Trip distribution for limited destinations: a case study for grocery shopping trips in the Netherlands

In this paper, we introduce a new trip distribution model for destinations that are not homogeneously distributed. The model is a gravity model in which the spatial configuration of destinations is incorporated in the modeling process. The performance was tested on a survey with reported grocery shopping trips in the Dutch city of Almelo. The results show that the new model outperforms the traditional gravity model. It is also superior to the intervening opportunities model, because the distribution can be described as a function of travel costs, without increasing the computational time. In this study, the distribution was described by a simple function of Euclidean distance, which provides a good fit to the survey data. The slope of the distribution is quite steep. This shows that most trips are made to nearby supermarkets. However, a significant fraction of trips, mainly made by car, still goes to supermarkets further away. We argue that modeling of these trips by the new method will improve traffic flow predictions.     

Trip generation of vulnerable populations in three Canadian cities: a spatial ordered probit approach

This paper provides an analysis of trip generation of three vulnerable groups: single-parent families, low income households, and the elderly. It compares the mobility of these groups to that of the general population in three Canadian urban areas of Hamilton, Montreal and Toronto, based on data from large-sample metropolitan transport surveys. An ordered probit model with spatially expanded coefficients is used for the analysis. Spatial expansion shows that there are spatial mobility trends for elderly populations and low-income populations even after socio-economic attributes are accounted for. Such spatial differences are not generally found for single parent families. This novel spatial analysis provides clues as to where vulnerable populations may experience greater degrees of social exclusion. It provides information to help prioritize transportation infrastructure projects or other social programs to take into account the needs of vulnerable populations with the lowest levels of mobility.     

Adapting the light · biomass (BZI) models of phytoplankton primary production to shallow marine ecosystems

Several authors have reported a strong linear relationship between daily phytoplankton production and the product of chlorophyll biomass, photic depth, and incident irradiance for a variety of estuaries. This “light · biomass” (BZ_pI_o) formulation has been proposed as an alternative to traditional mechanistic approaches for computing phytoplankton production in numerical estuarine models. One limitation to their application in shallow systems is that the BZ_pI_o models have been developed in relatively deep estuaries where light does not reach the bottom. We propose a nonlinear correction factor to adapt the BZ_pI_o relationship to shallow systems where light does reach the bottom. Our function takes into account variations in incident irradiance, attenuation coefficient for light, photosynthetic efficiency, and maximum rate of photosynthesis. A series of correction polynomials are proposed for various ranges of incident irradiance, and are integrated into a single multiple polynomial which applies across all irradiance levels. Our new correction factor was tested against a ¹⁴C-based productivity dataset from shallow stations in Narragansett Bay, RI and an O₂-based dataset from shallow (1.1 m) lagoon mesocosms at the University of Rhode Island. Results showed that our polynomials accurately correct BZ_pI_o-predicted rates of production in shallow water columns. Application of our correction factor to a series of shallow water productivity datasets from the literature together with theoretical calculations show how significant the shallow water correction can be, especially in very shallow water columns with low turbidity.     

Study of in-vehicle route guidance systems for improvement of right-side drivers in the Japanese traffic system

A country can adopt one of two standards for traffic flow — cars may travel on the left or right side of the road. When drivers who are accustomed to driving on the right side of the road drive on the left side, and vice versa, the mental workload is likely increased due to the driver’s unfamiliarity with a new language, the position of the driver’s seat, different driving directions, and other factors that differ from those of their home country. One method of doing this is to make sure that the in-vehicle route guidance information (RGI) is not overly complicated — thereby assisting drivers in improving their safety. Consequently, the aim of this study was to facilitate mobility and improve safety for natural right-side drivers driving temporarily in left-side traffic. In this study, driver behavior and workload — given various types of RGI — were evaluated in a driving simulator with a variety of prescribable test conditions. This research was composed of two experiments. In the first, various types of in-vehicle route guidance systems were tested and evaluated in terms of their characteristics and associated driver behaviors (while driving). In the second experiment, systemic factors and effectiveness were evaluated by two combined systems, arrow and map-type information, based on the results of the first experiment. In light of both experiments, the various types of route guidance systems were discussed in terms of their results. A navigation system was proposed to alleviate some of the secondary tasks such as route selection.     

