Transcript www.ivt.ethz.ch

Lecture II
September 23rd 2014
Outline
• Student Assignment
• Themes for Case studies
– Carsharing
– Extreme weather events
– Electric Vehicles
Student Assignment
In short…
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•
•
•
•
Investigation of a case study with MATSim
Groups of 1-2 students
Total workload of 60 hours (2 Credits)
Results in a scientific paper
Grade determined by report, paper and
presentation
Goals
• Become a MATSim-Superuser
• Investigate a Research Question in a Case
Study
• Produce a Research Paper
• Present your Paper as in a Conference
Structure of Student Assignment
Four Tasks:
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Task 1 – Development of a Research Question
Task 2 – MATSim-Introduction
Task 3 – Case Study
Task 4 – Presentation
Semester plan:
Semester
Week
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Calendar
Week
39
40
41
42
43
44
45
46
47
48
49
50
51
52
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1
1
2
2
2
3
3
3
3
3
3
4
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Task
Task 1 – Development of a Research
Question
• Starts Today!
• Three different case themes will be introduced.
• In your group you select one of them and get more detailed
information on it.
• Then you have 2 weeks to:
– do a literature and background research on the case theme,
– develop a research question in your case theme,
– and write the introduction of your paper.
• The introduction is due in week 4!
Task 2 – MATSim-Introduction
• Goal: Preparation of MATSim for the main study
• Consists of a mini case study which is the same for all
• Exercises:
– Installation and set-up of MATSim and of a suitable IDE to develop in
JAVA
– Do the mini case study and thus learn to run simulations with MATSim
– Visualize the results and prepare a short report
• The short report presenting the mini case study is due in week
7. The report is expected to contain meaningful visualizations
which supports the main conclusions of the case study.
Task 3 – Case Study
• Goal: Work on your research question and develop the
required tools
• Kick-off is in week 7 of the semester
• Duration: 6 weeks (30 workhours)
• ToDos:
– work on the case study
– answer the research questions
– write a research paper (specifications given in week 7)
• Full research paper is due in week 13, the second last week of
the semester
Task 4 – Presentation
• Goal: Present and defend your paper in a conference
like presentation
• Preparation of the presentation: From week 13 to
week 14
• Presentation: In week 14
• Template for the presenation will be handed out in
week 13
Grade
Weighted average of:
• 2 x Mini case report grade
• 6 x Paper (incl. Introduction) grade
• 2 x Presentation grade
No session exam. After the presentation you have
holidays!
Task 1 – Administration
• Starts Today!
• ToDos:
– do a literature and background research on the case
theme
– develop a research question within your case theme
– write the introduction of your paper
• The introduction (pdf-document) is due in week
4.
Task 1 – Writing an Introduction I
A good Introduction…
• puts your work in a given context:
– start with an overview of the field
– narrow it down to your research question and your hypothesis
• contains a literature review: Mention the most important literature
and work already done in the field and explain how you
differentiate your work. Why is your work important?
• gives an overall summary of the paper
• explains how the research problem is solved (in your case: broadly
how you plan to solve the problem with MATSim)
Task 2 – Writing an Introduction (II)
Paper Specifications:
• A paper should have the following parts: abstract,
introduction, methodology, results, discussion, conclusion
and references.
• Your paper, including the abstract, text, references, figures,
and tables, must not exceed 7,500 words. Each table,
figure, or photograph counts as 250 words. For example, if
two figures and three tables are submitted, the abstract,
text, and references may total no more than 6,250 words.
Themes for Case Studies
Verkehrsingenieurtag – 6. March 2014
Carsharing: Why to model carsharing demand and
how
F. Ciari
Outline
1.
2.
3.
4.
Introduction: What’s going on in the carsharing world?
Why to model carsharing demand?
Modeling carsharing with MATSim
Summary and future work
17
1.
2.
3.
4.
Introduction: What’s going on in the carsharing world?
Why to model carsharing demand?
