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Title: An Examination of some Road Based B.O.T Projects in India with Special Reference to Traffic Forecasting


1
An Examination of some Road Based B.O.T Projects
inIndia with Special Reference to Traffic
Forecasting
National Seminar on PPP in Road and Transport
Infrastructure
  • Dr S. L Dhingra         Institute Chair
    Professor Emeritus FellowTransportation
    Systems EnggCivil Engineering Department, IIT
    Bombay

2
Contents
  • Challenges of Urbanization
  • PPP
  • Private Sector Interest
  • Transportation Infrastructure Projects From
    Conception to Implementation
  • Fund Sources
  • Risks and Uncertainty in Projects
  • Effects of Toll rates in traffic projections
  • B.O.T projects based on government support and
    guarantees.
  • Conclusion

3
Challenges of Urbanization
4
Urbanisation
  • Urban areas contribute 75 of GDP and more than
    50 of our population to live in urban areas by
    2050.
  • Rurbanisation of the countryside to pose newer
    challenges.
  • Cities would be the key drivers to our economy
    but
  • unless a focused approach coupled with heavy
    investment in urban infrastructure is put in

Urban areas would keep presenting 100000 problems
which in essence are 100 problems multiplied 1000
times
5
Growing Demand for Urban Infrastructure
6
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7
Multifarious Responsibilities Limited Resources
  • Local Government Expenses vary between 20-29 in
    developed countries while they are only 7-8 in
    India
  • Limited revenue base and dependent fiscal
    Jurisdiction
  • Fairly Large Capital Investment decisions being
    thrust upon municipalities

8
Infrastructure Bottleneck
  • Infrastructure is the biggest bottleneck in
    India Growth Story
  • Transport system has severe capacity constraints
    highways, city roads, airports, seaports and
    railways
  • Urban and Utility infrastructure Huge
    demand-supply gap in drinking water, sewerage
    system, drainage and power supply
  • India needs US 480 billion investment in the
    coming Five Year Plan to meet current
    Infrastructure needs, at least 20 of this would
    be for the Urban Sector

9
Existing Scenario
  • Most towns and cities are growing Like this!

10
Quality of life
11
How we cope, presently
Premji raps Karnataka Govt for bad roads, power
situation in Sarjapur Our Bureau Bangalore ,
July 18
12
Private Sector Interest?
  • Urban Infrastructure, has not yet found investor
    interest in the absence of clear directions on
    various aspects - Risk, social/ political,
    Regulatory, cost recovery mechanisms, etc.
  • Various attempts are being made to convert Urban
    Service (water, waste-water, Solid waste, etc)
    into Bankable projects
  • This is likely to open a new area for
    investments
  • And a new breed of Operating companies to
    provide these services
  • But proper PROJECT DEVELOPMENT is the key here

13
Total Private Sector Investments in Indias
Infrastructure
  • Year of Investment Energy Telecom Transport
    Water and sewage Total
  • 1990 0 0 2 0 2
  • 1991 614 0 0 0 614
  • 1992 13 0 0 0 13
  • 1993 1,051 0 0 0 1,051
  • 1994 311 97 125 0 533
  • 1995 1,008 683 0 0 1,691
  • 1996 1,553 1,229 108 0 2,890
  • 1997 970 3,827 405 0 5,201
  • 1998 1,066 673 296 0 2,035
  • 1999 2,500 1,045 467 0 4,012
  • 2000 2,357 682 100 0 3,139
  • 2001 45 3,445 211 2 4,004
  • 2002 380 4,615 558 0 5,553
  • 2003 825 1,968 505 0 3,298
  • 2004 4,144 3,731 1,117 0 8,992
  • 2005 755 6,201 1,449 0 8,405

14
Beginnings made
  • May not be all success stories, but
  • Tamil Nadu
  • Tirupur, Alandur, TNUDF Pooled Finance
  • Municipal Bond issues
  • Ahmedabad, Hyderabad, Nashik
  • Urban infrastructure funds IFCG, Feedback
    U-Fund and MUIF
  • Not Successful
  • BATF in BangaloreBangalore Agenda Task Force
  • The Bangalore Agenda Task Force is meant to be a
    partnership between the citizens, corporates and
    the administrative agencies the BMP, BDA, BMTC,
    ...
  • Water OM PSPs (attempts!) in Pune, Goa,
    Bangalore, Hyderabad