Spatial fisheries ecology: Recent progress and future prospects

We review recent progresses made in the study of fish distribution and survival over space — i.e., fisheries spatial ecology. This is achieved by first surveying the most common statistical approaches and relative challenges associated with the analysis of fisheries spatial data, loosely grouped in geostatistical and regression approaches. Then we review a selected number of case-studies implementing the discussed techniques. We conclude by proposing new areas of statistical and ecological research to further our understanding of how fish distribute and survive in space. This review serves a dual purpose by emphasizing the scientific importance of studying spatial interactions to better understand the temporal dynamics of fish abundance, and by promoting the development of new analytical and ecological approaches for the analysis of spatial data. Through our survey we cover different statistical techniques, marine ecosystems and life stages. This analytical, geographic and ontogenetic variety is also purposely selected to highlight the importance of comparative and multidisciplinary studies across diverging ecological disciplines, ecosystems and life stages. Besides having a general ecological relevance this review also bears a more applied significance, owing to the increasing need for protecting renewable marine resources along with their primary habitat.     

Torque characteristics analysis for optimal design of a copper-layered eddy current brake system

An enhanced parametric model for a copper-layered eddy current electric machine (retarder) is introduced in this paper. The modeled torque characteristics of the copper-layered electromagnetic retarders are based on the results from a detailed electromagnetic finite element analysis (FEA) of these eddy current machines. The model uses a parameterized double-exponential function to model the steady state speed-torque characteristics of the retarder. The parameters are adjusted for optimal braking performance in conjunction with predicted speed-torque characteristics of a copper-layered retarder. A full vehicle model, along with the proposed retarder speed-torque model has been used to simulate a series braking events. The simulation results show that the peaks of the retarder speed-torque curves must be designed to occur within a specific range of speeds for optimal braking performance.     

Topological analysis of powertrains for refuse-collecting vehicles based on real routes–Part I: Hybrid hydraulic powertrain

In this two-part paper, a topological analysis of powertrains for refuse-collecting vehicles (RCVs) based on the simulation of different architectures (internal combustion engine, hybrid electric, and hybrid hydraulic) on real routes is proposed. In this first part, a characterization of a standard route is performed, analyzing the average power consumption and the most frequent working points of an internal combustion engine (ICE) in real routes. This information is used to define alternative powertrain architectures. A hybrid hydraulic powertrain architecture is proposed and modelled. The proposed powertrain model is executed using two different control algorithms, with and without predictive strategies, with data obtained from real routes. A calculation engine (an algorithm which runs the vehicle models on real routes), is presented and used for simulations. This calculation engine has been specifically designed to analyze if the different alternative powertrain delivers the same performance of the original ICE. Finally, the overall performance of the different architectures and control strategies are summarized into a fuel and energy consumption table, which will be used in the second part of this paper to compare with the different architectures based on hybrid electric powertrain. The overall performance of the different architectures indicates that the use of a hybrid hydraulic powertrain with simple control laws can reduce the fuel consumption up to a 14 %.     

Optimal scheduling of the flexray static segment based on two-dimensional bin-packing algorithm

FlexRay is a reliable and hard real-time in-vehicle communication protocol that is strongly promoted by car manufacturers as the de facto standard in the automotive domain. The protocol offers both a time-triggered and an eventtriggered architecture. This paper focuses on the optimal scheduling of the time-triggered component of FlexRay known as the static (ST) segment using a two-dimensional bin-packing technique. To maximize the bandwidth utilization in the ST segment, a fast heuristic as well as an efficient integer linear programming approach are proposed. Our methods directly schedule signals into slots including frame packing, according to signal-based data scheduling and the slot/ cycle multiplexing mechanisms presented by the latest version of the FlexRay protocol. The benefits of our proposed methods are demonstrated by extensive experiments on synthetic and an automotive X-by-wire system case study. An additional test case is examined to emphasize the superior performance of the proposed approach relative to that of existing optimal scheduling approaches.