Public perceptions of toll roads: A survey of the Texas perspective

Like many U.S. states, Texas is experiencing shortfalls in transportation funding, along with growing needs for system improvements. Accordingly, the Texas Department of Transportation (TxDOT) is turning to tolling to bridge the funding gap. To assist planning efforts and effectively direct public information, a telephone survey of 2111 Texans was undertaken statewide to gauge public opinion on tolling issues.Some issues yielded a definite consensus among survey respondents. Over 70% agreed on attending to existing roads first, keeping existing roads toll-free, reducing tolls after construction, using revenues within the same region, charging higher tolls for trucks, not imposing SOV tolls, and maintaining the same toll rates during rush-hours. Some opinions varied by region. Austinites were more likely to support additional transportation spending, while residents of the Lower Rio Grande Valley were less supportive of raising the gas tax and of public/private partnerships. Opinions also varied with survey design. In eight places in the survey, optional text was provided or question order was modified to intentionally influence response. For two questions, support for tolling was decreased when information on personal transportation costs and higher gas tax rates in other states was offered. Ordered probit and binomial and multinomial logit models were estimated to assess the impact of demographic and travel characteristics on respondent opinions, and results for key issues are presented here. Opinions across demographic groups also were examined. The survey was successful at measuring opinions on several key tolling issues and should prove a useful tool for transportation planners and policymakers.     

Scientific requirements for an abyssal benthic laboratory

For over thirty years man has studied “outer space” and installed satellites which watch the surface of the Earth. The great depths of the world ocean are, however, practically unknown and there is an urgent need to put abyssal benthic laboratories into “inner space” in order to study basic phenomena of interest to marine science and climatology as well as man's impact on the oceans.In view of the numerous problems related to global change, as a first step emphasis should first be on the role of the oceans and their inherent processes, which are the focus of such international programmes as the World Ocean Circulation Experiment (WOCE) and the Joint Global Ocean Flux Study (JGOFS). Multi-disciplinary registration of key events at selected key sites investigating the variability in time and space are of the utmost importance. The same methods and techniques must be used for the study of human impacts on the deep oceans caused by mining of metalliferous resources and by waste disposal as well as in basic studies. However, the investigation of the inner space of our planet has certain requirements. As long-term and large-scale investigations become more and more important, development of automized systems, largely independent from research vessels will be required. This will demand high capacities of energy for all technical functions as well as high storage capacities for data and samples. As a consequence the needs for two different—although overlapping—functional approaches are defined for future deep-sea deployments.(A) A system for long-term registration of the natural variability and long-term monitoring of human impacts: (B) A system for short-term observations and short-time experimentations. This report summarizes their technological demands. The envisioned interdisciplinary technology should deliver information on physical, biological and geochemical processes and their variabilities in the deep oceans. The prospected systems need to have the ability for real time video observation, data transfer and experimental manipulation, as well as sensing and sampling facilities with large storage capacities for long-term deployments.Prospective costs of the described multipurpose abyssal benthic laboratory will presumably exceed the funds for deep-sea research of a single country. A joint European effort could solve this problem and help to manifest a leading role for European marine science in international deep-sea and global change research.     

Modelling dual carriageway lane changing using neural networks

Neural networks offer a potential alternative method of modelling driver behaviour within road traffic systems. This paper explores the application of neural networks to modelling the lane-changing decisions of drivers on dual carriageways. Two approaches are considered. The first, preliminary approach uses a prediction type of neural network with a single hidden layer and the back propagation learning algorithm to model the behaviour of an individual driver. A series of consecutive time-scan traffic patterns, which describe the driver's environment and changes over time as the selected vehicle travels along a link, are input to the neural network, which then predicts the new lane and position of the vehicle. Training data are collected from a human subject using an interactive driving simulation. The trained neural network successfully exhibited the rudiments of driving behaviour in terms of lane and speed changes. A major disadvantage of this approach was the difficulty in recording real-life data, which are required to train the neural network, for individual drivers. The second approach concentrates specifically on lane changing and makes use of a learning vector quantization classification type of neural network. Input to the neural network still consists primarily of time-scan traffic patterns, but the format is changed to facilitate the possibility of data acquisition using image processing. The neural network output classifies the input data by determining the new lane for the vehicle concerned. Performance in both testing and training was very good for data generated by the rule-based driver-decision model of a microscopic simulation. Performance in testing was less satisfactory for data taken directly from a road and highlighted the need for extensive data sets for successful training.     