15
Pooled Finance
  • TNUDF sponsored issue, successful in Tamil Nadu
  • USAID (DCA) guarantee for 50 of principal
  • Karnataka (KUIDFC) pursued similar issue
  • Government of Indias proposed PFDF, also a
    pointer in this direction
  • Yet to take off
  • Issues of listing Trust-financed Bonds (SEBI),
    would have to be addressed to ensure a market for
    these instruments

16
Pooled Finance (2)
17
Viability Gap Funding
  • Proposed by Government of India
  • To Prop-up marginally viable projects
  • Established and clear guidelines for allocation
  • Problem may be in the lack of developed and
    structured projects, that are eligible to claim
    this assistance

18
Capital Market Access
  • Bond issues of Ahmedabad, Hyderabad, BMP, Nashik
    etc., have not led to large-scale replication
  • Issues of market appetite, end-use
  • Limited number of ULBs which can access financing
    on a standalone basis
  • Pooled Finance seems a more appropriate structure
    for small ULBs

19
Access to Domestic Financial Institutions
  • For the Local Body
  • Reluctance of Local bodies to accept FI
    conditions typically stipulated to mitigate
    project risks
  • ULBs have option of (a) FIs assistance (cash flow
    basis with conditions) Vs (b) MLA funding/ Govt.
    Institutions ( GoI/ State guaranteed soft push,
    if any)
  • ULB prefers the latter to the former (obvious!)
  • For the Domestic Institution
  • Guaranteed lending (state/ central) is no more
    risk-free, from regulatory considerations

20
PPP Some reasons to be optimistic
  • Realization of need for improvement of Urban
    Services, and concurrently, the finance needed
    for doing so
  • Various precedents are being tried and tested,
    and experience is maturing
  • But yet a long way to go
  • Key Words
  • Not Finance, but Developed Bankable Projects
  • Not Willingness to Pay, but Unwillingness to
    Charge

21
PPP Approach
Goal
  • Attract private investments for infrastructure
    projects
  • Lack of Budgetary Resources
  • Need to improve efficiency in service delivery

Need
PPP approach
  • Private Sector contribution for
  • - Financial investments
  • - Best Management practices
  • - Efficiency in service delivery
  • - Efficient use of capital resources
  • Public Sector contribution limited to
  • - Providing institutional commitment to
    project
  • - Project Development Selection of
    Developer
  • - Viability gap funding (VGF), if any

22
Background Issues
  • Ability to create a shelf of projects?
  • Project development requires funds and continuous
    support
  • Strengthening the capabilities of the mandated
    agency to create experiential learning
  • Standardized processes for Viability support for
    projects not viable on stand alone basis
  • No need to reinvent the wheel every time, learn
    from peers

Debate has shifted from financing of
infrastructure projects to creation of a shelf of
projects.
23
Structure
24
A PPP is not a transfer of responsibility
  • A PPP project DOES NOT Mean that the Government
    has little or no onus
  • Its objective has to be synergy between the
    private public sectors
  • Areas such as land acquisition, clearances,
    utilities, etc., can still be best done only by
    the Government

25
What are the advantages of private sector
participation ?
  • If properly structured and incentivized, the
    private sector can provide a more efficient or
    cost-effective service.
  • The private sector often has better access to
    capital financing and so it is able to use more
    efficient equipment.
  • The private sector may have easier access to
    specialist skills. For example companies can form
    joint ventures with international specialist
    firms.

26
Putting the projects on shelf
Project Preparation
Partnership Management
Project Identification
Viability
Structuring
Do-ability
Procurement Strategy
Bid Process Management Pre-bid
Bid Process Management Post-bid
Identification/ Assessment
  • Requires Project Preparation Partnership
    Management
  • Inca is the nodal agency mandated to do the above

State need to enhance the involvement of private
sector need a PPP! The challenge is the right
model and right process for engagement of private
sector!
27
Identification Stage
  • To convert wish list into a list of projects that
    are viable and amenable for PPP.

