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This paper explains the need for the application of cost-benefit analysis to the evaluation of alternative projects for investment in the transport field and outlines briefly the historical development of the technique. The results of a comparative survey of a number of cost-benefit studies which have been carried out in Britain and some conclusions as to their thoroughness and comprehensiveness (or otherwise) are presented. The article concludes with a number of specific and detailed recommendations to remedy apparent methodological weaknesses. Six of these recommendations seem to merit particular attention:
- The viewpoint of most studies should be extended so as to avoid confinement, for example, within an arbitrary local government boundary, and a wider range of “externalities” should be considered. Intangibles should be included explicitly in all such evaluation exercises.
- The actual incidence of costs and benefits should be examined in order to indicate the directional impact of the project and its implications in terms of equity. The elimination of transfer payments and double-counting should be postponed until the latest possible stage in the evaluation.
- Equity considerations should be investigated in any transportation plan, since most projects have considerable equity implications for particular areas or socio-economic groups.
- Discounted cash flow techniques, which are still used only in a minority of transportation studies, should become standard practice. Most evaluations are based on a single-year rate of return, or at best on simple trend forecasting. More resources should be devoted to proper evaluation of alternative plans which give due importance to the cost and benefit streams through time.
- Sensitivity analysis should be used in all transportation evaluations. Knowledge of the impact of different assignments, shadow prices, and discount rates are essential information for any decisionmaker.
- Last, but not least, much greater communication should exist between analyst and decisionmaker than has existed in the past.
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The focus of this paper is the degree to which day-to-day variability in the individual's travel pattern has a systematic, or nonrandom, component. We first review the different sources of variability in travel, emphasizing the difference between between-individual and within-individual variation and the implications of this difference for travel analysis. After discussing the impact of measurement (i.e. the way in which travel behavior is measured) on the study of repetition and variability, we use the Uppsala data to examine the level of systematic variability in an individual's longitudinal travel record. The analysis focuses on two questions: - How well does observation over one week capture longer-term (five-week) travel behavior; in other words, is behavior highly repetitive from week to week? - How systematic is within-individual variability; in other words, are certain stops distributed over the five-week record in a nonrandom, that is either regular or clustered, fashion? Using measures of travel that include more than one stop attribute (e.g. activity, mode, time of day, and location), we found that: - A seven-day record of travel does not capture most of the separate behaviors exhibited by the individual over a five-week period, but it does capture, for most people, a good sampling of the person's different typical daily travel patterns. - Whereas a considerable portion of intraindividual variability is systematic (nonrandom), clustering is a more important source of nonrandom variation than is regularity. The results suggest that behavior does not follow a weekly cycle closely enough for a one-week travel record to measure the longer-term frequency with which the individual makes certain stops or to assess the level of day-to-day variation present in the individual's record. Because these results are likely to reflect the particular measures of behavior we used, one conclusion of this study is the need for other studies that replicate the aims of this one but use a variety of other travel measures. Only through such additional work can we truly assess the sensitivity of our findings to measurement techniques. 相似文献
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This research examines the problem of route bus specification and vehicle manufacturability. In order for bus operators to provide transport services, a range of vehicle configurations must be available from bus manufacturers, generating variety which has a negative impact on the manufacturing process. Larger part inventories, uncontrolled labour tasks and more troublesome maintenance are known impacts of this variety. This research identifies the functional necessities in route bus interior design and reduces the problems in bus manufacture and operation caused by specification diversity by proposing a modularised system of bus design. In particular, it makes recommendations as to how bus configuration should be carried out, ensuring an optimum mix of operational and manufacturing needs:
- 1.Determine user needs before the bus specification process.
- 2.Designs to be developed by the manufacturer in response to user needs.
- 3.This design should be standardised where possible, as suggested by the user needs.
- 4.Where user needs dictate product variations, apply a mass customisation approach to accommodate these needs.
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This study gains insight into individual motivations for choosing to own and use autonomous vehicles and develops a model for autonomous vehicle long-term choice decisions. A stated preference questionnaire is distributed to 721 individuals living across Israel and North America. Based on the characteristics of their current commutes, individuals are presented with various scenarios and asked to choose the car they would use for their commute. A vehicle choice model which includes three options is estimated:
- (1)Continue to commute using a regular car that you have in your possession.
- (2)Buy and shift to commuting using a privately-owned autonomous vehicle (PAV).
- (3)Shift to using a shared-autonomous vehicle (SAV), from a fleet of on-demand cars for your commute.
