Modelling and simulation of transportation system effectiveness to reduce traffic congestion: a system dynamics framework

ABSTRACT

This paper is designed to evaluate and improve the effectiveness of transportation systems and reduce traffic congestion through the use of simulation models and scenario development. A system dynamics framework is used to test and evaluate the alternatives of future strategies for the city of Surabaya, Indonesia. Some factors affecting the effectiveness of transport systems include operational effectiveness and service effectiveness, as well as uncertainty. To improve the effectiveness of transportation systems, several strategies can be implemented, such as subsidizing public transportation, increasing the cost of private vehicle parking fees, raising taxes on private vehicles, and reducing delays in public transportation through scenario development. Scenario results show that, by pursuing these strategies, effectiveness could be improved by 80% as the impact of the increase in operational and service effectiveness, helping to mitigate traffic congestion. Congestion could be reduced to 70% (on average) due to the decrease in daily traffic.     

Changes in transport risk perception in urban populations in Norway from 2004 to 2013

Urban populations transport risk perception is interesting because it is associated with travel mode choices and use. This study investigates changes in transport-related risk constructs in the urban population in Norway in 2004 and 2013, and describes whether people perceive private or public to be associated with the highest risk. The results are based on self-completion questionnaire surveys conducted in two independent representative samples living in the same urban areas in 2004 (n?=?592) and 2013 (n?=?1035). Overall, the respondents perceived the risk as lower in 2013 than in 2004. For both time periods, people consistently assessed the risk constructs related to private motorized transportation as higher than corresponding risk in public transportation. The findings suggest that while transportation risk perception in urban populations may change over time, the pattern that private motorized transportation is associated with a higher perceived risk than public transportation remains stable.     

Valuation of strategic options in public–private partnerships

This paper investigates the feasibility of and develops an economic valuation model for strategic options in Comprehensive Development Agreements (CDAs). A CDA is a form of public–private partnership whereby the right to price and collect revenues from toll roads is leased to a private entity for a long but finite period of time. In exchange, this provides local and state governments with a quick influx of cash and/or additional infrastructure. Uncertainty associated with such long-term leases is of substantial public concern. This paper examines five different strategic options, namely a buyout option, a conditional buyout option, a revenue-sharing option, and two types of minimum revenue guarantee options. The buyout option in particular could give the public sector additional control over the future use of leased facilities and address potential concerns regarding long-run uncertainty and possible unforeseen windfalls for the private sector. The paper’s contributions include the analysis, feasibility assessment and valuation of several strategic options, sensitivity analysis of the solutions, an economic consumer demand-based revenue model for purposes of cash flow simulation, and analysis of option price sensitivity to “moneyness”. The main conclusion is that strategic options can provide useful risk reduction, but generally have significant value relative to the lease itself. By scaling down payoffs, options could be realistically included in CDAs and other PPPs. For some parameter values, option values to the developer and public authority are offsetting, allowing for costless risk reduction.     

The role of accessibility in basic transportation choice behavior

Accessibility measures reflect the level of service provided by transportation systems to various locations. Basic transportation choice behavior is defined to include those decisions of how many automobiles to own and how many trips to which destinations to make by automobile and by public transit. Here, these decisions are assumed to be made jointly by urban households and are conditional upon residential location decisions. It is the purpose of this paper to explore the role of accessibility as a causal factor in such basic transportation choice behavior.An economic utility theory model of choice behavior is postulated in which the benefits from making trips to specific destinations are reflected by measures of destination attraction. Through determination of utility-maximizing trip frequencies, indirect utility functions are developed which include accessibility concepts. Behavioral implications of these concepts are proposed and contrasts are drawn to accessibility measures used in conventional segregated models of trip distribution, modal choice, and automobile ownership.Sensitivity analyses of alternative empirical definitions of accessibility in the choice model are conducted using data from the Detroit Regional Transportation and Land Use Study — covering counties in southeastern Michigan. These analyses employ a multinomial logit estimation technique and focus on definitions of trip attraction. Results of these analyses indicate that more complicated attraction measures can be replaced by measures involving the proportion of either urban area population or urban area employment within a traffic analysis zone. Also, evidence is found that decision-makers in the case study area consider trips of up to 60 or even 90 minutes duration when evaluating accessibilities offered by alternative public and private transportation systems.     