Modeling carsharing with MATSim
Summary and future work
18
Worldwide growth of carsharing
Carsharing in terms of
members / vehicles is
growing fast
Source: Shaheen and Cohen, 2012
19
Actors
• The actors involved are increasingly large
• Car manufacturers  Daimler, BMW, Peugeot
• Traditional car rental companies  Avis, Sixth
• Public transport operators  DB
20
Competition
• The level of competition on the market is increasing
• At the start of modern carsharing operations (90’s
Switzerland and Germany) and until recently, operators
mostly were “local monopolists”
• Now many cities boast several carsharing operators
21
Services
• The world of shared mobility is evolving fast and new services
are coming to the market to challenge/complement the old
ones
•
•
•
•
Round trip-based carsharing (Mobility)
One-way (station based) carsharing (Autolib)
Free-floating carsharing (Car2go, DriveNow)
Peer-to-peer carsharing (RelayRides)
•
•
•
•
•
Bike-sharing
Carpooling
Dynamic ride sharing
Slugging
…
22
1.
2.
3.
4.
Introduction: What’s going on in the carsharing world?
Why to model carsharing demand?
Modeling carsharing with MATSim
Summary and future work
23
Why do we need to model carsharing demand?
Models are used to get insight on the behavior of a
transportation system under given circumstances
but
Is carsharing relevant?
24
Because…
• Still small but conceptually “mainstream” (“Shared economy”)
• Fits well with some societal developments (“Peak car”)
• Is often mentioned when it comes to make transport more
sustainable (but the mechanisms aren’t clear)
25
…and also because…
• The actors involved are increasingly large  Able to have a
“big bang” approach, implies large investments
• The level of competition on the market is increasing  Higher
investment risk
• The world of shared mobility is evolving fast  Incertitude
about integration/competition among different modes/systems
26
Research Goal
• Build a predictive and policy sensitive model that
can be used by practitioners (operators) and
policy makers
27
Methodology: Observations
• Inherent limitations of traditional models representing
carsharing – the importance of CS availability at precise
points in time and space is not fitting with vehicles per hour
flows
• Travel is the result of the individual need performing out-ofhome activities at different locations – this matters for
carsharing even more than for other modes! (according to the
length / location of the activities)
28
1.
2.
3.
4.
Introduction: What’s going on in the carsharing world?
Why to model carsharing demand?
Modeling carsharing with MATSim
Summary and future work
29
MATSim
It sketches individuals’ daily life using the agent paradigm.
Agents have personal attributes (age, gender, employment, etc.)
which influence their behavior
Agents autonomously try to carry out a daily plan being able to
modify some dimensions of their travel (time, mode, route,
activity location)
High temporal and spatial resolution
MATSim = Multi-agent transport simulation (www.matsim.org)
30
Carsharing model in MATSim – Current status
•
Traditional carsharing + Free-floating
• Agents always walk from the starting facility to the closest car
• Time and distance dependent fare
• Stations are located at the actual carsharing locations in the modeled
area
• Carsharing is available only to members
• Actual vehicle availability is accounted for
31
Test Case 1 - Berlin
Part of a German project called “Berlin elektroMobil”  Berlin, Germany
as a test case
Goals:
•
Understand the behavior of the whole transportation system under
different carsharing scenarios
•
Finding strategies to extend the carsharing supply in Berlin and get
hints on how to combine free-floating (FF) and station-based (SB)
carsharing
32
Scenarios
•
Scenario I: SBCS (Basis, station based only, reflecting actual supply)
•
Scenario II: Expanded SBCS (Station based only, additional stations and
members)
•
Scenario III: Scenario II + Free-floating
Scenario I
Scenario II
Scenario III
Population
4‘422‘012
4‘506‘058
4‘506‘058
# Members CS SB & FF
20‘000
38‘000
38‘000
# Members CSFF
-
-
194‘000
# CS Stations
82
152
152
# Vehicles (Station based)
175
329
329
# Vehicles Free-floating
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-
2‘500
# Members traveling (any mode)
16‘489
31‘358
191‘819
33
Statistics overview
CS SB
(Scenario I)
CS SB
(Scenario II)
CS SB
(Scenario III)
CS FF
(Scenario III)
496
1‘298
1‘379
10‘708
Avg. Trip Duration [min]
22.9
23.5
27.5
20.1
Avg. OD-Distance [km]
5.8
5.3
5.3
5.7
Total travel time [Days]
7.9
21.2
26.5
149.8
Total distance [km]
2‘900
6‘900
7‘300
60‘600
# Trips
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Over-proportional increase of SB rentals (increasing stations / cars)
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Trips (distance and travel time) essentially unchanged
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Adding FFCS (2’500 cars) 
~ 10’000 additional trips and SBCS grows
•
SB (S III) shorter trips (distance), FF slightly longer but faster trips.