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《Transportation Research Part C: Emerging Technologies》2001,9(4):249-263
Random utility models are undoubtedly the most used models for the simulation of transport demand. These models simulate the choice of a decision-maker among a set of feasible alternatives and their operational use requires that the analyst is able to correctly specify this choice-set for each individual.Some early applications basically ignored this problem by assuming that all decision-makers chose from the same pre-specified choice-set. This assumption may be unrealistic in many practical cases and cause significant misspecification problems (P. Stopher, Transportation Journal of ASCE 106 (1980) 427; H. Williams, J. Ortuzar, Transportation Research B 16 (1982) 167).The problem of choice-set simulation has been dealt within the literature following two basically different approaches:
- •simulating the perception/availability of an alternative implicitly in the choice model,
- •simulating the choice-set generation explicitly in a separate model.
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《Transportation Research Part B: Methodological》1987,21(3):233-248
The purpose of this study is to develop a valid and efficient method for estimating origin-destination tables from roadside survey data. Roadside surveys, whether conducted by interviews or postcard mailback methods, typically have in common the sampling of trip origin and destination information at survey stations. These survey stations are generally located where roads cross “screenlines,” which are imaginary barriers drawn to intercept the trip types of interest.Such surveys also include counts of traffic volumes, by which the partial origin-destination (O-D) tables obtained at the different stations can be expanded and combined to obtain the complete O-D table which represents travel throughout the entire study area. The procedure used to expand the sample O-D information from the survey stations must recognize and deal appropriately with a number of problems:
- 1.(i) The “double counting” problem: Long-distance trips may pass through more than one survey station location; thus certain trips have the possibility of being sampled and expanded more than once, leading to a potentially serious overrepresentation of long-distance trips in the complete expanded trip table.
- 2.(ii) The “leaky screenline” problem: Some route choices, particularly those using very lightly traveled roads, may miss the survey stations entirely, leading to an underestimation of certain O-D patterns, or to distorted estimates if such sites are arbitrarily coupled with actual nearby station locations.
- 3.(iii) The efficient use of the data: There is a need to adjust expansion factors to compensate for double counting and leaky screenlines. How can this be accomplished such that all of the data obtained at the stations are used without loss of information?
- 4.(iv) The consequences of uncertainty and unknown travel behavior: Since the O-D data and other sampled variables are subject to random error, and since in general the probability of encountering a long-distance trip at some survey stations is affected by traveler route-choice behavior, which is not understood, the sample expansion procedure must rely on the use of erroneous input data and questionable assumptions. The preferred procedure must minimize, rather than amplify, the effects of such input errors.
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This paper reports the results of a stated-preference study aimed at investigating how transport decisions are made by receivers
or by transport operators about the potential use of an urban freight consolidation centre in the city of Fano, Italy. Because
there are no revealed preference data, a stated-choice methodology is used. The stated-choice experiments present two alternatives—one
using a private vehicle subject to various traffic regulations and one using the urban freight consolidation centre with varying
cost and efficiency levels. Conventional discrete choice data modelling shows that the potential demand is influenced mainly
by the distance of the parking bay from the shop, by access permit cost, by the service cost of the urban freight consolidation
centre, and by the delay in delivery time. Simulations are then performed to assess how the potential demand is affected by
various incentives and regulations affecting urban goods distribution.