Uncertainty modeling for bus selection and allocation in a private transportation system

ABSTRACT

This paper describes the development of a probabilistic formulation that provides global optimum selection and allocation of a fleet of buses in a private transportation system of an organization where a third party is hired to provide transportation for its employees and their dependents. In this private transportation system, a fleet of buses is to be selected and allocated to serve employees and their independents on different prescheduled trips along different routes from the organization’s headquarters and residential compound where round-trip times of scheduled trips are subject to uncertainty due to random delays. We propose a probabilistic approach based on 0-1 integer programming for the selection and allocation to determine the optimal number and size of buses assigned to a set of prescheduled trips in a particular time interval. Examples and a case study are presented to illustrate the applicability and suitability of the proposed approach.     

Optimal transit fare in a bimodal network under demand uncertainty and bounded rationality

This paper investigates the optimal transit fare in a simple bimodal transportation system that comprises public transport and private car. We consider two new factors: demand uncertainty and bounded rationality. With demand uncertainty, travelers are assumed to consider both the mean travel cost and travel cost variability in their mode choice decision. Under bounded rationality, travelers do not necessarily choose the travel mode of which perceived travel cost is absolutely lower than the one of the other mode. To determine the optimal transit fare, a bi‐level programming is proposed. The upper‐level objective function is to minimize the mean of total travel cost, whereas the lower‐level programming adopts the logit‐based model to describe users' mode choice behaviors. Then a heuristic algorithm based on a sensitivity analysis approach is designed to solve the bi‐level programming. Numerical examples are presented to illustrate the effect of demand uncertainty and bounded rationality on the modal share, optimal transit fare and system performance. Copyright © 2013 John Wiley & Sons, Ltd.     

Remuneration models and revenue risk mitigation in road public–private partnership projects – a case study from Serbia

As a consequence of renewed interest in attracting private financing for infrastructure investments, public–private partnership (PPP) arrangements are mostly seen as a suitable mechanism for ensuring sound and quicker delivery of transport infrastructure projects. However, a general concern is that expectations of mobilizing private-sector funds have been overestimated in a number of cases. The purpose of this paper is to contribute to the risk analysis of transport PPP projects with substantial exogenous demand risk which could serve as a rationale for choosing the appropriate PPP model. The objective of this paper is to construct an analytical cash flow-based project model to facilitate the choice of the remuneration mechanism suitable for both private investors and public sector. The model provides an indication whether the project should be implemented as a ‘users pay’, a hybrid or an ‘annuity’ PPP model. The proposed methodology is illustrated using a case study from Serbia.     

Perceived accessibility,mobility, and connectivity of public transportation systems

Although public transportation is considered effective at reducing the external cost of driving private vehicles, many urbanites do not use public transportation. This study develops measures employing accessibility, mobility, and seamless connectivity for an entire public transportation service chain as indicators for evaluating public transport services, prioritizes underperforming scenarios from the perspective of urban travelers, and derives various market segmentation strategies that consider different socio-demographic characteristics. A conceptual model is set up herein to assess these latent constructs that describe unobservable and immeasurable characteristics. As a Likert ordinal scale can generate misleading statistical inferences, the Rasch model is used to eliminate bias generated by an ordinal scale when measuring these three latent constructs separately. The Rasch model compares person parameters with item parameters, which are then subjected to logarithmic transformation along a logit scale so as to recognize specific difficulties of service scenarios that cannot be easily eliminated by certain urban travelers. The multidimensional Rasch model also measures the perceptions of urban travelers in terms of the interactions between accessibility, mobility, and seamless connectivity of this public transportation system. While comparing urban travelers of two large cities in Taiwan, Taipei and Kaohsiung, the empirical results demonstrate that perceived accessibility, mobility, and seamless connectivity differ based on travelers’ age, frequency of weekly sports activities, and environmental awareness. This paper also advances appropriate improvement strategies and provides policy suggestions for urban planners, public transportation service operation agencies, and policy makers when they seek to create user-friendly public transportation services. The proposed approach can be generalized in other cities by considering their local context uniqueness and further evaluating their public transport services.     

