清管器皮碗在不同过盈量下的接触应力分析

在清管过程中,清管器的皮碗与管道之间过盈配合,不同过盈量时两者间的接触应力不同。采用有限元方法分析4种典型皮碗过盈量分别为1%~10%时的最大接触应力、接触长度以及接触应力的分布规律。结果表明:直板皮碗的最大接触应力随过盈量增大呈近似线性增加趋势,其接触长度取决于厚度;锥形皮碗和碟形皮碗,最大接触应力在较大过盈量时增加缓慢,但接触长度明显增加;圆形皮碗最大接触应力小,但接触长度大。     

营运性驾驶员适应性检测推广方案研究

结合营运性驾驶员管理的现状及驾驶适应性检测的重要性,本文提出将营运性驾驶员适应性检测方案推广应用于营运性驾驶员的准入机制、继续教育培训、退出机制等安全管理过程中,为营运性驾驶员的安全管理提供了有效的保障措施。     

Some remarks on Wilson's gravity model and a slight generalization of it

The aim of this note is to establish some connections between Wilson's gravity model, Jaynes' principle of maximum entropy, Kullback's divergence, Watanabe's measure of connection, the minimum information principle of Snickars and Weibull and Guiasu's principle of minimum interdependence as a special form of Kullback's minimum divergence. A slight generalization of Wilson's gravity model is proposed.     

钻铣除垢工具在大牛地气田气井油管中的应用

为了解决大牛地气田气井管柱结垢问题,提高气井生产能力,通过对传统机械除垢技术研究分析,采用机械钻铣除垢技术,并且根据大牛地气田气井管柱结构特点,设计了井内油管除垢工具和钻铣液配方。通过与水力喷射除垢技术在现场的试验应用对比,该技术可以有效除去井内油管管柱的结垢物,使气井产量分别提高33.3%、50.0%,而水力喷射技术增产能力提高5.9%。     

A model‐based demand‐balancing control for dynamically divided multiple urban subnetworks

Traffic control is an effective and efficient method for the problem of traffic congestion. It is necessary to design a high‐level controller to regulate the network traffic demands, because traffic congestion is not only caused by the improper management of the traffic network but also to a great extent caused by excessive network traffic demands. Therefore, we design a demand‐balance model predictive controller based on the macroscopic fundamental diagram‐based multi‐subnetwork model, which can optimize the network traffic mobility and the network traffic throughput by regulating the input traffic flows of the subnetworks. Because the transferring traffic flows among subnetworks are indirectly controlled and coordinated by the demand‐balance model predictive controller, the subnetwork division can variate dynamically according to real traffic states, and a global optimality can be achieved for the entire traffic network. The simulation results show the effectiveness of the proposed controller in improving the network traffic throughput. Copyright © 2016 John Wiley & Sons, Ltd.     

四川省绿色交通运输发展"十三五"规划调研

本文根据国家及交通部相关政策法规确定调研指导思想,结合四川省具体情况确定调研内容及方式,对四川省交通运输能源消耗及碳排放现状、主要问题及原因有了充分的认识,同时对四川省各地市州在十三五期间规划的绿色交通项目的投资金额、节能量、降碳量有了总体的掌握,为制定《四川省交通运输节能减排"十三五"发展规划》提供了重要依据和指导思想。     

西安市停车现状研究分析与思考

停车管理是静态交通管理中一项非常重要的工作,处理好城市中心区的停车问题,对缓解道路交通拥挤,减少交通事故,提高道路通行能力等方面都有极其重要的意义。文章结合西安市停车现状,对停车管理中存在的问题进行了深入分析,并提出了相应的改善措施及建议。     

A note on balancing procedures for trip distribution estimation

It is shown that the commonly used balancing procedure in trip distribution estimation is a simplified Newton method. One small numerical example is given.     

Selected node-pair analysis in dial's assignment algorithm

An algorithm is proposed to calculate the matrix of trips which use a particular link in a road network or alternatively pass through a particular set of nodes given the route-splitting assumptions inherent in the Dial assignment algorithm.     

Regulating transport’s environmental impacts in a deregulating world

In recent years, a growing awareness of the environmental impacts of transport has played a major part in the shift towards policies to manage the demand for travel. As a result, a substantial increase in the role of public transport has been identified as necessary in any strategy towards more environmentally sustainable transport patterns. At the same time there has been a quite separate process of deregulation and the withdrawal of the state from the transport market. These two trends appear to represent potentially contradictory processes. This article draws upon two major studies that explore the relationship between increasing needs for environmental regulation and the privatisation of bus and rail services. It is shown that, as currently organised in Britain, the development of bus and rail services are inadequately linked to strategic environmental policymaking and, rather than being part of the solution to transport’s environmental impacts, there is a real danger that these ‘green’ methods of transport could slide into simply being part of the problem itself. It is concluded that privatisation and deregulation does not mean the end of the need for policy mechanisms, but they do mean that policy has to be implemented in a very different way.     

