Measuring quality of service in dial-a-ride operations: the case of a Canadian city

In many countries, dial-a-ride services are provided by public authorities to elderly and handicapped people who cannot use regular transit. Cost minimization is key to running these services, but one can observe a growing interest in quality measurement and improvement. A first step in improving quality is to define a quality measurement scale specific to dial-a-ride services. A second step is to incorporate quality measurements in mathematical models that serve as a basis for optimization algorithms. To this end, an extensive survey of dial-a-ride users was conducted in Longueuil, the largest suburb of Montreal, Canada. This paper describes the steps of the survey and presents its main conclusions: (1) 56 attributes were identified based on interviews, (2) the questionnaire developed has proved to be reliable and valid, (3) an exploratory factor analysis allowed us to determine 13 dimensions of quality in dial-a-ride services, (4) the most important criteria for users were identified, and (5) population segmenting variables by which subgroups of users can be categorized were also determined. Managerial implications of our results are also discussed.     

Economic Outcomes for Harvesters under the West Coast Groundfish Trawl Catch Share Program: Have Goals and Objectives Been Met?

Abstract

The West Coast Groundfish Trawl Catch Share Program was designed to achieve multiple economic goals and objectives, including increasing net benefits, profitability, flexibility, and utilization of harvest allocations. In this article, we leverage seven years of comprehensive cost and earnings data to evaluate progress towards these goals with a focus on harvesters. Our assessment shows that five years post-implementation, net benefits to the nation have doubled, and indicators of productivity and profitability have increased. The fleet that targets Pacific whiting has seen the largest gains, due in part to increases in total allowable catch and the elimination of the race-to-fish. However, increased revenues have not been realized to the degree that was expected for harvesters targeting non-whiting groundfish, partly due to lower than predicted consolidation and relatively low quota utilization. Economic outcomes indicate that tradeoffs exist between certain objectives of the program, specifically between achieving full utilization and flexibility for harvesters. Results are discussed in the context of the design and evaluation of catch share programs for diverse, multispecies fisheries.     

Marine accident analysis for collision and grounding in oil tanker using FTA method

In this study, collision and grounding data registered in GISIS (Global Integrated Shipping Information System) were investigated for oil tankers. The database includes the information of the collision and grounding accidents during the period between 1998 and 2010 in oil tankers. The risk assessments were carried out using fault tree analysis (FTA) programme for the incidents as collision and grounding occurred in oil tankers. In this study, we were able to investigate first the potential problems which cause the collision and grounding accidents have been determined, second, the occurrence of accidents has been shown with causal factors by the FTA method, and, finally, the significance degree of the initial events causing occurrence of accidents have been put forth. Collision in oil tanker resulted in economical loss (81%), pollution (6%) and death or injury (13%). Grounding in oil tanker resulted in economical loss (91%) and pollution (9%). According to the FTA results, the main reason for the accidents originating from human error is as follows: for collision accidents, Convention on the International Regulations for Preventing Collisions at Sea (COLREG) violation and the lack of communication between vessels; and for grounding accidents, the interpretation failure of the officer on watch and lack of communication in the bridge resource management.     

On the numerical accuracy of the prediction of resistance coefficients in ship stern flow calculations

This article presents a study on the accuracy of the numerical determination of the friction and pressure resistance coefficients of ship hulls. The investigation was carried out for the KVLCC2 tanker at model- and full-scale Reynolds numbers. Gravity waves were neglected, i.e., we adopted the so-called double-model flow. Single-block grids with H–O topology were adopted for all the calculations. Three eddy viscosity models were employed: the one-equation eddy viscosity and the two-equation models proposed by Menter and the TNT version of the two-equation k-ω model. Verification exercises were performed in sets of nearly geometrically similar grids with different densities in the streamwise, normal, and girthwise directions. The friction and pressure resistance coefficients were calculated for different levels of the iterative error and for computational domains of different size. The results show that on the level of grid refinement used, it is possible to calculate the viscous resistance coefficients in H–O grids that do not match the ship contour with a numerical uncertainty of less than 1%. The differences between the predictions of different turbulence models were larger than the numerical uncertainty; however, these differences tended to decrease with increases in the Reynolds number. The pressure resistance was remarkably sensitive to domain size and far-field boundary conditions. Either a large domain or the application of a viscous–inviscid interaction procedure is needed for reliable results. This work was presented in part at the International Conference on Computational Methods in Marine Engineering—MARINE 2007, Barcelona, June 3–4, 2007.     

Practicability study on the suitability of artificial,neural networks for the approximation of unknown steering torques

For steer-by-wire systems, the steering feedback must be generated artificially due to the system characteristics. Classical control concepts require operating-point driven optimisations as well as increased calibration efforts in order to adequately simulate the steering torque in all driving states. Artificial neural networks (ANNs) are an innovative control concept; they are capable of learning arbitrary non-linear correlations without complex knowledge of physical dependencies. The present study investigates the suitability of neural networks for approximating unknown steering torques. To ensure robust processing of arbitrary data, network training with a sufficient volume of training data is required, that represents the relation between the input and target values in a wide range. The data were recorded in the course of various test drives. In this research, a variety of network topologies were trained, analysed and evaluated. Though the fundamental suitability of ANNs for the present control task was demonstrated.     

