Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows

Transportation - Predicting how changes to the urban environment layout will affect the spatial distribution of pedestrian flows is important for environmental, social and economic sustainability....     

Coastal Tourist Interest in Value-Added,Aquaculture-Based,Culinary Tourism Opportunities

Despite increasing focus on sustainable aquaculture investment in the U.S. coastal zones, the aquaculture industry continues to face skepticism among consumers due to perceived negative environmental impacts, and health and food safety concerns. Partnering with culinary tourism and local food promotion efforts has potential for improving public outreach about the benefits of aquaculture, especially in coastal destinations where sustainable marine aquaculture and tourism are both occurring. Culinary tourism implies that local foods reflect the local livelihood and culture, and may be important to the tourist's experience. Aquaculture is becoming increasingly valuable to coastal destinations for assuring the steady availability of local seafood to meet demand and retaining commercial fisheries as a means to differentiate themselves to tourists. This study examined the role of subjective knowledge and attitude about aquaculture, and their effect on intention to participate in value-added culinary aquaculture tourism experiences. The study found that tourists' subjective knowledge and attitude about aquaculture influenced intentions to participate in culinary aquaculture tourism. In order for farmers or tour operators to be successful in diversifying with value-added culinary aquaculture, attention needs to be paid to educating consumers, which may be possible through strategic partnerships with tourism organizations, chefs, and restaurants.     

Visualisation of uncertainty in probabilistic traffic models for policy and operations

This study investigates different methods to visualise uncertainty in static representations of probabilistic traffic models predictions on road-networks. Although various graphical cues may be used to represent uncertainty it is not a priori clear which of them are most suited for this purpose, since their legibility, intelligibility and the degree to which they interfere with other graphical elements in a representation differ widely. Several graphical uncertainty representations were therefore developed and analysed in expert sessions. A selection of the initial set of uncertainty visualisations was further evaluated in a cognitive alternative task-switching experiment. The results show that graphical representations are able to convey uncertainty information relatively accurately, while some uncertainty visualisations outperform others. It depends on the model and scenario which representation is most suited for a given application. This paper presents an overview of possible graphic uncertainty representations and the considerations involved when applying them to uncertainty in traffic model visualisations.     

Evaluating air emission inventories and indicators from cruise vessels at ports

This paper provides an estimation of air emissions (CO₂, NO_X, SO_X and PM) released by cruise vessels at the port level. The methodology is based on the “full bottom-up” approach and starts by evaluating the fuel consumed by each vessel on the basis of its individual port activities (manoeuvring, berthing and hoteling). The Port of Barcelona was selected as the site at which to perform the analysis, in which 125 calls of 30 cruise vessels were monitored. Real-time data from the automatic identification system (AIS), factor emissions from engine certificates and vessel characteristics from IHS Sea-web database were also collected for the analysis. The research findings show that the most appropriate indicators are inventory emissions per “port-time gross tonnage”, “port-time passenger” and “port time”. These emission indicators improve our understanding of cruise emissions and will facilitate the work that aims to estimate reliably and quickly the in-port ship emission inventories of cruise ports.     

Step-tolling with price-sensitive demand: Why more steps in the toll make the consumer better off

Most dynamic models of congestion pricing use fully time-variant tolls. However, in practice, tolls are uniform over the day, or at most have just a few steps. Such uniform and step tolls have received surprisingly little attention from the literature. Moreover, most models that do study them assume that demand is insensitive to the price. This seems an empirically questionable assumption that, as this paper finds, strongly affects the implications of step tolling for the consumer. In the bottleneck model, first-best tolling has no effect on the generalised price, and thus consumer surplus remains the same as without tolling. Conversely, under price-sensitive demand, step tolling increases the price, making the consumer worse off. The more steps the toll has, the closer it approximates the first-best toll, thereby increasing the welfare gain and making consumers better off. This indicates the importance for real-world tolls to have as many steps as possible: this not only raises welfare, but may also increase the political acceptability of the scheme by making consumers better off.     

