Transport planning with multiple criteria: The analytic hierarchy process applications and progress review

Five examples of applications of the Analytic Hierarchy Process (AHP) are made to illustrate the different uses of this ratio scale multicriteria decision method in transportation. They include a commuter route selection hierarchy, a best mix of routes to Pittsburgh's new International Airport, a benefits/costs hierarchy to choose the best mode to cross a river, a planning hierarchy for a transport system and a simple dependence with feedback cycle to choose a car when criteria depend on the alternatives. For a better appreciation of the use and power of the method, the examples are followed by a resume of developments in research on the (AHP) in the last few years.     

Use of an activity-based diary to collect household travel data

The paper describes the results of a pilot survey that used a one-day activity diary to collect origin-destination data, as opposed to a travel-based diary. The design of the diary is discussed, together with a comparison to a more conventional travel diary. The paper examines the extent to which the activity diary appears to have been capable of collecting good travel data that is at least comparable to travel diary efforts. In addition, a substantial portion of the paper is concerned with a comparison of the retrieval methods for the diaries. Two alternative methods were pilot-tested, one being the use of telephone retrieval and the other being mailback retrieval. Although the pilot test used small samples, the evidence appears to be strong that mailback is preferable to telephone retrieval, while telephone retrieval did not seem capable of providing some of the benefits often ascribed to it.     

Factors influencing the propensity to cycle to work

This paper describes the development of a mode choice model for the journey to work with special emphasis on the propensity to cycle. The model combines Revealed Preference (RP) and Stated Preference (SP) data to form a very large and comprehensive model. RP data from the National Travel Survey was combined with a specially commissioned RP survey. A number of SP surveys were also undertaken to examine the effects of different types of en-route and trip end cycle facilities and financial measures to encourage cycling.The development of the model is described in detail. The model was used to forecast trends in urban commuting shares over time and to predict the impacts of different measures to encourage cycling. Of the en-route cycle facilities, a completely segregated cycleway was forecast to have the greatest impact, but even the unfeasible scenario of universal provision of such facilities would only result in a 55% increase in cycling and a slight reduction in car commuting. Payments for cycling to work were found to be highly effective with a £2 daily payment almost doubling the level of cycling. The most effective policy would combine improvements in en-route facilities, a daily payment to cycle to work and comprehensive trip end facilities and this would also have a significant impact on car commuting.     

Parameter transfer of common-metric attributes in choice analysis: implications for willingness to pay

There is a growing literature that promotes the presence of a mix of compensatory and semi-compensatory processing strategies in the way that individuals evaluate packages of attributes in real or hypothetical markets, and make choices. This paper proposes a specification for the utility form in a choice model to test if, given a pair of attributes with a common-metric (e.g., components of travel time or cost), the attribute with the dominating level defines the marginal (dis)utility that is assigned to both attributes. We refer to this processing strategy as a parameter transfer rule. We use a stated choice data set, in the context of car driving individuals choosing between tolled and non-tolled routes, to estimate a mixed logit model which incorporates the presence of the parameter transfer rule and the conventional fully compensatory rule, both existing up to a probability. We find that if this parameter transfer heuristic is part of the mix, the WTP is more than 30% higher, on average, than when only a fully compensatory rule is imposed. We also contrast the parameter transfer rule with other semi-compensatory heuristics which have been investigated in other papers, and show that the finding adds further support to the accumulating evidence that a semi-compensatory attribute processing rules tend to result in higher mean WTP estimates compared to the fully compensatory attribute processing rule.     

Applications of intuitionistic fuzzy set aggregation operators in transport multi-factor project evaluation

Abstract

An intuitionistic fuzzy set (IFS) is a generalisation of a fuzzy set characterised by a truth membership function and a false membership function. The former is a lower bound on the grade of membership of the evidence in favour of a particular element belonging to the set and the latter is a lower bound on the negation of that element belonging to the set derived from evidence against that element belonging to the set. A similar concept is a vague set, though vague sets have been shown to be identical to IFSs. In the context of project evaluation, an IFS may be used to represent the degree to which a project satisfies a criterion and the degree to which it does not. Aggregation of such IFSs has been considered in recent years to identify a best project in terms of several criteria or factors. A particular desirable way to aggregate IFS is in terms of an ordered weighted average (OWA) which can be expressed in different forms such as arithmetic and geometric. In an OWA operator, weights are applied to the position of an element in the aggregation. In addition, hybrid OWA operators may be developed to not only weight the position of elements in the aggregation but the element itself. An example is given relating to the Kuranda Range Road upgrade (Queensland, Australia) which is limited by grade, poor overtaking opportunities, poor horizontal alignment and other constraints and the road is expected to become increasingly congested over the next few years. A more flexible multi-factor decision method is used to identify a ‘best’ project from a set of four alternative projects.     

