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BRT
Experiences and Challenges
Juan Carlos Muñoz
Bus Rapid Transit Centre of Excellence
Pontificia Universidad Católica de Chile
July 12, 2013
About the BRT Centre of Excellence
• Headquarters: Department of Transport Engineering and
Logistics at the Pontificia Universidad Católica de Chile
• Instituto Superior Técnico from the Lisbon Technical University
• Institute of Transport and Logistics Studies from the University
of Sydney
• Massachusetts Institute of Technology
• EMBARQ Network from The World Resources Institute Centre
for Sustainable Transport
• Other researchers as Orlando Strambi / Eduardo Vasconcellos
Our Vision
BRT systems are a feasible instrument to make metropolitan
areas more sustainable from the economic, financial, social,
political, technical and environmental perspectives, making
them more attractive places to live, work and visit.
We are not a BRT Advocacy agency. Instead, we provide clear
guidelines on when and how BRT projects can effectively
enhance mobility and meet accessibility needs.
Our Main Objective
Develop a new framework for the
planning,
design,
financing,
implementation and
operation
of BRT.
A BRT Observatory: gather, interpret and present BRT data.
Major Outcomes
BRT Observatory
A BRT Observatory:
A BRT Laboratory:
gather, interpret and present BRT data.
develop in-depth understanding of the
factors and relations underlying system
performance, developing or improving
analytical methods and their supporting
instruments.
Major Outcomes
BRT Laboratory
LS1) Structured assessment of BRT performance
LS2) Exploring the complexity of policy design
LS3) From vision to promise to delivery
LT2) Typology and analysis of business plans, contracts and incentives for BRT and urban
mobility systems.
LT3) Determine key elements of higher satisfaction for users and authorities
LT5) Modeling reliability, cost, travel times, safety, comfort and other relevant variables of
modal choice
LO1) Explore innovative ways to manage and control BRT services
O5) Create and provide a benchmark report
O6) Start case studies.
A BRT Observatory:
A BRT Laboratory:
A BRT Educational program:
gather, interpret and present BRT data.
develop in-depth understanding of the
factors and relations underlying system
performance, developing or improving
analytical methods and their supporting
instruments.
deploy the knowledge gained supporting
teaching, education and training for regular
and long-life learning.
Major Outcomes
Educational Program
13th International Conf Series on Competition and Ownership in Land Passenger Transport
Oxford, UK September 15 to 19, 2013.
14th International Conf Series on Competition and Ownership in Land Passenger Transport
Santiago, Chile September, 2015.
• International Workshop in Urban Transport
Sustainability
– Santiago, September 2-4, 2013
– http://iwuts.cedeus.cl/
Educational Program
MONTHLY WEBINAR, NEXT (nineth):
“EMBARQ Brasil and Rio: a partnership to implement a BRT network
for the Olympics 2016”
Prof. Luis Antonio Lindau, the President Director of EMBARQ Brasil
Friday, July 26th, 2013 at 1200 Brazil time
Register with lpaget@uc.cl
Several International Training Programs:
September 2012, Barcelona, Spain
November 2012, Pereira, Colombia
February 2013, Gothemburg, Sweden
July 2013, Rio de Janeiro, Brazil
September 2013, Oxford, UK
A BRT Observatory:
A BRT Laboratory:
A BRT Educational program:
Support Implementation:
gather, interpret and present BRT data.
develop in-depth understanding of the
factors and relations underlying system
performance, developing or improving
analytical methods and their supporting
instruments.
deploy the knowledge gained supporting
teaching, education and training for regular
and long-life learning.
Support one or more cities willing to start a
transformation of their public transport
system.
Major Outcomes
Support implementation
Strategic alliance with the Latin-American Association of Integrated
Transit Systems and BRT (SIBRT)
Outline Today
• Introduction to BRT Systems
• History and current state of the BRT industry
• Integrating safety into BRT planning and operations
• The Customer Experience
• Fare collection in the broader payments
environment
• Near-Capacity Operations
• Regulatory and contractual aspects
Motivation: Efficiency in the use of road space
www.BRT.cl
What can we say about bus service?
Bus is critical to provide a good door-to-door transit alternative
for many journeys:
• Much higher network density and coverage than rail
• Greater flexibility in network structure
• Low marginal cost for service expansion
BUT as traditionally operated, it also has serious limitations:
• Low-speed
• Subject to traffic congestion
• Unreliable
• Harder to convey network to the public
• Negative public image
What can we say about the user?
• Perceives waiting time and walking time twice as important as
travel time inside the vehicle.
• Avoids transferring, specially if they are uncomfortable
• Needs a reliable experience
• Requests a minimum comfort experience
• Requests information
• Needs to feel safe and secure
What are the bottlenecks?
Capacity per lane:
• “Only a fool breaks the two second rule” => 1,800 veq/hr-lane
• 1 Bus ≈ 2 veq => 900 buses/hr-lane
Capacity per lane at junctions:
• 40 – 60 % of lane capacity => 450 buses/hr-lane
Capacity at Bus Stops:
• Depends on the amount of passengers boarding and alighting
• ≈ 20 - 40 sec. per bay => 180 – 90 buses/hr-bay
This feeds this vicious cycle
Operation cost grows
Income and Population
grows
More cars in the city
Bus Demand drops
Car becomes more
attractive
Bus frequency drops Buses cover fewer miles
per day
Bus fare increases
And we need to make buses attractive to car drivers…
More congestion
And delays
However, this doesn’t affect Metro as
much
Can we provide Metro-like service with buses?
• Fast
• Low wait time
• Comfortable
• Reliable
• Good information
• Branding
Can we provide Metro-like service with buses?
