Risk assessment: method and case study for traffic projects

Applied Mechanics and Materials, 2014

The present paper aims at testing new techniques of Quantitative Risk Analysis (QRA), based on a Monte Carlo Simulation (MCS), to Cost-Benefit evaluation of transportation projects. Cost-Benefit analysis have been widely used for the evaluation of projects, especially in the phase of "feasibility study" in order to support decision makers in the choice between design alternatives compared to financial and socio economic performance indicators.However, the empirical experience has shown that investment appraisal can be affected by many elements of risk, due to system’s uncertainty and the multiplicity of interests involved [1,2] especially in a field such as the construction of a new road that will affect a community [3].Actually, the input and output variables of the model, can not always be determined with certainty by the analyst, but are influenced by elements of uncertainty due to numerous biases that "normally" connote a decision-making process in which mult...

Stochastic Optimization - Seeing the Optimal for the Uncertain, 2011

Journal of the Operational Research Society, 2013

ABSTRACT Since highway improvement project selection requires screening thousands of road segments with respect to crashes for further analysis and final project selection, we provide a two-step project selection methodology and describe an application case to demonstrate its advantages. In the first step of the proposed methodology, we will use odds against observing a given crash count, injury count, run-off road count and so on as measures of risk and a multi-criteria pre-selection technique with the objective to decrease the number of prospective improvement locations. In the second step, the final project selection is accomplished based on a composite efficiency measure of estimated cost, benefit and hazard assessment (odds) under budget constraints. To demonstrate the two-step methodology, we will analyze 4 years of accident data at 23,000 locations where the final projects are selected out of several hundred of potential locations.

2004

There are uncertainties in all stages of the project development cycle including uncertainty in the costs involved in planning, designing, constructing and operating transport infrastructure. These uncertainties represent project risks that have the potential of influencing the outcomes of projects. The project evaluation process should consider project uncertainty via the use of risk analysis techniques. This paper arises from research undertaken by ARRB Transport Research in developing the Austroads Guide to Project Evaluation, and provides an overview of risk analysis for the transport practitioner and its role in the project evaluation process. A discussion of the definitions of risk and types of risks that arise within the project development process is provided, including an example illustrating key steps of the risk analysis method. A Risk ExplorerTM tool that provides a learning environment to help the user identify, assess and analyse risks related to project evaluation is ...

Transport Policy, 2015

In this paper we give an overview of the use of Multi-Criteria Decision Analysis (MCDA) for transport project appraisal. The aim of this review is to provide an outline of the increasing use of MCDA methods in the evaluation of transport projects. We investigate for which kind of transport decisions the MCDA methods are applied. The review consists of identifying the transport related subjects, the interconnected arising decision problems and the kind of representative MCDA method(s) used for transport project evaluations. This review allowed deriving a general frame for the evaluation of transport projects. One of the conclusions resulted in the importance of integrating stakeholders in the decision process not yet very common in the transport projects that were reviewed. The Multi-Actor Multi-Criteria Analysis (MAMCA) approach is suggested as a direction for further research. The MAMCA methodology has already proven its usefulness in several transport related decision problems enabling to involve the stakeholders explicitly in the decision process.

2019

In this paper, I briefly review the key methods to evaluate transportation projects. These methods are: Financial analysis; Cost benefit (economic analysis); Multi-criteria analysis; Cost-effectiveness analysis; Social welfare analysis; and Risk analysis (Monte Carlo simulation). The importance of understanding these methods lies in the fact that transportation projects offer huge social benefits and costs; some are impossible or very complex to measure in monetary terms.

European Journal of Transport and Infrastructure Research, 2015

This following special issue of the European Journal of Transport Infrastructure Research (EJTIR) containing five scientific papers is the result of an open call for papers at the 1st International Conference on Uncertainties in Transport Project Evaluation that took place at the Technical University of Denmark, September 2013. The conference was held under the auspices of the project ‘Uncertainties in transport project evaluation’ (UNITE) which is a research project (2009-2014) financed by the Danish Strategic Research Agency. UNITE was coordinated by the Department of Transport of the Technical University of Denmark (DTU Transport) and carried out in cooperation with several Danish and international partners.

Journal of Transportation Engineering, 2009

One of the key steps in the highway investment decision-making process is to conduct project evaluation. The existing project level life-cycle cost analysis approaches for estimating project benefits maintain limited capacity of probabilistic risk assessments of input factors such as highway agency costs, traffic growth rates, and discount rates. However, they do not explicitly address cases where those factors are under uncertainty with no definable probability distributions. This paper introduces an uncertainty-based methodology for highway project level life-cycle benefit/cost analysis that handles certainty, risk, and uncertainty inherited with input factors for the computation. A case study is conducted to assess impacts of risk and uncertainty considerations on estimating project benefits and on network-level project selection. First, data on system preservation and expansion, usage, and candidate projects for state highway programming are used to compute project benefits using deterministic, risk-based, and uncertainty-based analysis approaches, respectively. Then, the three sets of estimated project benefits are implemented in a stochastic optimization model for project selection. Significant differences are revealed with and without uncertainty considerations.

Transportation Planning and Technology, 1984

American Society of …, 2009

Roadway planning can become a contentious process. Delays to projects are frequently due to opposition, conflicting interests and differing opinions from stakeholders, resource agencies, planning organizations and others. Due to the many factors affecting the decision making process, the lack of a unique solution and the plurality of opinions, computational tools may support conflict resolution and decision making. Multiple Criteria Decision Analysis (MCDA) offers a framework wherein differing opinions concerning priorities and values may be utilized in a structured process that considers decision factors, ranks factor criteria, and allocates weights to factors so that results reflect the appropriate priority of each factor considered. This paper addresses a GIS-based decision making framework focusing on environmental and early planning needs in a high impacted transportation corridors. It contains an implementation of MCDA called Analytical Hierarchy Process (AHP) into a geospatial analysis framework to support geo-spatial decision making in generating and selecting paths for roadway options. In this approach, each decision factor is represented as a thematic geospatial layer with attributes that express criteria being considered. Pair-wise comparisons of criteria give rise to relative ranking of criteria. For each factor, a numerical weight assigning relative priority in the decision process is computed. The weighted factors are then combined resulting in a cumulative cost surface. This cost surface is used to generate a least-cost path between selected locations on the surface. The AHP method was adapted to the selection of alternative alignments for Interstate-269, which bypasses the metropolitan area of Memphis-TN. The results show close similarity to results generated by use of traditional methods, but were generated using automated approaches. The methodology enables transportation alternatives to be generated in an efficient and systematic manner and enables multiple scenarios to be simultaneously considered in the transportation planning process to facilitate decisions. This procedure allows scientists and researchers to provide methods useful to decision makers and stakeholders in a balanced and rational way that helps to avoid conflict.