Objective
  • Prelim assessment of the opportunity
  • Prelim assessment of possibility of a PPP
  • Presence of necessary ingredients land, land
    use, basic approvals

Activities
28
Preparation Stage
  • Assessing feasibility and structuring the PPP
    (Value for Money) (Risk Return Ratio)

Objective
  • Assessment of Market opportunity
  • Technical Financial Feasibility
  • Financial structuring
  • Sharing of risk and Structuring PPP

Activities
29
Partner Selection Stage
  • To select Private Sector Partner in an open and
    transparent manner

Objective
  • Technical and financial capability criteria
  • Equal information sharing and support to all
    bidders
  • Rigorous specifications Contract
  • Efficient and time bound bidding process

Activities
30
Project Development Process
Track 2
  • PROJECT DEVELOPMENT
  • Techno-Economic Market Assessment
  • Legal Documentation
  • Policy amendments and notification
  • Contractual and Institutional Framework
  • DEVELOPER SEARCH
  • Expression of Interest
  • Request for Proposal (RFP)
  • Pre-Bid Conferences
  • Proposal Evaluation
  • Finalisation of Developer
  • Finalisation of Agreements
  • MARKETING COMMUNICATION
  • One-to-one meetings
  • Direct Mailers
  • Media release
  • Road Shows
  • Investors Conferences
  • Facilitating Consortia formation

Government Approvals, Facilitation Decision
Making
31
Different Structures
32
Transportation Infrastructure Projects From
Conception to Implementation
33
The Stages
  • Conception
  • Identification of project alternatives
  • Selection of the best alternative
  • Implementation
  • Construction of the project
  • Operation and Maintenance

34
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35
Classic Four-Stage Sequential Travel Demand Model
Trip Generation
Trip Distribution Demand
Modal Split
Traffic Assignment Supply
Considering Environmental Protection Economy
36
Travel Demand Modeling Planning Variables
  • Study area
  • Internal zones
  • External zones
  • Plan Periods
  • Demographic and Socio-economic data
  • Protection of planning variables
  • Transport network
  • Origin and Destination Survey

37
Tij
38
Travel Demand Modeling Other Approaches
  • Equilibrium Demand Modeling
  • Traveler as consumer of transit trips
  • Micro Economics - Utility Maximization
  • Activity based analysis (Factors)
  • Individual Traveler Level
  • Type and Time of Activity
  • Community Level
  • Social Level
  • Destination by mode
  • Congestion

39
Transport Priority Indices (TPI) in a Systems
Framework
  • The Need -
  • Huge investments involved and priority needs to
    be given to villages with higher population and
    potential market surplus.
  • The proposals discussed are those initiated by
  • the State Government of Karnataka
  • the Indonesian rural roads study group
  • the ARD (Accelerated Rural Development) road
    network of Thailand

40
Organizational Setup for Planning and Prioritizing
  • Formation of Technical Advisory Committee (TAC)
  • Preparation of proposal/tender document
  • Guidelines for selection of tenders
  • Pre-bid selection
  • Selection of PMC
  • Selection of contractors
  • Proof consultants

41
UNDP - Government of India Project on Pro-poor
Globalisation
  • Aim
  • Informed and participatory pro-poor policy
    making, strategy and programme formulation
  • Methodology
  • Review of already conducted research on pro-poor
    and anti-poor impacts of globalisation
  • Additional research and analysis
  • Involvement of the poor in the policy dialogue
  • Making information accessible to lay- person

42
Methodology for Selection of Proposal
  • Organisations short-listed on the basis of
    initial proposals
  • Selection of 3 top-ranked proposals based on
    their presentations
  • Initial contract awarded to these 3 organisations
    to further refine and detail their proposal, work
    plan and project strategy.
  • Review of final proposals by a panel
  • Project awarded to the highest ranked proposal

43
Decision Making
  • Importance of decision making at every stage
    during the project
  • Two important steps in the decision making
    process
  • Course of action, which contains recognition,
    discovery and contraction of ideas
  • Finding alternative strategies
  • Decision making is complex due to multiplicity of
    attributes

44
Multiple Criteria Decision Making (MCDM)
  • Importance in design and planning
  • Some MCDM techniques
  • Analytical Hierarchy Process (AHP)
  • Fuzzy Set Methodology
  • Metagame Theory

