n Related to social forceconsidered for the pedestrianmovement. It determines themaximum number ofpedestrians to be considerduring calculation of socialforce

Decrease It makes pedestrians morejitter and increase densityat the bottleneck, leads toformation of the group

8 5

Lambdamean (λ)

It considers the event andpedestrians behind apedestrian do not affect themovement of pedestrian

Increase Counter flow more efficient,flow through bottleneckdepending on the size ofjam,makes pedestrian pushmore

0.176 0.35


28

Model Calibration

Walkingbehaviourparameter

Explanation Change Effect Defaultvalue

Adjustedvalue

A socialIsotropic,A socialMean,B socialIsotropic,B SocialMean

Governs the directiondependency forcebetween two pedestrians

Increase Counter flow is handledvery smoothly,Lower density at thebottleneck,higher headwaybetween passengers

2.720,0.20,0.4,2.8

3.5,0.3,0.45,3

VD Decides when to evadeopposite pedestrian

Increase Increase distance forevade

3 4

Noise Parameter governs therandom force

Increase Prevents deadlocks 1.2 1.5

Grid size The distance at whichpedestrians have aneffect on each other

Decrease Reduce the maximumdistance of theinfluence

0.5 m 0.5 m


29

Model Validationo Validation is the process by which one checks the accuracy of

the model.o It determines how closely the simulation model is replicating the

actual study area based on the validation targets set.

Parameter Satisfying CriteriaGEH Statistic <5

Speed <15%

Screen line accuracy <5%

Source: Traffic Modelling Guidelines, Transport for London, 2010

o GEH statistic is generally use to check the goodness to fit of the model

o GEH= ( )( )Where K is observed flow

M is modelled flow

o GEH should be less than 5 for more than 85% cases of total run


30

Model Validation

GEH Statistics

55006365

42434774

6895

5266

6278

41804656

6733

0

1000

2000

3000

4000

5000

6000

7000

8000

1 2 3 4 5

Pass

enge

rsPassenger volume

Observed volume Modelled volume

2.96

1.09 0.97 1.09

1.96

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

1 2 3 4 5

GEH

Valu

e

Simulation run

GEH value

GEH is less than 5 for all cases, hence model isaccurate


31

Model Validation

Speed by Category

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Aver

age

Spee

d(k

mph

)

Passenger category

Average speed

Simulated Average speed Observed Average speed

o Maximum variation is 10%


32

Model Validation

Speed by Characteristics

0

1

2

3

4

Minor Young Elder Older

Spee

d (k

mh)

Age

Simulate average speed Observed average speed

0

1

2

3

4

Individual Group

Spee

d (k

mph

)

Group and individual

Simulated Average speed Observed average speed

0

1

2

3

4

Male Female

Spee

d (k

mph

)

Gender

Simulated average speed Observed average speed

0

1

2

3

4

Without luggage with luggage

Spee

d (k

mph

)

Luggage characteristics

Simulated average speed Observed average speed

o Maximum variation is 11%


0

15

30

45

60

75

90

105

120

135

150

165

180

195

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Pass

enge

rs

Simulation seconds

Passenger Flow

Simulated flow Observed Flow

33

Model Validation

Screen Line Accuracy

o Model is 99% accurate for total screen line flow


34

Model Output

LOS A

LOS B

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds

Average density

Platform 1 Platform 2 Trains on PF2Trains on PF1

LOS on Platforms


35

Model Output

LOS on FOB

LOS A

LOS BLOS C

LOS D

0

0.2

0.4

0.6

0.8

1

1.2

1.4

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (p

ed/m

2)

Simulation seconds

Average density on FOB

Avergae density Trains on PF2Trains on PF1

MaximumLOS B for 3

minutes


36

Model Output

LOS on Sections near gates

LOS A

LOS B

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds

Average density near gates

Gate 1 Gate 2 Gate 3 Trains on PF2Trains on PF1


37

Model Output

Sections


38

Model Output

Sections

LOS A LOS B


39

Model Output

Summaryo Both Platforms operate at level of service Ao Foot over bridge operates at Level of Service Bo All the sections operates at LOS A

o Thus infrastructure is underutilised.