Risk pricing inefficiency in public–private partnerships*

There is a drive towards delivering and operating public infrastructure through public–private partnership (PPP) rather than traditional public procurement. The assessment of the value for money achieved by the two alternative approaches rests in the cost of financing and their efficiency in delivery and operation. This paper focuses on the cost of financing, in particular the cost associated with transferring risk from the public to private sphere. If capital markets were efficient and complete, the cost of public (government) and private financing should be the same, with the relative delivery and operational efficiency remaining as the primary determinant of value-for-money. Evidence suggests, however, that the risk transfer to a PPP entails an inefficient risk pricing premium which goes beyond the direct cost of financing. We argue that a high price for PPPs results from large risk transfers, risk treatment within the private sector, and uncertainty around the past and future performance of public–private consortia. The corollary is that the efficiency gains from a PPP must be much higher than commonly expected to deliver a greater value for the money than under a traditional approach.     

A hybrid model of fuzzy and AHP for handling public assessments on transportation projects

Having an effective public participation in transportation planning and project development processes has been a major concern for developed countries. In the United States, for instance, all state Departments of Transportation are subject to the Transportation Equity Act (TEA-21) that formally requires public involvement in transportation planning. Since transportation planning involves public resources and values, judgments by the public should play a key role in determining final decisions. Therefore, all these agencies are required not only to disseminate information to the public, but also to solicit and consider public opinion in forming transportation policy. This work presents a decision support model, with public involvement and public oversight, to help policy makers select appropriate transportation projects for implementation. Since focus groups will face multiple objectives and inexact information in the process, a hybrid model of fuzzy logic and analytical hierarchy process (AHP) is proposed. A set of ‘if–then’ rules based on Weber’s psycho-physical law of 1834 is presented to reason from fuzzy numbers to capture essential subjective preferences, pairwise, among the alternatives. The AHP is then incorporated to estimate preference allotments among alternatives. An example application of the suggested method is provided seeking public approval of an appropriate public bus transportation system choosing between one run by municipal authorities and one run by private agencies to show how this procedure works.

A multi-criteria decision support methodology for implementing truck operation strategies

This study proposes a multi-criteria decision support methodology to enable the prioritization of potential alternative transportation system operations strategies and then demonstrates the effectiveness of the methodology using a case study involving truck operations. The primary feature of this methodology is its ability to help policymakers consider economic, public, and private sector standpoints simultaneously. The economic criterion is cost to the public sector where four criteria related to truck impacts on the transportation system are incorporated. These are traffic congestion, safety hazards, air pollution, and pavement damage. In addition, reliability and productivity are regarded as metrics representing the private sector viewpoint since they can significantly affect profitability. The methodology combines qualitative and quantitative aspects of these standpoints. In order to demonstrate the applicability of this methodology, a corridor with some of the highest truck traffic in the US is selected as a case study and three forms of left lane restrictions for trucks are considered. For qualitative analysis, survey data were collected from two groups classified as public agency and transportation industry professionals who are experts in trucking. In addition, a micro traffic simulation model was used to produce various performance measurements that can describe quantitative impacts. As a result, the methodology provides a rational argument for prioritizing potential alternative truck strategies.     

A multi-objective optimization approach to balancing economic efficiency and equity in accessibility to multi-use paths

Improving public health through active transpiration investments has increasingly become a new research focus in transportation planning. This study is to propose a multi-objective optimization modeling framework, through an optimal allocation of active transportation investments, to maximize the total accessibility while minimizing the total differences in accessibility over a city. Accessibility to multi-use paths is calculated for Fresno, California that measures the total length of multi-use paths a resident could reach with a 30-min cycling ride. Then, a geographically weighted regression (GWR) model is used to capture the local relationships between accessibility outcome and previous transportation investments. The marginal-effect analysis for the GWR results indicates economically efficient, inefficient, and indifferent locations for further investments. This study is one of the few to incorporate such a GWR model into a multi-objective optimization modeling framework to improve accessibility to multi-use paths and address inequality issues in transportation. Solving the multi-objective optimization model provides decision-makers a new insight into the making of an economically efficient and socially equal active transportation plan to improve public health.

