Lecture II September 23 rd 2014

Lecture II

September 23rd 2014

Outline

• Student Assignment

• Themes for Case studies– Carsharing– Extreme weather events– Electric Vehicles

Student Assignment

In short…

• 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:– 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

Task - 1 1 2 2 2 3 3 3 3 3 3 4 -

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. Introduction: What’s going on in the carsharing world?2. Why to model carsharing demand?3. Modeling carsharing with MATSim4. Summary and future work

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1. Introduction: What’s going on in the carsharing world?2. Why to model carsharing demand?3. Modeling carsharing with MATSim4. Summary and future work

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Worldwide growth of carsharing

Carsharing in terms of members / vehicles is growing fast

19Source: Shaheen and Cohen, 2012

Actors

• The actors involved are increasingly large

• Car manufacturers Daimler, BMW, Peugeot• Traditional car rental companies Avis, Sixth• Public transport operators DB

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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

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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• …

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1. Introduction: What’s going on in the carsharing world?2. Why to model carsharing demand?3. Modeling carsharing with MATSim4. Summary and future work

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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?

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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)

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…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

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Research Goal

• Build a predictive and policy sensitive model that can be used by practitioners (operators) and policy makers

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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-of-home activities at different locations – this matters for carsharing even more than for other modes! (according to the length / location of the activities)

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1. Introduction: What’s going on in the carsharing world?2. Why to model carsharing demand?3. Modeling carsharing with MATSim4. Summary and future work

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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)

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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

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

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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-floatingScenario 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 - - 2‘500

# Members traveling (any mode) 16‘489 31‘358 191‘819

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Statistics overview

• Over-proportional increase of SB rentals (increasing stations / cars)

• Trips (distance and travel time) essentially unchanged

• Adding FFCS (2’500 cars) ~ 10’000 additional trips and SBCS grows

• SB (S III) shorter trips (distance), FF slightly longer but faster trips.

CS SB (Scenario I) 

CS SB(Scenario II) 

CS SB (Scenario III) 

CS FF(Scenario III) 

# Trips 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

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Purpose

educati

on higher

educati

on primary

home

kinderg

arten

leisu

reother

servic

e

shop dail

y

shop other

work.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

SB Scenario ISB Scenario IISB Scenario IIIFF Scenario III

Activity Type

Trip

s [%

]

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 

Bike Car CS SB PT Walk.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

Mode substituted by FF CS

Trip

s [%

]

• 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

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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

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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

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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 Fee

0.18 SFr./Km 0.18 SFr./Km 0.18 SFr./Km 0.18 SFr./Km 0.18 SFr./Km

FF Time Fee - 0.237 SFr./min 0.118 SFr./min 0.118 SFr/min (10-16)0.237 SFr/min (rest of day)

0.237 SFr./min

FF Distance Fee

- 0.29 SFr./Km 0.29 SFr./Km 0.29 SFr./Km 0.29 SFr./Km

FF Free Distance

- 20 Km 20 Km 20 Km 0 Km

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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

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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’’

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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

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1. Introduction: What’s going on in the carsharing world?2. Why to model carsharing demand?3. Modeling carsharing with MATSim4. Summary and future work

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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

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Ongoing work

• Improving the existing membership model

• Testing our implementations of free-floating and one-way carsharing

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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

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Thank you for your attention!

www.matsim.org

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Modeling Impacts of WeatherTransport Microsimulations

Conditions in Agent-Based

Alexander StahelFrancesco Ciari

93rdTransportation Research BoardJanuary 2014

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 andtheir change over small periods.

• Climate change: Statistically significant variation in the mean state ofthe climate or its variability, persisting for an extended period

Introduction Weather impacts Climate impacts MATSim

Approaches

Motivation

Transport sector Climate change

Introduction Weather impacts Climate impacts MATSim

Approaches

Motivation

Transport sector Climate change

Introduction Weather impacts Climate impacts MATSim

Approaches

ToPDAd: Tool-supported policy-development for regional

adaption

• 7thEU Framework project

• The objective is to find the best strategies for businesses andregional governments to adapt to the expected short term and long term changes in climate

• Development of socioeconomic methods and tools for anintegrated 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

Introduction Weather impacts Climate impacts MATSim

Approaches

1)

Transport infrastructure

2) Safety

3) Travel behavior

Weather impacts on transport

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

travel behavior

weather conditions

sectors (e.g. tourism)

Introduction Weather impacts Climate impacts MATSim

Approaches

Event-specific impacts Cumulative impacts

Transport

infrastructure

-Breakdown

-Disturbance

-Elevated physical stress levels

-Changing maintenance costs

-Changing construction costs

-Reduced lifetime

Safety-Frequency of accidents

-Severity of accidents-Changing transport safety regulations

Travel behavior

-Mode, time, destination, route choice

-Reduced free-flow speed

-Changing long-term activity-

-Driver experience under adverse

Socio-economic

circumstances

-Structural changes in related

-Changes in mitigation policies

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 conditionsIncreased severity of adverse weather conditions

• The iterative approach of MATSim is not applicable

• Usage of the within-day-replanning module and a time-variantnetwork

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!