Adapting without Retreating: Responses to Shoreline Change on an Inlet-Associated Coastal Beach

Coastal barrier systems around the world are experiencing higher rates of flooding and shoreline erosion. Property owners on barriers have made significant financial investments in physical protections that shield their nearby properties from these hazards, constituting a type of adaptation to shoreline change. Factors that contribute to adaptation on Plum Island, a developed beach and dune system on the North Shore of Massachusetts, are investigated here. Plum Island experiences patterns of shoreline change that may be representative of many inlet-associated beaches, encompassing an equivocal and dynamically shifting mix of erosion and accretion. In the face of episodic floods and fleeting erosive events, and driven by a combination of strong northeast storms and cycles of erosion and accretion, the value of the average Plum Island residence increases by 34% for properties on the oceanfront where protection comprises a publicly constructed soft structure. Even in the face of state policies that ostensibly discourage physical protection as a means of adaptation, coastal communities face significant political and financial pressures to maintain existing protective structures or to allow contiguous groups of property owners to build new ones through collective action. These factors mitigate against adapting to shoreline change by retreating from the coast, thereby potentially increasing the adverse effects of coastal hazards.     

Genetics of traffic assignment models for strategic transport planning

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models.     

The design of interurban bus networks in city centers

This paper proposes a bilevel formulation for solving the Bus Network Design Problem (BNDP) of interurban services entering a major city. It is focused in interurban services because it is a growing problem in most of major cities, yet new in the literature. The layout of interurban bus routes and the locations of transfer stations in the main city are the key factors to provide a competitive public transportation service to commuters in a metropolitan area. The number of commuters in huge urban concentrations is growing due to the difficulties of living near the city center. The objective function of the first level is defined with the aim of reducing user and agency costs. In the second level the performance of users is addressed. Furthermore, a local search method based on the Tabu Search algorithm was carried out to guide the exploration in the solution domain. The results obtained in a set of test problems have demonstrated that the restart parameters of the algorithm play a significant role in the efficiency of the algorithm. Finally, implementation in the large network of Barcelona (Spain) reduces the total cost by 5% with regard to the present situation.     

Situation analysis forecasting: the case of European maritime clusters

Within the literature concerned with aspects of competitiveness, innovation and strategic management of industrial clusters, the body regarding forecasting of strategic management is still nascent. This work aspires to render a contribution within the domain of strategic management forecasting, through the indicative case of European maritime clusters. For this end, a two-tier model is formulated. A quantitative strengths, weaknesses, opportunities, and threats (SWOT) methodology that derives from the fusion of a quondam situation analysis and crosstabs’ theory is generated. This leads to the utilization of the crosstab’s conditional probabilities as transition probabilities; the latter are called to compile the transition matrix of a Markov chain. Through this methodology, and the successive Markov chain’s transition matrices, strategic forecasts are extracted for a devised European maritime cluster case. This work relinquishes a novel application with respect to strategic management forecasting, that provides a dichotomy of practical interpretations and scenarios for quantitative situation analysis. Thus, it may enable effective real-time decision-making for strategic management and/or policy drafting. The situation analysis forecasting model may find applicability in a plethora of practical and theoretical cases, wherein forecasting may be desirable. It may as well pertain to an intrinsic methodology for situation analysis forecasting of maritime clusters.     

Prediction of travel time variability for cost-benefit analysis

Unreliable travel times cause substantial costs to travelers. Nevertheless, they are often not taken into account in cost-benefit analyses (CBA), or only in very rough ways. This paper aims at providing simple rules to predict variability, based on travel time data from Dutch highways. Two different concepts of travel time variability are used, which differ in their assumptions on information availability to drivers. The first measure is based on the assumption that, for a given road link and given time of day, the expected travel time is constant across all working days (rough information: RI). In the second case, expected travel times are assumed to reflect day-specific factors such as weather conditions or weekdays (fine information: FI). For both definitions of variability, we find that the mean travel time is a good predictor. On average, longer delays are associated with higher variability. However, the derivative of variability with respect to delays is decreasing in delays. It can be shown that this result relates to differences in the relative shares of observed traffic ‘regimes’ (free-flow, congested, hyper-congested) in the mean delay. For most CBAs, no information on the relative shares of the traffic regimes is available. A non-linear model based on mean travel times can then be used as an approximation.