2_urban and regional transport planning

8/13/2019 2_Urban and Regional Transport Planning

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Chapter Two

Urban and RegionalTransport Planning

Er. Satya Ram Duwal

1Transportation planning and engineering

Er.Satya Ram Duwal

COURSE OUTLINE

Transportation planning and engineering

Er.Satya Ram Duwal2

1.Differences between urban and regional planning

2.Differences in planning for movement of people

and goods

3.Hierarchical structure to transportation planning:

intermodal approach and integrated development

approach

4.Transport demand surveys and studies: survey

design and field studies, data requirements for

passenger and freight movements

5.Predicting future demand


Er.Satya Ram Duwal3

Regional planning:

Regional planning is a category of planning and development

that deals with designing and placing infrastructure and other

elements across large area

Urban planning:

Urban, city and town planning is the integration of land use

planning and transport planning, to explore a very wide range

of aspects of the built and social environment of urbanized

municipalities and communities.


Er.Satya Ram Duwal4

Differences between urban and regional planning

Difference between planning for

movement of goods and people

Vehicles

Transportinfrastructure

Persons andGoods


Er.Satya Ram Duwal5

Transportation system hierarchy


Er.Satya Ram Duwal6


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Er.Satya Ram Duwal7


Er.Satya Ram Duwal8

Transportation Survey

Basic movements in Transportation

survey:

Internal to internal

Internal to external

External to external

External to internal


Er.Satya Ram Duwal9

Basic movement of transportation survey


Er.Satya Ram Duwal10

Externaltoe

xternal

Internaltoi

nternal

External to Internal

External Cordon

Screen line

InternaltoE

xternal

Fig. Basic movements in a transportation syrvey

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Survey data can be collected :

At home

During the trip

At the destination ends of trip.




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Following are some of the types of transportsurvey:

Home interview survey

Commercial vehicle survey

Taxi survey

Road side interview survey

Post card questionnaire survey

Registration number plate survey

Tags on vehicle survey

public transport survey

Traffic flow survey (roadside traffic count, intersectiontraffic count, vehicle speed survey)

Inventories of land-use and economic studies



1) Home interview survey Is the most reliable types of survey for the collection of

O-D data.

Is intended to yield data on the travel pattern of

residents of the household and general characteristicsof the household influencing trip making.

Information on travel pattern includes:

Number of trips made,

Origin and destination

Purpose of trip

Travel mode

Time of departure and arrival



Information on household characteristicsincludes:

Types of dwelling unit

Number of residents

Age, sex composition

Vehicle ownership

Number of driver

Family income

home interview may

Full interview technique

Home questionnaire



This is very expensive to conduct, thus generallymanuals on this survey have been developed.

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2) Commercial vehicle survey

It is conducted to obtain information on

journey made by all commercial vehicles

based within the study area. Address of the

operators is obtained and forms are issued to

drivers with the request that they record

particulars of all trips they could make.


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3) Taxi survey

Large urban areas usually have a

sizeable amount of travel is made bytaxi. In such cases separate taxi

survey is necessary to conduct. The

survey consists of issuing

questionnaire or log sheets to the

taxi drivers to complete them.



4) Road side interview survey

It is one of the methods of carryingout a screen line or cordon survey. Itcan be done by directly interviewingdrivers of the vehicles at selectedsurvey points or by issuing prepaidpost cards containing thequestionnaire to all or a sample ofthe drivers.




5) Post card questionnaire

In this method reply-paid

questionnaires are handed over to

each driver or a sample at the survey

points, and requesting them to

complete the information and result

by post. In developing country, this

method may not be suitable.




6) Registration Number Plate Survey

This method consists of noting theregistration numbers of vehicles entering

and leaving an area at survey points

located on the cordon line. By matching

the registration numbers of the vehicles

at points of the entry and exit from the

area, two points on the paths of the

vehicle can be identified.




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7) Tags on vehicle method

In this method at each point where the

roads cross the cordon lines vehicles are

stopped and a tag is fixed usually under

the windscreen wiper. The tags for

different survey stations have different

colour and shapes to identify the survey

station. The vehicles are stopped again at

the exit point when tags are collected




8) Public transport survey

In order to assess the number of bus

passenger passing through the external

cordon, the survey can either by direct

interview with passengers or by issuing post

card questionnaires.



