Pessimistic Equilibrium Flow and Its Network Design Implications

Quality of service in urban transportation network is very important to the users of this network. Travel time in street networks is one, very important, aspect of this service, particularly for trips with purposes such as work or school. A conservative route choice concept based on a pessimistic view of travel time has been proposed to render a pessimistic equilibrium flow (PEF). This flow is different from a user equilibrium flow (UEF), particularly in congested networks, and has sometimes a lower total travel time than UEF. A street network design problem has been proposed to take into account the travel time fluctuations (or service quality) in the network. This design model is based on PEF and is called pessimistic network design (PND) model. It is shown by an example network that an implication of PEF consideration in a PND model is that projects with lower potential in getting congested are chosen as compared with the conventional network design problem

Project Selection in Traffic Accident Prevention and Mitigation

This paper deals with two problems in relation to the accident treatment of urban street networks, i.e. accident prevention (AP) and accident mitigation (MP). These two problems are defined based on the concepts of suitable remaining trip-hours, link importance, and klink connectedness of node-destinations in the network. The objective of problem (AP) is to upgrade the important links so as to maximize a measure of the performance of the network. This is a before-accident treatment of the network. The objective of problem (MP) is to mitigate the accident effects in the network so as to maximize a measure of network connectedness. This is an after-accident treatment of the network, which is done by equippingauxiliary links in the network to join the available set of links, in order to make important 1-link connected node-destination pairs, k-link connected (k ≥ 2) . Two algorithms have been proposed to solve these two problems. The reasonability of the solution results has been shown by applying these two algorithms on a small-sized (6 nodes, 10 links) example network. The feasibility of the application of these algorithms on larger networks has been investigated by applying them on the network of Sioux Falls (24 nodes and 76 links)

Fuzzy random utility choice models: the case of telecommuting suitability

ABSTRACT: Random utility models have been widely used in many diverse fields. Considering utility as a random variable opened many new analytical doors to researchers in explaining behavioral phenomena. Introducing and incorporating the random error term into the utility function had several reasons, including accounting for unobserved variables. This paper incorporates fuzziness into random utility models to account for the imprecision of data intrinsic in human perception and statement. Fuzzy variables are contrasted with random variables, and a model is presented of relationships among real, perceived, and stated/reported conditions. The proposed fuzzy approach is applied to modeling telecommuting suitability, using data gathered from 242 employees in Tehran, Iran to construct fuzzy membership functions of job-tasks to the fuzzy set of telecommuting suitability. The resulting utility function can be viewed as representing the global wisdom of respondents. The enhancement in the fuzzy random utility model results, although modest, is promising and sets the stage for further research in the field of fuzzy logit models

Social welfare analysis of investment public-private partnership approaches for tansportation projects

This paper has two objectives: (1) to introduce a new approach to gaining widespread support for comprehensive road pricing; and (2) to develop a detailed social welfare analysis for road pricing schemes. We first describe a new approach to garnering support for system-wide road pricing, which we refer to as an investment public-private partnership, or IP3. This approach returns a significant portion of the economic value created by road pricing back to its citizen-owners. Next, we present a social welfare framework that estimates the benefits and costs of using the IP3 approach on an urban transportation network. Policy makers typically evaluate public-private partnership (P3) projects using Value for Money (VfM) analysis. However, a P3 project's impact on overall social welfare provides a more comprehensive evaluation criterion. Apart from several theoretical studies, a detailed social welfare analysis that includes all major P3 project stakeholders is lacking. Using Fresno City's transportation system as our case study, we show that system-optimal tolling scenarios favor average users, but that government¿and consequently taxpayers¿would pay for costly tolling systems. In contrast, unlimited profit-maximizing tolls raise substantial profits for government, for the infrastructure's citizen-owners, and for the private sector, but the average user is worse off. From a social welfare perspective, one should search for a Pareto-improvement under which all major stakeholders are better off. Our estimates indicate that a mixed private and public tolling scheme offers such an improvement. A mixed scheme results in the highest social welfare among all scenarios unless the weight placed on motorists' (i.e., transportation users') welfare is very low or the weight placed on residents' welfare is very high relative to the weight of other stakeholders