On the convergence of iterative methods for the distribution balancing problem

A general distribution balancing problem, specified by the given outflows and inflows and the factorial form of its solution, is formulated. Solution uniqueness and boundedness is discussed—primarily in graph theoretical terms. An entropy maximisation problem, subject to general linear constraints, is transformed into an unconstrained optimisation problem by application of standard duality theory, and a relevant general convergence theorem for iterative solution methods is given. The optimum solution in a special case is identified with the flow solution. When expressed in flow variables, the dual objective has a unique and bounded optimum solution and is an appropriate unifying concept for measuring the rate of convergence of different solution methods. By regarding the balancing procedure as an iterative optimisation method, a new and simple proof of its convergence is given, together with some asymptotic results, which are also compared with those of Newton's method. It is pointed out that there are two different forms of Newton's method, according to the choice of variables—untransformed or transformed— in the original distribution balancing problem. When Newton's method is applied to the whole system of equations simultaneously, the trajectory of iterates is observed to depend on this variable choice. For the transformed variables it is noticed that the convergence with the balancing procedure is quicker than with Newton's method applied to the outflow- and inflow- equations, alternately. To guarantee global convergence with Newton's method and to increase the rate a supplementary linear search routine is recommended.     

The origin of California’s zero emission vehicle mandate

The California Zero Emission Vehicle (ZEV) rule, adopted in 1990, is arguably one of the most daring and controversial air quality policies ever adopted. Some consider it a policy failure, while others credit it with launching a revolution in clean automotive technology. This paper is the first systematic empirical study of the policy process that resulted in the adoption of the ZEV mandate. We draw upon theoretical frameworks of the policy process, empirical data from public documents, and personal interviews with key stakeholders, to explain how a confluence of technology, policy, and political circumstances created a window of opportunity that led to the adoption of this policy. We expect the conclusions of our analysis to be useful to other policy debates that involve technological innovation.     

Further aspects of rectangular routeing in Smeed's City

Two types of routeing on a rectangular system of roads are examined in a simple circular city where homes and workplaces are uniformly and independently distributed. Expressions for the number of vehicles crossing a given line segment, the average distance travelled by a commuter and the total number of crossings of vehicle paths in the city are derived. Comparisons are made with other routeing systems in terms of average distance travelled, expected number of crossings and average travel time.     

A note on using Davidson's function in equilibrium assignment

This paper describes the use of the Davidson congestion function in modelling network flows using equilibrium assignment. A modification to the function is given, which defines the function over all flows values, and consequently removes computational difficulties noted in earlier studies. The modification requires the inclusion of an additional model parameter, and the selection of a suitable value for this parameter is studied for two sets of data. The modified Davidson function is also compared to two alternative functions; a step-wise linear function and a quartic polynomial function, which have both been proposed as congestion functions. Comparisons are made between observed link volumes and the assigned volumes from these models. It is concluded that the modified Davidson function is useful for inclusion in an equilibrium assignment model, given its ability to reflect differences in network link type (e.g. capacity and speed) and environment through its parameters, the conceptual advantage of the function through its derivation from queueing theory, and the previous discovery of reliable methods for estimating its parameters. A value of about 0.8–0.9 is suggested for the parameter (μ, 0 < μ < 1) introduced in the modification.     

Coordinated online in-vehicle routing balancing user optimality and system optimality through information perturbation

The inconsistence between system optimality and user optimality represents one of the key difficulties on network traffic congestion control. The advanced connected vehicle systems, enabling smart vehicles to possess/exchange real-time information and conduct portable computation, provide new opportunities to address this challenge. Motivated by this view, this study proposes a coordinated online in-vehicle routing mechanism with intentional information provision perturbation (CRM-IP), which seeks to shape individual vehicles online routing decisions so that user optimality and system optimality are balanced, by exploiting bounded rationality of the users. The proposed CRM-IP is modeled as a pure strategy atomic routing game, and implemented by a sequentially updating distributed algorithm. The mathematical analysis is conducted to quantify the absolute gain of system optimality corresponding to the loss of user optimality resulting from a given level of the information perturbation in the worst case so that the efficiency of the information perturbation can be evaluated. Furthermore, numerical experiments conducted based on City of Sioux Falls network investigate the average effects of the CRM-IP on system optimality and user optimality under various network traffic conditions, comparing to the CRM developed by Du et al. (in press). The results indicate that the improvement of system optimality and the reduction of individual vehicles’ travel time from the CRM is more significant when the network traffic is under an mild congestion state, such as under the levels of service (LOS’s) C, D, and E, rather than under extremely sparse or congested states, such as under LOS’s A and B, or F. Moreover, higher level of information perturbation benefits system optimality more, but the marginal effect decreases after the perturbation reaching certain level, such as $\lambda =0.1$ in this case study. In addition, a portion of vehicles may sacrifice user optimality due to the information perturbation, but the extent of the sacrifice is not significant, even though it increases with the information perturbation level. Hence, a small information perturbation is recommended to achieve an efficient network traffic control through the CRM-IP. Overall, this study proposes the CRM-IP as an efficient routing mechanism, which has a great potential to guide the routing decisions of individual vehicles so that their collective behavior improve network performance in both system optimality and user optimality.     