45
Analytical Hierarchy Process
  • Basic principles of AHP
  • Hierarchic representation and decomposition
  • Priority discrimination and synthesis
  • Logical consistency
  • Series of pair-wise comparisons carried out to
    obtain the preference order
  • Each decision alternative assigned a weight
  • Weights represent the alternatives desirability

46
  • Applications in fields like
  • conflict analysis
  • operations research
  • portfolio selection
  • bid evaluation
  • capital budgeting

47
FUZZY SET ANALYSIS
Transportation planning involves Qualitative and
quantitative analysis including uncertain
Attributes and Characteristics. Fuzzy Analysis
takes care of this important aspect of
transportation planning.
48
  • FUZZY LOGIC
  • Fuzziness in Transportation Analysis
  • In the study of transportation problems,
    fuzziness is
  • found in many aspects of analysis
  • Perception of data and information,
  • Knowledge base,
  • Statement of goals and objectives, and
  • Problem definition.

49
METHODOLOGY
The following are the steps of the methodology
1. Identifying the modes which will form
attributes (i,e., factors) of those
coordinated modes.
2. Categorizing different interest groups.
3. Forming termed rating matrix, with columns as
modes and rows as factors.
4. Constructing of different rating matrices as
per the views of respective interest groups
5. Aggregation of rating matrices
6. Forming dominance matrix from the dominance
of one mode over the other mode
7. Calculating the share of service by each
mode in a coordinated system.
50
Case Study
The city of Calcutta, with five different mass
transit modes, is considered for the case
study.
51
Case Study
The attributes considered for each mode are
52
Case Study
Rating matrix for commuters opinion
53
Case Study
Rating Matrix for Planners Opinion
54
ADVANTAGES
  • helps in the resolution of conflicts between
    parties having a difference of opinion.
  • a non-quantitative method of analysis
  • LIMITATIONS
  • quite complicated in case of multi player and
    multi choice conditions
  • May not always lead to a stable solution

55
CASE STUDIES
  • The following case studies will be discussed
  • Mumbai - Pune Expressway Project
  • The 50 Flyovers Project (Mumbai Traffic
    Improvement Mega-Project)
  • Western Freeway Sea Link Project
  • Bandra - Worli Sea Link Project, etc.

56
Fund Sources
57
Funding Sources
  • Public funds derived from general taxation
  • Funds from Debt
  • Long term debts
  • Short term debts
  • Funds from Equity
  • Funds from users charges

58
Funding Sources
  • Debt used around 60-90
  • Equity used is 10-40
  • Nearly the D/E ratio is more than 21

Sources of funding for BOT project ( Source
Malini 1997)
59
Funding Sources
  • Schaufelberger Et.Al. (2003) has reported an
    alternate financial strategies for BOT Funding
  • Using Equity to finance the construction work
  • Refinancing with Debt after major completion of
    construction work

60
Various schemes for implementation
  • BOT (Build/Operate/Transfer)
  • BOOT (Build/Own/Operate/Transfer)
  • BOO (Build/Own/Operate)
  • BLOT (Build/Lease/Operate/Transfer)
  • BOLT (Build/Operate/Lease/Transfer)
  • LOT (Lease/Operate/Transfer)
  • COT (Cooperate/Operate/Transfer)
  • Annuity and Service Outsourcing

61
BOT
A Conceptual Model for the Operation of BOT
Scheme ( Source Malini 1997)
62
Government Funding
  • Entire investment, construction, operating, and
    maintenance is by government
  • Direct budgetary devolution (tax-payer money)
  • Debt raised against government guarantees, (and
    letters of comfort)
  • Financing primarily by HUDCO and LIC
  • Financial requirements are increasing way beyond
    direct budgetary/ guarantee capacity
  • State budget deficits and statutory guarantee
    limits constraining State Gov. funding capacity

63
Local Authority Funding
  • After the 74th Amendment, there is increasingly,
    funding generated by the ULB
  • Escrowing revenues such as property tax, entry
    tax/ octroi
  • Selling/ securitizing land
  • But there is a limit to these numbers

