O Centro de Excelência em BRT Across Latitudes and Cultures (ALC-BRT CoE) promoveu o Bus Rapid Transit (BRT) Workshop: Experiences and Challenges (Workshop BRT: Experiências e Desafios) dia 12/07/2013, no Rio de Janeiro. O curso foi organizado pela EMBARQ Brasil, com patrocínio da Fetranspor e da VREF (Volvo Research and Education Foundations).
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
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
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
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
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
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.
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
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?
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.
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
Enforcing
- MetodologíaSon limitaciones porque retenciones planificadas no se realizanLa diferencia entre los fenómenos es cómo distribuyen las retenciones no realizadas.
- MetodologíaSon limitaciones porque retenciones planificadas no se realizanLa diferencia entre los fenómenos es cómo distribuyen las retenciones no realizadas.
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.