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9) Traffic flow survey

Roadside traffic count

Intersection traffic count

Vehicle speed survey



11) Inventory of land-use and economic

activities:

Inventory of land use: Zones and classified as:

Residential

Industrial

Commercial

Recreational

Open space

Institution etc



Inventory of economic activities:

Population zone wise

Age sex, family composition

Employment statistics

Housing statistics

Income study

Vehicle ownership



Data of User characteristics - passenger

The most commonly used surveys in urban

transportation planning focus on data

collection in

household

Work place or special work generating place

Visitor or tourist centers

Vehicle intercept and external stations

Transit lines


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Travel demand forecasting

Travel demand forecasting is the estimating

the demand for transport facilities and

services for future design period. Travel

demand forecasting is most important step in

transport planning.




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The traditional four step process

Trip generation forecasts the number of tripsthat will be made

Trip distribution determines where the trips go

Mode usage predicts how the trips will bedivided among the available modes of travel

Trip assignment predicts the routes that the tripswill take, resulting in traffic forecast for thehighway system and ridership forecast for thetransit system.





Four step transport planning

ER. SATYA RAM DUWAL 3912/11/2013

Chapter 3

urban transportation planning process

1. Planning phases: trip generation, trip

distribution, model split, and traffic

assignment

2. The supply side of transportation: the modes,

their roles and characteristics (capacity, costs

etc)

3. Other recent approaches to transportation

planning.



1. Trip generation

Trip generation is the process by which

measures of urban activity are converted in to

numbers of trips.

Trip ends are classified as being either a

productionor an attraction



Trip generationis the first step in the conventional four-

step transportation forecasting process (followed by trip

distribution, mode choice, and route assignment), widelyused for forecasting travel demands. It predicts the number

of trips originating in or destined for a particular traffic

analysis zone.

Typically, trip generation analysis focuses on residences,

and residential trip generation is thought of as a function

of the social and economic attributes of households. At the

level of the traffic analysis zone, residential land

uses"produce" or generate trips.

Trip Generation:

42ER. SATYA RAM DUWAL12/11/2013
http://en.wikipedia.org/wiki/Transportation_forecastinghttp://en.wikipedia.org/wiki/Trip_distributionhttp://en.wikipedia.org/wiki/Trip_distributionhttp://en.wikipedia.org/wiki/Mode_choicehttp://en.wikipedia.org/wiki/Route_assignmenthttp://en.wikipedia.org/wiki/Triphttp://en.wikipedia.org/wiki/Traffic_analysis_zonehttp://en.wikipedia.org/wiki/Traffic_analysis_zonehttp://en.wikipedia.org/wiki/Househttp://en.wikipedia.org/wiki/Householdhttp://en.wikipedia.org/wiki/Land_usehttp://en.wikipedia.org/wiki/Land_usehttp://en.wikipedia.org/wiki/Land_usehttp://en.wikipedia.org/wiki/Land_usehttp://en.wikipedia.org/wiki/Land_usehttp://en.wikipedia.org/wiki/Householdhttp://en.wikipedia.org/wiki/Househttp://en.wikipedia.org/wiki/Traffic_analysis_zonehttp://en.wikipedia.org/wiki/Traffic_analysis_zonehttp://en.wikipedia.org/wiki/Traffic_analysis_zonehttp://en.wikipedia.org/wiki/Traffic_analysis_zonehttp://en.wikipedia.org/wiki/Traffic_analysis_zonehttp://en.wikipedia.org/wiki/Triphttp://en.wikipedia.org/wiki/Route_assignmenthttp://en.wikipedia.org/wiki/Route_assignmenthttp://en.wikipedia.org/wiki/Route_assignmenthttp://en.wikipedia.org/wiki/Mode_choicehttp://en.wikipedia.org/wiki/Mode_choicehttp://en.wikipedia.org/wiki/Mode_choicehttp://en.wikipedia.org/wiki/Trip_distributionhttp://en.wikipedia.org/wiki/Trip_distributionhttp://en.wikipedia.org/wiki/Trip_distributionhttp://en.wikipedia.org/wiki/Transportation_forecastinghttp://en.wikipedia.org/wiki/Transportation_forecastinghttp://en.wikipedia.org/wiki/Transportation_forecasting


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Factors that influence production

The following factors influence the production of a zone:

Households characteristics-Income

-Household structure (number going to work, number going toschool, age )

-Car ownership

Zone characteristics

-Land use

-Land price

-Residential density, rate of urbanisation

Accessibility

-Extent of transport options from the zone.