Transit Leaders Roundtable MIT, June 2011
• Fast
• Low wait time
• Comfortable
• Reliable
• Good information
• Branding
Yes we can … We still believe
(several pieces are already there in cities worldwide)
Can we provide Metro-like service with buses?
The good news are:
COURAGE WILL BE REWARDED
IMPROVED
EFFICIENCY
IMPROVED
SERVICE QUALITY
Reduced bus
costs
•Less buses required
•Lower cost per km
Improved bus
productivity
•More pax/bus-day
Attracts more
passegers
Improves revenue
IMPROVED
FINANCIAL
VIABILITY
Better buses
More investment into
new buses & cleaner
technology
Lower
Subsidies
Reduced private car use
& traffic congestion
Improved energy
efficiency
Reduced emissions
Operational
benefits
•Shorter cycle time
•Reliable operations
•Higher productivity
Increase Bus speed, Frequency,
Capacity and Reliability Passenger
benefits
•Reduced travel time
•Reduced waiting
time
•Higher comfort
•Reliability
Source: Frits Olyslagers, May 2011
Fast Reliable
Metro
Attributes
Actions
ComfortLow waits
Main
drivers
Increase
Speed
Regular
Headways
Increase
Capacity
Increase
Frequency
(in the afternoon, be patient…)
BRT
Experiences and Challenges
Juan Carlos Muñoz
Bus Rapid Transit Centre of Excellence
Pontificia Universidad Católica de Chile
July 12, 2013
Future of BRT:
Flexible Capacity Operations
Juan Carlos Muñoz and Ricardo Giesen
Bus Rapid Transit Centre of Excellence
Pontificia Universidad Católica de Chile
July 12, 2013
Fast Reliable
Metro
Attributes
Actions
ComfortLow waits
Main
drivers
Increase
Speed
Regular
Headways
Increase
Capacity
Increase
Frequency
•Segregated ways/lanes
Segregated ways/lanes
Low Flow: Intermittent Bus Lanes
Medium Flow: Bus-Only lanes
High Flow and Limited Capacity: Only bus street
J. M. Viegas
Low Flow: Intermittent Bus Lane (IBL)
Demonstration in Lisbon
Implementation: Technical Components
Installation of the Loop Detectors IBL local controller
Static signalization
(advance notice)
Variable message
longitudinal LEDs
Vertical variable message
signal
Ricardo Giesen ©
Without IBL vs. with IBL (51 sec)
Demonstration
Only Bus Lanes
BUS ONLY
Setback!
R. Fernández
Partial closure of streets for cars, but not for buses
Closed Junction (Brussels)Closed lane (Zurich)
P. Furth
Fast Reliable
Metro
Attributes
Actions
Comfort
Increase
Speed
Regular
Headways
Main
drivers
Increase
Capacity
Increase
Frequency
•Segregated ways/lanes
•Reduce dwell times
•Fare payment off-bus
•Buses with multiple doors
Low waits
Guayaquil, Ecuador
Level bording in Quito, Ecuador
Guayaquil, Ecuador
TransMilenio, Bogota, Colombia
TransMilenio
Istanbul BRT
Istanbul BRT
Divided Bus Stops
Bus only street?
Weaving distance: 3-4 bus
R. Fernández
Platform 2 Platform 1
Stop area 2 Stop area 1
Divided bus stop
Divided rail station
Platform 2
Platform 1
R. Fernández
Divided Bus Stops
Fast Reliable
Metro
Attributes
Actions
Comfort
Increase
Speed
Regular
Headways
Main
drivers
Increase
Capacity
Increase
Frequency
•Segregated ways/lanes
•Reduce dwell times
•Fare payment off-bus
•Buses with multiple doors
•Increase distance between stations
Low waits
Fast Reliable
Metro
Attributes
Actions
ComfortLow waits
Increase
Speed
Regular
Headways
Main
drivers
Increase
Capacity
Increase
Frequency
•Segregated ways/lanes
•Reduce dwell times
•Fare payment off-bus
•Buses with multiple doors
•Increase distance between stations
•Express services
Choosing the Right Express Services for a
Bus Corridor with Capacity
Constraints
Homero Larrain, Ricardo Giesen and
Juan Carlos Muñoz
Department of Transport Engineering and Logistics
Pontificia Universidad Católica de Chile
Introduction
Operación “Carretera” Operación Expresa
Higher in-vehicle travel time Lower in-vehicle travel time
No transfers May force some transfers
Higher operation costs, in
terms of $/Km
Lower operation costs, in
terms of $/Km
Other aspects: capacity, comfort, accessibility, etc.
Limited stop servicesAll stop services
*Jointly operated with all stop services,
assuming a constant fleet size.
*
Objective
• Formulate a model that allows to choose
which combination of services to provide on a
corridor, and their optimal frequencies.
• Determine opportunities for express services
(or limited stop) on a corridor based on its
demand characteristics.
The Problem
p1 p2 pi pn
… …
The Problem
• Different operation schemes.
p1 p2 pi pn
… …
… …l1, f1
… …l2, f2
… …l3, f3
… …l4, f4
The goal is to find which services to offer, and their optimal frequencies.
li: Line i
fi: frequency of line i
The Model
• The goal of this model is to find the set of
services that minimize social costs:
– Operator costs: will depend on what services are
provided, and their frequencies.
– User costs:
• In-vehicle travel time.
• Wait time.
• Transfers.
The Model: Assumptions
• Given transit corridor, with a given set of
stops.
• Fares are constant for a full trip.
• Number of trips between stops is known for a
certain time frame.
