CAN总线在雪铁龙C5轿车中的应用及检修

雪铁龙C5轿车是法国雪铁龙公司的新一代主流产品。介绍了应用在雪铁龙C5轿车上的CAN数据总线的特点、组成与结构，CAN数据总线的传输原理与过程，以及BSI智能服务器(网关)的组成与功能。另外，介绍了CAN网络的检修。     

交互劳务代数分配法实际操作研究

本文研究辅助生产部门交互劳务代数分配法的实际操作问题,解决了该方法的辅助生产费用分配表的设计、联立方程组的建立和帐务处理等问题。笔者提出的实际应用程序可操作性强。     

Towards a generic benchmarking platform for origin–destination flows estimation/updating algorithms: Design,demonstration and validation

Estimation/updating of Origin–Destination (OD) flows and other traffic state parameters is a classical, widely adopted procedure in transport engineering, both in off-line and in on-line contexts. Notwithstanding numerous approaches proposed in the literature, there is still room for considerable improvements, also leveraging the unprecedented opportunity offered by information and communication technologies and big data. A key issue relates to the unobservability of OD flows in real networks – except from closed highway systems – thus leading to inherent difficulties in measuring performance of OD flows estimation/updating methods and algorithms. Starting from these premises, the paper proposes a common evaluation and benchmarking framework, providing a synthetic test bed, which enables implementation and comparison of OD estimation/updating algorithms and methodologies under “standardized” conditions. The framework, implemented in a platform available to interested parties upon request, has been flexibly designed and allows comparing a variety of approaches under various settings and conditions. Specifically, the structure and the key features of the framework are presented, along with a detailed experimental design for the application of different dynamic OD flow estimation algorithms. By way of example, applications to both off-line/planning and on-line algorithms are presented, together with a demonstration of the extensibility of the presented framework to accommodate additional data sources.     

The best of times and the worst of times: A new best–worst measure of attitudes toward public transport experiences

Attitudes play an important role in determining individual transit behaviour and the measurement of attitudes is relied on by public transit authorities’ world over. Given their role in behaviour and policy making, the accurate measurement of attitudes is of critical importance. Traditional satisfaction scales are prone to bias and on their own they are only a partial measure of attitudes. Given that satisfaction scales have been used to assist with large scale transport infrastructure investment decisions, to aid policy makers examining reactions to alternative policy changes and reform, and to measure the success of new initiatives, deriving robust satisfaction scales should be of critical importance. This paper introduces a dual version of best–worst scaling as an alternative measure of satisfaction. Best–worst scaling is free of the biases inherent in traditional response scales and is ideal for handling the comparative evaluation of large amount of attributes, particularly those which are inherently qualitative. The paper makes a further innovative contribution by proposing a model structure for the joint estimation of satisfaction and importance. Our model shows a better delineation between the attributes used to measure attitudes towards bus use and a more detailed understanding of the relationship between importance and satisfaction; enabling transport operators to better understand what counts most and assess their performance.     

Optimization models for differentiating quality of service levels in probabilistic network capacity design problems

This paper develops various chance-constrained models for optimizing the probabilistic network design problem (PNDP), where we differentiate the quality of service (QoS) and measure the related network performance under uncertain demand. The upper level problem of PNDP designs continuous/discrete link capacities shared by multi-commodity flows, and the lower level problem differentiates the corresponding QoS for demand satisfaction, to prioritize customers and/or commodities. We consider PNDP variants that have either fixed flows (formulated at the upper level) or recourse flows (at the lower level) according to different applications. We transform each probabilistic model into a mixed-integer program, and derive polynomial-time algorithms for special cases with single-row chance constraints. The paper formulates benchmark stochastic programming models by either enforcing to meet all demand or penalizing unmet demand via a linear penalty function. We compare different models and approaches by testing randomly generated network instances and an instance built on the Sioux–Falls network. Numerical results demonstrate the computational efficacy of the solution approaches and derive managerial insights.     

The passenger vessel services act and America's cruise tourism industry

The Passenger Vessel Services Act (PVSA) of 1886, a cabotage law, attempts to shield U.S. maritime shipping from foreign competition. It also applies to the U.S. cruise ship industry. The PVSA requires foreign cruise ships that carry passengers between U.S. ports to also stop at foreign ports. Norwegian Cruise Line America (NCLA), which operates one U.S. flagged cruise ship in Hawaii, wants the U.S. Customs and Border Protection to require foreign cruise ships offering Hawaii itineraries from the U.S. west coast to spend more time in foreign ports. We analyze the merits of NCLA's proposal. We argue that rather than making the PVSA even more protectionist, the law should be repealed.     

Application of genetic algorithms for joint optimization of signal setting parameters and dynamic traffic assignment for the real network data

This paper presents the joint optimization of signal setting parameters and dynamic user equilibrium (DUE) traffic assignment for the congested urban road network. The simulation-based approach is employed to obtain the DUE condition for the case of multiple-origin multiple-destination traffic flows. The dynamic traffic assignment simulation program (DTASP), developed in C language is used to assign the traffic dynamically on the road network, whereas method of successive averages (MSA) is modified and used to arrive at the DUE condition. The artificial intelligence technique of genetic algorithms (GAs) is applied to obtain the optimal signal setting parameters and path flow distribution factor for DUE condition. The methodology developed in such a way that joint optimization of signal setting parameters with DUE is obtained. The proposed method is applied to the real network data of Fort Area of Mumbai city comprising of 17 nodes and 56 unidirectional links with 72 Origin–Destination pairs, where all the 17 nodes are signalized intersections. The traffic flow condition for the optimized signal setting parameters is considerably improved compared to the existing signal settings. The results prove that the GA is an effective technique to solve the joint optimization problem for the real network data.     

谈服务区“后浇带”施工

详细论述了高速公路服务区综合楼"后浇带"的施工方法,对"后浇带"浇注时间的确定、"后浇带"支撑与拆除方法及成品保护、安全措施提出了详细要求和理论依据,对"后浇带"施工有一定指导意义.     

Intermodal and international freight network modeling

The authors describe the development and application of a single, integrated digital representation of a multimodal and transcontinental freight transportation network. The network was constructed to support the simulation of some five million origin to destination freight shipments reported as part of the 1997 United States Commodity Flow Survey. The paper focuses on the routing of the tens of thousands of intermodal freight movements reported in this survey. Routings involve different combinations of truck, rail and water transportation. Geographic information systems (GIS) technology was invaluable in the cost-effective construction and maintenance of this network and in the subsequent validation of mode sequences and route selections. However, computationally efficient routing of intermodal freight shipments was found to be most efficiently accomplished outside the GIS. Selection of appropriate intermodal routes required procedures for linking freight origins and destinations to the transportation network, procedures for modeling intermodal terminal transfers and inter-carrier interlining practices, and a procedure for generating multimodal impedance functions to reflect the relative costs of alternative, survey reported mode sequences.     

Efficient multiple model particle filtering for joint traffic state estimation and incident detection

This article proposes an efficient multiple model particle filter (EMMPF) to solve the problems of traffic state estimation and incident detection, which requires significantly less computation time compared to existing multiple model nonlinear filters. To incorporate the on ramps and off ramps on the highway, junction solvers for a traffic flow model with incident dynamics are developed. The effectiveness of the proposed EMMPF is assessed using a benchmark hybrid state estimation problem, and using synthetic traffic data generated by a micro-simulation software. Then, the traffic estimation framework is implemented using field data collected on Interstate 880 in California. The results show the EMMPF is capable of estimating the traffic state and detecting incidents and requires an order of magnitude less computation time compared to existing algorithms, especially when the hybrid system has a large number of rare models.