-Quality of transport options from the zone




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Factors that influence attraction Number of employees

Land-use

-Industrial (type of industry, occupied area)

-Educational facilities

-Shops (floor area, sales)-Service sector (hospitals, banks, governmentinstitutions, conference centres )

-Recreational (sport centres, tourist- or amenity sites,theatres )

-Storage and transfer (harbours, airports )

Accessibility

-Extent of transport options to the zone

-Quality of transport options to the zone



1.1 Trip generation models:



iii tFT

Basic equation for the Growth factor model ing

1.1.1. Growth facto r mo del ing

Where, Ti and tiare respectively future and current trips in zone i

and Fi is the growth factor. Normally growth factor is related to

variables such as population (P), income (I), car ownership (C), in a

function such that:

)(

)(

ci

ci

ci

di

di

di

iCIPf

CIPfF

Wheref can be a direct multiplicative function with no parameter,

and the superscripts dand cdenote the design and current years

respectively



Example: Consider a zone with 250 households with

a car and 250 households without car. Assuming we

know the average trip generation rate of each group:

Car owning household produce: 6 trips /day

Non-car owning household produce: 2.5 trips /day

daytripsXXti /0.21250.62505.2250



Let us assume that in the future all household

will have a car; therefore, assuming that

income and population remain constant, we

can estimate simple multiplicative growth

factor:

2ci

di

iC

CF



daytripsXTi /425021252

daytripsXTi /30006500

Applying the growth factor model;

However, this method is crud.

We can estimate future number of trips generated as:




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.........332211 XbXbXbaY

1.1.2. Regression analysis

In a linear regression model we try to predict a

variable Y as a linear function of one or more

influence variablesXi







Dependent Variable

(Y) = Trip generation per household

Independent Variable X1= cost per trip

X2= No of workers per household

X3= vehicle ownership

The Regression equation will be

Y = a X1+ b X2+ c X3+d

ER. SATYA RAM DUWAL 59

Regression Analysis

12/11/2013

Y X1

X2

X3

Trip generation

per household

Total Cost of

trip

No of workers

per household

Vehicle

ownership

6 48 4 0

4 34 2 1

3 24 2 0

5 191 3 2

6 48 4 0

6 198 4 4

3 24 2 0

3 48 2 1

2 16 1 1

4 66 2 2ER. SATYA RAM DUWAL 60

Trip Generation Survey (site Pepsikola)

12/11/2013


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Trip generation

per household

Total Cost of

trip

No of workers

per household

Vehicle

ownership

6 48 4 0

3 68 2 12 16 1 0

6 108 4 1

2 16 1 0

2 25 1 1

6 318 4 3

5 40 3 0

4 32 2 0

6 327 4 4


Trip Generation Survey (site Kupandol)

12/11/2013

Trip generation

per household

Total Cost of

trip

No of workers

per household

Vehicle

ownership

4 98 2 2

6 57 4 25 68 3 1

3 24 2 0

3 64 2 1

6 84 4 1

6 228 4 2

4 32 2 0

5 40 3 0

6 66 4 2


Trip Generation Survey (site Kritipur)

12/11/2013

Categories Total Numbers Categories Total Numbers

0 vehicle 12 No Vehicle 12

1 vehicle 9 With Vehicle 18

2 vehicle 6

3 vehicle 1

4 vehicle 2

ER. SATYA RAM DUWAL 6312/11/2013

Correlation between the independent variable must be

avoid for regression analysis.

Analysis Options for Three independent Variables

Dependent Variable(Y) vary only one variable for best fit.

Dependent variable(Y) vary only two variable for best fit.

Dependent variable(Y) vary three variable for best fit.


