household interview survey

Presentation on HIS

WorkshopOctober 18, 2010

Shogo Uchida, JICA Study Team

There is no royal road to learning.

Before this study

There is no officer’s road to technical transfer

Contents of PresentationBasic Concept of “Person Trip Survey”Person Trip Survey in JapanPerson Trip Survey in JICA StudiesBasic Concept of OD MatrixDemand Forecast and Interview Items Sampling of HIS in Karachi

Basic Concept of Person Trip Survey

What is “Person Trip Survey”?Survey for trip information of people:

What kind of person makes a tripWhenFrom where to whereFor what purposeBy which transport mode

All trip information for a person in a dayHousehold Interview Survey (HIS) is the main part of PT Survey

Home

Office

Customer

Shop

(1) Commuting (2) Business

(3) Business(4) Shopping

(5) To Home

Home Office

Walk Bus Rickshaw

1 Trip

What is “trip”

Minibus

Why?Base for transport analysis to formulate the transport master plan

Analysis of people’s trip behaviorAnalysis of trip flow in relation with urban structure and land useBasic data for Demand Forecast

Ave. no. of trips by age, gender, income level, ..etc

Mode Preference

Bus Rickshaw Taxi Private Car Walk

Peak time of travel

Ave. travel time

Ave. trip length Ave. no. of transfer

Trip purpose

Analysis of People’s Trip Behavior

Person Trip Survey in Japan

50 years history

Person Trip Surveys in JapanOfficial Survey by Local Government

Need approval from Ministry for Internal AffairsSubsidy from GOJ

Major Cities (more than 40)1962 -Every 10 yearUsed for transport master planMethod: household drop-off/pick-upSampling: “household” list

Person Trip Surveys in Japan

Person Trip Survey in Japan

Person Trip Surveys in Japan

Trip rate:Around 3.0 (who made trips)Around 2.5 (total)

Person Trip Survey by JICA in the World

More than 30 cities

Person Trip Surveys by JICA in the World

Characteristics of JICA PT SurveysShort periodUnreliable socio-economic data

Adjusted by screen line surveySubcontract to local firms

No experience of local firms in PT surveysWith socio-economic surveyOpinion surveyDirect interview method

Issues of JICA PT SurveyRapid growth and developmentRapid motorization

Rapid changes in transport pattern O/D becomes old in several years.

Technical transfer SurveyDemand forecast model

Basic Concept of OD Matrix

What is OD matrix and how to produce from samples

A-ZoneB-Zone

C-Zone

D-Zone

Bus Terminal

Traffic Flow on Bus RouteTraffic Flow on Bus Route

A-ZoneB-Zone

C-Zone

D-Zone

Desired RoutesDesired Routes

Potential corridors will be identified.

Analysis of People’s Movement

Total

ZoneN

…

Zone2

Zone1

TotalZoneN…Zone2Zone1

Origin-Destination Matrices Generation

AttractionAttraction

by

Mode

Purpose

Income level

Age

Gender

Etc.

OD – Basic data for transport analysis

Expansion of samplesPopulation size (total number) of trips is unknown.Sampling rate of the trip information can not be calculated.

Trips are expanded based on “person”

Total

12.1%2.4%1.8%1.5%D Town

2.4%18.2%3.6%4.2%C Town

1.8%3.6%24.2%3.0%B Town

1.5%4.2%3.0%12.1%A Town

TotalD TownC TownB TownA Town

Expansion factor (EF)= 1/ (sample rate of person)

1 trip of Mr. A is converted to EF trips

- Karachi HIS: 1 trip 80 trips(40,000*5)/16,000,000 = 80

Screen Line SurveyTraffic count along a “screen line”, which divides the survey areaTo count the total number of traffic crossing the lineTo check the O/D matrix produced from HIS

Lyari River was selected as the screen line3.5 million persons cross the screen line per day (2008, JICA)

Screen Line

Cordon Line SurveySamples of HIS are only residents:

movement of visitors is not included

O/D interview survey at “cordon lines”: enter-exit points

RoadsAirportsPortsStations

Karachi:Highway (3 points)AirportStation

JICA 2008 Study90,000 visitors from/to highway cordons15,000 visitors by railway10,000 visitors by air

Vehicle O/DHIS only collects trips by residents.Other surveys or models are needed to estimate Vehicle O/D.