     

Factors affecting public transportation usage rate: Geographically weighted regression

As the number of private vehicles grows worldwide, so does air pollution and traffic congestion, which typically constrain economic development. To achieve transportation sustainability and continued economic development, the dependency on private vehicles must be decreased by increasing public transportation usage. However, without knowing the key factors that affect public transportation usage, developing strategies that effectively improve public transportation usage is impossible. Therefore, this study respectively applies global and local regression models to identify the key factors of usage rates for 348 regions (township or districts) in Taiwan. The global regression model, the Tobit regression model (TRM), is used to estimate one set of parameters that are associated with explanatory variables and explain regional differences in usage rates, while the local regression model, geographically weighted regression (GWR), estimates parameters differently depending on spatial correlations among neighbouring regions. By referencing related studies, 32 potential explanatory variables in four categories, social-economic, land use, public transportation, and private transportation, are chosen. Model performance is compared in terms of mean absolute percentage error (MAPE) and spatial autocorrelation coefficient (Moran’ I). Estimation results show that the GWR model has better prediction accuracy and better accommodation of spatial autocorrelation. Seven variables are significantly tested, and most have parameters that differ across regions in Taiwan. Based on these findings, strategies are proposed that improve public transportation usage.     

Risk-based maintenance and rehabilitation decisions for transportation infrastructure networks

A method for determining optimal risk-based maintenance and rehabilitation (M&R) policies for transportation infrastructure is presented. The proposed policies guarantee a certain performance level across the network under a predefined level of risk. The long-term model is formulated in the Markov Decision Process framework with risk-averse actions and transitional probabilities describing the uncertainty in the deterioration process. The well known Conditional Value at Risk (CVaR) is used as the measure of risk. The steady-state risk-averse M&R policies are modeled assuming no budget restriction. To address the short-term resource allocation problem, two linear programming models are presented to generate network-level polices with different objectives. While the proposed methodology is general and can be used with any performance indicator, pavement roughness is used for numerical studies and an analytical expression for computing CVaR is derived.     

Evaluating the public investment mix in US freight transportation infrastructure

This research empirically evaluates the public sector investment in the US freight transportation infrastructure. In particular, the infrastructures to support the two most comparable modes of freight transportation – highway and intermodal rail – are examined as alternatives for public fund allocation. Indicators for public sector transportation infrastructure investment mix are established based on financial analysis of both private and social costs and benefits, as well as the propensity of freight shippers to utilize such infrastructures. The research results in recommendations for the aggregate allocation of public funds in the US based on these indicators. We find that approximately a quarter of truck freight could be handled at a 25% lower cost if rail infrastructure to support it existed. Because an additional 80% reduction in social costs could be achieved through this modal conversion, the public sector is a critical participant in creating a more efficient transportation infrastructure.     

Quality of institutions and private participation in transport infrastructure investment: Evidence from developing countries

In recent decades, owing to a series of public debt crises and constraints on government expenditure, infrastructure investment has dropped significantly in both developed and developing countries. To counterbalance this trend, Public–Private Partnerships (PPPs) schemes have been increasingly adopted. In this paper, we explore the determinants of the degree of private participation in transport infrastructure projects in a large sample of developing countries. By using a large sample of transport projects included in the World Bank Private Participation in Infrastructure Projects database, we document that greater participation by private parties in PPP contracts is associated with better institutions in terms of lower corruption, civil freedom, and a better regulatory framework.     

Vehicle inspection and maintenance,and air pollution in Mexico City

Information from the Mandatory Inspection and Maintenance (I/M) Program carried out in October 1996 and the first semester of 1998 provides a useful emission database for Mexico City. Carbon monoxide (CO) and hydrocarbon (HC) exhaust emission levels were measured for at least a million private and public transportation vehicles. Analysis of this database leads us to conclude that this information can be used to test anti-pollutant policies, and is useful as a performance quality index for vehicle manufacturers. Some of the results of this analysis include: the finding of a typical exhaust emission distribution curve for each vehicle manufacturer, with differences for each brand and model for the same manufacturer, the fact that not all new vehicles pass the I/M test; and public transportation vehicles in Mexico City have almost useless catalytic converters.