• Random arrival of passengers at constant
average rate.
• Passengers minimize their expected travel
times.
The Experiment
• Steps:
– Defining network topology.
– Defining demand profiles.
• Load profile shape.
• Demand scale.
• Demand unbalance.
• Average trip length.
– Build scenarios and construct an O/D matrix for each one.
– Optimize scenarios defining the optimal set of lines for
each one.
Express Services: Main Conclusions
• Allow increasing the capacity of the system
• Significantly reduces social costs
• Few services bring most of the benefits
• Limited stop services are more promising in these
situations:
– The longer the average trip length
– High demand
– High stop density
– Demand is mostly concentrated into a few O/D pairs
Fast Reliable
Metro
Attributes
Actions
ComfortLow waits
Increase
Speed
Regular
Headways
Main
drivers
Increase
Capacity
Increase
Frequency
•Segregated ways/lanes and priority at junctions
•Reduce dwell times
•Fare payment off-bus
•Buses with multiple doors
•Increase distance between stations
•Express services
•Traffic signal priority and priority at intersectons
Anticipated Green Light for Buses
R. Fernández
• Move pedestrian crossing
• “Do not block”
Protection of Buses on Right Turns
P. Furth
• Move pedestrian crossing
• “Do not block”
• Exclusive phase for
pedestrian
P. Furth
Protection of Buses on Right Turns
Metro
Attributes
Actions
Increase
Speed
Regular
Headways
Main
drivers
Increase
Capacity
Increase
Frequency
•Segregated ways/lanes
•Reduce dwell times
•Fare payment off-bus
•Buses with multiple doors
•Increase distance between stations
•Express services
•Traffic signal priority and priority at intersectons
•Improved headway control
Fast ComfortLow waits Reliable
Santiago, Chile
Time-space trajectories
Line 201, March 25th, 2009
0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300
0
2.5
5
7.5
10
12.5
15
17.5
20
22.5
25
27.5
30
32.5
35
Tiempo (minutos)
Posición(Km.)
6:30 AM 8:30 AM
Boston, MA; line 1 during winter
Boston, MA; line 1 during summer
Is keeping regular headways that
difficult?
Transit Leaders Roundtable MIT, June 2011
Ricardo Giesen ©
Bus
Bus
Stop Stop
Waiting
Passengers
Waiting
Passengers
Bus Operations without Control
Ricardo Giesen ©
BusBusStop Stop
a small perturbation…
Waiting
Passengers
Waiting
Passengers
Bus Operations without Control
Ricardo Giesen ©
Bus
Bus
Stop Stop
While one bus is still loading passengers the other bus already left its
last stop
Bus Operations without Control
Ricardo Giesen ©
Bus
BusStop Stop
Bus Operations without Control
Ricardo Giesen ©
Bus
Bus
Stop Stop
Without bus control, bus bunching occurs!!!
Bus Operations without Control
Stable versus unstable equilibrium
Stable versus unstable equilibrium
Stable versus unstable equilibrium
Stable versus unstable equilibrium
Stable versus unstable equilibrium
Stable versus unstable equilibrium
+ - + - + - +
+ - + - + - +
+ - + - + - +
+ - + - + - +
And so on so forth.
Our challenge is to keep an inherently unstable system: buses evenly spaced
Now, if we want to prevent bunching from occurring … when is the right time to intervene?
Bus bunching is
specially serious,
where bus capacity
is an active
constraint.
Bus bunching
 Severe problem if not controlled
 Most passengers wait longer than they should for crowded
buses
 Reduces reliability affecting passengers and operators
 Affects Cycle time and capacity
 Creates frictions between buses (safety)
 Put pressure in the authority for more buses
Contribution: Control Mechanism to Avoid Bus Bunching
based on real-time GPS data
2. Research
 Propose a headway control mechanism for a high frequency & capacity-
constrained corridor.
 Consider a single control strategies: Holding
 Based on real-time information (or estimations) about Bus position, Bus
loads and # of Passengers waiting at each stop
 We run a rolling-horizon optimization model each time a bus reaches a
stop or every certain amount of time (e.g. 2 minutes)
 The model minimizes:
Time waiting for first bus + time waiting for subsequent buses + time held
No control
Spontaneous evolution of the system.
Buses dispatched from terminal as soon as they arrive or until the design headway is
reached.
No other control action is taken along the route.
Threshold control
Myopic rule of regularization of headways between buses at every stop.
A bus can be held at every stop to reach a minimum headway with the previous bus.
Holding (HRT)
Solve the rolling horizon optimization model not including green extension or boarding
limits.
Estrategias de control simuladas
4. Experiment: Control strategies
5. Results: Simulation Animation
Simulation includes events randomness
2 hours of bus operation. 15 minutes “warm-up” period.
No HRT
control
Wfirst 4552.10 805.33
Std. Dev. 459.78 187.28
% reduction -82.31
Wextra 1107.37 97.49
Std. Dev. 577.01 122.59
% reduction -91.20
Win-veh 270.57 1649.28
Std. Dev. 36.00 129.56
% reduction 509.57
Tot 5930.03 2552.10
Std. Dev. 863.80 390.01
% reduction -56.96
Results: Time savings
Results: Time-space trajectories
0 20 40 60 80 100 120
0
1
2
3
4
5
6
7
8
9
10
s2 NETS sc corrida17
Distance(Km)
Time(minutes)
HRT
0 20 40 60 80 100 120
0
1
2
3
4
5
6
7
8
9
10
Scenario 1 threshold run17
Distance(Km)
Time(minutes)
No Control
This impacts comfort, reliability for users and for operators
Results: Bus Loads
0 5 10 15 20 25 30
0
20
40
60
80
100
120
Scenario 1 HBLRT alpha=05 Beta=05
Load(Pax.)
