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.     

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.     

A new methodology for incident detection and characterization on surface streets

In this paper, a new methodology is presented for real-time detection and characterization of incidents on surface streets. The proposed automatic incident detection approach is capable of detecting incidents promptly as well as characterizing incidents in terms of time-varying lane-changing fractions and queue lengths in blocked lanes, lanes blocked due to incidents, and incident duration. The architecture of the proposed incident detection approach consists of three sequential procedures: (1) Symptom Identification for identification of incident symptoms, (2) Signal Processing for real-time prediction of incident-related lane traffic characteristics and (3) Pattern Recognition for incident recognition. Lane traffic counts and occupancy are the only two major types of input data, which can be readily collected from point detectors. The primary techniques utilized in this paper include: (1) a discrete-time, nonlinear, stochastic system with boundary constraints to predict real-time lane-changing fractions and queue lengths and (2) a pattern-recognition-based algorithm employing modified sequential probability ratio tests (MSPRT) to detect incidents. Off-line tests based on simulated as well as video-based real data were conducted to assess the performance of the proposed algorithm. The test results have indicated the feasibility of achieving real-time incident detection using the proposed methodology.     

Scheduling short-term marine transport of bulk products

A multinational company uses a personal computer to schedule a fleet of coastal tankers and barges transporting liquid bulk products among plants, distribution centres (tank farms), and industrial customers. A simple spreadsheet interface cloaks a sophisticated optimization-based decision support system and makes this system useable via a varity of natural languages. The dispatchers, whose native language is not English, and some of whom presumably speak no English at all, communicate via the spreadsheet, and view recommended schedules displayed in Gantt charts both internationally familiar tools. Inside the spreadsheet, a highly detailed simulation can generate every feasible alternate vessel employment schedule, and an integer linear set partitioning model selects one schedule for each vessel so that all loads and deliveries are completed at minimal cost while satisfying all operational requirements. The optimized fleet employment schedule is displyed graphically with hourly time resolution over a planning horizon of 2-3 weeks. Each vessel will customarily make several voyages and many port calls to load and unload products during this time.     

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.