neil douglas cilt talk 9/4/2014 how many people can you ......
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How many people can you get on a train and how long does it take to get them on and off?
CILT talk By Neil Douglas April 9th 2014
Neil Douglas CILT Talk 9/4/2014
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How many people can you get on a train and how long does it take to get them on and off?
Neil Douglas CILT Talk 9/4/2014
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Neil Douglas CILT Talk 9/4/2014
Japan
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Neil Douglas CILT Talk 9/4/2014
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The UK
Neil Douglas CILT Talk 9/4/2014
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Wellington Auckland
Relevant to single/double deck bus introduction in NZ: Seats/capacity v bus stop dwell time
NZ
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Neil Douglas CILT Talk 9/4/2014 Back to Sydney
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North West Rail Link circa 2004
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$400 million wasted on Metro project - INSW
“a number of major projects that have been selected have either been delayed or cancelled – notably the Sydney metro, a $400 million bill for taxpayers for nothing at all. The underlying failures leading to these outcomes have been poor planning and project selection rather than an inability to deliver”. Infrastructure NSW
NWRL morphed into a metro project
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Slide Courtesy of Sandy Thomas
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Note – old – new developments But the aim of a new through CBD rail line is still being considered
New Sydney CBD Rail Link
Latest plans to link NS and Bankstown lines with a metro style operation
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Slide Courtesy of Sandy Thomas
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Slide Courtesy of Sandy Thomas
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Slide Courtesy of Sandy Thomas
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Slide Courtesy of Sandy Thomas
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NOTE!
That’s some background So what was my ‘secret’ report about?
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Acknowledge: Client: Gary Davey and Scott De Martino, TfNSW; Ian Kearns TfNSW (statistics on-time running ) Michael Doggett of TfNSW (dwell time survey data). Following experts for information and advice: Paul Stanley & Marc Caplan of Arup (station pedestrian simulation) Malcolm Bradley & Pascal Suisse, Parsons Brinckerhoff (station & train simulation ) Prof Keith Still of Bucks New University UK (crowd modelling) Prof Luis Ferreira Univ. of QLD (views on crowd modelling) Peter Howarth Interfleet & John Rosser Institute of Electrical Engineers UK (Thameslink and CrossRail London) Peter Thornton & Alex Wardrop (static capacity modelling) Andrew Mein (AureAlis simulation) Uli Mohr, Rail Management Consultants Australia (views on integrating dwell time into rail simulation).
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What is the best analysis tool to answer: What is the feasible peak capacity in passengers per hour on the existing North Shore rail line between Chatswood and Redfern? Is it possible to increase train frequency, and hence to lower the boardings and alightings, the train and platform loadings and hence the dwell times? What would be the Dwell times for a new rail line? What would the dwell time be with single deckers?
The questions my study aimed to help answer
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Douglas Economics was asked to:
Look at TfNSW’s required outcomes from a computational model. Identify the constraints on passenger carrying capacity Undertake a desktop review of studies that had been undertaken to date Undertake a review of products available within the marketplace against the desired TfNSW outcomes (notably simulation models versus static models)
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The situation on the North Shore Line in 2011
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Train Passenger Capacity Seats + Standing
Max/Passengers/Train/Hour
Train Line Capacity Max Trains /Hour
Signalling Clearance Time
Train Dwell Time at Stations
Station/Platform Passenger Capacity
Max Passengers/Hour
Line Capacity Passengers/Hour
Train Passenger Capacity
Max Passengers /Hour
Station Capacity: Platform Width
Vertical Transport Capacity Accessway/Concourse
Capacity Ticket Barriers/Machines
Douglas Economics DwellModels.ppt
Station Access/Egress & Bus Interchange
Capacity
Train/Line Capacity Station Capacity
Factors Determining Rail Capacity
Demographic/ Socio-
econ factors e.g. size, gender
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Standards
Demand Capacity Modelling
Inter-relationships
E.g. nobody should stand for more than 20 minutes – Sydney Customer Service Obligation 23
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Train Service Standards
Station Standards
Space Occupancy &
Flow Circulation
Service Reliability
Passenger Capacity
Evacuation Standards
Capacity & Level of Service Standards
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Types of Approach: Static and Dynamic Modelling Approaches
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Capacity Double
Deck
Single
Deck
Comment
Seated
Capacity
900 400 Rounded figures (Waratah has 896 seats)
Nominal
Capacity
1,200 900 Standing in double deck vestibules
(19/vestibule) only and at approximately
2P/M2 for single deck
Peak Capacity 1,400 1,120 Double deck maximum load observed on
Western Line; 3P/M2 for single deck
Max Capacity 1,750 1,350 Standing at 4P/M2. Only observed at
special events
Question 1: How many people can you get on a train?
