公路运输站场规划方案的综合评价方法

文章将层次分析法与模糊综合评价方法相结合,针对公路运输站场规划方案的综合评价,进行了多层次模糊综合评价方法的研究,阐述了该方法的原理及其在公路运输站场规划方案综合评价中的应用,证明了该方法应用的易操作性与可行性。     

Changes in transport planning policy: Changes in transport planning methodology?

The 1990s saw the emergence of influential transport legislation both in the UK and in the USA. This "watershed" period appears to indicate that a significant turning point in transport policy is underway. There is now a need to re-evaluate how transport planning is done, and to consider changes to commonly used methods. Criticisms of urban transport planning are traced in the paper. These often focus on the four-stage modelling approach, but some authors also criticise the "rational comprehensive" paradigmatical framework within which the use of four-stage computer models is situated. It is argued that the rational comprehensive model of thinking is less useful today, due to the increasing complexity of the transport planning exercise; the rejection by the public of the transport planner as "expert"; and the highly political nature of transport planning. Alternative approaches are needed in order to address the new types of problems which transport planners face. The use of one such alternative approach, the Soft Systems Methodology, is illustrated as suitable for investigating complex decision-making systems in transport planning. It is suggested that this method could be beneficial in other problematic transport planning situations where the rational comprehensive approaches prove inadequate. Finally, the paper briefly looks ahead and considers the implications of a changing policy environment to the training of transport planners in the future.     

Scenario construction for transport planning

This paper argues that the types of uncertainty having the most serious consequences for transport planning are not captured by existing modelling procedures, which typically rely on a limited amount of sensitivity testing of plans based on extrapolative forecasts. It recommends as an alternative scenario‐based planning, an approach which is finding increasing application in private sector policy formation. The paper summarises the origins of scenario planning and the gradual broadening in its range of application, before going on to suggest methods of scenario construction suitable for transport planning applications. It considers the arguments for and against associating probabilities with scenarios and also addresses the problems of formulating transport strategies and evaluating them within the context of a scenario‐based approach to strategy choice.     

Things planners believe in,and things they deny

The paper examines the economic theory of consumer behavior from the Modern Psychoanalytic point of view with a metaphor of (transport) planning as a backdrop. It is claimed that the utility maximization principle of economic theory, no matter how broadly interpreted, does not envelop the motivation of human behavior and that the economic explanation of the aims of human behavior, which disregards the "dark side" of man, will result in narrowly conceived plans and policies.The application of economic theory, and other social sciences, to public policy has led to disjointedness of data collection, method of analysis, and planning and implementation. This, combined with a tautological behavioral theory, has made the current planning and public policy procedures self-verifying, and issues an invitation for a new theoretical approach which is comprehensive, does not ignore complexity and the large "error term", and appreciates the unity of data collection, method of investigation, and process of implementation.It is argued that unsatisfactory performance of the transport system, large errors inherent in data and models, the inability of extant transportation planning and policy to address key issues successfully, the environmental problem, and the value of the individual all call for new kinds of skills from the planners and policy makers.Freud's dualistic formulation of instinctual drives -- the life and death instincts -- is used as the new framework of explanation. This theory is seen to offer a convincing, more realistic and deeper understanding of the forces motivating human behavior, and one which is more in accordance with observable facts. If applied, the theory will lead to significantly different planning processes and to a profoundly different approach to public policy.     

Intermodal freight transport planning – A receding horizon control approach

This paper investigates intermodal freight transport planning problems among deep-sea terminals and inland terminals in hinterland haulage for a horizontally fully integrated intermodal freight transport operator at the tactical container flow level. An intermodal freight transport network (IFTN) model is first developed to capture the key characteristics of intermodal freight transport such as the modality change phenomena at intermodal terminals, physical capacity constraints of the network, time-dependent transport times on freeways, and time schedules for trains and barges. After that, the intermodal freight transport planning problem is formulated as an optimal intermodal container flow control problem from a system and control perspective with the use of the proposed IFTN model. To deal with the dynamic transport demands and dynamic traffic conditions in the IFTN, a receding horizon intermodal container flow control (RIFC) approach is proposed to control and to reassign intermodal container flows in a receding horizon way. This container flow control approach involves solving linear programming problems and is suited for transport planning on large-sized networks. Both an all-or-nothing approach and the proposed RIFC approach are evaluated through simulation studies. Simulation results show the potential of the proposed RIFC approach.     

