The Added Value of Accounting For Users’ Flexibility and Information on the Potential of a Station-Based One-Way Car-Sharing System: An Application in Lisbon,Portugal

Car-sharing systems are an alternative to private transportation whereby a person may use an automobile without having to own the vehicle. The classical systems in Europe are organized in stations scattered around the city where a person may pick up a vehicle and afterward return it to the same station (round trip). Allowing a person to drop off the vehicle at any station, called one-way system, poses a significant logistics problem because it creates a significant stock imbalance at the stations, which means that there will be times when users will not have a vehicle available for their trip. Previous mathematical programming formulations have tried to overcome this limitation by optimizing trip selection and station location in a city in order to capture the best trips for balancing the system. But there was one main limitation: The users were assumed to be inflexible with respect to their choice of a station, and held to use only the one closest to their origin and destination. If the user is willing to use the second or even the third closest station the user could benefit from using real-time information on vehicle stocks at each station and be able to select the one with available capacity. In this article we extend a previous model for trip selection and station location that takes that aspect into account by considering more vehicle pick-up and drop-off station options and then apply it to a trip origin–destination matrix from the Lisbon region in Portugal. Through the extended formulation we were able to conclude that user flexibility allied with having information on vehicle stocks increases the profit of the company, as people will go directly to a station with a vehicle available, thus making the use of the fleet more efficient. Observing the size of the stations resulting from the model, we also concluded that the effect of information is enhanced by large car-sharing systems consisting of many small stations.     

The missing link: bicycle infrastructure networks and ridership in 74 US cities

Cities promote strong bicycle networks to support and encourage bicycle commuting. However, the application of network science to bicycle facilities is not very well studied. Previous work has found relationships between the amount of bicycle infrastructure in a city and aggregate bicycle ridership, and between microscopic network structure and individual tripmaking patterns. This study fills the missing link between these two bodies of literature by developing a standard methodology for measuring bicycle facility network quality at the macroscopic level and testing its association with bicycle commuting. Bicycle infrastructure maps were collected for 74 Unites States cities and systematically analyzed to evaluate their network structure. Linear regression models revealed that connectivity and directness are important factors in predicting bicycle commuting after controlling for demographic variables and the size of the city. These findings provide a framework for transportation planners and policymakers to evaluate their local bicycle facility networks and set regional priorities that support nonmotorized travel behavior, and for continued research on the structure and quality of bicycle infrastructure and behavior.     

Agent-based model for continuous activity planning with an open planning horizon

The paper proposes the microscopic travel demand model continuous target-based activity planning (C-TAP) that generates multi-week schedules by means of a continuous planning approach with an open planning horizon. C-TAP introduces behavioral targets to describe people’s motivation to perform activities, and it uses a planning heuristic to make on-the-fly decisions about upcoming activities. The planning heuristic bases its decisions on three aspects: a discomfort index derived from deviations from agents’ past performance with regard to their behavioral targets; the effectiveness of the immediate execution; and activity execution options available in the near future. The paper reports the results of a test scenario based on an existing 6-week continuous travel diary and validates C-TAP by comparing simulation results with observed behavioral patterns along several dimensions (weekday similarities, weekday execution probabilities of activities, transition probabilities between activities, duration distributions of activities, frequency distributions of activities, execution interval distributions of activities and weekly travel probability distributions). The results show that C-TAP has the capability to reproduce observed behavior and the flexibility to introduces new behavioral patterns.     

Tollroads are only part of the overall trip: the error of our ways in past willingness to pay studies

With rare exception, actual tollroad traffic in many countries has failed to reproduce forecast traffic levels, regardless of whether the assessment is made after an initial year of operation or as long as 10 years after opening. Pundits have offered many reasons for this divergence, including optimism bias, strategic misrepresentation, the promise to equity investors of early returns on investment, errors in land use forecasts, and specific assumptions underlying the traffic assignment models used to develop traffic forecasts. One such assumption is the selection of a behaviourally meaningful value of travel time savings (VTTS) for use in a generalised cost or generalised time user benefit expression that is the main behavioural feature of the traffic assignment (route choice) model. Numerous empirical studies using stated choice experiments have designed choice sets of alternatives as if users choose a tolled route or a free route under the (implied) assumption that the tolled route is tolled for the entire trip. Reality is often very different, with a high incidence of use of a non-tolled road leading into and connecting out of a tolled link. In this paper we recognise this feature of route choice and redesign the stated choice experiment to account for it. Furthermore, this study is a follow up to a previous study undertaken before a new toll road was in place, and it benefits from real exposure to the new toll road. We find that the VTTS is noticeably reduced, and if the VTTS is a significant contributing influence on errors on traffic forecasts, then the lower estimates make sense behaviourally.     

