Modelling World 2011

MODAL CHOICE DECISION MAKING BY TRAVELLERS

Embracing changing behaviour in a world of exploding information on options and ever changing prices : a forecasting perspective

Luis Willumsen

KEY REQU

IREMEN

TSThe four pillars of good The four pillars of good forecastingforecasting models models

• Good future population synthesis

• Good future population synthesis

• System equilibrium

• System equilibrium

• Consistency of future behaviour

• Consistency of future behaviour

• Behavioural choice modelling

• Behavioural choice modelling

Utility functions and choice models

applied at different levels of aggregation

Utility functions and choice models

applied at different levels of aggregation

The parameters in the utility functions

remain the same

The parameters in the utility functions

remain the same

Accurate allocation of populations and

activities in the future

Accurate allocation of populations and

activities in the future

Appropriate feed-back through all

relevant submodels to ensure consistent

results

Appropriate feed-back through all

relevant submodels to ensure consistent

results

j

m

U

j U

m

eP

e

jq jq jqU V

ForecastingForecasting

BEHAVIO

URAL M

OD

ELSUtility functionsUtility functions

Modelling choicesModelling choices

Homo EconomicusHomo EconomicusRational individuals j seeking to maximise their utilityChoosing among different alternatives qModeller has incomplete knowledge but can estimate the most significant part of the “utility function”The systematic component Vjq

contains attributes like: time, fare, income, sex and an ASC (comfort, convenience.....)

The random component ejq absorbs all the unknown variable influences and the unexplained behaviour.

jq jq jqU V

j

m

U

j U

m

eP

e

• The number of options available keeps increasing

• Prices are becoming less crisp, fixed and predictable

• But some things still appear to be free

• Moreover, we change our mind...

• Behavioural Economics and the 2008/9 crisis have established the inexistence of Homo Economicus

• What does this means for modelling?

• Have we reached the limits of forecastability?

• What should we do then?

A c

han

gin

g

con

text

In a changing world...

Homo EconomicusHomo Economicus

A "rational" being that considers opportunities and seeks to optimise his/her utility by careful choices.

We cannot have access to these “utilities” but can infer the most important components by means of utility functions and choice models

Homer SapiensHomer Sapiens

A partly rational but also emotional and collaborative being that tries to find happiness, respect from peers and a sense of purpose in what he/she does.

Behavioural Economics sheds some light on the predictatibility of his/her behaviour, often inconsistent with our models

THE D

IFFICULTIES O

F HO

MO

ECON

OM

ICUS

Plethora of choicesPlethora of choices

There is clear evidence that we cannot really consider more than a few alternatives at a time, perhaps 3-4If more than 3 we use heuristics: habit, elimination by aspects, affect (emotion), resemblance, confirmation

How do we incorporate these into our demand models?

Known biases in choiceKnown biases in choice

Anchoring, Attentional Bias, Groupthink, Bias blind spot, Choice-supportive bias. Confirmation bias, Congruence bias, Contrast effect, Denomination effect, Distinction bias, Endowment effect, Expectation bias, Focusing effect, Framing effect, Hostile media effect, Hyperbolic discounting, Illusion of control, Impact bias, Information bias, Irrational escalation, Loss aversion, Mere exposure effect, Money illusion, Moral credential effect, Negativity bias, Neglect of probability, Normalcy bias, Omission bias, Outcome bias, Planning fallacy, Post-purchase rationalization, Pseudocertainty effect, Reactance, Restraint bias, Selective perception, Semmelweis reflex, Social comparison bias, Status quo bias, Unit bias, Wishful thinking, Zero-risk bias

THERE IS ALSO A PROBLEM WITH MONEY...THERE IS ALSO A PROBLEM WITH MONEY...

IS MO

NEY ALW

AYS MO

NEY?

Different kinds of moneyDifferent kinds of money There is evidence thatThere is evidence that

As we move away from cash price (money) becomes less well defined...and willingness to pay is easier..As we increase the time elapsed between use and payment a similar effect is found

If prices change significantly over time and we pay electronically the effect is amplified

UN

DERSTAN

DIN

G M

ON

EYThe knowledge of prices The knowledge of prices

Is becoming more tenuous

Extreme examples: information is available but it is impossible to use.

Almost inevitably this happens in large and complex toll roads;

But may also happen in extensive Public Transport networks with complex fare structures.