Stop
HRT
0 5 10 15 20 25 30
0
20
40
60
80
100
120
Scenario 1 HBLRT alpha=05 Beta=05
Load(Pax.)
Stop
No Control
Results: Cycle Time
25 30 35 40 45
0
50
100
150
200
250
300
350
mean =33.64
Std.Dev. =3.51
No control
Frequency
Cycle Time (Minutes)
25 30 35 40 45
0
50
100
150
200
250
300
350
mean =32.11
Std.Dev. =1.2
HRT 05
Frequency
Cycle Time (Minutes)
HRTNo Control
5. Results: Waiting time Distribution
% of passengers that have to wait between:
Period 15-25 Period 25-120
0-2 min 2-4 min > 4 min 0-2 min 2-4 min > 4 min
No Control 57.76 29.60 12.64 63.46 27.68 8.86
HRT 79.24 20.29 0.47 87.30 12.62 0.08
Disobeying
Drivers
Similar
disobedience
across all drivers
A subset of
drivers never
obey
Technological
Disruption
Random signal
fail
Failure in the
signal receptor
equipment
Signal-less
zone
Homogeneous
distribution across
buses
Concentration in
certain buses
Concentration in
certain stops
6. Impact of implementation failures
Impact of implementation failures
Common disobedience rate across drivers
8000
9000
10000
11000
12000
13000
14000
15000
0%10%20%30%40%50%60%70%80%90%100%
TotalWaitingTime[Min]
Obedience rate
HRT, Beta=0,5
Sin Control
Full disobedience of a set of drivers
8000
9000
10000
11000
12000
13000
14000
15000
16000
0 1 2 3 4 5 6 7
TotalWaitingTime[Min]
Deaf Buses from a total of 15 buses
Implementation
• The tool has been tested through two pilot plans in
buses of line 210 of SuBus from Transantiago
(Santiago, Chile) along its full path from 7:00 to 9:30 AM.
• We chose 24 out of 130 stops to hold buses
• One person in each of these 24 stops received text
messages (from a central computer) into their cell
phones indicating when each bus should depart from the
stop.
Plan Description
Implementation
Real time GPS
information of
each bus
Program optimizing
dispatch times for each
bus from each stop
Text messages were sent
automatically to each person
in each of the 24 stops
Buses are held according to
the text message instructions
(never more than one minute)
Control Points
The results were very promising
even though the conditions were far
from ideal
Main results
• Transantiago computes an indicator for
regularity based on intervals exceeding twice
the expected headway (and for how much).
$ 10,000
$ 20,000
$ 30,000
$ 40,000
$ 50,000
$ 60,000
$ 70,000
$ 80,000
$ 90,000
$ 100,000
$ 110,000
Multas($CLP)
Main results: cycle times
2:24:00 AM
2:31:12 AM
2:38:24 AM
2:45:36 AM
2:52:48 AM
3:00:00 AM
3:07:12 AM
3:14:24 AM
3:21:36 AM
3:28:48 AM
3:36:00 AM
5:52:48 AM6:00:00 AM6:07:12 AM6:14:24 AM6:21:36 AM6:28:48 AM6:36:00 AM6:43:12 AM6:50:24 AM6:57:36 AM
Cycletime
Dispatch time
Piloto 1
Prueba10
Prueba12
Prueba13
Prueba15
Prueba16
Prueba17
 No significant differences for cycle times
• Line 210 captured an extra 20% demand!
94,000
96,000
98,000
100,000
102,000
104,000
106,000
7,400 7,600 7,800 8,000 8,200 8,400 8,600 8,800
Demand for Line 210 (pax)
Demand on
All lines
(pax)
Unexpected result
8. Conclusions
Developed a tool for headway control using Holding in real time reaching
simulation-based time savings of 60%
Huge improvements in comfort and reliability
The tool is fast enough for real time applications.
Two pilot plans have shown significant improvements in headway regularity.
During 2013 we will build a prototype to communicate directly to each driver.
Publications and working papers
• Delgado, F., Muñoz, J.C., Giesen, R., Cipriano, A. (2009) Real-Time Control of Buses in a
Transit Corridor Based on Vehicle Holding and Boarding Limits. Transportation
Research Record, Vol 2090, 55-67
• Munoz, J.C. and Giesen, R. (2010). Optimization of Public Transportation Systems.
Encyclopedia of Operations Research and Management Science, Vol 6, 3886-3896.
• Delgado, F., J.C. Muñoz and R. Giesen (2012) How much can holding and limiting
boarding improve transit performance? Trans Res Part B, , vol.46 (9), 1202-1217
• Muñoz, J.C., C. Cortés, F. Delgado, F. Valencia, R. Giesen, D. Sáez and A. Cipriano
(2013) Comparison of dynamic control strategies for transit operations. Trans Res Part C.
• Hernández, D., J.C. Muñoz, R. Giesen, F. Delgado (2013) Holding strategy in a multiple
bus service corridor. Accepted at TRISTAN conference.
• Phillips, W., J.C. Muñoz, F. Delgado, R. Giesen (2013) Limitations in the
implementation of real-time information control strategies preventing bus bunching.
