Storage space allocation in container terminals

Container terminals are essential intermodal interfaces in the global transportation network. Efficient container handling at terminals is important in reducing transportation costs and keeping shipping schedules. In this paper, we study the storage space allocation problem in the storage yards of terminals. This problem is related to all the resources in terminal operations, including quay cranes, yard cranes, storage space, and internal trucks. We solve the problem using a rolling-horizon approach. For each planning horizon, the problem is decomposed into two levels and each level is formulated as a mathematical programming model. At the first level, the total number of containers to be placed in each storage block in each time period of the planning horizon is set to balance two types of workloads among blocks. The second level determines the number of containers associated with each vessel that constitutes the total number of containers in each block in each period, in order to minimize the total distance to transport the containers between their storage blocks and the vessel berthing locations. Numerical runs show that with short computation time the method significantly reduces the workload imbalance in the yard, avoiding possible bottlenecks in terminal operations.     

Speed variation during peak and off-peak hours on urban arterials in Shanghai

Increased speed variation on urban arterials is associated with reductions in both operational performance and safety. Traffic flow, mean speed, traffic control parameters and geometric design features are known to affect speed variation. An exploratory study of the relationships among these variables could provide a foundation for improving the operational and safety performance of urban arterials, however, such a study has been hampered by problems in measuring speeds. The measurement of speed has traditionally been accomplished using spot speed collection methods such as radar, laser and loop detectors. These methods can cover only limited locations, and consequently are not able to capture speed distributions along an entire network, or even throughout any single road segment. In Shanghai, it is possible to acquire the speed distribution of any roadway segment, over any period of interest, by capturing data from Shanghai’s 50,000+ taxis equipped with Global Positional Systems (GPS). These data, hereafter called Floating Car Data, were used to calculate mean speed and speed variation on 234 road segments from eight urban arterials in downtown Shanghai. Hierarchical models with random variables were developed to account for spatial correlations among segments within each arterial and heterogeneities among arterials. Considering that traffic demand changes throughout the day, AM peak, Noon off-peak, and PM peak hours were studied separately. Results showed that increases in number of lanes and number of access points, the presence of bus stops and increases in mean speed were all associated with increased speed variation, and that increases in traffic volume and traffic signal green times were associated with reduced speed variation. These findings can be used by engineers to minimize speed differences during the road network planning stage and continuing through the traffic management phase.     

Adapt-Traf: An adaptive multiagent road traffic management system based on hybrid ant-hierarchical fuzzy model

Usually, road networks are characterized by their great dynamics including different entities in interactions. This leads to more complex road traffic management. This paper proposes an adaptive multiagent system based on the ant colony behavior and the hierarchical fuzzy model. This system allows adjusting efficiently the road traffic according to the real-time changes in road networks by the integration of an adaptive vehicle route guidance system. The proposed system is implemented and simulated under a multiagent platform in order to discuss the improvement of the global road traffic quality in terms of time, fluidity and adaptivity.     

30m装配式预应力混凝土连续T梁施工简介

介绍了30m装配式预应力混凝土连续T梁的预制、安装以及体系转换施工工艺。     

A multiscale material-structure-hydroelasticity coupled analytical model for floating sandwich structures with hierarchical cores

A novel material-structure-hydroelasticity coupling analytical model is proposed for marine structures, which is utilized for the calculation and optimization of a very large floating sandwich structure (VLFSS) with a hierarchical ultrahigh-performance concrete (UHPC) core in this study. For the coupling material and structure analysis, three-dimensional representative volume element and self-consistent methods are developed to reveal the physical relations between the UHPC core's macroscale mechanical properties (e.g., modulus and density) and mesoscale hierarchical characteristics (e.g., aggregate and porosity) and to obtain the corresponding parameterized formulas. For the coupling material-structure-hydroelasticity analysis, a sixth-order dynamical equation for the potential flow model of the VLFSS, in which the hierarchical core's parameters are introduced through the material-structure coupling formulas, is developed. The hydroelasticity equations containing multiscale parameters are solved, and the mechanical responses are calculated. Using this coupled multiscale method, the shear force in the representative VLFSS is optimized for a smaller amplitude, which relies on the interactivity of the hierarchical structural parameters and wave conditions. These results demonstrate the potential of the multiscale coupling methodology to achieve the physically significant optimization of a floating composite structure in ocean engineering.     

