town-planning ppt 2

8/10/2019 Town-Planning Ppt 2

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rban Transportation Planning

Process

Background

Movement of goods & people

Traffic and Transportation ProblemsDemographic and Socio-Economic


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Basis of Transportation Planning

Process

Travel Patterns are tangible

Movement Demand can be determined

nter-relation bet!een modes

Transportation S"stem nfluencesdevelopment of an area

Transportation Planning is an integralpart of overall planning


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Development of TPP #ro!th $actor %and use Traffic $lo! Traffic $unctional '(ongestion) Dela")

Poor *ccessibilit" and *ccidents) +e!$acilities etc,

*lternative $uture %and Use Dra! back Transportation S"stem to

fit Predetermined %and use


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INVENTORIESTransportation facilities

Land Use

Travel

LAND- USE

FORECASTPoplation

Econo!ic activit"

Land Use

TRAVEL FORECASTTrip #eneration

Trip Distri$tion

Ftre Travel De!and

PLAN PREPARATIONLand Use

Transportation S"ste!

PLAN TESTIN#Trip #eneration

Trip Distri$tion

Traffic Flo%

O&'ECTIVES (

STANDARDS

EVALUATION

$igure. Transportation Planning Process


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$actors nfluencing Transport

Demand %ocation of *ctivities

*vailabilit" of Transport S"stems Demographic and Socio-economic


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Demograph" Population Si/e

Population Structure

0ousehold Si/e

ncome %evel


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Urban Transportation Planning

Process Method of determining urban travel

demand

1ith group of models kno!n as2Se3uential *ggregate Models4


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5 distinct phases.

* surve" anal"sis and model buildingphase

$orecasting phase

Evaluation Phase


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Steps. Data collection

Establishment of basic relationships $our stage UTP

Prediction of input parameters

Prediction of future travel demand Plan preparation )Evaluation and

mplementation


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Trip #eneration

Person Trip Ends

Model Split

Transit trip ends +on-transit trip ends

Transit trip distribution

+on-transit tripdistribution

Trip End Models


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Trip

assignment

6 78

9 ::

5 66;

Production

;

5 ??

6 9 5

:=;

79;

6>?;

6

5

9

*ttraction

#eneration Distribution Mode (hoice

Mode 6=

Mode 9=

@oute a =

route b 68

route c 5


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Trip #eneration

Person Trip Ends

Model Split

Transit Trips +on-transit Trips

Trip nterchange Models

Trip Movements

Trip Distribution


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Definition of *reaABoundar"

-(ountr"

-@egion

-(it"

Establishment of (ordon lines

-Screen lines

-


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Manpo!er re3uirement Time involved 'Bar- (hart


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*nal"sis of Data & Modelling

*nal"sis carried out through four stage

se3uential planning process) traditionall"

kno!n as UTP 'Urban Transport Planning,

Trip #eneration

Trip Distribution Modal Split

Trip *ssignment


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Definition of T@PC

ne !a" movement from one place toanother place,

0D E

1D@

S0D


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T!o main classes of Trips

6, 0ome based Trips

-1ork Trip

-School Trip

-Shopping Trip

-Social Trip

9,

+0B Trips

-Bet!een !ork & Shopping

-Bet!een t!o places of emplo"ment


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Trip #eneration

Trip Production. *ssociated !ith tripsgeneration !ith residential trips,

Trip *ttraction. Trips associated to

describe generated b" activities at non-residential areas 'shops etc,,


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$actors *ffecting Trip#eneration

T@P P@D (T+

%and se $actors

F ntensities of residential activities

F Total population

F +o, of d!elling unitsF Population densit"


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0ousehold $actors

ncome $amil" Si/e

Gehicle o!nership $amil" Structure

Socio-Economic $actors

*ge) SeH


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ccupation

Propert" Galue

rbani/ation $actors

Degree of urbani/ation Distance

$rom (BD

*ccessibilit" $actors


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T@P *TT@*(T+

%and se $actors

(ommercial land use

ndustrial land use

Emplo"ment centers

Manufacturing @etail & 1holesale trade

@ecreational centers


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*ctivit" $actors

*ccessibilit" & %ocation $actors


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Methods of Trip #enerationModels


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Trip Production I f 'population)JJ,

Trip *ttraction I f 'Emplo"ment)JJ,

K I b; L b6H6L b9H9L JJL bH

b; I interceptb6 )b9,,,,b

To be estimated from

regression method


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Main issues in thedevelopment of this model

dentification of those variable !hich havesignificant and separate effects of trips

generation The model must not onl" provide good

statistical fit to present da" data but must

also be of a logical and meaningful form, The variables must be capable of being

estimated for future "ear,


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0ousehold %east S3uare@egression anal"sis