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Capacity also a ‘flow’ – more than one train Single v Double Decker Trains
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Assessment of Train Type & Signalling Control
Passenger Capacity (Pax/hr) Alternative train types (Existing Signalling)
Double-deck 20tph Normal load 24,000 Double-deck 20tph Peak load 28,000 Single-deck 22tph Normal load 19,800 Single-deck 22tph Peak load 25,000
Passenger Capacity (Pax/hr) with enhanced Signalling (ETCS Level 2)
Double-deck 24tph Normal load 28,800 Double-deck 24tph Peak load 33,600 Single-deck 26tph Normal load 23,400 Single-deck 26tph Peak load 29,200
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The cost of crowding
Comfort & Safety Issues
Train Station
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Train Crowding Comfort Cost Function
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Station Crowding – A ‘Comfort’ Cost Function
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Dwell time: Question 2: Long it will take to get people on an off? Modelling Approaches:
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Passenger Volume -Number boarding and alighting - flow composition -Onboard through travelling passengers -Load distribution through train
Passenger Profile - Mobility Status (old/infirm/wheelchair) - Journey Purpose (commuters, leisure trips, school children) - Regularity (familiarity) - Size of the passengers - Culture/religion
Train Design -Door opening/closing speed -Door Number and Width - Seat Configuration -Double/single deck -Aisle width - Vestibule Size
Platform Design -Stairs/escalators/lifts (number, capacity, location) -Distribution of passengers along platform -Platform Width (level of passenger crowding) -Door/platform step height and gap -Platform Signing, Seating
Dwell Time
Timetable Factors - Service Frequency & Pattern -Timed / Untimed Stop - Planned interchange -Crew change
Factors affecting Train Dwell Time
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Dwell Time
Cruise Speed
Arrival Time
Departure Time
Station A Depart Time
Station B
Spe
ed
Elapsed Time
Passenger Dwell Time
Doors Open & Close
Awaits Departure
Statistical Models of Train Dwell Time
The bit which varies with passenger numbers 35
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Algorithm:
Ultimate Client Aim : Predict the dwell times for an individual train for a station Based on board and alight numbers, train design, onboard passenger load and distribution by carriage, platform layout (escalator/staircases) and passenger distribution along platform. Extend algorithm into a forecasting model for a particular line Feed in timetable data and patronage forecasts. Repeat the dwell time calculations for successive train stations for a particular service.
Static Models
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Train Dwell Time Models (Algorithms):
London Underground Line – Train Service Model Massachusetts Bay Transport Authority Boston Douglas Economics – Sydney Data TMG Nomogram – other factors
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London Underground Dwell Time Algorithm
Predicted Train Dwell using LUL Formula
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Boston Dwell Time Model
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Plat Time Survey Sample Passenger Dwell (secs) Alight + Board Passengers
Station Number Period Date Size Average Min Max Average Min Max
Central 17 AM 9/11/2006 29 23 6 53 32 11 63
Town
Hall 2 PM 8/11/2006 102 33 10 81 47 9 86
Town
Hall 3 AM 16/11/2006 32 33 12 67 40 18 71
Town
Hall 4 PM 10/4/2007 35 20 4 46 32 9 60
Town
Hall 5 AM 10/4/2007 32 26 11 65 35 13 89
Wynyard 3 AM 15/11/2006 16 23 0 60 31 0 78
Total na na na 246 28 0 81 40 0 89
RCTables
RailCorp Dwell Time Surveys
November 2006 & March 2007
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Passenger Dwell Time v Alighting + Boarding Volume
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Live & Simulated Passenger Dwell Time RailCorp ‘Live’ Surveys at Town Hall, Central & Wynyard &
Simulated Surveys (2006 and 2007)
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Stop to
Doors
Opening
Doors
Open to
Last
Boarder
Last
Boarder
to Doors
Close
Doors
Close to
Train
Depart
Total
Dwell
Sample
Size obs
Average 3 36 19 11 70 65
Max 8 78 70 60 104 65
Min 2 14 4 4 42 65
Components of Dwell Time (seconds) Sydney CBD North-Shore/Main West
ddddd BAStdBdAdBAPFD .005.0))((007.04.19.110 7.07.0
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Predicted Passenger Dwell Times
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Dwell Time Lookup Tables For Double Deck Trains Douglas Economics
Threshold When does the dwell time take longer than a minute?