Statistical estimation of the parameters of Daganzo's gap acceptance model

In a recent article in Transportation Research, Daganzo (1981) described a model of gap acceptance that permits the mean of the gap acceptance function to vary among drivers and permits the duration of the shortest acceptable gap for each driver to vary among gaps. The model contains several constant parameters whose values must be estimated statistically from observations of drivers' behavior. The results of numerical experiments reported by Daganzo (1981) suggested that the values of the parameters cannot be estimated by the method of maximum likelihood, which is the most obvious estimation technique, and Daganzo proposed using a sequential estimation method instead. The sequential method appeared to yield reasonable numerical results. In this paper, it is shown that subject to certain reasonable assumptions concerning the true parameter values and the probability distribution of gap durations, the maximum likelihood method does, in fact, yield consistent estimates of the parameters of Daganzo's model, whereas the sequential method does not. Hence, maximum likelihood is the better estimation method for this model.     

Manual vs. adaptive cruise control – Can driver’s expectation be matched?

The role of the driver in the longitudinal car following control task will change from operator to supervisor with most of manual control replaced by automation as adaptive cruise control (ACC) technologies become commonplace. The extent to which manual control can be replaced by ACC will be determined by many factors. An important issue is the compatibility between ACC performance and the driver’s expectations.This paper describes the results of a simulation study of the performance of ACC relative to driver expectation. Driver’s expectation is quantitatively defined as the expected deceleration rate for several time-to-collision (TTC) levels, and an absolute minimum TTC that drivers tried to avoid in all cases. A two-level ACC algorithm was used to simulate the performance of an ACC equipped vehicle in various scenarios, and the result was compared to the driver’s expectations. The investigation has focused on scenarios which ACC is able to manage technically, but where driver expectations might be breached.By systematically changing variables such as the parameters of the ACC algorithms, traffic scenarios and time-headway settings, a large number of situations have been tested. The results have revealed that whilst appropriate ACC settings can be found which will meet the driver’s expectations, the ACC settings that are most capable in a range of traffic conditions are not necessarily the most user-friendly. A discussion on the implications of the findings is also presented.     

Integrated airline planning: Robust update of scheduling and fleet balancing under demand uncertainty

The airline schedule planning problem is defined as the sequence of decisions that need to be made to obtain a fully operational flight schedule. Historically, the airline scheduling problem has been sequentially solved. However, there have already been many attempts in order to obtain airline schedules in an integrated way. But due to tractability issues it is nowadays impossible to determine a fully operative and optimal schedule with an integrated model which accounts for all the key airline related aspects such as competitive effects, stochastic demand figures and uncertain operating conditions. Airlines usually develop base schedules, which are obtained much time in advance to the day of operations and not accounting for all the related uncertainty. This paper proposes a mathematical model in order to update base schedules in terms of timetable and fleet assignments while considering stochastic demand figures and uncertain operating conditions, and where robust itineraries are introduced in order to ameliorate miss-connected passengers. The proposed model leads to a large-scale problem which is difficult to be solved. Therefore, a novel improved and accelerated Benders decomposition approach is proposed. The analytical work is supported with case studies involving the Spanish legacy airline, IBERIA. The presented approach shows that the number of miss-connected passengers may be reduced when robust planning is applied.     

Evaluating gravel transport sustainability: A case study of Taiwan’s northeast corridor

We use social-eco-efficient analysis in the form of SEEbalance to evaluate gravel transport sustainability for trucking and two kinds of intermodal transportation. Results show that switching from trucks to intermodal transportation can improve the sustainability of gravel transportation in the northeast corridor of Taiwan. Sensitivity analysis shows that rail combined with truck intermodal transportation has competitive advantage despite the terminal’s location factor.     

A multi-objective optimization approach to balancing economic efficiency and equity in accessibility to multi-use paths

Improving public health through active transpiration investments has increasingly become a new research focus in transportation planning. This study is to propose a multi-objective optimization modeling framework, through an optimal allocation of active transportation investments, to maximize the total accessibility while minimizing the total differences in accessibility over a city. Accessibility to multi-use paths is calculated for Fresno, California that measures the total length of multi-use paths a resident could reach with a 30-min cycling ride. Then, a geographically weighted regression (GWR) model is used to capture the local relationships between accessibility outcome and previous transportation investments. The marginal-effect analysis for the GWR results indicates economically efficient, inefficient, and indifferent locations for further investments. This study is one of the few to incorporate such a GWR model into a multi-objective optimization modeling framework to improve accessibility to multi-use paths and address inequality issues in transportation. Solving the multi-objective optimization model provides decision-makers a new insight into the making of an economically efficient and socially equal active transportation plan to improve public health.