高速铁路牵引计算层次约束方法

为了实现高速铁路牵引计算过程的连续性和自动化,研究并提出层次约束方法.根据高速列车具有连续控制能力的技术特点,给出以限速约束为主线、辅以操纵约束的层次约束方法计算步骤.按照当前限速段的出口速度必须满足下一限速段限速、当前限速段的入口状态应是前一限速段的出口状态的要求,通过建立入口状态反馈机制实现限速约束,解决了牵引计算的连续性问题;通过标准操纵曲线的运用实现了操纵约束,解决了牵引计算结果的实施性问题.以京沪高速铁路牵引计算为例验证了层次约束方法的实用性.     

城市道路建设项目后评价中过程评价的指标与方法研究

对城市道路建设项目中过程评价的指标体系和评价方法进行了探讨,并根据城市道路交通建设项目后评价的特点,提出了采用层次分析的方法进行项目的过程评价。     

自动紧急制动系统控制策略仿真验证

为了在危险情况时辅助驾驶员实现纵向避撞或减小碰撞造成的伤害,文章提出了一种考虑实际制动过程与驾驶员制动行为的分级制动控制策略。通过试验得到相关参数,根据新车评价标准的AEB测试工况与评价指标,搭建测试场景并评价新车AEB功能。仿真结果表明,AEB控制策略在所有工况下都能达到新车评价规程中AEB功能的标准。提出的分级制动控制策略具有一定的参考价值。仿真模型可以方便地更改参数以适用于不同车辆,可作为新车评价AEB功能的仿真工具,减小试验成本,具有实用价值。     

Dynamics of heterogeneity in urban networks: aggregated traffic modeling and hierarchical control

Real traffic data and simulation analysis reveal that for some urban networks a well-defined Macroscopic Fundamental Diagram (MFD) exists, which provides a unimodal and low-scatter relationship between the network vehicle density and outflow. Recent studies demonstrate that link density heterogeneity plays a significant role in the shape and scatter level of MFD and can cause hysteresis loops that influence the network performance. Evidently, a more homogeneous network in terms of link density can result in higher network outflow, which implies a network performance improvement. In this article, we introduce two aggregated models, region- and subregion-based MFDs, to study the dynamics of heterogeneity and how they can affect the accuracy scatter and hysteresis of a multi-subregion MFD model. We also introduce a hierarchical perimeter flow control problem by integrating the MFD heterogeneous modeling. The perimeter flow controllers operate on the border between urban regions, and manipulate the percentages of flows that transfer between the regions such that the network delay is minimized and the distribution of congestion is more homogeneous. The first level of the hierarchical control problem can be solved by a model predictive control approach, where the prediction model is the aggregated parsimonious region-based MFD and the plant (reality) is formulated by the subregion-based MFDs, which is a more detailed model. At the lower level, a feedback controller of the hierarchical structure, tries to maximize the outflow of critical regions, by increasing their homogeneity. With inputs that can be observed with existing monitoring techniques and without the need for detailed traffic state information, the proposed framework succeeds to increase network flows and decrease the hysteresis loop of the MFD. Comparison with existing perimeter controllers without considering the more advanced heterogeneity modeling of MFD highlights the importance of such approach for traffic modeling and control.     

The role of alternative fuel vehicles: Using behavioral and sensor data to model hierarchies in travel

Greater adoption and use of alternative fuel vehicles (AFVs) can be environmentally beneficial and reduce dependence on gasoline. The use of AFVs vis-à-vis conventional gasoline vehicles is not well understood, especially when it comes to travel choices and short-term driving decisions. Using data that contains a sufficiently large number of early AFV adopters (who have overcome obstacles to adoption), this study explores differences in use of AFVs and conventional gasoline vehicles (and hybrid vehicles). The study analyzes large-scale behavioral data integrated with sensor data from global positioning system devices, representing advances in large-scale data analytics. Specifically, it makes sense of data containing 54,043,889 s of speed observations, and 65,652 trips made by 2908 drivers in 5 regions of California. The study answers important research questions about AFV use patterns (e.g., trip frequency and daily vehicle miles traveled) and driving practices. Driving volatility, as one measure of driving practice, is used as a key metric in this study to capture acceleration, and vehicular jerk decisions that exceed certain thresholds during a trip. The results show that AFVs cannot be viewed as monolithic; there are important differences within AFV use, i.e., between plug-in hybrids, battery electric, or compressed natural gas vehicles. Multi-level models are particularly appropriate for analysis, given that the data are nested, i.e., multiple trips are made by different drivers who reside in various regions. Using such models, the study also found that driving volatility varies significantly between trips, driver groups, and regions in California. Some alternative fuel vehicles are associated with calmer driving compared with conventional vehicles. The implications of the results for safety, informed consumer choices and large-scale data analytics are discussed.