Accepted at WCTR conference
Other activities
• Three chilean operators will test our tool this year
• Raised interest from operators in Cali and Istanbul
• A research and development team is consolidating
• Pedagogic tool to teach bus headway control
Minimizing Bus Bunching
A strategy that cuts wait times, improve comfort
and brings reliability to bus services
Juan Carlos Muñoz
Bus Rapid Transit Centre of Excellence
Department of Transport Engineering and Logistics
Pontificia Universidad Católica de Chile
Future of BRT:
Flexible Capacity Operations
Juan Carlos Muñoz and Ricardo Giesen
Bus Rapid Transit Centre of Excellence
Pontificia Universidad Católica de Chile
July 12, 2013

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BRT Workshop - Intro

  • 1. BRT Experiences and Challenges Juan Carlos Muñoz Bus Rapid Transit Centre of Excellence Pontificia Universidad Católica de Chile July 12, 2013
  • 2. About the BRT Centre of Excellence • Headquarters: Department of Transport Engineering and Logistics at the Pontificia Universidad Católica de Chile • Instituto Superior Técnico from the Lisbon Technical University • Institute of Transport and Logistics Studies from the University of Sydney • Massachusetts Institute of Technology • EMBARQ Network from The World Resources Institute Centre for Sustainable Transport • Other researchers as Orlando Strambi / Eduardo Vasconcellos
  • 3. Our Vision BRT systems are a feasible instrument to make metropolitan areas more sustainable from the economic, financial, social, political, technical and environmental perspectives, making them more attractive places to live, work and visit. We are not a BRT Advocacy agency. Instead, we provide clear guidelines on when and how BRT projects can effectively enhance mobility and meet accessibility needs.
  • 4. Our Main Objective Develop a new framework for the planning, design, financing, implementation and operation of BRT.
  • 5. A BRT Observatory: gather, interpret and present BRT data. Major Outcomes
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12. A BRT Observatory: A BRT Laboratory: gather, interpret and present BRT data. develop in-depth understanding of the factors and relations underlying system performance, developing or improving analytical methods and their supporting instruments. Major Outcomes
  • 13. BRT Laboratory LS1) Structured assessment of BRT performance LS2) Exploring the complexity of policy design LS3) From vision to promise to delivery LT2) Typology and analysis of business plans, contracts and incentives for BRT and urban mobility systems. LT3) Determine key elements of higher satisfaction for users and authorities LT5) Modeling reliability, cost, travel times, safety, comfort and other relevant variables of modal choice LO1) Explore innovative ways to manage and control BRT services O5) Create and provide a benchmark report O6) Start case studies.
  • 14. A BRT Observatory: A BRT Laboratory: A BRT Educational program: gather, interpret and present BRT data. develop in-depth understanding of the factors and relations underlying system performance, developing or improving analytical methods and their supporting instruments. deploy the knowledge gained supporting teaching, education and training for regular and long-life learning. Major Outcomes
  • 15. Educational Program 13th International Conf Series on Competition and Ownership in Land Passenger Transport Oxford, UK September 15 to 19, 2013. 14th International Conf Series on Competition and Ownership in Land Passenger Transport Santiago, Chile September, 2015. • International Workshop in Urban Transport Sustainability – Santiago, September 2-4, 2013 – http://iwuts.cedeus.cl/
  • 16. Educational Program MONTHLY WEBINAR, NEXT (nineth): “EMBARQ Brasil and Rio: a partnership to implement a BRT network for the Olympics 2016” Prof. Luis Antonio Lindau, the President Director of EMBARQ Brasil Friday, July 26th, 2013 at 1200 Brazil time Register with lpaget@uc.cl Several International Training Programs: September 2012, Barcelona, Spain November 2012, Pereira, Colombia February 2013, Gothemburg, Sweden July 2013, Rio de Janeiro, Brazil September 2013, Oxford, UK
  • 17. A BRT Observatory: A BRT Laboratory: A BRT Educational program: Support Implementation: gather, interpret and present BRT data. develop in-depth understanding of the factors and relations underlying system performance, developing or improving analytical methods and their supporting instruments. deploy the knowledge gained supporting teaching, education and training for regular and long-life learning. Support one or more cities willing to start a transformation of their public transport system. Major Outcomes
  • 18. Support implementation Strategic alliance with the Latin-American Association of Integrated Transit Systems and BRT (SIBRT)
  • 19. Outline Today • Introduction to BRT Systems • History and current state of the BRT industry • Integrating safety into BRT planning and operations • The Customer Experience • Fare collection in the broader payments environment • Near-Capacity Operations • Regulatory and contractual aspects
  • 20.
