evaluation of supply quality in passenger transport as a basis for

Stuttgart, 27.09.2012

DB Netz AG – I.NVT 7

Univ.-Prof. Dr.-Ing. Andreas Oetting, Angela Rio

presenter: Michael Rittner

Evaluation of supply quality in passenger transport

as a basis for the assessment of railway infrastructure measures

2

Outline

Introduction & Requirements

Empirical Methods

Findings & Conclusions

DB Netz AG, Michael Rittner, I.NVT 7, 27.09.2012

Outlook

3 DB Netz AG, Michael Rittner, I.NVT 7, 27.09.2012

Regarding future traffic growth the project „FreeFloat 1“ supports

the objectives of DB Netz AG as well as the requirements of politics

objectives of DB Netz AG requirements of politics

manage the future traffic growth in an

economically efficient and sustainable way

strengthen competitiveness of the railway

ensure an efficient and modern railway

infrastructure

strengthen the economic position of Germany

enable traffic growth

use investment ressources optimally

defuse bottlenecks in the network

make system reserves useable

enhance punctuality

FreeFloat 1 funded by:

State of the art:

The evaluation of quality measures is limited

4

travel costs

scheduled travel time

transport demand models generally regard

increase of capacity

reduction of in-vehicle-times

improvement of timetable quality

improvement of operational quality

benefits of an infrastructure measure

scheduled

travel time

travel time

travel time

travel costs

travel costs

travel costs

example


5

benefits

economic evaluation of quality improving

measures (in particular delay reducing measures)

comparison of capacity and quality measures by a

common criterion

identification of the most suitable set of measures

to increase the attractiveness of the railway

system

consistent evaluation of measures along the value

chain of the infrastructure manager

ne

ga

tive

va

luatio

n

delays

scheduled

in-vehicle-times

revenues

costs

profit

contribution

€

The model to be developed by Evalinfra provides the basis for an

economic evaluation of the quality impacts of infrastructure measures

„Evalinfra“ project contents


deduction of a quantitative relationship between the

valuations of different components of supply quality

integration into transport demand models

example: delays

Transport demand models have to consider the basic characteristics

of supply quality that can be influenced by the infrastructure manager

6

impact of infrastructure measures on supply quality


reduction of scheduled waiting times

impact on supply quality


no impact on supply quality, economic

evaluation by number of saleable trainpaths

reduction of delays leading to

- fewer waiting times at the originating station

- fewer in-verhicle-times

- shortened or extended changing times

increase of capacity


improvement of timetable quality

improvement of operational quality


Evalinfra is devided into 4 work packages (WP)

WP 1

Survey freight transport

WP 4

Implementation and application on a first example

WP 3

Demand models for the valuation of supply quality

WP 2

Survey passenger transport

network planning (macro) network planning (micro) scheduling disposition

8

Outline


Empirical Methods



Outlook

9

example: conjoint measurement matrix

objective:

deduction of a quantitative relationship between the

valuations of different components of supply quality with

focus on delays

method: nationwide survey in long-distance and local

passenger trains

main survey period: October / November 2009

utilizable return:

approx. 3,200 of 5,000 questionnaires (64%)

survey content:

- core of the questionnaire: conjoint measurement matrix

(5 different, jointly analyzable matrices)

- supplementary information on the customers’ perceptions

and opinions

- information on „today‘s“ journey

- basic information on the person

different questionnaires for:

- long-distance and local passenger trains

- three travel distances (50 km, 130 km, 400 km)

A survey was conducted to gain more specific information on

how passengers value different components of travel time


delay at

originating station

waiting time caused by

missed connecting train

changing time

travel costs

delay at

orig. station



changing

time

travel

costs

method of the survey in passenger transport

10

example: conjoint measurement matrix

Conjoint analysis was used to deduce a quantitative relationship

between the valuations of different characteristics of supply quality


method of analysis

e.g. additional time

(ne

ga

tive)

sta

nd

ard

ized

pa

rt w

ort

h u

tilit

y

regression line

utility attribute 1

regression line

utility attribute 2

marginal utility attribute 2

marginal utility attribute 1 conjo

int

ana

lysis

*

delay at

originating station



changing time

travel costs

delay at

orig. station



changing

time

travel

costs

* in the project conducted by Prof. H.E. Jochim, FH Aachen University of Applied Sciences,

Fachbereich Bauingenieurwesen, Lehrgebiet Bahnanlagen und öffentlicher Verkehr;

literature: Backhaus, K., Erichson, B., Plinke, W., Weiber, R.: Multivariate Analysemethoden;

10. Aufl., Berlin/Heidelberg 2003

11

Outline


Empirical Methods



Outlook


Passengers generally seem to value stops more negatively

than in-motion times

Part worth utilities for in-vehicle-times and the

number of stops both are represented very well by

linear functions.