变压器保护方法的发展

介绍了用于电力变压器保护的数字继电器的发展及其应用技术和原理,简述了变压器保护的传统方法,重点介绍了人工神经网络(ANN)和模糊逻辑概念等最新技术及其涉及的技术成果.     

Inertial waves in the Ibiza channel

Currentmeter data taken in the Ibiza Channel show the almost permanent presence of near-inertial motions below the mixed layer. They correspond to downwards progressing waves with a vertical group velocity of some m/day. The presence of the Balearic Front sensibly affects the propagation of these inertial waves. Although situations exist in which the passage of atmospheric fronts along the Channel is clearly the generating force of these near-inertial motions we find others in which the energy density in mid-depths is higher than in any other depth. These last situations are closely related to the arrival to the Channel of some of the different water masses which flow around there. A clear correspondence between the presence of relatively strong inertial waves and a noticeable vertical shear of the subinertial flow, evidenced by an averaged Richardson number, is also observed. In some circumstances, the vertical shear of the whole flow (inertial plus subinertial) is higher than the stability limit, that is, Ri < 0.25, favoring the braking of the internal waves. This could be a plausible cause of their decay and a reason to explain why they do not penetrate further than certain depths.     

Optimal Preview Control of Rear Suspension Using Nonlinear Neural Networks

The performance of neural networks to be used for identification and optimal control of nonlinear vehicle suspensions is analyzed. It is shown that neuro-vehicle models can be efficiently trained to identify the dynamical characteristics of actual vehicle suspensions. After trained, this neuro-vehicle is used to train both front and rear suspension neuro-controllers under a nonlinear rear preview control scheme. To do that, a neuro-observer is trained to identify the inverse dynamics of the front suspension so that front road disturbances can be identified and used to improve the response of the rear suspension. The performance of the vehicle with neuro-control and with LQ control are compared.     

Contributors to this issue

Contributors to this issue     

重新审视砂再生

过去10年,美国环境保护机构已经对铸造工厂施加了更大的压力,以迫使他们减少废弃物的排出. 在金属铸造业,废砂占到整个铸造业废弃物总量的近70%.每生产1 t铸件,大约平均要用363kg砂,这就意味美国铸造工业每年大概要产出700～800万t废砂.     

Intraunion conflict: the changing marine engineer

In this paper we describe the shift in membership of the Marine Engineers' Beneficial Association (MEBA), the major us marine engneer labour union, and the problems asssociated with this change. The problematic nature of this change is examined by describing the changing membership of MEBA: demonstrating a relationship between the occupational socialzation of members prior to entering the union and their behaviour as members; and by explaining how the actions of MEBA led to the creation of the problem and the policy it implemented to alleviate the sitution. Data are gathared from participant observation, interviews with union officials and marine engineers. Implications for the formation of sentient groups are discussed.     

Experimental validation of a mathematical model of a reed-valve reciprocating air compressor from an automotive-braking system

Mathematical simulation is the process of designing a model of a real system and then conducting experiments with the simulation to understand the system’s behavior. Mathematical simulation is widely used for investigating and designing compressors, and with a minimal number of simplifying assumptions, mathematical models can be used in conjunction with modern computing tools to solve complicated problems. A considerable amount of previous research has focused on the mathematical modeling of reciprocating air compressors used in automotive braking. The aim of the present work was to experimentally validate the mathematical model for such compressors. We present a simplified and effective mathematical model for estimating compressor performance, and this model can easily be executed using personal computers. Parameters such as compressor speed, discharge pressure and clearance volume were evaluated in terms of their effect on the thermodynamic behavior of compressors. The model can predict cylinder pressure, cylinder volume, cylinder temperature, valve lift and resultant torque at different crank angles; it can also predict the free air delivered and the indicated power of the compressor. Therefore, the model has been validated using experimental results.