Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

The accuracy of proxy responses in a stated choice setting: A re-examination and some controversial conclusions

Data is typically gathered from an individual respondent who represents the group or the household. This individual is often identified as the “primary decision maker” and is asked to provide responses as a proxy for the group given that the cost of interviewing each member individually is impractical and/or expensive. The collection of joint preferences is rarely undertaken, with the use of proxy responses not uncommon in travel behaviour research. Under such a framework, there exists an assumption that the primary decision maker has perfect knowledge of other group member preferences, and bargaining behaviour, and is able to synthesise this information when providing a response on their behalf. The validity of such an assumption however remains an open question, with recent research calling the reliability of proxy responses into account (Bateman and Munro, 2009). In this paper, using three models estimated in willingness to pay space, we examine the accuracy of proxy responses in a stated choice experiment. We find that there is overlap between a proxy response and the own preferences of the individual providing the proxy choice, but while the proxy responses fail to represent the full preference heterogeneity that exists in the actual choices made by individuals, the proxy responses in aggregate provide a suitable replacement for actual data, subject to a number of caveats.     

Multi‐objective highway alignment optimization using a genetic algorithm

The available highway alignment optimization algorithms use the total cost as the objective function. This is a single objective optimization process. In this process, travel‐time, vehicle operation accident earthwork land acquisition and pavement construction costs are the basic components of the total cost. This single objective highway alignment optimization process has limited capability in handling the cost components separately. Moreover, this process cannot yield a set of alternative solutions from a single run. This paper presents a multi‐objective approach to overcome these shortcomings. Some of the cost components of highway alignments are conflicting in nature. Minimizing some of them will yield a straighter alignment; whereas, minimizing others would make the alignment circuitous. Therefore, the goal of the multiobjective optimization approach is to handle the trade‐off amongst the highway alignment design objectives and present a set of near optimal solutions. The highway alignment objectives, i.e., cost functions, are not continuous in nature. Hence, a special genetic algorithm based multi‐objective optimization algorithm is suggested The proposed methodology is demonstrated via a case study at the end.     

Application of new parameterizations of gas transfer velocity and their impact on regional and global marine CO2 budgets

One of the dominant sources of uncertainty in the calculation of air–sea flux of carbon dioxide on a global scale originates from the various parameterizations of the gas transfer velocity, k, that are in use. Whilst it is undisputed that most of these parameterizations have shortcomings and neglect processes which influence air–sea gas exchange and do not scale with wind speed alone, there is no general agreement about their relative accuracy.The most widely used parameterizations are based on non-linear functions of wind speed and, to a lesser extent, on sea surface temperature and salinity. Processes such as surface film damping and whitecapping are known to have an effect on air–sea exchange. More recently published parameterizations use friction velocity, sea surface roughness, and significant wave height. These new parameters can account to some extent for processes such as film damping and whitecapping and could potentially explain the spread of wind-speed based transfer velocities published in the literature.We combine some of the principles of two recently published k parameterizations [Glover, D.M., Frew, N.M., McCue, S.J. and Bock, E.J., 2002. A multiyear time series of global gas transfer velocity from the TOPEX dual frequency, normalized radar backscatter algorithm. In: Donelan, M.A., Drennan, W.M., Saltzman, E.S., and Wanninkhof, R. (Eds.), Gas Transfer at Water Surfaces, Geophys. Monograph 127. AGU,Washington, DC, 325–331; Woolf, D.K., 2005. Parameterization of gas transfer velocities and sea-state dependent wave breaking. Tellus, 57B: 87–94] to calculate k as the sum of a linear function of total mean square slope of the sea surface and a wave breaking parameter. This separates contributions from direct and bubble-mediated gas transfer as suggested by Woolf [Woolf, D.K., 2005. Parameterization of gas transfer velocities and sea-state dependent wave breaking. Tellus, 57B: 87–94] and allows us to quantify contributions from these two processes independently.We then apply our parameterization to a monthly TOPEX altimeter gridded 1.5° × 1.5° data set and compare our results to transfer velocities calculated using the popular wind-based k parameterizations by Wanninkhof [Wanninkhof, R., 1992. Relationship between wind speed and gas exchange over the ocean. J. Geophys. Res., 97: 7373–7382.] and Wanninkhof and McGillis [Wanninkhof, R. and McGillis, W., 1999. A cubic relationship between air−sea CO2 exchange and wind speed. Geophys. Res. Lett., 26(13): 1889–1892]. We show that despite good agreement of the globally averaged transfer velocities, global and regional fluxes differ by up to 100%. These discrepancies are a result of different spatio-temporal distributions of the processes involved in the parameterizations of k, indicating the importance of wave field parameters and a need for further validation.     