64
Multilateral/ Bilateral Funding
  • World Bank, ADB, DFID
  • Based on reform agenda
  • Fairly detailed appraisals done
  • Sectoral or project-wise
  • Generally addresses needs of urban poor
  • However, for commercial loans, based on
    Government of India Guarantees as security
  • Very elaborate and complex processes

65
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66
JNNURM
  • Excellent scheme to lead reform-based financing
  • Presents a new opportunity to
  • Establish key reforms
  • And thereby draw investment into key
    infrastructure
  • But the scheme is available only to some cities
  • Also focus towards commercial finance, which will
    be a significant percentage of the project
    investment PPPs are envisaged to be the way
    forward

67
Risks and Uncertainty in Projects
68
Risk and Uncertainty
  • Risk and Uncertainty is always there for both the
    Government and Private Sector
  • Risk is mainly of three types
  • Financial Risk
  • Political risk
  • Currency Devaluation Risk

69
Risk and Uncertainty
  • Financial Risk includes
  • Termination Risk
  • Regulation Risk
  • Construction Risk
  • Information Risk

70
Risk and Uncertainty
  • Political risk arouse due to
  • Change in government
  • Change in policies
  • Currency Devaluation risk is aroused when
  • Finance/debt is been done by foreign companies

71
Treatments of Risks and Uncertainty in Projects
  • The availability of partial or imperfect
    information about a problem leads to two new
    category of decision-making techniques
  • Decisions under risk (In terms of a probability
    function)
  • Decisions under Uncertainty (No probability
    function is secure)

72
Decisions under risk
  • Decisions under risk are usually based on one of
    the following criteria
  • Expected Value
  • Combined Expected value and variance
  • Known Aspiration level
  • Most likely occurrence of a future state

73
Expected Value Criterion
  • Expressed in terms of either actual money or its
    utility
  • Decision Makers attitude towards the worth or
    utility of money is important
  • The final decision should ultimately be made by
    considering all pertinent factors that affect the
    decision makers attitude towards the utility of
    money
  • The drawback of this is that use of expected
    value criterion may be misleading fro the
    decisions that are applied only a few number of
    times i.e small sample sizes

74
Example 1
  • A preventive maintenance policy requires making
    decisions about when a machine (or a piece of
    equipment) should be serviced on a regular basis
    in order to minimize the cost of sudden breakdown
  • The decision situation is summarized as follows.
    A machine in a group of n machines is serviced
    when it breaks down. At the end of T periods,
    preventive maintenance is performed by servicing
    all n machines. The decision problem is to
    determine the optimum T that minimizes the total
    cost per period of servicing broken machines and
    applying preventive maintenance

75
  • Let pt be the probability that machine would
    break down in period t
  • Let nt be the random variable representing the
    number of broken machines in the same period.
  • C1 is the cost of repairing a broken machine
  • C2 the preventive maintenance of the machine
  • The expected cost per period can be written as
  • Where Ent is the expected number of broken
    machines in period t.
  • nt is a binominal random variable with parameter
    (n,pt), Entnpt
  • The necessary condition for T to minimize EC(T)
    are
  • EC(T-1)gt EC(T) and EC(T1)gt EC(T)

76
  • To illustrate the above formulation, suppose
    c1Rs.100, c2Rs.10 and n50
  • The values of pt and EC(T) are tabulated below
  • T

T pt Cumulative pt EC(T)
1 0.05 0 500
2 0.07 0.05 375
3 0.10 0.12 366.7
4 0.13 0.22 400
5 0.18 0.35 450
77
Multi-Modal International Hub Airport at Nagpur
78
MIHAN
  • MASTER PLAN
  • INTERNATIONAL HUB AIRPORT
  • STATE OF ART AIRPORT
  • RAIL ROAD TERMINAL
  • SPECIAL ECONOMIC ZONE
  • Health City
  • Captive Power Plant
  • IT Park
  • INTERNATIONAL SCHOOL, HOTELS,
  • ENTERTAINMEMNT AND RESIDENTIAL AREA
  • Mahrashtra Airport Development Company Company
    Established By Government Of Mahrashtra
  • Expansion of airport at Nagpur
  • Development of Special Economic Zone (SEZ)