  • 21. Motivation: Efficiency in the use of road space www.BRT.cl
  • 22. What can we say about bus service? Bus is critical to provide a good door-to-door transit alternative for many journeys: • Much higher network density and coverage than rail • Greater flexibility in network structure • Low marginal cost for service expansion BUT as traditionally operated, it also has serious limitations: • Low-speed • Subject to traffic congestion • Unreliable • Harder to convey network to the public • Negative public image
  • 23. What can we say about the user? • Perceives waiting time and walking time twice as important as travel time inside the vehicle. • Avoids transferring, specially if they are uncomfortable • Needs a reliable experience • Requests a minimum comfort experience • Requests information • Needs to feel safe and secure
  • 24. What are the bottlenecks? Capacity per lane: • “Only a fool breaks the two second rule” => 1,800 veq/hr-lane • 1 Bus ≈ 2 veq => 900 buses/hr-lane Capacity per lane at junctions: • 40 – 60 % of lane capacity => 450 buses/hr-lane Capacity at Bus Stops: • Depends on the amount of passengers boarding and alighting • ≈ 20 - 40 sec. per bay => 180 – 90 buses/hr-bay
  • 25. This feeds this vicious cycle Operation cost grows Income and Population grows More cars in the city Bus Demand drops Car becomes more attractive Bus frequency drops Buses cover fewer miles per day Bus fare increases And we need to make buses attractive to car drivers… More congestion And delays
  • 26. However, this doesn’t affect Metro as much
  • 27. Can we provide Metro-like service with buses? • Fast • Low wait time • Comfortable • Reliable • Good information • Branding
  • 28. Can we provide Metro-like service with buses? Transit Leaders Roundtable MIT, June 2011 • Fast • Low wait time • Comfortable • Reliable • Good information • Branding
  • 29. Yes we can … We still believe (several pieces are already there in cities worldwide) Can we provide Metro-like service with buses? The good news are: COURAGE WILL BE REWARDED
  • 30. IMPROVED EFFICIENCY IMPROVED SERVICE QUALITY Reduced bus costs •Less buses required •Lower cost per km Improved bus productivity •More pax/bus-day Attracts more passegers Improves revenue IMPROVED FINANCIAL VIABILITY Better buses More investment into new buses & cleaner technology Lower Subsidies Reduced private car use & traffic congestion Improved energy efficiency Reduced emissions Operational benefits •Shorter cycle time •Reliable operations •Higher productivity Increase Bus speed, Frequency, Capacity and Reliability Passenger benefits •Reduced travel time •Reduced waiting time •Higher comfort •Reliability Source: Frits Olyslagers, May 2011
  • 32. BRT Experiences and Challenges Juan Carlos Muñoz Bus Rapid Transit Centre of Excellence Pontificia Universidad Católica de Chile July 12, 2013
  • 33. Future of BRT: Flexible Capacity Operations Juan Carlos Muñoz and Ricardo Giesen Bus Rapid Transit Centre of Excellence Pontificia Universidad Católica de Chile July 12, 2013
  • 35. Segregated ways/lanes Low Flow: Intermittent Bus Lanes Medium Flow: Bus-Only lanes High Flow and Limited Capacity: Only bus street
  • 36. J. M. Viegas Low Flow: Intermittent Bus Lane (IBL)
  • 37. Demonstration in Lisbon Implementation: Technical Components Installation of the Loop Detectors IBL local controller Static signalization (advance notice) Variable message longitudinal LEDs Vertical variable message signal
  • 39. Without IBL vs. with IBL (51 sec) Demonstration
  • 40. Only Bus Lanes BUS ONLY Setback! R. Fernández
  • 41. Partial closure of streets for cars, but not for buses Closed Junction (Brussels)Closed lane (Zurich) P. Furth
  • 43.
  • 45. Level bording in Quito, Ecuador
  • 51. Divided Bus Stops Bus only street? Weaving distance: 3-4 bus R. Fernández
  • 52. Platform 2 Platform 1 Stop area 2 Stop area 1 Divided bus stop Divided rail station Platform 2 Platform 1 R. Fernández Divided Bus Stops
  • 53. Fast Reliable Metro Attributes Actions Comfort Increase Speed Regular Headways Main drivers Increase Capacity Increase Frequency •Segregated ways/lanes •Reduce dwell times •Fare payment off-bus •Buses with multiple doors •Increase distance between stations Low waits
  • 54. Fast Reliable Metro Attributes Actions ComfortLow waits Increase Speed Regular Headways Main drivers Increase Capacity Increase Frequency •Segregated ways/lanes •Reduce dwell times •Fare payment off-bus •Buses with multiple doors •Increase distance between stations •Express services
  • 55. Choosing the Right Express Services for a Bus Corridor with Capacity Constraints Homero Larrain, Ricardo Giesen and Juan Carlos Muñoz Department of Transport Engineering and Logistics Pontificia Universidad Católica de Chile
  • 56. Introduction Operación “Carretera” Operación Expresa Higher in-vehicle travel time Lower in-vehicle travel time No transfers May force some transfers Higher operation costs, in terms of $/Km Lower operation costs, in terms of $/Km Other aspects: capacity, comfort, accessibility, etc. Limited stop servicesAll stop services *Jointly operated with all stop services, assuming a constant fleet size. *
  • 57. Objective • Formulate a model that allows to choose which combination of services to provide on a corridor, and their optimal frequencies. • Determine opportunities for express services (or limited stop) on a corridor based on its demand characteristics.
  • 58. The Problem p1 p2 pi pn … …
  • 59. The Problem • Different operation schemes. p1 p2 pi pn … … … …l1, f1 … …l2, f2 … …l3, f3 … …l4, f4 The goal is to find which services to offer, and their optimal frequencies. li: Line i fi: frequency of line i
  • 60. The Model • The goal of this model is to find the set of services that minimize social costs: – Operator costs: will depend on what services are provided, and their frequencies. – User costs: • In-vehicle travel time. • Wait time. • Transfers.
  • 61. The Model: Assumptions • Given transit corridor, with a given set of stops. • Fares are constant for a full trip. • Number of trips between stops is known for a certain time frame. • Random arrival of passengers at constant average rate. • Passengers minimize their expected travel times.
  • 62. The Experiment • Steps: – Defining network topology. – Defining demand profiles. • Load profile shape. • Demand scale. • Demand unbalance. • Average trip length. – Build scenarios and construct an O/D matrix for each one. – Optimize scenarios defining the optimal set of lines for each one.