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Purpose
40.0
35.0
Trips [%]
30.0
25.0
SB Scenario I
SB Scenario II
SB Scenario III
FF Scenario III
20.0
15.0
10.0
5.0
.0
Activity Type
FF CS has more Work and less Leisure travel compared to SB CS
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Modal substitution
Mode substituted by free-floating carsharing
35.0
30.0
Trips [%]
25.0
20.0
15.0
10.0
5.0
.0
Bike
Car
CS SB
PT
Walk
Mode substituted by FF CS
•
Car travel is the mode which is reduced the most (> 30%) of the free-floating trips were
car trips before its introduction
•
Overall car travel (VMT) grows with FF compared to SB only  modal substitution
patterns for free-floating carsharing might be problematic
•
Relatively few agents changed from SB to FF carsharing
36
Conclusions
• Untapped potential for SBCS in Berlin – Over-proportional
growth of SB doubling # carsharing cars
• SB carsharing is used more intensively after FF carsharing is
introduced
• Some differences in the use of the two CS modes (purpose,
time, distance)
• Substitution patterns are a possible concern for FF
• Apparently FF and SB are rather complementary
37
Test Case 2 - Zürich
Goals:
• Understand the behavior of the whole carsharing system
under different (carsharing) pricing scenarios
• Get hints on the interactions between traditional station based
carsharing and free-floating carsharing under such scenarios
38
Scenarios
Scenario I
Scenario II
Scenario III
Scenario IV
Scenario V
SB Time Fee
4.52 SFr./h
4.52 SFr./h
4.52 SFr./h
4.52 SFr./h
4.52 SFr./h
SB Distance
0.18 SFr./Km
0.18 SFr./Km
0.18 SFr./Km
0.18 SFr./Km
0.18 SFr./Km
-
0.237 SFr./min
0.118 SFr./min
0.118 SFr/min
0.237 SFr./min
Fee
FF Time Fee
(10-16)
0.237 SFr/min
(rest of day)
FF Distance
-
0.29 SFr./Km
0.29 SFr./Km
0.29 SFr./Km
0.29 SFr./Km
-
20 Km
20 Km
20 Km
0 Km
Fee
FF Free
Distance
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Vehicles in Motion
Modal substitution
Modes substituted by free-floating carsharing in scenarios II
to V as compared to scenario I. The secondary axis shows
the number of free-floating rentals for the scenario
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Rentals spatial patterns
42
Purpose of the rental
Scenario I
Scenario II
Scenario III
Scenario IV
Scenario V
RT CS
1h23’9’’
1h39’7’’
1h44’7’’
1h24’28’’
1h26’29’’
FF CS
-
2h45’58’’
2h16’56’’
2h34’38’’
2h12’45’’
Car
3h58’2’’
3h58’14’’
3h58’
3h57’53’’
3h57’47’’
43
Conclusions
•
The impact of different pricing schemes is not limited to increasing
or reducing the aggregate level of usage
•
Pricing strategy structurally affects the interactions between the two
carsharing types
•
Complex interactions between spatiotemporal availability of
carsharing vehicles and users are observed
•
The realism of some aspects (i.e. purpose, modal substitution) is
still unclear
44
1.
2.
3.
4.
Introduction: What’s going on in the carsharing world?
Why to model carsharing demand?
Modeling carsharing with MATSim
Summary and future work
45
Summary
•
Carsharing is growing fast and is becoming «mainstream»
•
Instruments for the modeling of carsharing are becoming
necessary
•
Traditional models are not well suited to model carsharing
•
MATSim is already able to simulate carsharing and to
evaluate complex scenarios…
…but there are still many limitations
46
Ongoing work
• Improving the existing membership model
• Testing our implementations of free-floating and one-way
carsharing
47
Future work
• Further validation of the existing results with empirical data
• Applying the tool for analysis on new scenarios, possibly
relying on new empirical data
• Improve the simulation with better behavioral models
• New case studies where different shared mobility options
(Autonomous Vehicles, Ride Sharing) are combined
48
Thank you for your attention!
www.matsim.org
49
Modeling Impacts of Weather Conditions in Agent-Based
Transport Microsimulations
Alexander Stahel
Francesco Ciari
Transportation Research Board
January 2014
93rd Annual Meeting
Terminology
«Climate is what you expect, weather is what you get.» (Robert Heinlein)
• Climate: Measure of the average weather observed over a certain period
• Weather: Description of the momentary state of the atmosphere and
their change over small periods.