Similar eHcept instead of /oneC) ChouseholdC

is considered a trip making unit,

*dvantageous because of disaggregation

0o!ever) not used so far because of(ategor" anal"sis


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(ategor" *nal"sis

Developed b" 1ootan & pick 'U,,

0ouseholds are categori/ed into

ncome ': ranges

(ar-o!nership '5 ranges 0ousehold structure ': ranges


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Thus in all :5:I6;? categories are

established,

To each of these categories a trip rate is

assigned on the basis of surve" data,

P

i

I h

i

'c , T 'c

P

i

I +o, of trips produced b" /one b" a

certain t"pe of people,

h

i

'c I +o, of house holds in /one in

categor" c,

T 'c I trip production rate of household

categor",


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Problems.

Deriving trip rate for each categor"

*llocating household to categories in

the base "ear and future "ears,


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Trip Distribution

#ro!th $actor Models

- Uniform factor

TiNthI TiN

b , $

-*verage factorITiN

b, $iL $N

9


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- Detroit method

I $i , $N$

- $ratar methodI$i , $N, %iL %N

9

- $urness method #ravit" Models


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EHample. Detroit Method

9=9=;

=;

8=

9;; 7;;5;;

6;;

9= 6=;

6

9

5

9=9=;

=;

8=

9;; 7;;5;;

6;;

9= 6=;

6

9

5

6596;;;

=;

8=

68= ?;;5;;

5;;

55 =9=

6

9

5

659

659

5;;

6

9

5

Total 5;; L 6;;; L ?;; L 5;; I 97;;

bserved total 6;; L 9=; L7;; L5;; I6;=;

Therefore) $I97;;A6;=; I 9,9?

TiN I 9= '57A9,9? I 659


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#ravit" Models

*dopted from %a! f #ravit"

$

69

I #, M

6

M

9

d

69

9

T

iN

I @

i

(

N

P

i

*

N

f ' (

iN

T

iN

I Trip bet!een /ones i & N

P

i

I Production at

*

i

I *ttraction at N

f ' (

iN

I function that separates i & N

@

i

(

N

I constant of proportionalit"


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Unconstrained #ravit" model

Production constrained

*ttraction constrained

$ull" constrained


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#ravit" (alibration Procedure

Simulated & observed trip %ength fre3uenc"

distribution should eHhibit the follo!ing t!o

characteristics.

Shape & position of both curves should beclose to each other !hen comparedvisuall"

The difference of *v, Trip length should be!ithin O5,


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)

*

+)

+*

,)

+) +* +- ,) ,+ ,* ,- ,. /) // /* /. 0) 0, 0* *) ** 1)

Travel ti!e 2!in3

4ofto

taltrips

O$served

Si!lated


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If t5e fre6enc" crves do not !eet t5ese

criteria7 t5an a ne% set of travel ti!e

factors are esti!ated fro! t5e follo%in89f 2 Ci:

;3 < f 2 Ci:3 OD4=#>4

T5en plot?


40/45

$or calibration !e need to have /onal

production of trips ) /onal attraction of

trips and time matriH,

)

+)

,)

/)

0)

*)

1)

+) ,) /) 0) *)

Travel ti!e

Travelti!efac

tor


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Methods

0ome ntervie!

Postal 'Questioner

@oad side intervie!

#oods vehicle surve") ntermediate Public

Transport 'PT surve") Public Transportused also for Transport modeling purpose,


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$our stage UTP modeling

Trip #eneration

Trip Distribution

Modal Split *ssignment

The stud" area is grouped onto /ones and basic

information Adata are obtained from each /one,nformation of -D are prepared through -D

table 8Aor Desire-line diagram,

6 9 5 7

7

5

9

6

D


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+et!ork *ssignment

Essentiall" deals !ith the route choice of

traveller, steps involved.

(oding the net!ork 'node) centroids &links

(hoosing the shortest path

*ssigning the trips onto the net!orkthrough shortest paths,


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$rom +ode To +ode Distance 'm Speed

69; 696 6,7 7;

69; 69= 6,9 =;

696 69; 6,7 7;

696 699 6,; 7;

699 698 6,9 5;

698 699 6,7 7;

69= 69: 6,7 7;

69: 69= 6,9 =;

69;

69=

696 699

69:

698

5=

centroid


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Deficiencies *nal"sis

Proposed '%ong term

EHisting

Proposed 'short term

$easibilit" of %inks

EngineeringEconomic

town-planning ppt 2

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