Local Level Fisheries Management in Diani-Chale,Kenya: Current Status and Future Directions

The current regime of fisheries management and the prospects for attaining a more locally oriented, collaborative system of fisheries management in Diani-Chale, Kenya are examined. At present fisheries management in Diani-Chale is characterized by diminished government capacity for regulation, weakened local institutions, and little ability to exert control over the use of fisheries. Local level management requires the development and use of local institutions that can govern the use of fishery resources. The fish landing sites used by fishers and their associated fishing grounds were identified to be at the appropriate level for resolving fishery management issues. A more formal role for these entities, the clarification of fishing ground tenure and access rights, and support for the development and enforcement of local fishing rules can further local management. The socioeconomic condition of fishers, their fear of losing landing sites, and the continued perception of the imposition of a marine reserve pose barriers to initiatives seeking to further local level management.     

Motorway signals and the detection of incidents

A mathematical model of automobile trip tours is presented. Within a framework of eight common restrictions on automobile trip making, all travel behavior is assumed random and all of the ways in which tours can be arranged are assumed equally likely. Three probability distributions are derived from the model: (1) the probability that a household makes a given number of tours in a day; (2) the probability that a household makes a given number of trips in a day; and (3) the probability that a tour reaches a given number of destinations. It is shown that the model agrees with similar probability distributions generated from home‐interview data for Milwaukee.     

A dynamic model for marginal cost pricing of port infrastructures

ABSTRACT

A dynamic model for marginal cost pricing of port infrastructures links costs to system performance by combining a power-law function with time-dependent queueing analysis. Additionally, the model incorporates the marginal cost of capacity, including the effects of economies of scale. This allows the calculation of the marginal cost price under a dynamic framework. The model accounts for nonlinear behaviour of port demand, which is sensitive to price and service levels. The effects over time of cost and service levels on the port’s operational performance are quantified. The proposed model allows determining the optimal timing for capacity investment. The model is a starting point for the application of marginal cost pricing to ports. However, for practical application of such pricing method it is necessary to apply a system’s approach, as productivity and costs must be assessed at the terminal’s component level. This should allow the derivation of a marginal cost function at the terminal’s component level.     

On the use of mathematical programming in the evaluation of transport policies

This paper focuses on the evaluation processes by which decisions regarding transportation alternatives can be assisted. A multidimensional approach usually called multiple criteria decision making is required to represent the complexity of transportation policy and systems.

The multiple criteria decision making techniques can be divided into two groups. The first is based on a ranking scheme approach and the second on a mathematical programming approach.

A multiple objective mathematical programming procedure known as Goal Programming is presented. The authors examined the use of that procedure in real transportation problems.

The results suggest that multiple objective mathematical programming techniques in general do not appear to be appropriate in transportation policy analysis involving mutually exclusive alternatives. Their use can be limited to special cases in the private sector.     

Impacts of biodiesel blending on freight emissions in the Midwestern United States

We use a combination of petroleum–diesel models, datasets and tools along with biodiesel-specific corrections to create a roadway-level emissions inventory capable of evaluating spatial, temporal and scale aspects of fuel distribution options for the Midwestern US. Specifically, we compare the emissions of a year-round “low-blend” biodiesel implementation scenario, already under consideration in a variety of states, with a more strategic summer-only, interstate-only “high-blend” scenario. Our results indicate that spatial and seasonal distribution decisions do affect the overall emissions impacts of any biodiesel deployment, even those at low-blend levels. However, we also finds that changes in emissions due to biodiesel are considerably smaller than those anticipated from improvements to engine and control technologies.     

A Training Framework for Understanding Conflict in the Coastal Zone

The coastal zone is attractive for human settlement because it tends to be resource rich, providing a good location to generate incomes and livelihoods. Equally, however, it is a complex and powerful natural environment, which means that the coastal zone often becomes a focus of conflict with multiple users competing for limited space and resources. Understanding the causes of, and determining solutions to, the ensuing problems requires inputs from a range of analyses across sectors and disciplines. However, different disciplinary and sectoral approaches frequently use different investigative methods, language, and means of presenting results. This article presents a framework that has been developed in collaboration with Indian institutions over the past three years in an effort to address some of these fundamental problems of analysis and translation into policy action. Key components addressed by the framework are strengthening the capacity to practice, knowing how to proceed and how to find out what needs to be known using experience-based problem solving.