Singapore Before and AfterSingapore Before and After

SANTIAG

O TO

LL ROAD

S

5 + 1 concessions

All with three level pricing:6/12/18 US cents/km

Interoperable tags

~ 1.2 million tags in 2006

Full toll collection started January 2005

Santiago ETC urban systemSantiago ETC urban system

CONGESTION

CHARGI

NG

IN

SANTIAGO

Speed flow relationship for Autopista Central motorway link

0

20

40

60

80

100

120

0 1000 2000 3000 4000 5000 6000 7000 8000

Flow Veh/h

Sp

eed

km

/h

40 Ch$/km

Capacity

20 Ch$/km

60 Ch$/km

Objective: free-flow roadObjective: free-flow roadSAN

TIAGO

TOLL RO

ADS

EXAMPLE O

F EXPECTED CH

ARGIN

G SCH

EDU

LE

AM FP PT SA DO AM FP PT SA DO AM FP PT SA DO1 NS TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP1 SN TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP2 NS TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP2 SN TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP3 NS TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TS TBFP TBFP3 SN TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TS TBFP TBFP TBFP TBFP4 NS TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP4 SN TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP5 NS TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TS TBFP TBFP5 SN TBP TBFP TBFP TBFP TBFP TS TBFP TBFP TBFP TBFP TS TBFP TBFP TBFP TBFP6 NS TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBP TS TBFP TBFP6 SN TBP TBFP TBFP TBFP TBFP TS TBFP TBFP TBFP TBFP TS TBFP TBFP TBFP TBFP7 NS TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TS TBFP TBP TBFP TBFP7 SN TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP8 NS TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBP TS TBFP TBFP8 SN TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP9 NS TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP9 SN TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP10 NS TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TBFP TS TBFP TBFP10 SN TBFP TBFP TBFP TBFP TBFP TS TBFP TBFP TBFP TBFP TS TBFP TBFP TBFP TBFP11 NS TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TS TBFP TBFP11 SN TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TS TBFP TBFP TBFP TBFP12 NS TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP12 SN TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TS TBFP TBFP TBFP TBFP13 NS TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP13 SN TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP TBP TBFP TBFP TBFP TBFP

2010Section Direction

2007 2015

Simplified Price Structure Simplified Price Structure (changes in 30 mins intervals)(changes in 30 mins intervals)

PLUS, A COUPLE OF COMPLEXITIES FROM BEHAVIOURAL PLUS, A COUPLE OF COMPLEXITIES FROM BEHAVIOURAL ECONOMICS...ECONOMICS...

OVERVALU

ING

WH

AT WE H

AVEOther considerations from Behavioural EconomicsOther considerations from Behavioural Economics

Price elasticities are not symmetric: a 10% loss in utility is not compensated by a 10% gain

The role of big changes The final state of a system

depends on the sequence of interventions

System Equilibrium may be less useful than we believe

The high price of ownership: cars vs public transport

OVERU

SING

WH

AT SEEMS TO

BE FREEOther considerations from Behavioural EconomicsOther considerations from Behavioural Economics

The high cost of Zero Price Gratis blind us to rational

decision making ..at a great cost in

congestion, pollution and quality of life

Pricing for externalities is inevitable

We can start with HOT lanes

• Therefore understanding how we parse variable and fuzzy prices will become paramount

THE LIM

ITS OF M

OD

ELLING

So....So....

Human nature limits the accuracy of our models

There is scope for improving our models, recognising Homer Sapiens decision making and the fuzziness of money

We will learn more about human behaviour and improve short-term forecasting

..but the contribution to accurate long-term forecasting will be limited

Interpretation and judgement will have to become more open and transparent

..and, we need to explore new sources of data and new tools of analysis to improve forecasting

ABUN

DAN

CE OF D

ATAFor example.....For example.....

There are a lot of sensors and data out there

GPS units Bluetooth units Mobile phones CCTV cameras ATC, ITS

• These create new opportunities for data & representative experiments

• We should seek to obtain more from this abundance of data

POIN

TERS FOR FU

TURE RESEARCH

What about the future then?What about the future then?

• We need transport demand forecasting but our existing tools are less reliable than we pretend

• Future models should be based more on Homer Sapiens than on Homo Economicus

• Interpretation and judgement, professional responsibility, should be more open and transparent

• The use of complementary models, that look at the future from different perspectives, should help long-range forecasting

• Exploiting the overabundance of data out there will lead to a different approach to policy advice, experimentation and decision making support

THANK YOUTHANK YOU