长大公路隧道火灾模式下的烟雾特性研究

公路隧道火灾初期对人员逃生造成威胁的并不是高温,而是烟雾。为了更好地控制隧道火灾的蔓延,就必须更好地对隧道火灾烟雾的特性进行研究,总结出一些普遍规律,为火灾救援提供试验基础。文章通过秦岭终南山特长公路隧道的火灾模型试验,对长大公路隧道发生火灾时的烟雾特性进行了研究。     

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.     

Determining intermediate origin-destination matrices for the analysis of composite mode trips

We consider in this paper the problem of determining intermediate origin-destination matrices for composite mode trips that involve a trip by private car to a parking facility and the continuation of the trip to the destination either by walking or by a transit mode. The intermediate origin-destination matrices relate to each component of the composite mode trip: a matrix from the trip origins to intermediate destinations which are parking lots and a matrix from the parking lots to the final destinations. The approach that we propose to solve this problem is to modify the entropy based trip distribution models to consider inequality constraints related to parking lot capacities. Such models may be easily calibrated by using well known calibration methods or generalization of these methods and may be easily solved by applying a primal feasible direction method of nonlinear programming.     

Passengers’ willingness to pay for airport ground access time savings

There are cases when passengers are willing to pay a premium to reduce the travel time, in particular when the trip has to be made. This paper aims to provide insight into factors that determine passengers’ willingness to pay to reduce travel time for their ground access to an airport. A methodology is developed that comprises two steps: the identification of the passengers with zero willingness to pay and from the rest the estimation of the additional price they are willing to pay to reduce their travel time. For the first step a Probit model was formulated and for the second a linear regression model. To this purpose, data has been collected employing stated preference from passengers at the Athens International Airport. It has been found that a high percentage of passengers have zero willingness to pay, and of the remaining ones those using public transport have a significant willingness to pay to reduce access travel time. The methodology and the models are structured in such a way that their transferability to any airport environment is possible, thus providing a useful tool for decisions relating to airport ground access measures.     

Role of the Railways in the Future of Air Transport

Abstract

The role of the railways in the air transport industry is usually limited to provision of access to airports. However, the development of high-speed rail networks and the congestion and environmental problems faced by the air transport industry suggest the railways could have a greater role in working with the airlines to provide an integrated transport service for medium-distance journeys (up to 800 km). Many air journeys involve two flights and a transfer at a hub airport. The alternative being investigated here would replace air journeys by a rail journey and a flight, and a transfer between them at the hub airport. Such integration could offer a positive alternative to aircraft on some routes and lead to railway journeys to airports becoming part of air transport services, and not only to provide access to them. Integration could therefore provide a better use of available air capacity rather than duplicating some high-speed rail routes and services.     

The impact of job assignment rules for straddle carriers on the throughput of container terminals

Straddle carriers represent a critical resource in the handling of containers within a container terminal. It is essential that they are deployed in an as efficient manner as possible. The research presented in this paper is motivated by the need to critically evaluate job assignment rules for straddle carriers that operate in a multiple straddle environment. This is achieved by developing a discrete event simulation model using industrial simulation software to model a container terminal located in Melbourne, Australia. The model accounts for variables such as the number of straddle carriers needed, the speed of straddle carriers, the arrival rate of trucks, and the job assignment rule. A principal finding of the study is that increasing the number of straddles in the present set‐up from 6 to 7 has a negligible effect on daily throughput. However, an increase in the number of straddles to 7 is expected to have a profound effect on reducing the average waiting time of trucks within the terminal from over 16 minutes to under 9 minutes, a decrease of 46.5%. However, a further increase in the number of straddles results in no further increase in daily throughput. It was observed that the throughput of the terminal is very sensitive to the speeds at which straddles travel. The management of the terminal has proposed a new heuristic job assignment rule for straddles, because the present rule does not assign the jobs to straddles closest to the truck requesting to load or unload a container. As a result a new heuristic job assignment rule was tested. The simulation results revealed that both the old and new rules performed equally well using performance indicators such as average container flow time, daily throughput, average waiting time of jobs, number of jobs in the queue, and straddle utilisation. Therefore, the new rule will not improve these performance measures if implemented     

