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.     

Transportation agencies experiences with decision support systems for airport ground access planning

This article reports on a field investigation into the ways that transportation agencies use quantitative and qualitative information for making strategic decisions regarding airport ground access. The study analyzes the value of this information for planning airport ground access improvements at seven major international airport sites.The major finding of the research is that quantitative modeling for strategic decision support is very difficult, costly and time consuming. Modelers are confident that the models are accurate and reliable but executives generally lack confidence in the results. Transportation officials believe that the information supplied is flawed by a number of defects that minimize its value for strategic decision makers. The information defects described in this article provide an analysis of the structural difficulty of using quantitative modeling for transportation problems of strategic importance. To date, qualitative information is not frequently used, but some transportation agencies are considering its application to designing transportation services. Although this study is limited to airport ground access, the authors feel that this evidence, in conjunction with the evidence from other studies in the transportation area, dictates a need for wariness in the development of decision support systems for transportation planners. Developers of decision support systems for transportation planners must be aware of modeling costs and defects and consider how to improve the timeliness, relevance and credibility of information quantitative models provide transportation executives. Fundamentally it is important to recognize that decision makers tend, either singularly or in concert with other individuals or groups, to be the champions of a long-term vision for the community. When modeling produces inconsistent or wide ranging results that contradict their position, decision makers may not only discard modeling activities, but lose confidence in the models altogether. As a consequence, transportation planners are faced with the challenge of how to improve quantitative modeling. The most reliable and effective means for improvement is incorporation of qualitative techniques which provide greater understanding of customer perceptions and human behavior.     

Classification issues in the analysis of complex travel behavior

Researchers have devoted considerable effort to identifying homogeneous travel-behavior groups, each of which also has distinctive sociodemographic characteristics. Interest in these efforts has been fueled by both theoretical and applied concerns. From a theoretical perspective, if such behaviorally and sociodemographically homogeneous groups cari be identified, we would have an improved understanding of the determinants of travel. From an applied perspective, because spatial choice models assume behavioral homogeneity within each sociodemographically defined subgroup, one would like to be able to identify groups that are homogeneous with respect to both behavior and sociodemographics. Most previous efforts to define such groups have classified individuals on the basis of one-day travel records. In this paper we review these efforts, note the problems inherent in using one-day travel records for identifying homogeneous travel-behavior groups, and use standard grouping procedures to classify individuals on the basis of behavior observed over a longer time period (five weeks). Using multi-day travel data means that the travel measures employed in classifying individuals are different from and more complex than those used with one-day data. We identify five travel-behavior groups, each of which has distinctive socio-demographic characteristics. Considerable intra-group variability remains, however, even though the groups are classified on the basis of longer-term behavior. The paper concludes with an examination of the implications of day-to-day variability in individual travel for classification procedures.     

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.     

Improving the predictiveness of the quasi-d combustion model for spark ignition engines with flexible intake systems

Fast and predictive simulation tools are prerequisites for pursuing simulation based engine control development. A particularly attractive tradeoff between speed and fidelity is achieved with a co-simulation approach that marries a commercial gas dynamic code WAVE™ with an in-house quasi-dimensional combustion model. Gas dynamics are critical for predicting the effect of wave action in intake and exhaust systems, while the quasi-D turbulent flame entrainment model provides sensitivity to variations of composition and turbulence in the cylinder. This paper proposes a calibration procedure for such a tool that maximizes its range of validity and therefore achieves a fully predictive combustion model for the analysis of a high degree of freedom (HDOF) engines. Inclusion of a charge motion control device in the intake runner presented a particular challenge, since anything altering the flow upstream of the intake valve remains “invisible” to the zero-D turbulence model applied to the cylinder control volume. The solution is based on the use of turbulence multiplier and scheduling of its value. Consequently, proposed calibration procedure considers two scalar variables (dissipation constant C _β and turbulence multiplier C _M ), and the refinements of flame front area maps to capture details of the spark-plug design, i.e. the actual distance between the spark and the surface of the cylinder head. The procedure is demonstrated using an SI engine system with dual-independent cam phasing and charge motion control valves (CMCV) in the intake runner. A limited number of iterations led to convergence, thanks to a small number of adjustable constants. After calibrating constants at the reference operating point, the predictions are validated for a range of engine speeds, loads and residual fractions.     

伟大的希冀

<正>阿斯顿马丁期望全新Vantage能够成功,但它需要先争得几个不可小觑的竞争对手的同意,比如奥迪R8 V10 Plus、迈凯轮540C和保时捷911 Carrera 4 GTS终于,我必须要感叹一声,终于开上了阿斯顿马丁Vantage。之前无论是在北极圈冰面上工程车的测试还是葡萄牙盛大发布会上的体验都像是被别人刻意安排好的节目。不能否认,Vantage在柏油路面上确实快得惊人,在赛道上又可以随心漂移,但仅凭这两项很难让人对于     

严峻问题

今年关于太平洋航线有两个不确定因素,即美国进口量增长将会大大放缓,同时美国出口量会继续增加.因此,几乎所有其他的问题都是不确定的:进口量是否会增长还是会减少?     

严峻问题——经济、燃油或本、运力、码头运输工人联盟谈判产生了不确定性

今年关于太平洋航线有两个不确定因素，即美国进口量增长将会大大放缓，同时美国出口量会继续增加。因此，几乎所有其他的问题都是不确定的：进口量是否会增长还是会减少？航运公司是否会随着船只规模的增加，而为贸易业务分配更多运力，或者仅仅保持现有运力？他们是否能够成功增加运费以弥补成本的增长？发货人是否同意支付完全不固定的船舶燃油附加费？