Modeling discrete choice behavior using concepts from fuzzy set theory,approximate reasoning and neural networks

Models of discrete choice analysis are usually based on the random utility framework. They assume that decision makers make decisions that maximize their utility. Alternative formulations of the problem have also been proposed in the literature. These approaches model the decision makers’ perceptions of the attributes of the various alternatives using fuzzy sets and linguistic variables, and the decision process itself, using concepts from approximate reasoning and fuzzy control. The underlying assumption is that decision makers use a few simple rules that relate their vague perceptions of the various attributes to their preferences towards the available alternatives. The paper extends this approach by incorporating rule weights, which capture the importance of a particular rule in the decision process. It also presents an approach for calibrating the weights using concepts from neural networks. A case study, involving mode choice, is used to demonstrate the potential of the approach and compare it to alternative formulations and methodologies.     

Multiple criteria and fuzzy based evaluation of logistics performance for intermodal transportation

This paper presents a framework to evaluate the logistics performance of intermodal freight transportation. Fuzzy set techniques are applied to assess the logistics performance within the decision process of freight operators. Using a fuzzy‐based approach, fuzzy‐AHP is applied to assess the criteria by different judgment procedures. Consequently, fuzzy‐MCDM is used to assess operators' perception of the logistics performance via proper assignment of numerical scores. The subjective judgments for hierarchical criteria are transformed into fuzzy degrees of score. The methodology provides an alternative approach to facilitate the importance of a set of performance criteria. It can also entail use of improved corresponding parameters to develop a better freight transport system.     

Bi-level GA and GIS for Multi-objective TSP Route Planning

Abstract

Route planning is usually carried out to achieve a single objective such as to minimize transport cost, distance traveled or travel time. This article explores an approach to multi-objective route planning using a genetic algorithm (GA) and geographical information system (GIS) approach. The method is applied to the case of a tourist sight-seeing itinerary, where a route is planned by a tour operator to cover a set of places of interest within a given area. The route planning takes into account four criteria including travel time, vehicle operating cost, safety and surrounding scenic view quality. The multi-objective route planning in this paper can be viewed as an extension of the traditional traveling salesman problem (TSP) since a tourist needs to pass through a number of sight points. The four criteria are quantified using the spatial analytic functions of GIS and a generalized cost for each link is calculated. As different criteria play different roles in the route selection process, and the best order of the multiple points needs to be determined, a bi-level GA has been devised. The upper level aims to determine the weights of each criterion, while the lower level attempts to determine the best order of the sights to be visited based on the new generalized cost that is derived from the weights at the upper level. Both levels collaborate during the iterations and the route with the minimal generalized cost is thus determined. The above sight-seeing route planning methodology has been examined in a region within the central area of Singapore covering 19 places of interest.     

Income-contingent user preferences in policy evaluation: application and discussion based on multi-agent transport simulations

Standard economic policy evaluation allows the realization of projects if the aggregated economic benefit outweighs their costs. The use of one single aggregated welfare measure for evaluating and ranking projects has often been criticized for many reasons. A major issue is that differentiated effects on individuals or subgroups of the population are not taken into consideration. This leads to the need for transport planning tools that provide additional information for politicians and decision makers. The microscopic multi-agent simulation approach presented in this paper is capable of helping to design better solutions in such situations. In particular, it is shown that the inclusion of individual income in utility calculations allows a better understanding of problems linked to public acceptance. First, individual income-contingent utility functions are estimated based on survey data in order to describe human mobility behavior. Subsequently, using the MATSim framework, the implementation is tested in a test scenario. Furthermore, and going beyond Franklin (2006), it is shown that the approach works in a large-scale real world example. Based on a hypothetical speed increase of public transit, effects on the welfare distribution of the population are discussed. It is shown that the identification of winners and losers seems to be quite robust. However, results indicate that a conversion or aggregation of individual utility changes for welfare analysis is highly dependent on the functional form of the utility functions as well as on the choice of the aggregation procedure.     