Edoardo Marcucci is Associate Professor of Applied Economics at the Faculty of Political Sciences, University of Roma Tre, Italy, General Secretary of the Italian Society of Transportation Economists, and co-founder of the Kuhmo—Nectar Conference and Summer School Series on Pricing, Financing, Regulating Transport Infrastructures and Services. He has studied freight transportation concentrating on interactions along logistic supply chains. Romeo Danielis is Full Professor at the University of Trieste, Italy. He is managing editor of European Transport\Trasporti Europei. He has published articles on input-output modelling, regional environmental policy, social costing of transport externalities, EU enlargement and on several transport issues including road pricing, the Down-Thompson paradox, energy use and CO2 emissions, freight transport demand and stated preferences. 相似文献
Edoardo MarcucciEmail: |
Edoardo Marcucci is Associate Professor of Applied Economics at the Faculty of Political Sciences, University of Roma Tre, Italy, General Secretary of the Italian Society of Transportation Economists, and co-founder of the Kuhmo—Nectar Conference and Summer School Series on Pricing, Financing, Regulating Transport Infrastructures and Services. He has studied freight transportation concentrating on interactions along logistic supply chains. Romeo Danielis is Full Professor at the University of Trieste, Italy. He is managing editor of European Transport\Trasporti Europei. He has published articles on input-output modelling, regional environmental policy, social costing of transport externalities, EU enlargement and on several transport issues including road pricing, the Down-Thompson paradox, energy use and CO2 emissions, freight transport demand and stated preferences. 相似文献
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Urban sprawl is pervasive in Australian cities arising from the low density development of dwellings with the consequence that private vehicle use dominates daily travel in Australia. This paper examines a community based social marketing program, TravelSmart, which targeted reducing vehicle kilometres travelled as part of a transport demand management strategy. This paper uses 3-year panel data collected by GPS tracking and a conventional survey methodology in northern Adelaide, South Australia, to examine whether TravelSmart had a sustained impact and whether this was impacted by socio-economic and built-environment factors. A latent growth model is employed and demonstrates TravelSmart led to a declining trend in private car driving over the 3 years at both individual and household levels with effects being sustained beyond 1 year and up to 2 years. There is some evidence of compensatory behaviour between household members. Socio-demographic factors are significant with males decreasing their driving times faster than females. Built environment impacts were also significant with different levels of walkability showing different trajectories in the reduction of car trips after the implementation of TravelSmart, suggesting social marketing interventions work better when supported by hard policies such as a supportive built environment. 相似文献
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In order to plan bus operations, it is necessary for transit planners to understand what factors may influence travelers’ choice of buses for travels within a city. The proposed method involves various scenarios of a hypothetical bus operation which was rated by a group of individuals. Analysis of Covariance technique is employed to analyze people's sensitivities to their perceived levels of bus service characteristics. The technique involves:
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testing for the significant effects of varying levels of service characteristics upon people's intentions to use bus service, and
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assessing differences among various population segments in their sensitivity patterns towards bus service characteristics.
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Traffic microsimulation models normally include a large number of parameters that must be calibrated before the model can
be used as a tool for prediction. A wave of methodologies for calibrating such models has been recently proposed in the literature,
but there have been no attempts to identify general calibration principles based on their collective experience. The current
paper attempts to guide traffic analysts through the basic requirements of the calibration of microsimulation models. Among
the issues discussed here are underlying assumptions of the calibration process, the scope of the calibration problem, formulation
and automation, measuring goodness-of-fit, and the need for repeated model runs.
Yaron Hollander is a transport analyst, working for Steer Davies Gleave in London. His work combines advanced demand modelling, Stated Preference, appraisal, design of public transport systems, transport policy and network modelling. He completed his PhD at the Institute for Transport Studies in Leeds, and previously worked for the Technion – Israel Institute for Technology; for the Israeli Institute for Transportation Planning and Research; and for the public transport department at Ayalon Highways Co. Ronghui Liu is a Senior Research Fellow at the Institute for Transport Studies, University of Leeds. Her main research interests are modelling of traffic and microsimulation of driver behaviour and dynamical systems. She develops and applies network microsimulation models to a wide range of areas from transport policy instruments such as road pricing, to public transport operations and traffic signal controls. 相似文献
Ronghui LiuEmail: |
Yaron Hollander is a transport analyst, working for Steer Davies Gleave in London. His work combines advanced demand modelling, Stated Preference, appraisal, design of public transport systems, transport policy and network modelling. He completed his PhD at the Institute for Transport Studies in Leeds, and previously worked for the Technion – Israel Institute for Technology; for the Israeli Institute for Transportation Planning and Research; and for the public transport department at Ayalon Highways Co. Ronghui Liu is a Senior Research Fellow at the Institute for Transport Studies, University of Leeds. Her main research interests are modelling of traffic and microsimulation of driver behaviour and dynamical systems. She develops and applies network microsimulation models to a wide range of areas from transport policy instruments such as road pricing, to public transport operations and traffic signal controls. 相似文献