  • 63. Express Services: Main Conclusions • Allow increasing the capacity of the system • Significantly reduces social costs • Few services bring most of the benefits • Limited stop services are more promising in these situations: – The longer the average trip length – High demand – High stop density – Demand is mostly concentrated into a few O/D pairs
  • 64. Fast Reliable Metro Attributes Actions ComfortLow waits Increase Speed Regular Headways Main drivers Increase Capacity Increase Frequency •Segregated ways/lanes and priority at junctions •Reduce dwell times •Fare payment off-bus •Buses with multiple doors •Increase distance between stations •Express services •Traffic signal priority and priority at intersectons
  • 65. Anticipated Green Light for Buses R. Fernández
  • 66. • Move pedestrian crossing • “Do not block” Protection of Buses on Right Turns P. Furth
  • 67. • Move pedestrian crossing • “Do not block” • Exclusive phase for pedestrian P. Furth Protection of Buses on Right Turns
  • 68. Metro Attributes Actions Increase Speed Regular Headways Main drivers Increase Capacity Increase Frequency •Segregated ways/lanes •Reduce dwell times •Fare payment off-bus •Buses with multiple doors •Increase distance between stations •Express services •Traffic signal priority and priority at intersectons •Improved headway control Fast ComfortLow waits Reliable
  • 70. Time-space trajectories Line 201, March 25th, 2009 0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 30 32.5 35 Tiempo (minutos) Posición(Km.) 6:30 AM 8:30 AM
  • 71. Boston, MA; line 1 during winter
  • 72. Boston, MA; line 1 during summer
  • 73. Is keeping regular headways that difficult? Transit Leaders Roundtable MIT, June 2011
  • 74. Ricardo Giesen © Bus Bus Stop Stop Waiting Passengers Waiting Passengers Bus Operations without Control
  • 75. Ricardo Giesen © BusBusStop Stop a small perturbation… Waiting Passengers Waiting Passengers Bus Operations without Control
  • 76. Ricardo Giesen © Bus Bus Stop Stop While one bus is still loading passengers the other bus already left its last stop Bus Operations without Control
  • 77. Ricardo Giesen © Bus BusStop Stop Bus Operations without Control
  • 78. Ricardo Giesen © Bus Bus Stop Stop Without bus control, bus bunching occurs!!! Bus Operations without Control
  • 79. Stable versus unstable equilibrium
  • 80. Stable versus unstable equilibrium
  • 81. Stable versus unstable equilibrium
  • 82. Stable versus unstable equilibrium
  • 83. Stable versus unstable equilibrium
  • 84. Stable versus unstable equilibrium
  • 85. + - + - + - +
  • 86. + - + - + - +
  • 87. + - + - + - +
  • 88. + - + - + - + And so on so forth. Our challenge is to keep an inherently unstable system: buses evenly spaced Now, if we want to prevent bunching from occurring … when is the right time to intervene?
  • 89. Bus bunching is specially serious, where bus capacity is an active constraint.
  • 90. Bus bunching  Severe problem if not controlled  Most passengers wait longer than they should for crowded buses  Reduces reliability affecting passengers and operators  Affects Cycle time and capacity  Creates frictions between buses (safety)  Put pressure in the authority for more buses Contribution: Control Mechanism to Avoid Bus Bunching based on real-time GPS data
  • 91. 2. Research  Propose a headway control mechanism for a high frequency & capacity- constrained corridor.  Consider a single control strategies: Holding  Based on real-time information (or estimations) about Bus position, Bus loads and # of Passengers waiting at each stop  We run a rolling-horizon optimization model each time a bus reaches a stop or every certain amount of time (e.g. 2 minutes)  The model minimizes: Time waiting for first bus + time waiting for subsequent buses + time held
  • 92. No control Spontaneous evolution of the system. Buses dispatched from terminal as soon as they arrive or until the design headway is reached. No other control action is taken along the route. Threshold control Myopic rule of regularization of headways between buses at every stop. A bus can be held at every stop to reach a minimum headway with the previous bus. Holding (HRT) Solve the rolling horizon optimization model not including green extension or boarding limits. Estrategias de control simuladas 4. Experiment: Control strategies
  • 93. 5. Results: Simulation Animation Simulation includes events randomness 2 hours of bus operation. 15 minutes “warm-up” period.
  • 94. No HRT control Wfirst 4552.10 805.33 Std. Dev. 459.78 187.28 % reduction -82.31 Wextra 1107.37 97.49 Std. Dev. 577.01 122.59 % reduction -91.20 Win-veh 270.57 1649.28 Std. Dev. 36.00 129.56 % reduction 509.57 Tot 5930.03 2552.10 Std. Dev. 863.80 390.01 % reduction -56.96 Results: Time savings
  • 95. Results: Time-space trajectories 0 20 40 60 80 100 120 0 1 2 3 4 5 6 7 8 9 10 s2 NETS sc corrida17 Distance(Km) Time(minutes) HRT 0 20 40 60 80 100 120 0 1 2 3 4 5 6 7 8 9 10 Scenario 1 threshold run17 Distance(Km) Time(minutes) No Control This impacts comfort, reliability for users and for operators
  • 96. Results: Bus Loads 0 5 10 15 20 25 30 0 20 40 60 80 100 120 Scenario 1 HBLRT alpha=05 Beta=05 Load(Pax.) Stop HRT 0 5 10 15 20 25 30 0 20 40 60 80 100 120 Scenario 1 HBLRT alpha=05 Beta=05 Load(Pax.) Stop No Control
  • 97. Results: Cycle Time 25 30 35 40 45 0 50 100 150 200 250 300 350 mean =33.64 Std.Dev. =3.51 No control Frequency Cycle Time (Minutes) 25 30 35 40 45 0 50 100 150 200 250 300 350 mean =32.11 Std.Dev. =1.2 HRT 05 Frequency Cycle Time (Minutes) HRTNo Control
  • 98. 5. Results: Waiting time Distribution % of passengers that have to wait between: Period 15-25 Period 25-120 0-2 min 2-4 min > 4 min 0-2 min 2-4 min > 4 min No Control 57.76 29.60 12.64 63.46 27.68 8.86 HRT 79.24 20.29 0.47 87.30 12.62 0.08
  • 99. Disobeying Drivers Similar disobedience across all drivers A subset of drivers never obey Technological Disruption Random signal fail Failure in the signal receptor equipment Signal-less zone Homogeneous distribution across buses Concentration in certain buses Concentration in certain stops 6. Impact of implementation failures
  • 101. Common disobedience rate across drivers 8000 9000 10000 11000 12000 13000 14000 15000 0%10%20%30%40%50%60%70%80%90%100% TotalWaitingTime[Min] Obedience rate HRT, Beta=0,5 Sin Control
  • 102. Full disobedience of a set of drivers 8000 9000 10000 11000 12000 13000 14000 15000 16000 0 1 2 3 4 5 6 7 TotalWaitingTime[Min] Deaf Buses from a total of 15 buses
  • 103. Implementation • The tool has been tested through two pilot plans in buses of line 210 of SuBus from Transantiago (Santiago, Chile) along its full path from 7:00 to 9:30 AM. • We chose 24 out of 130 stops to hold buses • One person in each of these 24 stops received text messages (from a central computer) into their cell phones indicating when each bus should depart from the stop.