NoNoTruck

NoNoTaxi (empty)

No (OK by CL survey)NoNon-Residents

OKOKResidents

Inside-OutsideWithin the areaTrip by

Demand Forecast and Interview Items

Why we ask the question?

Demand Forecast ModelTraditional Demand Forecast Model – 4 step demand forecast

Trip productionTrip generation/ attraction modelTrip distribution modelTrip assignment model

OD of “Trips” is the base of the modelLinkage of trips of a person is ignored.Modeling becomes simple and stable.

Trip Production Model

PaTP ⋅= a = trip rate per personP = population of Karachi

ccc PaTP ⋅= c = 1: car own householdc = 2: household without car

Simple

Complex

∑ ⋅=i

cicic PaTP

),...,,( 21 nxxxfTP = x = all available variables

i: personal attributes - Age & Gender- Age & Gender & Income- Age & Gender & Income & Job status

∑ ⋅=i

cicpicp PaTP p: trip purpose

Trip Generation/ Attraction Model

Simple

Complex

rrr PaTP ⋅= ar = trip rate per person of zone rPr = population of zone r

rcrcrc PaTP ⋅= c = 1: car own householdc = 2: household without car

∑ ⋅=i

rcircirc PaTP

),...,,( 21 nxxxfTP = x = all available variables

i: personal attributes - Age & Gender- Age & Gender & Income- Age & Gender & Income & Job status

∑ ⋅=i

rcircpircp PaTP p: trip purpose

h: peak factor

by job statusby job status5

by income groupby income group4

by age group, genderby genderby car-license status

3

by purpose

by time, by mode

AllOD

by age groupby purpose

2

by car-ownership1: Need

per person0: MustProduction, G/ALevel

Necessary Model Parameters

Necessary InformationFor modeling

Household Income LevelCar ownershipJob Status (worker, jobless, students,…)Age, genderCar licensePersonal income levelZone of householdZone of working place/ school

For surveyAccurate addressTelephone numberNameFamily structure

Trip InformationOrigin and destination (address, type)Departure and arrival timesModePurposeTransfer pointsCost (fare) of transportSelf-Drive or not

Linked trip and unlinked tripLinked trip

Trip on purposeUnlinked trip

Trip on mode

Linked trip is the base of demand forecastInfo. on unlinked trip is used to make the present OD by mode

Used for calibration

Home Office

Walk Bus Minibus Walk

1 Trip (Linked Trip)

Unlinked trips

Priority mode of a linked tripOD of Linked Trip:

By purpose clearBy mode not clear

OD by mode is made using “Priority mode”.Priority mode is the major mode in a trip.Identification of priority mode is not easy

Simply decide by hierarchy

TrainBusCarTaxiRickshawWalk

Usage of OD by mode depends on modeling

High

Low

Sampling and Expansion

Statistical approach

Statistical background

answer of % :psize Sample :n

size Population :Ninterval confidence 95%for 96.1

)1(1

=

−⋅

−−

±=

Zn

ppN

nNZerror

Formulation of Error

2

2

2

2

25.0

)1()/11(1

1

eZ

eZ

ppN

N

n

≅

⋅−

−+

=

Necessary no. of samples(N is large, p=0.5)

0

5

10

15

20

0 500 1000 1500 2000

Err

or (%

)

No. of samples

Error and no. of samples under 95% confidence interval

400 samples can achieve 5% error level

Sampling rates in Japan Sampling rate is calculated using

Sampling example:Tokyo: 2.68%Nagoya: 2.8%Osaka/Kyoto: 2.3%

modes of No.purposes of No.zones of No.:K

rate Sampling :r trips)(Total size Population :N

96.120% error relativeRSD

)1()1(

××

===

−⋅−±=

Z

rNrKZRSD

Sampling check after the surveyExample problem – Male : Female

53.9% : 46.1% in Karachi (1998 Census)560 : 440 from 1000 samples Is this OK? (Should be 539: 461 ….?)If not OK, sampling was wrong.

Chi-square test

( )∑=

−=

N

i i

ii

EEO

1

22χ

…

…

11.0709.4887.8155.9913.8415%

54321Degree of freedom

Oi : Observed valueEi : Expected value

Sampling check after the surveyExample Problem: It’s OK.