Complementing distance based charges with discounted registration fees in the reform of road user charges: the impact for motorists and government revenue

The call for a congestion charge is getting louder and more frequent in many countries as major metropolitan areas experience increasing levels of road congestion. This is often accompanied by a recognition that governments need to find new sources of revenue to maintain existing road networks and to invest in new transport infrastructure. Although reform of road pricing is almost certain to occur at some time in the future in a number of countries, a key challenge is in selling the idea to the community of road users as well as a whole raft of interest groups that influence the views of society and politicians. Simply announcing a need for a congestion charge (often misleadingly called a tax) does little to progress the reform agenda. What is required is a carefully structured demonstration of what might be done to progressively introduce adjustments in road user charges that are seen as reducing the costs to motorists while ensuring no loss of revenue to government. In this paper we show, in the context of Sydney (Australia), that this can be achieved by the reform of registration fees in the presence of a distance-based charging regime that can deliver financial gains to motorists, with prospects of revenue growth to the State Treasury.     

Overcoming public aversion to congestion pricing

We have completed a survey of Southern California residents designed to examine whether the details of policy design can make congestion pricing more attractive to the motoring public. A congestion fee proposal is often regarded as simply a tax increase; also, especially in the US, motorists apparently regard the use of congestion fees as coercive, in that they often have few if any practical alternatives to paying the fee. Unlike most opinion surveys on congestion pricing, our survey was quite explicit about the fate of the collected revenues. For example, we presented respondents with policies that returned a substantial portion of the revenues to the public, either in the form of cash (through reductions in sales taxes and vehicle registration fees or through income tax credits) or in the form of coupons to be used for vehicle emissions equipment repair, transit, and the like. In addition, we examined whether the typically intense opposition to congestion pricing if applied only to a part of a roadway, leaving the motorist free to choose between free lanes and toll lanes. We find that a promise to offset the imposition of congestion fees by other taxes can result in a 7% point increase in support for congestion pricing policies, and the restriction of congestion pricing to a single lane on a freeway attracts from 9% to 17% points of additional support.     

Compromising system and user interests in shelter location and evacuation planning

Traffic management during an evacuation and the decision of where to locate the shelters are of critical importance to the performance of an evacuation plan. From the evacuation management authority’s point of view, the desirable goal is to minimize the total evacuation time by computing a system optimum (SO). However, evacuees may not be willing to take long routes enforced on them by a SO solution; but they may consent to taking routes with lengths not longer than the shortest path to the nearest shelter site by more than a tolerable factor. We develop a model that optimally locates shelters and assigns evacuees to the nearest shelter sites by assigning them to shortest paths, shortest and nearest with a given degree of tolerance, so that the total evacuation time is minimized. As the travel time on a road segment is often modeled as a nonlinear function of the flow on the segment, the resulting model is a nonlinear mixed integer programming model. We develop a solution method that can handle practical size problems using second order cone programming techniques. Using our model, we investigate the importance of the number and locations of shelter sites and the trade-off between efficiency and fairness.     

Design of an expert system for aircraft gate assignment

The task of assigning arriving flights at an airport to the available gates is a key activity in airline station operations. With the development of large connecting hub operations, and the resulting volumes of passengers and baggage transferring between flights, the complexity of the task and the number of factors to be considered have increased significantly. Traditional approaches utilizing classical operations research techniques have difficulty with uncertain information and multiple performance criteria, and do not adapt well to the needs of real-time operations support. As a result, several airlines have been exploring the use of expert systems for operational control of ramp activity.This paper discusses the factors that arise in deciding how to allocate flights to gates, and describes the knowledge base structure, data requirements and inference process of an expert system that would recommend gate allocation decisions to ramp control personnel, taking into account the constraints imposed by the available facilities and personnel to handle the aircraft, and the consequences on downstream operations of particular assignment decisions. The paper describes how these concepts have been implemented in a prototype expert system that has been designed to address a restricted set of gate assignment issues within a framework that could be extended to consider a broader range of factors. The operation of the expert system is illustrated through a case study application to a typical flight schedule at a major hub airport.     