Supply and demand for the Eastern Canadian Arctic Sealift

The annual sealift of cargo to the Canadian Arctic has long been an essential part of the livelihood of Inuit communities. Over the past two decades, many structural changes were brought to this service and the demand has grown substantially. This paper aims to provide a better understanding of these changes by analysing demand and supply for Eastern Canadian Arctic sealift services. This analysis is based on Canadian Coast Guard vessel movement data and Statistics Canada port traffic data. It reveals that between 1987 and 2010, continuous and extreme variations in demand made it quite difficult for ship operators to adjust carrying capacity and optimise productivity. Yet, the recent industrial and population growth in the region has enabled them to reach significant gains in fleet utilisation levels.     

A multinomial logit car use model for a megacity of the developing world: Istanbul

The increase in motor vehicle use is one of the important factors that cause traffic congestion, especially in megacities. Thus, the reasons behind this increase require serious attention. This paper offers an analysis of this kind, for a megacity from the developing world, Istanbul. A stratified multinomial logit model accounting for the availability of a second vehicle in the household is estimated for a sample drawn from a questionnaire to gather information of actual car use in Istanbul. This estimation is only possible through a unique data generation process that converts actual preferences into a choice study setting. In addition, a simulation study, generally utilized in the analyses of discrimination between certain layers of society, and a scenario analysis related to changes in income are also included in the paper for a better understanding of the nature of the topic. The results show that the behavior of households with a second vehicle available and not available varies significantly due to household, individual and professional-related characteristics.     

Prediction of wave parameters by using fuzzy inference system and the parametric models along the south coasts of the Black Sea

Forecasting of sea-state characteristics has a great importance in coastal and ocean engineering studies. Therefore, the purpose of this study was to investigate performances of Adaptive-Network-Based Fuzzy Inference System (ANFIS) and several parametric methods in the Black Sea. For this purpose, different fuzzy models with different input combinations were developed for two different wind data sources (TSMS and ECMWF) at two offshore buoy stations. It also aimed to apply several approaches to event-based data sets for wave predictions. Generally, in literature the tendency is to use time series data for wave predictions. In this kind of prediction approach, lagged time series data are taken as inputs and current or future variables are taken as output. In this study, event-based data for each independent storm were extracted from time series data. Simultaneous or concurrent data of wind speed, blowing duration, fetch length and wave characteristics were detected for each single storm. These event data were then used to set up models. The hindcast results were validated with significant wave height and mean wave period data recorded in Hopa and Sinop buoy stations. The performance of developed fuzzy models were also compared with that of four different parametric methods (Wilson, SPM, Jonswap, and CEM methods) applied for two wind data sources at both buoy stations. Finally, it was determined that in the prediction of both wave parameters (H _s and T _z) the ANFIS models (R = 0.66, squared correlation coefficient, and MAE = 0.37 m, mean absolute error, for the best model in prediction of H _s) were more accurate than the parametric methods (R = 0.63 and MAE = 0.75 m for the best model in prediction of H _s).     

Shorebased Processor Outcomes Under Catch Shares

Abstract

Fishery management measures often aim to regulate harvesting behavior but can have downstream effects on fish processors, output markets, and consumers. Empirical analysis of these impacts is generally limited due to data availability. In this article, we utilize census costs and earnings data to examine operational characteristics and economic outcomes for shorebased processors before and after implementation of the West Coast Groundfish Trawl Catch Share Program. While the overall number of buyers of catch share species along the coast decreased and fish input prices generally increased, patterns in outcomes were different for processors with Pacific whiting operations compared to those that produce nonwhiting groundfish, including lengthened seasonal whiting operations but a decrease in the number of days receiving nonwhiting groundfish. These differences in outcomes illustrate the complexities involved in the management of multispecies fisheries with heterogeneous participants in both the harvest and post-harvest sectors. This review contributes to the fairly limited empirical work on the fish processing sector, which is an integral part of the seafood supply chain and important to the economic resilience of coastal fishing communities.     

Autonomous vehicles: scientometric and bibliometric review*

ABSTRACT

This paper presents a scientometric and bibliometric review of the research on autonomous vehicles (AVs) to identify its main characteristics, evolution, and potential trends for future studies. Relevant articles were searched on WoS, yielding a research corpus of 10,580 papers, and the software CiteSpace was subsequently used for analysis. The results showed that AV research is heterogeneous and registered a growing demand over time. Multidisciplinarity is present, with 96 science fields being identified. As in any other sector, it is necessary to understand broader aspects of this industry such as the market factors surrounding it, as well as other economic and managerial issues. In this sense, we observed a migration of the research field from multidisciplinarity to pluridisciplinarity with a greater number of studies focusing on the latter. We understand that terminology standardisation contributes to achieving pluridisciplinarity. As such, it is important to highlight that sustainability, public policies, liability, and safety, as well as business issues such as performance and business models are some of the tendencies in the field of AVs. For future studies, we suggest a more in-depth analysis of publications in terms of individual search terms, as well as the sub-areas identified as trends in this paper.