Parking restraint policy and urban vitality

The aim of the paper is to examine whether parking restraint policies may have impacts on the economic vitality of urban centres. Literature from empirical, attitudinal and modelling studies is reviewed within a structure based around a conceptual framework of parking impacts. The search for relevant material was undertaken both for the UK and overseas, but the discussion and conclusions were related to the UK context. Original modelling was undertaken and is reported here. This review found that as parking restraint policies have not been previously implemented with consistency or longevity, there is a lack of direct evidence, given that land-use impacts typically involve a long-term response. Furthermore, different methods of examining impacts have come to very different conclusions. Attitudinal evidence suggests that there is a high level of sensitivity to parking provision, whereas aggregate statistical studies tend to find only a weak relationship. The reasons underlying these differences are discussed. Land-use/transport models show impacts if there is sufficient change in generalized cost, although the spatial distribution of impacts, and impacts by household or employment disaggregation, vary considerably. Given the inconclusive nature of the evidence to date, only tentative policy implications can be drawn. Recommendations for further research are outlined, both for empirical study and for model enhancements.     

Issue Definition and Planning for Whalewatching Management Strategies in Ensenada,Mexico

The exceptional growth of whalewatching in Baja California Sur (BCS) and other parts of Mexico during the last 10 years motivated the design and implementation of a Mexican whalewatching law based on experiences in BCS. However, recent research in the Ensenada whalewatching area confirms that this law is insufficient in this area because whalewatching boats and other fishing, cruising, or drifting boats influence the behavior (swimming direction and velocity) of migrating gray whales. In the long term, the migration corridor might be displaced offshore, and whalewatching may become infeasible. This study proposes a management planning process to adapt regulations to this area, to promote adherence to regulations by encouraging self-regulation and strengthening law enforcement, and to enhance the tourist service on board. The actors involved were identified.     

Stated preference analysis of travel choices: the state of practice

Stated preference (SP) methods are widely used in travel behaviour research and practice to identify behavioural responses to choice situations which are not revealed in the market, and where the attribute levels offered by existing choices are modified to such an extent that the reliability of revealed preference models as predictors of response is brought into question. This paper reviews recent developments in the application of SP models which add to their growing relevance in demand modelling and prediction. The main themes addressed include a comparative assessment of choice models and preference models, the importance of scaling when pooling different types of data, especially the appeal of SP data as an enriching strategy in the context of revealed preference models, hierarchical designs when the number of attributes make single experiments too complex for the respondent, and ways of accommodating dynamics (i.e. serial correlation and state dependence) in SP modelling.An earlier modified version was presented as the keynote address to the 1993 National Conference on Tourism Research, held at the University of Sydney, 19 March 1993. The comments of Jordan Louviere, Lester Johnson, Paul Hooper, W.G. Waters II and Mark Bradley are appreciated.     

Generating complete all-day activity plans with genetic algorithms

Activity-based demand generation contructs complete all-day activity plans for each member of a population, and derives transportation demand from the fact that consecutive activities at different locations need to be connected by travel. Besides many other advantages, activity-based demand generation also fits well into the paradigm of multi-agent simulation, where each traveler is kept as an individual throughout the whole modeling process. In this paper, we present a new approach to the problem, which uses genetic algorithms (GA). Our GA keeps, for each member of the population, several instances of possible all-day activity plans in memory. Those plans are modified by mutation and crossover, while bad instances are eventually discarded. Any GA needs a fitness function to evaluate the performance of each instance. For all-day activity plans, it makes sense to use a utility function to obtain such a fitness. In consequence, a significant part of the paper is spent discussing such a utility function. In addition, the paper shows the performance of the algorithm to a few selected problems, including very busy and rather non-busy days.     

The rational locator reexamined: Are travel times still stable?

The rational locator hypothesis posits that individuals can, if they choose, maintain approximately steady journey-to-work travel times by adjusting their home and workplace. This hypothesis was coupled with the observation of long-term stability in drive alone journey-to-work times in metropolitan Washington (those times were unchanged from 1957 through 1968 to 1988). Despite the increase of average commuting distance and congestion, trip duration remained constant or even declined when controlling for travel purpose and travel mode because of shifting a share of traffic from slow urban routes to faster suburban routes. This observation has significance, as it is important to know for travel demand analysis if there is an underlying budget, or even a regularity, as this helps us determine whether our forecasts are reasonable. To re-test the underlying rationale for the hypothesis that travel times are stable, intra-metropolitan comparisons of travel times are made using Washington DC data from 1968, 1988, and 1994, and Twin Cities data from 1990 and 2000. The results depend upon geography. For the larger Washington DC region, keeping the same geography shows little change in commute times, but using the larger 1994 area suggests an increase in commute times. However, the Twin Cities, starting from a much shorter commute time, shows a marked increase over the decade, using either the smaller or the larger geography. Despite the remarkable continuing observation of stability in drive alone commuting times in metropolitan Washington, we reject the theory of personal commuting budgets, as we find that not only are commuting times not generally stable over time at the intra-metropolitan area, but that commuting time clearly depends on metropolitan spatial structure.     