A fuzzy-stochastic optimization model for the intermodal fleet management problem of an international transportation company

ABSTRACT

In this paper, a fuzzy-stochastic optimization model is developed for an intermodal fleet management system of a large international transportation company. The proposed model integrates various strategic, tactical and operational level decisions simultaneously. Since real-life fleet planning problems may involve different types of uncertainty jointly such as randomness and fuzziness, a hybrid chance-constrained programming and fuzzy interactive resolution-based approach is employed. Therefore, stochastic import/export freight demand and fuzzy transit times, truck/trailer availabilities, the transport capacity of Ro-Ro vessels, bounds on block train services, etc. can also be taken into account concurrently. In addition to minimize overall transportation costs, optimization of total transit times and CO₂ emission values are also incorporated in order to provide sustainable fleet plans by maximizing customer satisfaction and environmental considerations. Computational results show that effective and efficient fleet plans can be produced by making use of the proposed optimization model.     

Q-analysis and transport: A false start?

The utility for transport research of a number of key ideas from the methodology of Q-analysis is critically evaluated in this paper. It is argued through discussion of specific features of the approach that the literature on this subject has considerably overstated its utility, and that there has been a neglect of alternative methods that could achieve some of the desired ends.     

On appropriate microstate descriptions in entropy modelling

Using an information-theoretic approach to entropy modelling, expressions for the possible number of microstates are derived from the sets of choices available to households and firms in given location/transport planning situations. In planning applications, the urban space is usually subdivided into discrete zones, and various classes of householders and firms are grouped into separate activities. Nevertheless, the location sites within zones may vary considerably in accessibility, price and quality, and amenity v. cost trade-offs between location and travel many differ markedly between individuals within the same activity group. The inclusion of such variations within a random utility framework is demonstrated to be equivalent to maximizing entropy with the microstates disaggregated to the level where these variations occur. Using constraints based on spatial conditions, observed behaviour and planning policy, entropy maximization is used to determine the most probable macrostate according to each choice set specification. The resulting distributions are compared and their revelance discussed.     

Examining transport futures with scenario analysis and MCA

Climate change is a global problem and across the world the transport sector is finding it difficult to break projected increases in carbon dioxide (CO₂) emissions; there are very few contexts where deep reductions in transport CO₂ emissions are being made. A number of research studies are now examining the potential for future lower CO₂ emissions in the transport sector. This paper develops this work to consider some of the wider sustainability impacts (economic, social and local environmental) as well as the lower CO₂ transport impacts of different policy trajectories. Hence the central argument made is for an integrated approach to transport policy making over the longer term - incorporating scenario analysis and multi-criteria assessment (MCA) - to help assess likely progress against a range of objectives.The analysis is based on work carried out in Oxfordshire, UK. Different packages of measures are selected and two scenarios developed which satisfy lower CO₂ aspirations, one of which also provides wider positive sustainability impacts. A simulation model has been produced to help explore the strategic policy choices and tensions evident for decision-makers involved in local transport planning. The paper argues for a ‘strategic conversation’ (Van der Heijden, 1996) at the sub-regional and city level, based upon future scenario analysis and MCA, discussing the priorities for intervention. Such an approach will help us examine the scale of change and trade-offs required in moving towards sustainable transport futures.     

Experiential Incrementalism: On the Theory and Technique to Implement Transport Plans and Policies

The paper describes an approach to the vexing problem of transport planning and policy. It deals jointly with three questions, which in today's practice are addressed separately: How are hypotheses about transport problems and alternatives to their solution developed? How can a good plan or policy be identified? What is the process of implementing a transport plan or policy? In doing this the paper has the ambitious objective of proposing a new model and process for transport planning and policy. It is applicable in developed and developing countries and is not restricted to the transport sector. The paper builds on, and is a reinterpretation of two cornerstone transport planning and decision-making models – the CATS (Chicago Area Transportation Study) Planning and Design Model and Braybrooke and Lindblom's Disjointed Incrementalism. It advances a technique of experiential incrementalism (termed polisanalysis) to develop and implement plans and policies. It proposes that problems should be diagnosed by observation and continuous data collection; that their continuous analysis, finding the “cure”, and implementation take place through the method of experiential incrementalism. In this method interventions are grounded on the theories of neoinstitutional economics and psychoanalysis and derived using contact function, explained in the paper, which renders the method scientific replicability. Experiential incrementalism can employ a wider array of options in planning and policy than is presently thought possible. Like other scientific methods, its application requires rigorous training.     