  • 105. Implementation Real time GPS information of each bus Program optimizing dispatch times for each bus from each stop Text messages were sent automatically to each person in each of the 24 stops Buses are held according to the text message instructions (never more than one minute)
  • 107. The results were very promising even though the conditions were far from ideal
  • 108. Main results • Transantiago computes an indicator for regularity based on intervals exceeding twice the expected headway (and for how much). $ 10,000 $ 20,000 $ 30,000 $ 40,000 $ 50,000 $ 60,000 $ 70,000 $ 80,000 $ 90,000 $ 100,000 $ 110,000 Multas($CLP)
  • 109. Main results: cycle times 2:24:00 AM 2:31:12 AM 2:38:24 AM 2:45:36 AM 2:52:48 AM 3:00:00 AM 3:07:12 AM 3:14:24 AM 3:21:36 AM 3:28:48 AM 3:36:00 AM 5:52:48 AM6:00:00 AM6:07:12 AM6:14:24 AM6:21:36 AM6:28:48 AM6:36:00 AM6:43:12 AM6:50:24 AM6:57:36 AM Cycletime Dispatch time Piloto 1 Prueba10 Prueba12 Prueba13 Prueba15 Prueba16 Prueba17  No significant differences for cycle times
  • 110. • Line 210 captured an extra 20% demand! 94,000 96,000 98,000 100,000 102,000 104,000 106,000 7,400 7,600 7,800 8,000 8,200 8,400 8,600 8,800 Demand for Line 210 (pax) Demand on All lines (pax) Unexpected result
  • 111. 8. Conclusions Developed a tool for headway control using Holding in real time reaching simulation-based time savings of 60% Huge improvements in comfort and reliability The tool is fast enough for real time applications. Two pilot plans have shown significant improvements in headway regularity. During 2013 we will build a prototype to communicate directly to each driver.
  • 112.
  • 113. Publications and working papers • Delgado, F., Muñoz, J.C., Giesen, R., Cipriano, A. (2009) Real-Time Control of Buses in a Transit Corridor Based on Vehicle Holding and Boarding Limits. Transportation Research Record, Vol 2090, 55-67 • Munoz, J.C. and Giesen, R. (2010). Optimization of Public Transportation Systems. Encyclopedia of Operations Research and Management Science, Vol 6, 3886-3896. • Delgado, F., J.C. Muñoz and R. Giesen (2012) How much can holding and limiting boarding improve transit performance? Trans Res Part B, , vol.46 (9), 1202-1217 • Muñoz, J.C., C. Cortés, F. Delgado, F. Valencia, R. Giesen, D. Sáez and A. Cipriano (2013) Comparison of dynamic control strategies for transit operations. Trans Res Part C. • Hernández, D., J.C. Muñoz, R. Giesen, F. Delgado (2013) Holding strategy in a multiple bus service corridor. Accepted at TRISTAN conference. • Phillips, W., J.C. Muñoz, F. Delgado, R. Giesen (2013) Limitations in the implementation of real-time information control strategies preventing bus bunching. Accepted at WCTR conference
  • 114. Other activities • Three chilean operators will test our tool this year • Raised interest from operators in Cali and Istanbul • A research and development team is consolidating • Pedagogic tool to teach bus headway control
  • 115. Minimizing Bus Bunching A strategy that cuts wait times, improve comfort and brings reliability to bus services Juan Carlos Muñoz Bus Rapid Transit Centre of Excellence Department of Transport Engineering and Logistics Pontificia Universidad Católica de Chile
  • 116. Future of BRT: Flexible Capacity Operations Juan Carlos Muñoz and Ricardo Giesen Bus Rapid Transit Centre of Excellence Pontificia Universidad Católica de Chile July 12, 2013

Hinweis der Redaktion

  1. Enforcing
  2. - MetodologíaSon limitaciones porque retenciones planificadas no se realizanLa diferencia entre los fenómenos es cómo distribuyen las retenciones no realizadas.
  3. - MetodologíaSon limitaciones porque retenciones planificadas no se realizanLa diferencia entre los fenómenos es cómo distribuyen las retenciones no realizadas.
  4. La baja cantidad de datos se debe a que el periodo de análisis va desde las 6:15 a las 9:45, no teniendo tantos buses que durante este periodo completen el ciclo de inicio a fin.