Analysis Options and relation between the variable

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Regression

Statistics

Trip generation per

household Vs.Cost per trip

(b=c=0)

No of workers per

household (a=c=0)

Vehicle ownership

(a=b=0)

Multiple R 0.549430149 0.976051408 0.415821653

R Square 0.301873489 0.952676352 0.172907647

Adjusted R Square 0.276940399 0.950986222 0.143368635

Standard Error 1.275004881 0.331958574 1.387783709

Observations 30 30 30


Analysis Using Single Variable

Y = a X1+ b X2+ c X3+d

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Regression

Statistics

Trip generation per

household Vs.

Cost per trip (a=0)No of workers per

household (b=0)

Vehicle ownership

(c=0)

Multiple R 0.549430149 0.976051408 0.415821653

R Square 0.301873489 0.952676352 0.172907647

Adjusted R Square 0.276940399 0.950986222 0.143368635

Standard Error 1.275004881 0.331958574 1.387783709

Observations 30 30 30


Analysis Using Two Variable

Y = a X1+ b X2+ c X3+d

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Regression Statistics

Multiple R 0.976292927

R Square 0.953147879

Adjusted R Square 0.947741865

Standard Error 0.342769168

Observations 30


Analysis Using Three Variable

Result: Best fit Regression model is, Using Three

Variables

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CoefficientsStandard

Errort Stat P-value Lower 95% Upper 95%

Intercept 0.791660 0.173657 4.558746 0.00011 0.43470 1.14862

Cost per trip -0.000494 0.001463 -0.337578 0.73839 -0.00350 0.00251

No of workers

per household1.316094 0.069439 18.953341 9.65E-17 1.17336 1.45883

Vehicle

ownership0.048230 0.095827 0.503308 0.61899 -0.14874 0.24520


The Regresin Equation may beY= -0.000494 X1+1.316094 X2+ 0.048230 X3+ 0.791660

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0

1

2

3

4

5

6

7

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

NumberofTripgereratedperhousehold

Household Indicator number

Actual Trip generation per household Predicted Trip generation per household

Analysis between Actual trips and Estimated trips


-1

0

1

2

3

4

5

6

7

1 4 7 10 13 16 19 22 25 28


Household Indicator number

Predicted Trip generation per household Residuals Actual Trip generation per household


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Regression Statistics

Multiple R 0.976292927

R Square 0.953147879

Adjusted R Square 0.951474589

Standard Error 0.322470174

Observations 30



Result: The relation between Actual and Estimated trip is

considerable so we can use this model for estimate trip

generation.12/11/20 13 ER. SATYA RAM DUWAL 72

-1

0

1

2

3

4

5

6

7

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29


Predicted Trip generation per household Residuals Actual Trip generation per household


12/11/2013


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1.1.3. Category analysis or cross classification

In a category analysis the population of the

study area is divided into a number of

homogenous groups or categories, based on

specific socio-economic characteristics.

The trip behavior is determined for each of

the categories, with the understanding that

this will remain stable over time.



Example:

A Number of household and total trips made, categorized by

household size and car ownership level.



a)Automobile ownership

0 1 2 or more

Family

size HH No

Total

trips HH No

Total

trips HH No

Total

trips

1 925 1098 1872 4821 121 206

2 1471 2105 1934 6129 692 1501

3 1268 1850 3071 13989 4178 19782

4 or

more 745 1509 4181 18411 4967 25106



b)Household trip rates

Automobile ownership

Family size 0 1 2 or more

1 1.19 2.58 1.70

2 1.43 3.17 2.17

3 1.46 4.56 4.734 or more 2.03 4.40 5.05

1098/925

c)Forecasted number of households in one zone,

categorized by household size and car

ownership level




Family

size 0 1 2 or more

1 24 42 8

2 10 51 107

3 11 31 158

4 or more 3 17 309

d) Forecasted number of trips for this

zone




Familysize 0 1 2 or more Total

1 28 108 14 150

2 14 162 232 408

3 16 141 748 905

4 or more 6 75 1562 1643

Total 65 486 2556 3106

24 X 1.19

1.2 Trip Distribution models

The aim of a distribution model can now be

described as follows:

Distribute the trips that originate in a particular zone over

all destinations

Distribute the trips with a destination in a particular zone

over all origins

Therefore main aim is to determine the O-D

table for a particular forecast year




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1.2.1 Gravity model:



Ti-jNumber of trips from itoj

K and n-constant

Piis production of i

Ai is the attraction ofi

D is the distance betweenI and j



zones Trips

produced

Trips attracted

A 1500 2500

B 2500 3000

C 3000 1500

Example: Total trips produced in and attracted to the 3 zones A,B,C of a survey

area in the design year is tabulated as:

It is known that the trips between two zones are inversely proportion to the

second power of the travel time between zones, which is uniformly 25

minutes. If the trip interchange between zones B and C is known to be 350,

calculate the interchange between zones A and B, A and C , B and A and C

and B

Solution hint

Determine value of K using given data Ti-j=350, d=25,

Pi=PB=2500 , Pj = Pc=1500, n=2 given on question

For trip interchange between A and C, d=25,

Pi=PA=1500 , Pj = Pc=1500, n=2 and so on

Use i as trip produced and j as trip attracted.



1.2.2 GROWTH FACTOR METHOD

1.2.2.1 Uniform Growth (constant) factor method





1.2.2.1.1 Singly constrained growth factor methods

Used where information is available on the expected growth in

trips originating from zones.

Consider the following trip matrix



Method

Multiply each cell in Row 1 by 400/355





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1.2.2.1.2 The Furness Method (Doubly constrained

growth factor method)







Comments on Growth Factor Methods

1. Tends to overestimate the trips between

densely populated zones which probably have

little further development potential

2. Tends to underestimate the future trips

between underdeveloped zones which could

be extensively populated in the future



Travel impedance and the deterrence

function

Travel impedance

The effort involved, or the resistance againstundertaking a trip is called travel impedance.

It would seem obvious to express this impedance

simply in terms of the travel time or distance

involved




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The total impedance of a trip fromi tojvia route rfor a specific

transport mode can be written as a linear combination of the

experienced subjective time duration and monetary costs .

The minimum of this expression calculated over all possible routes is

the travel impedance cij between i and j.

Here the value of time is expressed in money-units per time unit

(euro/hour, forexample).

The value of time indicates that the traveller is prepared to pay

money-units for a saved time-unit of travel time. In the formula, the

monetary costs Kijr have been converted to time units via the .

In public transport the duration times ts and costs ks of the

various components which together make up the journey

from i to j via route r are multiplied by the weighting factors

sands



Deterrence function It is intuitively clear that the number of trips to a destination

decreases as the distance (or rather the travel impedance) to that

destination increases.

This travel impedance effect on the distribution of trips is expressed

by the deterrence function F(cij) .

Separate deterrence functions are applied depending on the

purpose of the trip, on personal characteristics and on the mode of

transport.

Some functions that have been used are:



Parametersa and b in the functions above are determined through

calibration using observations from the study area.

The general shape of the functions for some values of the

parameters is given as:



1.3 Modal split models

(Mode choice model)

Going somewhere not only involves a choice

of route but also a choice of transport mode.

The distribution of trips over the various

transport modes is called the modal split.

Modeling transport mode choice is one of the

classical problems in traffic engineering.






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Factors that influence transport mode choiceSocioeconomic Characteristics of Trip Maker

- Car Availability and/or ownership

- Possession of driving license

- Household Structure

- Income

- Residential Density

Characteristics of Journey

- Trip purpose

- Time of day of travel

Characteristics of Transport System

- Travel time

- Waiting Time

- Travel cost

- Comfort & Convenience

- Reliability & regularity

- Protection & Security



People who have no choice but to use one orother transport mode are called captivesof thattransport mode.

Those people who are not captive to one or otherform of transport are called choice-travelers.

When a household has no access to a car whilethe destination is too far away to cycle or walk,and when family income does not stretch to carhire or taxi, the family member is said to be apublic transport captive.



LOGITMODEL



. The formula shows that the probability that

alternative a is chosen, depends on the observed

utilities of the alternatives, and also on the dispersion

parameter.

If we let = 1, the logit model becomes



Pr(a) = the probability that a will be chosen.