An increasing marginal utility cannot be confirmed

by the given results for both attributes.

Passengers don‘t seem to distinguish between

„expected“ and additional in-vehicle-times.

Passengers generally seem to value stops 1.5 to

2.5 times more negatively than in-motion times.

valuation of stop times

va

luati

on

of

sto

p t

ime

s

in r

ela

tio

n t

o in

-ve

hic

le-t

ime

s

[min

]

travel distance

A valuation of about 2.5 to 3 for most travel purposes

could be confirmed for delays on the train in relation to in-vehicle-times


valuation of delays as a prolongation of in-vehicle-time

The valuation of delays in relation to in-vehicle-times of JOCHIM [1] could be confirmed for delays

that passengers undergo on the train:

valuation by long-distance passengers on business or private trips between 2.5 and about 3

valuation by vacation travellers a little higher, yet at the same time scheduled in-vehicle-times are

attached less value to by this group

A valuation for long-distance commuters could be deduced, comparable very well to the valuation by

business and private travellers.

A weighting factor of 2.5 could be deduced for travel distances of less than 100 km, which can be

used for mass passenger transport.

[1] Jochim, H. E.: Verkehrswirtschaftliche Ermittlung von Qualitätsmaßstäben im Eisenbahnbetrieb; Veröffentlichungen des

Verkehrswissenschaftlichen Institutes der RWTH Aachen, Heft 54 (1999).

It can be assumed that all waiting times at a train station

caused by delays are valued by passengers in the same way


valuation of delays at a station

The means for the negative standardized part worth utilities indicate a common function with a constant to diminishing

marginal utility for delays at the originating station and waiting times caused by a missed connecting train.

assumption: All waiting times at a train station caused by delays are valued by passengers in the same way (e.g. also

waiting times at a station because of a delayed connecting train).

A simplified approach was used to roughly estimate a constant factor for the time being.

Quelle: FH Aachen

A comprehensive approach could be deduced for

the valuation of transfers


valuation of transfers

An average transfer with unknown platform

(including up to 10 min walking) is valued by

passengers like about 15 to 30 minutes additional

in-vehicle-time.

An average transfer includes an average need of

changing platforms. (assumption: With a probability

of 90% a transfer requires a change of platforms.)

Long-distance passengers attach a negative value

of about 15 to 20 minutes of in-vehicle-time to the

need of changing platforms for a transfer.

The value of a transfer can be reduced to about 10

to 15 minutes of in-vehicle-time, when it is ensured

that a change of platforms is not required (same

platform).

same

platform

unknown

platform

0

5

10

15

20

25

30

35

> 200 km100 - 200 km< 100 km

va

luati

on

of

tra

nsfe

rs

in r

ela

tio

n t

o in

-ve

hic

le-t

ime

[min

]

travel distance

90% • (valuation of change of platforms)

16

Outline


Empirical Methods



Outlook


Outlook

next steps

Within the project Evalinfra DB Netz AG has integrated the deduced factors in a travel

demand model.

The model has been implemented in the network planning system “WiZug/MOSES”.

An implementation of the model in further systems is pursued in order to achieve a consistent

assessment of qualitative infrastructure measures.

The deduced weighting factors and coherences can be integrated in further travel demand

models; yet, attention should be paid to the fact that if parameters are newly integrated in a

system of parameters, the whole system should be jointly adjusted according to its strengths

and weaknesses.

further research

Further research should concentrate on a further detailing of the weighting factors by the

purpose of the journey for the single attributes.

Particularly for the valuation of delays causing additional waiting times at a station a non-linear

approach should be pursued.

evaluation of supply quality in passenger transport as a basis for

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