DEVELOPMENT CREATES JOBS, COMMERCE, TRADE AND
STABILTY.
79
International Hubbing Concept
80
OBJECTIVES
  • An attractive hub Airport
  • Financially viable bankable project
  • Minimum social and environmental impact
  • Develop self-generating traffic

81
Aerial view of Airport
82
AIRSIDE VIEW
83
SALIENT FEATURES OF THE PROJECT
  • MIHAN project area 2535 Hectares
  • Runways Existing runway to be extended to 4000m
    length and 60m width Provision made for an
    additional parallel runway 4000mx60m
  • Terminal facilities a semi-circular terminal
    building 3,00,000 sqm area with an outer diameter
    of 810m. Separate international and domestic
    cargo terminals.
  • Aircraft Parking - 50 aircrafts in the Terminal
    50 aircrafts remote.
  • Projected Traffic 14 million passengers a year
    (70 international) and 8,70,000 tons of cargo
    (90 international) a year.
  • Type of Airport International Hub Airport for
    Passengers Cargo
  • Type of connectivity - Multi-Modal Airport,
    Railway Terminal for Passengers Goods, Truck
    Terminal, MRTS Terminal all in one Project
  • Special Economic Zone

84
MAJOR BENEFITS
  • Various types of tax and duty concessions within
    SEZ
  • Efficient operating norms for the
    Airport-Aircraft turn-around time, Passenger
    walk-through time, cargo clearance time etc.
  • All infrastructure facilities available - power
    , water, telecommunications, computer
    connectivity etc.
  • Economic benefits to the Vidarbha Region and
    Nagpur City and the overall Country through the
    International and Domestic Hub.
  • Development of Hinterland through multi-modal
    connectivity to the other parts of the Country.

85
Economic Benefits
  • Increase in Exports
  • Wealth Creation
  • Employment creation
  • Increase in revenues from tourists
  • Value addition
  • Fiscal benefits to the Central and State
    Government

86
Economic Fiscal Benefits
87
FINANCIAL ECONOMIC HIGHLIGHTS
  • The total project cost is Rs.25810 million over
    30 years
  • The total investment required in various
    facilities in the MIHAN Project area by other
    agencies is approximately Rs.26000 million till
    2035
  • The project is viable with an IRR of 15.8
  • The Net Economic Value added to the region till
    2035 will be Rs.522,254 million, apart from the
    creation of thousands of jobs
  • Employment generated in airport, allied
    activities and tourism

88
Aspiration Level Criterion
  • This method does not yield an optimal decision in
    the sense of maximizing profit or minimizing cost
  • It is a means of determining acceptable courses
    of action
  • Most Likely Future Criterion
  • Converting the probabilistic situation into
    deterministic situation by replacing the random
    variable with the single value that has the
    highest probability of occurrence

89
Decisions under uncertainty
  • They assume that there is no probability
    distributions available to the random variable.
  • The methods under this are
  • The Laplace Criterion
  • The Minimax criterion
  • The Savage criterion
  • The Hurwicz criterion

90
Laplace Criterion
  • This Criterion is based on what is known as the
    principle of insufficiency
  • ai is the selection yielding the largest expected
    gain
  • Selection of the action ai corresponding
  • where 1/n is the probability that

91
Example 2
  • A recreational facility must decide on the level
    of supply it must stock to meet the needs of its
    customers during one of the holiday. The exact
    number of customers is not known, but it is
    expected to be of four categories200,250,300 or
    350 customers. Four levels of supplies are thus
    suggested with level i being ideal (from the view
    point of the costs) if the number of customer
    falls in category i. Deviation from these levels
    results in additional costs either because extra
    supplies are stocked needlessly or because demand
    cannot be satisfied. The table below provides the
    costs in thousands of dollars
  • a1, a2, a3 and a4 are the supplies level

Customer Category Customer Category Customer Category Customer Category Customer Category
  q1 q2 q3 q4
a1 5 10 18 25
a2 8 7 8 23
a3 21 18 12 21
a4 30 22 19 15
92
  • Solution by Laplace Criterion
  • Ea1 (1/4)(5101825) 14.5
  • Ea2 (1/4)(87823) 11.5
  • Ea3 (1/4)(21181221) 18.0
  • Ea4 (1/4)(30221915) 21.5
  • Thus the best level of inventory according to
    Laplace criterion is specified by a2.