Test: distribution of gender and age groupNeed population data by gender by age group

If expansion factor is determined by gender by age, this test is not required.

Also need reliable data by gender by age group

( ) ( ) 841.3775.1461

461440539

539560 222 <=

−+

−=χ

Limitation of HIS data Breakdown will decrease reliabilityExample:

OD (UC Level) by purpose by mode by gender by age group

maybe unreliableOD (UC Level) by mode by income level by car ownership by occupation almost impossible

Need to check relative error before using breakdownRelative Error

Within 20%

answer of % :psize Sample :n

size Population :N

)1(1

96.1pn

pN

nNpp −

⋅−−

±=Δ

Breakdown Check: Example

Trips by mode by purpose by townExample: Purpose 20% (to work, for example), Mode 12% (Car), Town (1/24) p=0.2*0.12*(1/24)=0.01 (1%)n = 10,000 (per town)0.8% < p < 1.2%

Relative error = 20% OK

In case less n (ex. 2,000) (breakdown by age, gender, etc) 0.5% < p < 1.5%

Relative error = 44% No use

Trips by mode by UCExample: Mode 20% (Minibus), UC (1/200) p=0.2* (1/200)=0.001 (0.1%)n = 400 (per UC)0% < p < 0.4%

Relative error = 300% No use

Check is available after HIS

Why “household” survey for “person” trip?

Traditional demand forecast uses “trips”.Personal interview

Only trips for his/hersHH interview

Only trips for only the members’ of the HH

Reliability of HH sampling is lower than that of personal sampling

Random sampling of “trips”is practically impossible.

HH survey can collect many samples by one visit.

Reliability can be improved by larger no. of samples.

HH survey is the best in terms of cost and time

performance.

Sampling and Expansion

Household

Member

Trip

Population samples

Household

Member

Trip

sampling

sampling(all)

All trips

Calculate expansion factor

Expansion

Expansion factorin case statistics of age and gender are not available

Data Layout of the Result1 Trip = 1 Record (is popular)

Household InformationTrip-ID Personal

Attribution Trip information Expansion Factor

Same data repeated

Origin Destination Purpose Mode-1 Mode-nDate Start

timeend time

Sampling in Karachi

As random as possible

SamplingSamples should represent the population

Sampling should be “random”Random sampling is very difficult when a list of households is not available.

In Japan, sample households are selected randomly from household lists.

In Karachi, randomness cannot be ensured; however, sampling should be as much as random.

Condition of randomness in PT SurveySample households should reflect proportion of socio-economic of UC.Area distribution of sample households should also be random.

Even if this sample reflect the socio-economic proportions of the population, trip information is not random.

triptrip

trip

trip

Sub division of UCUC is divided into 3-5 sub zones to ensure the randomness of place.This sub-divided UC is called “Survey Zone” – more than 750 survey zonesAccurate UC boundary maps are necessary.

Sampling in a sub-zoneThere are three methods:

Put identity number to every houses in maps and select samples at random (1)Visit a house for every 100 buildings (2)Pick up a representative area in the sub-zone and visit all the houses (3)

Comparison of three methods

If the sub-zone consists of similar type of houses, this is proper method.

- Randomness is ensured only if the area represents the population.- Lower area randomness

- Can avoid surveyors’preference for house selection.- Surveyors mobilization is easy.

3

Apply this method under proper supervising

- Surveyors tend to visit houses which is easy to access (in terms of hospitality and friendly)

- Randomness of place is ensured.- Field survey is simple and practical.

2

Impassible due to limited resources

- Time-consuming work- Difficult to reach the target due to low literacy of surveyors for map reading

- Randomness is ensured.1

EvaluationDisadvantageAdvantageNo

Sampling method in this StudyMixture of 2 and 3Select representative blocks in the center of a Survey ZoneDeploy enumerators along streets in the blocksEasy to supervise and organize

Date check (Editing) and CodingEditor: check the survey forms after interview

Logical checkFill in blank, if possibleDecipher hand writing

Coder: translate text to number

Find zone code from address is the major work.

Example of editing“Bus stop” near origin and destination can be translated to address. Gender can be assumed by the name.1 and 7 can be distinguished by other information.06:00 after 9:00 may be 18:00