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.     

Conditional modelling of tanker market risk using route specific freight rates

This paper provides statistical evidence in support of the view, widely held in the tanker industry, that there are systematic differences in the degree of risk involved in investing in tankers of different sizes, and in operating tankers in spot and time charter markets. The industry view, broadly supported by the results of this paper, is that larger vessels are 'risker' assets than smaller vessels, and operating vessels in the time-charter market is less risky than employing them on a spot basis. The results are obtained by using a method derived from the financial economics literature, which models both the conditional mean and variance of a variable, known as GARCH modelling. Only one other paper has applied this method to the tanker market, and these results provide confirmatory support of those findings.     

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.     

Computer Vision and Highway Automation

A survey is given on the development of machine vision for road vehicle guidance. Through early work in real-time simulation with real hardware in the loop at UBM, and through the EUREKA-project 'Prometheus' from 1987 to 1994 following the 100 th anniversary of road vehicle developments since 1886, Europe has pioneered the field. Since first fully autonomous testdrives in 1986, and first participation in public traffic in 1992, considerable progress has been achieved. With continuous growth in computing power of microprocessors at a rate of about one order of magnitude every four to five years, sufficient performance levels for dynamic machine vision will be available within one or two decades. The principles of dynamic vision as developed at UBM and performance levels achieved are discussed.     

Identification of potential sites for deep-ocean waste isolation with a geographic site-selection model

Identification of optimal sites for the isolation of waste on the abyssal seafloor was performed with two approaches: by the traditional method of map overlays of relevant attributes, and by a specially developed, automated Site-Selection Model (SSM). Five initial, Surrogate Sites, identified with the map-overlay approach, were then compared with the more rigorously produced scores from the SSM. The SSM, a process for optimization of site locations, accepts subjective, expert-based judgments and transforms them into a quantitative, reproducible, and documented product. The SSM is adaptable to any siting scenario. Forty-one factors relevant to the isolation scenario, including 21 weightable factors having a total of 123 scorable categories, have been entered into the SSM. Factors are grouped under project definition, unique environments, anthropogenic, geologic, biologic, weather, oceanographic and distance criteria. The factor scores are linked to a georeferenced database array of all factors, corresponding to 1°×1° latitude–longitude squares. The SSM includes a total of 2241 one-degree squares within 1000 n.m. of the U.S. coasts, including the western North Atlantic, the Gulf of Mexico, and the eastern North Pacific. Under a carefully weighted and scored scenario of isolation, the most favorable sites identified with the SSM are on the Hatteras and Nares Abyssal Plains in the Atlantic. High-scoring sites are also located in the Pacific abyssal hills province between the Murray and Molokai Fracture Zones. Acceptable 1° squares in the Gulf of Mexico are few and of lower quality, with the optimum location on the northern Sigsbee Abyssal Plain. Two of the five Surrogate Site locations, on the Hatteras and Sigsbee Abyssal Plains, correspond to the best SSM sites in each ocean area. Two Pacific and a second Atlantic Surrogate Site are located in low-scoring regions or excluded by the SSM. Site-selection results from the SSM, although robust, are an initial attempt to quantify the site-selection process. The SSM database exposes a significant lack of high-quality information for many areally mappable attributes on the abyssal seafloor, particularly bottom-current speed and measures of biologic productivity and flux. Terminologies and classifications of some measures, such as sediment types, suffer from parochialism and vary by ocean. Considerable research is needed even for a broad understanding of the environmental measures required to make sound societal decisions about use of the abyssal seafloor for disposal or other purposes.     

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.     

Management of coastal eutrophication: Integration of field data, ecosystem-scale simulations and screening models

A hybrid approach for eutrophication assessment in estuarine and coastal ecosystems is presented. The ASSETS screening model (http://www.eutro.org) classifies eutrophication status into five classes: High (better), Good, Moderate, Poor and Bad (worse). This model was applied to a dataset from a shallow coastal barrier island system in southwest Europe (Ria Formosa), with a resulting score of Good. A detailed dynamic model was developed for this ecosystem, and the outputs were used to drive the screening model. Four scenarios were run on the research model: pristine, standard (simulates present loading), half and double the current nutrient loading. The Ria Formosa has a short water residence time and eutrophication symptoms are not apparent in the water column. However, benthic symptoms are expressed as excessive macroalgal growth and strong dissolved oxygen fluctuations in the tide pools. The standard simulation results showed an ASSETS grade identical to the field data application. The application of the screening model to the other scenario outputs showed the responsiveness of ASSETS to changes in pressure, state and response, scoring a grade of High under pristine conditions, Good for half the standard scenario and Moderate for double the present loadings. The use of this hybrid approach allows managers to test the outcome of measures against a set of well-defined metrics for the evaluation of state. It additionally provides a way of testing and improving the pressure component of ASSETS. Sensitivity analysis revealed that sub-sampling the output of the research model at a monthly scale, typical for the acquisition of field data, may significantly affect the outcome of the screening model, by overlooking extreme events such as occasional night-time anoxia in tide pools.