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Wardrop Nomagram
Relationship between Train Configuration, Passenger Turnover, Station Dwell Time, Signalling System and Hourly Passenger Flow based on Standard Sydney Double Deck Suburban Train
Putting it all together into a static model
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Operational Comparison of Different Suburban Railways and Metro Systems
Source: Alex Wardrop Worley Parsons 47
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Train Service Delayed
Service Interval Lengthens
Passenger Buildup on Platform
Train Board Time Increases
Increased Train Load
Train Delay Increases
Impacts on Other Trains
Train Recovery Time
The Snowball Effect
One train affects the next one
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Train travel times were estimated to increase 50% by Hibino (2010) from passenger crowding As increased station dwell times causes slower train run times.
A Japanese study Passenger crowding on Tokyo Metro
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Different issues in the AM & PM Peaks – Station performance important
Sydney CBD Station Occupancy
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Two types of model: Passenger Movement Models (mostly Station pedestrian crowding models) Train Movement Models
Full solution would require both types of model But data transfer between models was (is still?) a problem - for feasible modelling
Dynamic Models => Simulation Models
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Train Movement Models: ‘Off-the shelf’ Transport Simulation Packages Rail Operations simulation modelling Used for train lines/networks to look at reliability OpenTrack, RAILSYS, RailSIM, Simu++ TRAKATTK. Transport simulation packages Paramics, AimSun Have been used for bus and Light Rail - interchange General simulation packages Eg Arena.
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Double Deck Single Deck
Station Average Range Average Range
Redfern 50 40-60 40 30-50
Central 60 40-80 50 30-70
Town Hall 70 50-90 60 40-80
Wynyard 60 40-80 50 30-70
Milsons Pt 35 25-45 30 30-40
North Sydney 60 40-80 50 50-70
Waverton 25 25-45 30 20-40
Wollstonecraft 35 25-45 30 30-40
St Leonards 40 30-50 30 20-40
Artarmon 35 25-45 30 20-40
Chatswood 50 30-70 40 30-50
PB-CHA Dwell Times (seconds) for North Shore Line
Train Simulation Model
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How do you model dwell time? – a statistical distribution
Dwell times independent – no ‘snow balls’ included
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RMCon – hybrid approach:
German Rail regulation Ril813 for platform and station capacity. Like the TRB framework Divide platform into different functional areas (waiting, walking towards an exit, cueing in front of an escalator, etc) a) model passenger behaviour b) look into ways to manage peoples' behaviour, c) work out different alternatives, such as modifying the platform layout.
Would determine the train dwell times, Input into train operations simulation package RailSYS and provide other outputs Based on alight/board and transfer passengers on platforms “RMCon considered that the method would be quite accurate, although passenger movement simulation could be more accurate by about 1% to 2% but would take significantly more effort time and money.”
Assessment: Improvement on PB’s assumptions but not full simulation or able to model snow balling
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Microscopic or Agent Based Models
Macroscopic Flow Based - PedRoute
Simulation Approaches
Cellular Automata
Swarm Models
Multi-agent Social Force
Econometric Video Surveillance
Based Models
Artificial Life Video Based
Station Pedestrian Simulation Models
To model the train dwell time in congested situation you also have to mode the platform
But this is a second order effect
The wall of passengers
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Pedestrian Simulation Packages
Off the shelf packages Legion NOMAD Paramics Pedflow PedGO PedRoute – LUL SimWalk VISSIM AureALIS - Auckland – used in Melbourne
General Simulation Software Arena Simulation Languages Rindsfuser SeSAM
But where do the parameters come from and how are models validated? No redundancy for observations.
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Rolling Stock Simulations
Beijing – cellular automata – lattice of cells Thameslink – Arup mockup carriage Melbourne Arup (Legion) >>>> Toronto AECOM – (Legion) UK Bombadier – Keith Still
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Comparing Pedestrian Simulation Models Assessment criteria:
Accuracy: in ability to represent station, passengers & behaviour
Computing: Size limitations, computational time & memory consumption
Quality of visual presentation such as 2D, 3D
Presentation & output of results to enable further analysis
User friendliness ease of building models, changing layout & running simulations
AureALIS
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Train & Station Simulation
Unlinked Simulations Fine for most situations There was no linked simulation of train and multiple stations But computing is getting exponentially better....
System Simulation Bus Rapid Transit Line example - VISSIM
Linked Simulation Feed results from station simulation into train operations simulation Data transfer issues takes actual time – so real time simulation? Set up and maintenance cost of models
Dwell Time studies: Still No substitute for statistical observations in actuality not mockup cars compare cities eg Melbourne single decks with Sydney double decks
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Questions?
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