• Climate change: Statistically significant variation in the mean state of
the climate or its variability, persisting for an extended period
Introduction
Weather impacts
Climate impacts
MATSim
Approaches
Motivation
Transport sector
Introduction
Weather impacts
Climate impacts
Climate change
MATSim
Approaches
Motivation
Transport sector
Introduction
Weather impacts
Climate impacts
Climate change
MATSim
Approaches
ToPDAd: Tool-supported policy-development
for regional adaption
• EU 7th Framework project
• The objective is to find the best strategies for businesses and
regional governments to adapt to the expected short term and
long term changes in climate
• Development of socioeconomic methods and tools for an
integrated assessment
• Sectors: Transport, Energy, and Tourism
Introduction
Weather impacts
Climate impacts
MATSim
Approaches
Open questions
1.
Which aspects of the transport system are affected by the weather?
2.
Which aspects of the transport system are affected by climate change?
3.
How can these impacts be modelled?
Introduction
Weather impacts
Climate impacts
MATSim
Approaches
Weather impacts on transport
1) Transport infrastructure
2) Safety
3) Travel behavior
Introduction
Weather impacts
Climate impacts
MATSim
Approaches
Climate change impacts on transport
• Cannot be equated with weather impacts
• Also cumulative effects in the long-run are important
1) Transport infrastructure
2) Safety
3) Travel behavior
4) Socio-economic circumstances
Introduction
Weather impacts
Climate impacts
MATSim
Approaches
Climate change impacts on transport
Event-specific impacts
Transport
infrastructure
Safety
-Breakdown
-Changing maintenance costs
-Disturbance
-Changing construction costs
-Elevated physical stress levels
-Reduced lifetime
-Frequency of accidents
-Changing transport safety
regulations
-Severity of accidents
Travel behavior
Cumulative impacts
-Mode, time, destination, route
choice
-Reduced free-flow speed
-Changing long-term activitytravel behavior
-Driver experience under adverse
weather conditions
Socio-economic
-Structural changes in related
sectors (e.g. tourism)
circumstances
-Changes in mitigation policies
Introduction
Weather impacts
Climate impacts
MATSim
Approaches
MATSim
• Agent- and activity-based transport simulation
• The actors of the modeled system are represented at individual level
• Based on Java
• Open source at www.matsim.org
• Jointly developed by ETH Zurich, TU Berlin, and others
Introduction
Weather impacts
Climate impacts
MATSim
Approaches
Regular weather conditions
• Aspects of climate change:
• Increased average temperature
• Increase in the number of hot days
• Decrease in the number of cold days
• Sea level rise
• More precipitation or drought events
• Longer summer/shorter winter
• The iterative approach of MATSim is applicable
• Search for tipping points
Introduction
Weather impacts
Climate impacts
MATSim
Approaches
Unexpected weather conditions
• Aspects of climate change:
• Increased frequency of adverse weather conditions
• Increased severity of adverse weather conditions
• The iterative approach of MATSim is not applicable
• Usage of the within-day-replanning module and a time-variant
network
Introduction
Weather impacts
Climate impacts
MATSim
Approaches
Project ToPDAd – Weather Influence
Scenarios investigated with MATSim:
1. Baseline:
Zurich 2030 standard scenario, no change.
2. Disturbance: Reduced traffic network capacity and speed due
to
unfavourable weather conditions.
3. Disruption (momentary/when occuring): Traffic network
capacity
becomes largely unavailable during simulation due to
unfavorable weather conditions.
4. Disruption (momentary/when occuring): Traffic network
capacity
becomes largely unavailable during simulation due to
unfavorable weather conditions. Level of informedness is
varied to mimic effects of innovations.
5. Disruption (lasting): Traffic network capacity is largely
unavailable during the whole simulation due to earlier,
unfavourable weather conditions.
Project ToPDAd – Zurich Scenario
Thank you for your attention!