Asymmetry of Columbia River tidal plume fronts

Columbia River tidal plume dynamics can be explained in terms of two asymmetries related to plume-front depth and internal wave generation. These asymmetries may be an important factor contributing to the observed greater primary productivity and phytoplankton standing crop on the Washington shelf. The tidal plume (the most recent ebb outflow from the estuary) is initially supercritical with respect to the frontal internal Froude number F_R on strong ebbs. It is separated from the rotating plume bulge by a front, whose properties are very different under upwelling vs. downwelling conditions. Under summer upwelling conditions, tidal plume fronts are sharp and narrow (< 20–50 m wide) on their upwind or northern side and mark a transition from supercritical to subcritical flow for up to 12 h after high water. Such sharp fronts are a source of turbulent mixing, despite the strong stratification. Because the tidal plume may overlie newly upwelled waters, these fronts can mix nutrients into the plume. Symmetry would suggest that there should be a sharp front south of the estuary mouth under summer downwelling conditions. Instead, the downwelling tidal plume front is usually diffuse on its upstream side. Mixing is weaker, and the water masses immediately below are low in nutrients. There is also an upwelling–downwelling asymmetry in internal wave generation. During upwelling and weak wind conditions, plume fronts often generate trains of non-linear internal waves as they transition from a supercritical to a subcritical state. Under downwelling conditions, internal wave release is less common and the waves are less energetic. Furthermore, regardless of wind conditions, solition formation almost always begins on the south side of the plume so that the front “unzips” from south to north. This distinction is important, because these internal waves contribute to vertical mixing in the plume bulge and transport low-salinity water across the tidal plume into the plume bulge.F_R and plume depth are key parameters in distinguishing the upwelling and downwelling situations, and these two asymmetries can be explained in terms of potential vorticity conservation. The divergence of the tidal outflow after it leaves the estuary embeds relative vorticity in the emerging tidal plume water mass. This vorticity controls the transition of the tidal plume front to a subcritical state and consequently the timing and location of internal wave generation by plume fronts.     

Advances in population synthesis: fitting many attributes per agent and fitting to household and person margins simultaneously

Agent-based microsimulation models of transportation, land use or other socioeconomic processes require an initial synthetic population derived from census data, conventionally created using the iterative proportional fitting (IPF) procedure. This paper introduces a novel computational method that allows the synthesis of many more attributes and finer attribute categories than previous approaches, both of which are long-standing limitations discussed in the literature. Additionally, a new approach is used to fit household and person zonal attribute distributions simultaneously. This technique was first adopted to address limitations specific to Canadian census data, but could also be useful in U.S. and other applications. The results of each new method are evaluated empirically in terms of goodness-of-fit.     

Inferring attribute non-attendance from stated choice data: implications for willingness to pay estimates and a warning for stated choice experiment design

There is a growing interest in traveller behaviour research to explore alternative information processing strategies (often referred to as heuristics or rules) adopted by individuals when assessing packages of attributes describing alternatives in a choice set, and making a choice. One popular attribute processing rule relates to attributes not being considered (i.e., being ignored), for all manner of reasons, referred to in the small but growing literature as attribute non-attendance or non-preservation. Researchers have used a mixture of methods to study the role of attribute non-attendance, including supplementary questions on whether each attribute is ignored or not, and methods in which the functional form of the utility expressions defining an alternative can recognise the possibility, up to a probability, of an attribute being ignored. Although supplementary questions are worthy of further consideration, despite the controversy as to the reliability of the response, recent interest has focused on ways to establish the incidence of attribute non-attendance without recourse to such evidence. In this paper we use an existing data set of choice amongst four attributes describing alternative car non-commuting trips, to illustrate the proposed method, and to compare values of travel time savings under each possible combination of non-attendance attributes relative to a model in which all attributes are assumed to be fully attended to. The paper reveals a major concern with the way that attribute levels and ranges are selected in the design of choice experiments, which can induce non-attendance situations where willingness to pay estimates cannot be obtained.     

Not bored yet - Revisiting respondent fatigue in stated choice experiments

Stated choice surveys are used extensively in the study of choice behaviour across many different areas of research, notably in transport. One of their main characteristics in comparison with most types of revealed preference (RP) surveys is the ability to capture behaviour by the same respondent under varying choice scenarios. While this ability to capture multiple choices is generally seen as an advantage, there is a certain amount of unease about survey length. The precise definition about what constitutes a large number of choice tasks however varies across disciplines, and it is not uncommon to see surveys with up to twenty tasks per respondent in some areas. The argument against this practice has always been one of reducing respondent engagement, which could be interpreted as a result of fatigue or boredom, with frequent reference to the findings of Bradley and Daly (1994) who showed a significant drop in utility scale, i.e. an increase in error, as a respondent moved from one choice experiment to the next, an effect they related to respondent fatigue. While the work by Bradley and Daly has become a standard reference in this context, it should be recognised that not only was the fatigue part of the work based on a single dataset, but the state-of-the-art and the state-of-practice in stated choice survey design and implementation has moved on significantly since their study. In this paper, we review other literature and present a more comprehensive study investigating evidence of respondent fatigue across a larger number of different surveys. Using a comprehensive testing framework employing both Logit and mixed Logit structures, we provide strong evidence that the concerns about fatigue in the literature are possibly overstated, with no clear decreasing trend in scale across choice tasks in any of our studies. For the data sets tested, we find that accommodating any scale heterogeneity has little or no impact on substantive model results, that the role of constants generally decreases as the survey progresses, and that there is evidence of significant attribute level (as opposed to scale) heterogeneity across choice tasks.     

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.