Analysis of automated driving diffusion: Potential diffusion paths … · 2020. 11. 9. · Dr....

Analysis of automated driving diffusion: Potential

diffusion paths into the German Market

Dr. Christine Eisenmann

SIP-adus Meeting, 12/11/2020

In collaboration with:

Dr. Christian Winkler, Dennis Seibert, Nina Thomsen (DLR)

Prof. Tobias Kuhnimhof, Michael Schrömbges (RWTH)

Dr. Thomas Meissner, Dr. Peter Phleps (BMW)

> SIP-adus > Christine Eisenmann • CAD Diffusion Germany > November 12, 2020DLR.de • Chart 2

Research objectives and contents

Diffusion of connected and automated

driving (CAD) (focus: car market)

Changes in car ownership, individual

travel behaviour and collective travel

demand

Reserch

objectives

Potential

diffusion

paths

The private autonomous car Autonomous Mobility as a Service MaaS

(resp. ODM, ridehailing)

Potential

diffusion

paths

DLR.de • Chart 3

Research objectives and contents

Research

questions

in this

regard

• How do those diffusion paths affect car ownership, the new car market, the car stock and

travel demand?

• Which effects do the different diffusion paths have on transport sustainability and on the car

industry?

• Is the narrative (told in Germany) realistic that private cars will be replaced by automated

services and that automation will lead to a reduction of the car fleet? And if so, under which

conditions?

•

> SIP-adus > Christine Eisenmann • CAD Diffusion Germany > November 12, 2020

DLR.de • Chart 4

To analyse CAD diffusion from a quantitiative perspective, a model chain is

being implemented

Eff

ec

tso

n

Market entry of CAD (connected and automated driving)

Vehicle ownership

in households

New car market

and car stockTravel demand

and CAD services

Resulting impacts of CAD diffusion


DLR.de • Chart 5

Key questions on market entryE

ffe

cts

on


Vehicle ownership

in households

New car market


and CAD services


When will automated cars be available on the German market?

When will we have automated MaaS vehicles on the streets?


DLR.de • Chart 6

Model assumptions on the entry of level 4 automated vehicles into the

German market are derived from interviews with industry experts

2030 2035 2040 2045

Level 4 luxury class vehicles

Level 4 medium class vehicles

Mobility as a Service


DLR.de • Chart 7

Key questions on vehicle ownership in householdsE

ffe

cts

on


Vehicle ownership

in households

New car market


and CAD services


How does automation affect the car ownership decisions of private households on

(i) the private cars diffusion path or (ii) the MaaS diffusion path?

Under which conditions might the availability of MaaS lead to household decisions

against an own car?


DLR.de • Chart 8

A discrete choice model for car ownership in households is being developed

Two successive

logistic regression

models

Diffusion paths

- private car

diffusion path

- MaaS diffusion

path

GoalModel car

ownership in private

households

Household

attributes

Socio-economics

Built environment

Transport supply

Personal attributes

Future

?

Model estimation for future scenarios

Model calibration with the national travel survey „Mobility in Germany“


DLR.de • Chart 9

Key questions on the new car market and the vehicle stockE

ffe

cts

on


Vehicle ownership

in households

New car market


and CAD services


How many automated cars will we have in the German new car market and car stock

in 2030, 2040 and 2050 at (i) the private car diffusion path or (ii) the MaaS diffusion

path?

How will automation affect the used car market?


DLR.de • Chart 10

An agent-based vehicle stock model is being used to study the effects of

automation to the new car market and the vehicle stock

The German vehicle stock is modeled dynamicly

1.1

.1995

1.1

.1996

1.1

.1997

1.1

.1998

1.1

.1999

1.1

.2000

1.1

.2001

1.1

.2002

1.1

.2003

1.1

.2004

1.1

.2005

1.1

.2006

1.1

.2007

1.1

.2008

1.1

.2009

1.1

.2010

1.1

.2011

1.1

.2012

1.1

.2013

1.1

.2014

1.1

.2015

1.1

.2016

removals (export & scrapping)

new vehicle registrations

ownership transfers

Annual, agent-based simulation of household

choices

Purchase decision Used vehicle market decision

BadAverageGood

Vehicle technologydecision

Vehicle segment

Drivetrain

Automation-level

No purchase

New vehicle (commercial)

New vehicle (private)

Used vehicle

Yearlyhousehold

choices


DLR.de • Chart 11

Ac rising demand for automated cars on the new car market has a ladded

effect on the car stock

Exemplary, preliminary results for the private car diffusion path

0

1

2

3

4

5

2020 2025 2030 2035 2040 2045 2050

Ca

rs [

mio

.]

New car sales

Level 0-3 Level 4+ optimistic Level 4+ pessimistic

0

10

20

30

40

50

2020 2025 2030 2035 2040 2045 2050

Ca

rs [

mio

.]

Car stock

Level 0-3 Level 4+ optimistic Level 4+ pessimistic

? ?


DLR.de • Chart 12

Key questions on travel demand and CAD servicesE

ffe

cts

on


Vehicle ownership

in households

New car market


and CAD services

Resulting impacts of CAD diffusionHow will future travel mode choice change on (i) the private car diffusion path or (ii)

the MaaS diffusion path?

How does the operation of MaaS fleets work?


DLR.de • Chart 13

A german-wide transport demand model is being extended, to analyze the

impacts of automation on travel demand

Macroscopic travel demand model for Germany (DEMO)

Diffusion of CAD within

the private vehicle fleet

Autonomous MaaS

vehicles

Trip generation

Trip distribution

Mode choice

Route assignment


DLR.de • Chart 14

In the travel demand model MaaS is being applied in large cities

MaaS will be available in cities

with more than 100,000

inhabitants (marked in orange)

The city of Weimar is used

as a reference for the

algorithm development• Only 3 to 6 MaaS vehicles per 1,000 inhabitants

are needed to enable a MaaS modal share of 7%

to 11%

• MaaS vehicles cover about eight times more

distance per day than private cars

• The occupancy rate indicates that only a few

MaaS trips are shared

Modal

Share

MaaS fleet Daily mileage Occupancy rate

[vehicles per 1,000

inhabitants]

[km per vehicle] [passengers per

trip]

7 % 3.8 269 1.1

11 % 5.2 261 1.3

Exemplary results on MaaS for the Weimar region


DLR.de • Chart 15

Key questions on resulting impacts of CAD (at a later stage of the project)E

ffe

cts

on


Vehicle ownership

in households

New car market


and CAD services


What are the resulting effects of CAD diffusion (on transport, the environment,

industry) at (i) the private car diffusion path or (ii) MaaS diffusion path?


DLR.de • Chart 16

Conclusion and outlook

• With this project we are applying a unique and solid model chain to adequately display two likely diffusion

paths of automated vehicles into the German market and their effects on sustainability and the industry

• The applied model chain enables us to shed light into the discussion (in Germany), whether and under which

conditions automation might lead to a reduced car fleet.

• The Japanese-German collaboration:

• The joint reflection of assumptions, scenarios and model approaches is very beneficial for the project

activities.

• Comparisons on CAD diffusion in Japan and Germany given structural similarities but also

geographical, social and regulatory differences are helpful for the development and implementation of

CAD

• A major question remains as to what impact the current development and the corona pandemic will have on

the probability of either of the diffusion paths occurring


Thank you for your attention!

Dr. Christine Eisenmann

DLR Institute of Transport Research

[email protected]

DLR.de • Chart 17

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