A biologically inspired network design model

A network design problem is to select a subset of links in a transport network that satisfy passengers or cargo transportation demands while minimizing the overall costs of the transportation. We propose a mathematical model of the foraging behaviour of slime mould P. polycephalum to solve the network design problem and construct optimal transport networks. In our algorithm, a traffic flow between any two cities is estimated using a gravity model. The flow is imitated by the model of the slime mould. The algorithm model converges to a steady state, which represents a solution of the problem. We validate our approach on examples of major transport networks in Mexico and China. By comparing networks developed in our approach with the man-made highways, networks developed by the slime mould, and a cellular automata model inspired by slime mould, we demonstrate the flexibility and efficiency of our approach

A Metaheuristic Framework for Bi-level Programming Problems with Multi-disciplinary Applications

Bi-level programming problems arise in situations when the decision maker has to take into account the responses of the users to his decisions. Several problems arising in engineering and economics can be cast within the bi-level programming framework. The bi-level programming model is also known as a Stackleberg or leader-follower game in which the leader chooses his variables so as to optimise his objective function, taking into account the response of the follower(s) who separately optimise their own objectives, treating the leader’s decisions as exogenous. In this chapter, we present a unified framework fully consistent with the Stackleberg paradigm of bi-level programming that allows for the integration of meta-heuristic algorithms with traditional gradient based optimisation algorithms for the solution of bi-level programming problems. In particular we employ Differential Evolution as the main meta-heuristic in our proposal.We subsequently apply the proposed method (DEBLP) to a range of problems from many fields such as transportation systems management, parameter estimation and game theory. It is demonstrated that DEBLP is a robust and powerful search heuristic for this class of problems characterised by non smoothness and non convexity

An Ant System application to the Bus Network Design Problem: an algorithm and a case study

Bus system design is a difficult problem, and hence is usually decomposed into a series of sub-problems solved sequentially. Bus network design is foremost in this series of problems. The bus network design problem in this study is the problem of choosing a subset of interconnected bus routes from among a given set of such routes, which minimizes the total travel time of the users of the network, while being feasible in fleet requirements. The Ant System concept has been exploited to solve this problem. The algorithm has been applied to the problem and calibrated based on the network of Sioux Falls. For this purpose, several fleet assignment routines have been tested, some sensitivity analyses are made to estimate suitable parameter values, and alternative ways of laying pheromone on bus routes have been examined. Experiments are conducted to investigate the performance of the solution algorithm when the number of routes, or bus fleet size, increases. Moreover, other experiments help to determine the number of algorithmic iterations. These experiments prepared the algorithm to be applied to design the bus network of the City of Mashhad, with a population of over 2 million. The results have been compared with those of another solution to the same problem, obtained by another meta-heuristic, namely a Genetic Algorithm

Peer evaluation of multi-attribute analysis techniques: Case of a light rail transit network choice

This paper attempts to present a method for differentiating between multi-attribute decision procedures and to identify some competent procedures for major decision problems, where a matrix of alternative-measure of effectiveness and a vector of weights for the latter are available. In this respect, several known multi-attribute analysis procedures are chosen, and the same procedures are exploited to evaluate themselves, based on some evaluation criteria. This is done from an engineering viewpoint and in the context of a transportation problem, using a real case light rail transit network choice problem for the City of Mashhad, and the results are presented. Two concepts have been proposed in this respect and used in this evaluation; peer evaluation and information evaluation, which are investigated in this paper. In the evaluation of five multi-attribute decision procedures, based on nine criteria, and with the help of these procedures themselves in the context of the case under study, the results revealed that these procedures found Electre, Linear Assignment, Simple Additive Weighting, TOPSIS, and Minkowski Distance better than others, in the same order as given. This is backed by a wide range of sensitivity analyses. Nevertheless, despite specific conclusions made regarding the better decision procedures among those evaluated, this paper finds its contribution mainly in the approach to such evaluations and choices