Scenario DevelopmentMinistry of Railways, IndiaVolume increased by 50%Volume increased by100%


41

Scenario Development

ScenarioDevelopment tocheck capacity

As per Manual forstandards and

specifications forstation design by

Ministry ofRailways, India

50% increasein volume

100%increase in

volume

IdentifyingBottlenecks tocheck capacity


42

As per Ministry of Railways, India

LOS on Platforms

LOS A

LOS B

0.00

0.20

0.40

0.60

0.80

1.00

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds

Average density


LOS on FOB

LOS ALOS BLOS CLOS D

00.20.40.60.8

11.21.4

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (p

ax/m

2)

Simulation seconds

Average density

Average density

Maximum LOSC

Trains on PF2Trains on PF1


43


LOS on Sections near Gates

LOS A

LOS B

LOS C

LOS D

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds



MaximumLOS D faced

by 1%passengers


44


LOS on Various Sections

% Passengers under LOS

LOS A LOS B LOS C LOS D

Bottlenecks

0%

50%

100%

1 2 3 4 5 6 7 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 44% o

f pas

seng

ers

Section number

% of passengers under LOS

LOS A LOS B LOS C LOS D LOS E LOS F

LOS D facedby 1%

passengersonly..


45

Volume Increased by 50%

LOS on Platforms

LOS on FOB

LOS A

LOS B


0

0.2

0.4

0.6

0.8

1

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds

Average density

Platform 1 Platform 2


-0.1

0.4

0.9

1.4

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds

FOB

Average Density Trains on PF2Trains on PF1

Maximum LOS Dfaced by 1%passengers


46



LOS A

LOS B

LOS C

LOS D

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds




47



% Passengers under LOSLOS A LOS B LOS C LOS D

Bottlenecks

0%

50%

100%

1 2 3 4 5 6 7 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 44% o

f pas

seng

ers

Sections

% of passengers


LOS D facedby 1%

passengersonly..


48


LOS on Platforms

LOS on FOB

LOS A

LOS B

0

0.2

0.4

0.6

0.8

1

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds

Average density




0

0.5

1

1.5

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds

Average density

FOB


49




LOS A

LOS BLOS C

LOS D

0

0.5

1

1.5

2

2.5

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds

Average density

Gate 1 Gate 2 Gate 3

Maximum LOSD, when 2 trainsarrives within 10

minutes timeperiod


50



% Passengers under LOSLOS A LOS B LOS C LOS D

Bottlenecks

0%

20%

40%

60%

80%

100%

1 2 3 4 5 6 7 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 44

% o

f pas

seng

ers

Section number

% of passenger


21%passenger

faces LOS Don section 31


Findings & RecommendationsFindingsRecommendations


52

Findingso The worst case in all the scenario is when two train arrives on platform 1

within time period of 10 minutes.

Scenario detail BottlenecksBase scenario None

Scenario 1: Capacity check as perMinistry of Railways

Gate 2

Section besides FOB on PF 1

Scenario 2: Volume increased by 50% Gate 2

FOB

Section beside FOB on PF1

Scenario 3: Volume increased by 100% Gate 2

FOB

Section near FOB on PF1

Section beside FOB on PF 1


53

Recommendationso As there is no issue of infrastructure in scenario 1, trains can be

terminate at Maninagar railway station instead of Ahmedabadrailway station.

o To improve Level of service at gate 2, it is recommended toprovide alternative exit point.

o To improve level of service on FOB, it is recommended to increasewidth of FOB, to provide another FOB. Instead of steps,Escalators/lift can be tested for the level of service.

o The recommendation with increasing FOB width is considered asanother scenario and analysis is carried out.

o By increasing width it is found that the level of service on theFOB has improved along with sections near FOB.


54

Recommendationso The scenario with increased width of FOB has been tested

with volume increased by 100%.


0

0.2

0.4

0.6

0.8

1

300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 8100 8400

Dens

ity (P

ax/m

2)

Simulation seconds

FOB

Average densityTrains on PF2Trains on PF1

0%

20%

40%

60%

80%

100%

Base scenario Scenario 1 Scenario 2 Scenario 3 Recommendation scenario

% o

f pas

seng

ers

LOS

% of Passengers under LOS



55

Recommendations

0%

20%

40%

60%

80%

100%

Base scenario Scenario 1 Scenario 2 Scenario 3 Recommendation scenario

% o

f Pas

seng

ers

LOS

% of Passengers on section near FOB on PF2


0%

20%

40%

60%

80%

100%

Base scenario Scenario 1 Scenario 2 Scenario 3 Recommendation scenarion

% o

f pas

seng

ers

LOS

% of Passengers on section near FOB on PF1



56

Conclusiono VISSIM- an important tool to analyse pedestrian

infrastructure Capacity Bottlenecks Alternative analysis

o Further scope of work using VISSIM Analysis of decision making area Analysis of ITS improvement and pedestrian infrastructure for the

station Evacuation study for station Alternative analysis for physical integration of Maninagar railway

station and BRTS station


Thank you..


57

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