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Travel behaviour analysis has recently witnessed a rapidly growing interest in regret-based models of choice behaviour. Two different model specifications have been introduced in the transportation literature. Chorus et al. (Transportation Research B 42: 1–18, 2008a; in: Proceedings 87th Annual Meeting of the Transportation Research Board, Washington DC, 2008b) specified regret as a (non) linear function of the difference between the best-foregone choice alternative and the chosen alternative. Later, as an approximation to the original specification, Chorus (2010) suggested a logarithm function of utility differences between all choice alternatives, mainly for ease of estimation. This paper makes two contributions to this literature. First, formal analyses are conducted to identify the parameter space where the logarithmic specification becomes theoretically inferior to the original specification. Second, an empirical stated choice study on the choice of shopping centre is conducted to empirically test which specification best describes stated choices. Results suggest that for the collected data the original specification outperforms the new specification. Implications of this finding for the application of regret-based choice models in travel behaviour analysis are discussed. 相似文献
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Whereas transportation planners commonly predict the negative impacts of mass transportation, there is increasing empirical evidence of the existence of positive mass effects, whereby increased use of a mode by the ‘mass’ will generally increase its attractiveness for future travellers. In this paper we consider the dynamic impact of such an effect on the problem of travel demand forecasting, with particular regards to social network effects. Our proposed modelling approach is inspired by literature from social physics, evolutionary game theory and marketing. For simplicity of exposition, our model is specified for a scenario in which (a) there is a binary choice between two mobility lifestyles, referred to as car-oriented and transit-oriented, and (b) there are two population groups, where one is the “leading” or “innovative” population group and the other the “following” or “imitating” population group. This latter distinction follows the rather well-known Bass model from the marketing literature (1969). We develop the transition probabilities and transition dynamics. We illustrate with a numerical case study that despite lower intrinsic utility for the transit lifestyle, significant changes towards this lifestyle can be achieved by considering congestion, service improvements and mass effects. We further illustrate that mass effects can be positive or negative. In all cases we explore the sensitivity of our conclusions to the assumed parameter values. 相似文献
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The use of high-technology systems in the transport sector has increased steadily over recent years. This paper outlines the development of vehicle monitoring and control systems and their use in the public transport arena. The paper shows how one such system, that operated by Datatrak Ltd., has been adapted to provide a real time passenger information system for the RiverBus Partnership in London. 1 The RiverBus service described in this article ceased operation in August 1993. The collapse of the RiverBus Partnership followed the financial difficulties surrounding Olympia and York, developers of Canary Wharf in London Docklands. Passenger use and perception of the system is evaluated, based on surveys of RiverBus users. This provides an evaluation of the system, and highlights the importance of introducing such systems based on user information needs and as part of the total marketing package. 相似文献
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The rapid and continuing changes in travel and mobility needs in India over the last decade necessitates the development and
use of dynamic models for travel demand forecasting rather than cross-sectional models. In this context, this paper investigates
mode choice dynamics among workers in Chennai city, India over a period of five years (1999–2004). Dynamics in mode choice
is captured at four levels: exogenous variable change, state-dependence, changes in users’ sensitivity to attributes, and
unobserved error terms. The results show that the dynamic models provide a substantial improvement (of over 500 log-likelihood
points and ρ2 increases from 44% to 68%) over the cross-sectional model. The performance was compared using two illustrative policy scenarios
with important methodological and practical implications. The results indicate that cross-sectional models tend to provide
inflated estimates of potential improvement measures. Improving the Level of Service (LOS) alone will not produce the anticipated
benefits to transit agencies, as it fails to overcome the persistent inertia captured in the state-dependence factors. The
results and models have important applications in the context of growing motorization and congestion management in developing
countries.
相似文献
P. BhargaviEmail: |
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Despite widespread growth in on-road public transport priority schemes, road management authorities have few tools to evaluate
the impacts of these schemes on all road users. This paper describes a methodology developed in Melbourne, Australia to assist
the road management authority, VicRoads, evaluate trade-offs in the use of its limited road-space for new bus and tram priority
projects. The approach employs traffic micro-simulation modelling to assess road-space re-allocation impacts, travel behaviour
modelling to assess changes in travel patterns and a social cost benefit framework to evaluate impacts. The evaluation considers
a comprehensive range of impacts including the environmental benefits of improved public transport services. Impacts on public
transport reliability improvements are also considered. Although improved bus and tram reliability is a major rationale for
traffic priority its use in previous evaluations is rare. The paper critiques previous approaches, describes the proposed
method and explores some of the results found in its application. A major finding is that despite a more comprehensive approach
to measuring the benefits of bus and tram priority, road-space reallocation is difficult to economically justify in road networks
where public transport usage is low and car usage high. Strategies involving the balanced deployment of bus and tram priority
measures where the allocation of time and space to PT minimises negative traffic impacts is shown to improve the overall management
of road-space. A discussion of the approach is also provided including suggestions for further methodology development.
相似文献
Bill YoungEmail: |