煤柱(Coal Log)在水力输送管道内的流动性状

煤柱水力输送管道（CoalLogPipeline）是目前正在美国进行研究和开发的一种最新型的管道输煤技术．本文就这种管道输煤技术的水力学原理，即压制成圆柱形的煤柱在管道中的流动性状进行分析讨论．这些流动性状包括管道煤柱流的区域划分，煤柱的起动速度和悬浮机理，以及沿管道的压力损失．通过分析导出的有关的水力学计算公式简单易行，可为煤柱水力输送管道的设计提供基本的设计参数．     

Spanning tree-based genetic algorithm for bicriteria transportation problem

In this paper, we present a new approach which is spanning tree-based genetic algorithm for bicriteria transportation problem. The transportation problem have the special data structure in solution characterized as a spanning tree. In encoding transportation problem, we introduce one of node encoding which is adopted as it is capable of equally and uniquely representing all possible basic solutions. The crossover and mutation was designed based on this encoding. And we designed the criterion that chromosome always feasibility converted to a transportation tree. In the evolutionary process, the mixed strategy and roulette wheel selection is used. Numerical experiments will be shown the effectiveness and efficiency of the proposed algorithm.     

8098单片机测速道口防护系统的研究

文中讨论了在我国众多的铁路与公路的平交道口设立新型测速道口防护系统的必要性，提出了８０９８单片机测速道口系统的构思及可行性，并且对系统的软件，硬件的主要组成单元进行了分析。     

Vehicle routing and scheduling with dynamic travel times

The field of dynamic vehicle routing and scheduling is growing at a fast pace nowadays, due to many potential applications in courier services, emergency services, truckload and less-than-truckload trucking, and many others. In this paper, a dynamic vehicle routing and scheduling problem with time windows is described where both real-time customer requests and dynamic travel times are considered. Different reactive dispatching strategies are defined and compared through the setting of a single “tolerance” parameter. The results show that some tolerance to deviations with the current planned solution usually leads to better solutions.     

基于Java 3D技术的虚拟车辆仿真系统

虚拟车辆仿真是智能交通研究中的重要课题,而运用Java3D技术构建该系统则是一个崭新的研究方向。该文详细地阐述了Java3D技术在虚拟车辆仿真系统中的运用,就具体的设计和所涉及的技术问题进行了系统、深入的分析,并提出新的解决办法。最后,对该领域的技术前景进行了展望。     

Bi-objective optimization of three echelon supply chain involving truck selection and loading using NSGA-II with heuristics algorithm

This paper models a three echelon supply chain distribution problem considering multiple time periods, multi-products and uncertain demands. To take the problem closer to reality we consider multiple truck types and focus on the truck selection and loading sub-problem. Truck selection is important because the quantity of goods to be transported varies regularly and also because different trucks have different hiring cost, mileage and speed. Truck loading is important when considering the optimal loading pattern of products having different shapes and sizes on trucks, which themselves have distinct loading capacities. The two objectives considered here are the cost and responsiveness of the supply chain. The distribution problem is solved using the non-dominated sorting genetic algorithm (NSGA-II). However, the genetic algorithms compromise the optimality of the sub-problems while optimizing the entire system. But the optimality of truck selection and loading sub-problem is non-compromisable in nature. Hence a heuristic algorithm is used innovatively along with the NSGA-II to produce much better solutions. To make our model more realistic, the distribution chain is modelled as a push–pull based supply chain having multiple time periods and using demand aggregation over time. Using a separate algorithm also gives the advantage of utilizing the difference in nature of the push and pull part of the supply chain by giving every individual truck different objectives. Real life like data is generated and the optimality gap between the heuristic and non-heuristic approach is calculated. A clear improvement in objectives can be seen while using the heuristic approach.     

Mapping commuter cycling risk in urban areas

Cycling is becoming an increasingly important transportation option for commuters. Cycling offers exercise opportunities and reduces the burden of motor vehicle travel on society. Mapping the risk of collision between cyclists and motor vehicles in urban areas is important to understanding safe cyclist route opportunities, making informed transportation planning decisions, and exploring patterns of injury epidemiology. To date, many geographic analyses and representations of cyclist risk have not taken the concept of exposure into account. Instead, risk is either expressed as a rate per capita, or as a count of events. Using data associated with the City of Hamilton, Canada, we illustrate a method for mapping commuter cyclist collision risk per distance travelled. This measure can be used to more realistically represent the underlying geography of cycling risk, and provide more geographically and empirically meaningful information to those interested in understanding how cycling safety varies over space.     

An analysis of activity scheduling behavior of airport travelers

A nested logit model is presented that can be used to predict the activity pattern of travelers inside an airport based on their socio-demographical characteristics (e.g. gender, age), group size, and travel related information (e.g. number of bags, airport size, and total available time). The availability of such a model enhances representation of the behavior dynamics when simulating airport pedestrian traffic. An internet-based revealed preference survey was used to collect data from persons that visit airports including both travelers and non-travelers. The survey focused on the agenda of subjects’ most recent airport trip, the frequency and attitude concerning certain types of activities they performed inside the airport, and the socio-demographic characteristics of each respondent. Three possible nested logit model structures are analyzed and one has been identified as a plausible and statistically acceptable nested structure. Also, the empirical results demonstrate the applicability of a nested logit model for use in identifying travelers’ activity patterns in an airport.     

Optimized load planning for motorail transportation

This paper studies a real-world problem arising in the area of motorail transportation. The considered problem deals with the loading of cars and motorcycles onto motorail wagons under realistic technical and legal constraints. The load planning problem, introduced as motorail transportation problem (MTP), occurs during the booking process and afterwards during the loading process at motorail terminals. Optimization based decision support is highly valuable due to the combinatorial nature of these problems. In practical applications, the fast generation of good solutions is essential. Previous model formulations in literature reveal considerable optimality gaps in real-world instances. Hence, we propose and evaluate two novel integer linear programming formulations of the MTP. The first formulation is a simplified reformulation of the original problem, uses less variables and provides a tighter LP relaxation. The second model is a column-generation formulation of the reformulated model which is solved using branch-and-price. Both novel model formulations are compared and evaluated on the basis of real-world data sets and considerably outperform previous approaches in terms of solution quality and speed.     

浅谈智能交通系统技术及发展

本文主要介绍了智能交通系统及其相关技术，分析了智能技术对交通系统的影响，最后对智能交通系统的现状及未来趋势进行了探讨。