Vk = the observable utility of travel mode k

K = the number of alternative travel modes

EAMPLE:1



Imagine a situation in which one can choose between three transport modes:

car, bus and bicycle. Assume that the observable utilities Vkfor a particular

group of people (who have the same personal characteristics) can be given by

the following functions:

Where; T and K are, respectively, travel time and travel costs, and they have

the following values:

What is the probability that a particular travel mode will be chosen by

individuals


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EXAMPLE :2The calibrated utility function for private car and

public transport travel are:

where, X= in-vehicle travel time; Y=out of

vehicle travel time; C=cost of travel/income

What is the probability that a person with income Rs.10000 will

travel by public transport?



private car: Vc= -0.3-0.04X-0.1Y-.03C

public transport: Cp= - 0.04X-0.1Y-0.03C

private car public transport

in-vehicle travel time 15 40

out-of vehicle travel time 5 10

travel cost(Rs.) 300 75

1.4 Traffic assignment

The primary concern in traffic assignment

models is route choice. It would appear self-

evident that a traveler would, in principle,

choose the shortest route to his point of

destination. This is why shortest route

algorithms play an important role in traffic

assignment models.



The application of traffic assignment

To determine the deficiencies in the existing

transportation system by assigning the future

trips to the existing system;

To evaluate the effects of the limited

improvements;

To develop the construction priorities by

assigning estimated future trips for intermediate

years to the transportation system; To test the transportation system proposals;



Types of assignment model

Travelers will choose the route which will take minimum travel time,

minimum travel distance dependent on the traffic volume on theroad.

The following are commonly used traffic assignment models.

1) All-or-nothing assignment model

2) Multiple route assignment model

3) Capacity restraint assignment model

4) Capacity restraint multipath route assignment model

5) Diversion curves technique model



1.4.1 All-Or-Nothing Assignment Model:

simplest model and is based on the premise that the

route followed by traffic is one having the least travel

resistance.

This model is also called shortest path model.

The resistance itself can be measured in terms of

travel time, distance, cost or a suitable combination

of these parameters.

This model assumes that either all drivers prefer a

particular route or nobody will take that route.




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1.4.2 Multiple Route Assignment Model:

All road users may not be able to judge the minimumpath for themselves.

It may also happen that all road users may not have thesame criteria for judging the shortest route.

These limitations of the all-or-nothing approach arerecognized in the multiple route assignment models.

The method consists of assigning the inter zonal flowto a series of routes, the proportion of total flowassigned to each being a function of the length of thatroute in relation to the shortest route.



1.4.3 Capacity Restraint Assignment Model:

This is the process in which the travel resistance of a link is

increased according to a relation between the practical capacity of

the link and the volume assigned to the link.

This model assumed that if the traffic volume on a road is increased

beyond the capacity its resistance to flow is also increased.

This model is also known as the Wyne state arterial assignment.



1.4.4 Capacity Restraint Multipath Route Assignment

Model:

This model is almost same as multipath route

assignment model but in this model we also

consider the capacity of each link instead of

only distance.

This model can be considered as combination

of capacity restraint and multipath model.



1.4.5 Diversion Curves Model:

Diversion curves represent empirically derived

relationship showing the proportion of traffic that is

likely to be diverted on a new facility (bypass, new

expressway, new arterial street, etc.) once such a

facility is constructed.

It is a one of the frequently used assignment model.

This model is based on the travel time saved,

distance saved, travel time ratio, travel distance ratio,

distance and speed ratio, travel cost ratio, etc.



Bureau of Public Roads curve fitted to this formula:

P = 100/(1+tr 6)

Where, P=% of the traffic diverted to new system

tr=travel time ratio(time on new system /time on old system)

California Curves Model:

In the California curves model, travel time saved and distance saved for

two routes can be assigned the traffic.



Example:

In order to relieve congestion on an urban street network

a motorway is proposed to be constructed. The travel timefrom one zone centroid to another via the proposed

motorway is estimated to be 10 mins whereas the time for

the same travel via existing street is 18 mins. The flow

between the two zone centroids is 1000 vehicles per hour.

Assign the flow between the new motorway and existing

streets.



2_urban and regional transport planning

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