Dynamic process model of mass effects on travel demand

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.     

Pruning and ranking the Pareto optimal set,application for the dynamic multi‐objective network design problem

Solving the multi‐objective network design problem (MONDP) resorts to a Pareto optimal set. This set can provide additional information like trade‐offs between objectives for the decision making process, which is not available if the compensation principle would be chosen in advance. However, the Pareto optimal set of solutions can become large, especially if the objectives are mainly opposed. As a consequence, the Pareto optimal set may become difficult to analyze and to comprehend. In this case, pruning and ranking becomes attractive to reduce the Pareto optimal set and to rank the solutions to assist the decision maker. Because the method used, may influence the eventual decisions taken, it is important to choose a method that corresponds best with the underlying decision process and is in accordance with the qualities of the data used. We provided a review of some methods to prune and rank the Pareto optimal set to illustrate the advantages and disadvantages of these methods. The methods are applied using the outcome of solving the dynamic MONDP in which minimizing externalities of traffic are the objectives, and dynamic traffic management measures are the decision variables. For this, we solved the dynamic MONDP for a realistic network of the city Almelo in the Netherlands using the non‐dominated sorting genetic algorithm II. For ranking, we propose to use a fuzzy outranking method that can take uncertainties regarding the data quality and the perception of decision makers into account; and for pruning, a method that explicitly reckons with significant trade‐offs has been identified as the more suitable method to assist the decision making process. Copyright © 2012 John Wiley & Sons, Ltd.     

Green shipping practices and firm performance

Global economic development is facilitated by the commercial shipping industry. Shipping operations contribute to the growth of international trade activities, which heavily count on ships to carry cargoes from places of production to places of consumption. Despite its importance, there have been growing concerns about the environmental impacts caused by shipping activities in international trade. To balance environmental protection and productivity, many shipping firms have begun to adopt green shipping practices (GSPs) to improve their operations in a more environmentally friendly manner. GSP consists of six dimensions, namely, company policy and procedure (CPP), shipping documentation (SD), shipping equipment (SE), shipper cooperation (SC), shipping materials (SM), and shipping design and compliance (SDC). GSP is becoming an important aspect of shipping operations. It is timely for the shipping industry to evaluate firm capability in carrying out greening operations, that is, firms’ “greening” capability. Firm capability comprises two key elements: one is embedded in firms’ business routines or activities, and the other concerns firms’ ability in transforming inputs into outputs. GSPs can be considered as inputs while firm performance measures as outputs. This study uses an input/output approach to examine the greening capability (GC) of shipping firms. The results indicate that shipping firms are relatively weak in the practices of SC and SE, while the capability scores of SM, CPP, SDC, and SD are all close to 1, with an average score of 0.927, 0.920, 0.924, and 0.978, respectively. Academic and managerial significance of the findings are highlighted.     

Constraint Mapping as a Means of Further Refining Saltmarsh Re-Creation Opportunities for the UK Solent Region

Based on geomorphological criteria, the Coastal Habitat Management Plan (CHaMP) for the Solent identified some 4,800 hectares of land potentially suitable for the creation of intertidal habitat, principally saltmarsh, through the use of managed realignment. Using “constraint mapping,” this study set out to illustrate that limitations to habitat re-creation through inundation are not merely geomorphological in nature. Indeed, a broad range of social, political, legal, technical, and economic constraints exist and must be evaluated in conjunction with physical parameters if the objectives of the European Birds and Habitats Directives are to be met, and so that future coastal defense policies ensure maintenance of the “favorable conservation status” of designated sites. A numerical filter system has been used to re-evaluate individual sites to establish “realistic” opportunities for compensatory saltmarsh creation in the Solent. As a result of taking into account wider socioeconomic constraints, it is clear that fewer areas are available for habitat creation purposes than were initially identified in the Solent CHaMP study.     

Transport policy scenario-building

Long-term planning decisions must be as robust as possible to withstand such changes in the policy-making environment. This calls for a new approach for identifying how policies might fare under different types of conditions and for identifying robust no-regrets strategies. This paper outlines a systematic and logical framework for the development of policy scenarios and shows how scenarios can be used in the analysis of future policy options. The article discusses how scenario analysis can be used to identify, anticipate and assess policy options for the future in an environment of uncertainty, mainly using examples of transport policy in Europe.