Multi-agent simulation of individual mobility behavior in carpooling

Carpooling is an emerging alternative transportation mode that is eco-friendly and sustainable as it enables commuters to save time, travel resource, reduce emission and traffic congestion. The procedure of carpooling consists of a number of steps namely; (i) create a motive to carpool, (ii) communicate this motive with other agents, (iii) negotiate a plan with the interested agents, (iv) execute the agreed plans, and (v) provide a feedback to all concerned agents. In this paper, we present a conceptual design of an agent-based model (ABM) for the carpooling a that serves as a proof of concept. Our model for the carpooling application is a computational model that is used for simulating the interactions of autonomous agents and to analyze the effects of change in factors related to the infrastructure, behavior and cost. In our carpooling application, we use agent profiles and social networks to initiate our agent communication model and then employ a route matching algorithm, and a utility function to trigger the negotiation process between agents. We developed a prototype of our agent-based carpooling application based on the work presented in this paper and carried out a validation study of our results with real data collected in Flanders, Belgium.     

Large-scale dynamic transportation network simulation: A space-time-event parallel computing approach

This paper describes a computationally efficient parallel-computing framework for mesoscopic transportation simulation on large-scale networks. By introducing an overall data structure for mesoscopic dynamic transportation simulation, we discuss a set of implementation issues for enabling flexible parallel computing on a multi-core shared memory architecture. First, we embed an event-based simulation logic to implement a simplified kinematic wave model and reduce simulation overhead. Second, we present a space-time-event computing framework to decompose simulation steps to reduce communication overhead in parallel execution and an OpenMP-based space-time-processor implementation method that is used to automate task partition tasks. According to the spatial and temporal attributes, various types of simulation events are mapped to independent logical processes that can concurrently execute their procedures while maintaining good load balance. We propose a synchronous space-parallel simulation strategy to dynamically assign the logical processes to different threads. The proposed method is then applied to simulate large-scale, real-world networks to examine the computational efficiency under different numbers of CPU threads. Numerical experiments demonstrate that the implemented parallel computing algorithm can significantly improve the computational efficiency and it can reach up to a speedup of 10 on a workstation with 32 computing threads.     

Shift of reference point and implications on behavioral reaction to gains and losses

It is widely recognized that individual decision-making is subject to the evaluation of gains and losses around a reference point. The estimation of discrete choice models increasingly use data from stated choice experiments which are pivoted around a reference alternative. However, to date, the specification of a reference alternative in transport studies has been fixed, whereas it is common to observe individuals adjusting their preferences according to a change in their reference point. This paper focuses on individual reactions, in a freight choice context, to a negative change in the reference alternative values, identifying the behavioural implications in terms of loss aversion and diminishing sensitivity. The results show a significant adjustment in the valuation of gains and losses around a shifted reference alternative. In particular, we find an average increase in loss aversion for cost and time attributes, and a substantial decrease for punctuality. These findings are translated to significant differences in the willingness to pay and willingness to accept measures, providing supporting evidence of respondents’ behavioural reaction.     

Estimating the willingness to pay and value of risk reduction for car occupants in the road environment

In recent years there has been a re-focus on the valuation of a statistical life from the ex post or human capital method to an ex ante willingness to pay (WTP) approach. This is in part a recognition that we may have been undervaluing the cost of fatalities and injuries to society associated with crashes, but also a strong belief in the need to focus on establishing the amount, ex ante, that individuals are willing to pay to reduce the risk of exposure to circumstances that might lead to death or degree of injury on the road network. This study has developed a framework in which to identify the degree of preference heterogeneity in willingness to pay by individuals who are drivers or passengers in cars to avoid being killed or injured. A stated choice experiment approach is developed. The empirical setting is a choice of route for a particular trip that a sample of individuals periodically undertakes in Australia. The particular trip is described in enough detail to provide the respondent with a familiar market environment, providing all the relevant background information required for making a decision. Mixed logit models are estimated to obtain the marginal (dis)utilities associated with each influence on the choice amongst the attribute packages offered in the stated choice scenarios. These estimates are used to obtain the WTP distributions for fatality and injury avoidance, which are then aggregated to obtain estimates of the value of risk reduction (VRR), of which the fatality class is also known as the value of a statistical life (VSL).