Uncertainty in the context of highway appraisal

Transport planning is based on traffic forecasts which are subject to great uncertainties. These uncertainties have generally been ignored or, at least, not explicitly included in the planning process. This paper describes the principles behind the estimation of the uncertainty (or range of error) of the forecasts of a traffic model and discusses the means by which this information can be absorbed into the decision-making in transport planning projects. These principles have been applied to the appraisal of a British highway project and throughout the paper reference is made to this project in order to illustrate the results of the practical application of an explicit treatment of uncertainty. It is believed that this approach can and should be developed for application in most areas of transport planning, leading inevitably to an improvement in the quality of the decisions taken.     

General fuzzy rule base for isolated traffic signal control‐rule formulation

Traffic signal control is one of the oldest applications of fuzzy logic, at least in transportation engineering. The aim of this paper is to present a systematic approach to fuzzy traffic signal control and to derive the linguistic control rules based on expert knowledge. Traffic signal programming is generally divided into two problems: firstly, the choice and sequencing of signal stages to be used, and secondly, optimizing the relative lengths of these stages. The rule bases for both problems are introduced in our paper. The results of tested rule bases and field tests of fuzzy control have been promising. The fuzzy signal control algorithms offer better measures of effectiveness than the traditional vehicle‐actuated control.     

Forecasting transport development: Testing the utility of a simple regression approach

The analysis tests the utility of a simple regression approach in postdictively explaining transport development in West Malaysia from 1887 to 1968. The growth of the network is modelled as a process of contagious diffusion where transport densities of adjacent cells are used as predictor variables on a lagged basis. The partial regression coefficients provide measures of network orientation over time. The results demonstrate the importance of the contagion process in transport forecasting and provide equivalent levels of explanation when compared with a model which utilizes modernization indexes as predictor weights.I am grateful to Peter Gould for his advice and suggestions in the early stages of the research and for the comments of Peter Haggett, Mark Monmonier and J. Barry Riddell, all of whom read drafts of the paper. I also wish to acknowledge the financial support provided by a University of Vermont Faculty Fellowship.     

Level of public transport service evaluation: A fuzzy set approach

The success of any enterprise, in a market-oriented economy, depends upon it's quality. This paper describes the results of a survey of commuters on the quality of services and their relative weights, and of the attributes that determine the service level of bus transport undertakings. The model uses the theory of fuzzy sets to process the information obtained. A composite index, called level-of-public transport-service (LOPTS), is defined and used to measure the service qualities. This approach is presented with guidelines for rating the quality of services, fuzzy-set representations of the linguistic grades, definition of LOPTS and its use in a public transport quality data base. An example is presents how the approach can be employed to analyse data bases generated from a quality survey. This approach is compared with the numerical rating approach with single number representation.     

Valuation of users’ benefits in transport systems

Transport projects involve costs and benefits. Benefits to users appear in the form of more and/or better trips. Once the neoclassical idea of demand is accepted, the variation of utility levels underlie the measurement of benefits. In the evaluation process, benefits have to be compared with costs, and this can be done converting utility into monetary units. This paper deals with the treatment of this problem, starting with the general relation among utility, demand and the various forms of consumers’ surplus, to move further into the particular forms that these relations take in the transport field. The rule‐of‐a‐half is followed from the intuitive initial justification to a strict (and general) analytical derivation. More rigorous forms of users’ surplus variation are then presented for fairly general cases, including both aggregate and disaggregate transport demand models, emphasizing the manner in which welfare measures are derived in each case. Discussion is centred around the comparative advantages and limitations of available approaches, searching for improvements in demand formulation and benefits measurement.