93
Minimax (Maxmini) Criterion
  • This is the most conservative criterion since it
    is based on making the best out of the worst
    possible conditions
  • If the outcome v(ai,?j) represents loss for the
    decision maker, then, for, ai the worst loss
    regardless of what ?j may be is max ?j v(ai,?j)
  • The minimax criterion then selects the action ai
    associated with min ai max ?j v(ai,?j)
  • Similarly if v(ai,?j) represents gain, the
    criterion selects the action ai associated with
    max ai min ?j v(ai,?j)
  • This is called the maxmini criterion

94
  • Applying this criterion to the Example 2
  • Thus the best level of inventory according to
    this criterion is specified by a3

Customer Category Customer Category Customer Category Customer Category Customer Category Max
Supply  q1 q2 q3 q4 Max
a1 5 10 18 25 25
a2 8 7 8 23 23
a3 21 18 12 21 21
a4 30 22 19 15 30
Minimax value
95
Effects of Toll rates in traffic projections
  • Traffic and revenue (TR) forecasts - typically
    point estimates
  • Bond investors, rating agencies, etc. prefer
    rigorous sensitivity/risk assessments in toll
    road TR forecasts
  • Risk analysis helps to
  • Quantify uncertainties in inputs
  • Determine impacts of inputs on output
  • Analyze output sensitivities
  • Quantify uncertainties of the output
  • Multi-agency toll project financing negotiations
  • Evolving risk analysis processes in TR
    estimation

96
Typical TR Process

Planned
Existing
Forecasted
Existing
(MTP, CIP, etc.)
Demand
Supply
Toll Diversion
Model
Toll Traffic/Transactions
Transponder Shares, Revenue Recovery, Truck
Shares, Revenue Days, Toll Rates

Sensitivity Analysis
Toll Revenue
96
97
TR Risk Analysis Process

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Uncertainties in Input Variables
Transaction Variables
Population (Census vs. Forecast)
Employment (Census vs. Forecast)
VOT (SP Survey, CPI)
Toll Rates, Vehicle Operating Costs (AAA, CPI)
General Uncertainty/Safety Factor
Revenue Variables
Truck Shares (based on observed trends on similar toll facilities)
Revenue Days (based on observed trends on similar toll facilities)
Transponder Shares (based on observed trends on similar toll facilities)



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Impacts of Population on Toll Traffic
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Impacts of Employment on Toll Traffic
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Impacts of Value of Time on Toll Traffic
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Impacts of Vehicle Operating Cost on Toll Traffic
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TR Uncertainties
Year Traffic Distributions Traffic Distributions Traffic Distributions
Year Lower Bound (P5) Mean Upper Bound (P95)
2011 96 100 104
2030 80 100 122
Year Revenue Distributions Revenue Distributions Revenue Distributions
Year Lower Bound (P5) Mean Upper Bound (P95)
2011 83 100 111
2030 69 100 141
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Contd.
  • Quantification of TR uncertainties very
    important given the inherent uncertainties/imperfe
    ctions in inputs and models
  • Possible ways to quantify TR uncertainties
  • Discrete sensitivity analysis
  • Risk analysis to create probability ranges for
    the outputs
  • Combined sensitivity analysis, risk analysis and
    extreme event impacts (recommended)

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B.O.T projects based on government support and
guarantees

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SUMMARY
  • Traditional four stage Transportation Planning
    methodology is discussed.
  • Fundamentals behind the various techniques
    adopted in decision making for mega
    transportation infrastructure projects are
    discussed.
  • An insight is provided into the procedure
    involved from conception to implementation stage
    supported by case studies of various
    transportation projects.

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CONCLUSIONS
  • Projects should be well-conceived and
    economically efficient, using latest tools for
    decision analysis.
  • Decision analysis should be through PMC , TAC as
    well as conflict resolution, for different stages
    in the projects.
  • It is necessary to have appropriate institutional
    set up for effective conception, planning,
    prioritization, decision analysis, PMC/contractor
    selection and effective implementation through
    Q/A checks.

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Thank You
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