视讯会议系统“一键点名”功能硏究

以铁路视讯会议网工程建设标准和视讯会议系统网管的标准配置文件为基础,通过反复试验和结果分析,确定广铁集团视讯会议操作繁琐的原因,并提出相应的优化方案,提高了广铁集团视讯会议系统会议控制的效率。     

隧道爆炸冲击波的危害及控制措施

目前山岭隧道施工基本以钻爆法为主,爆破过程中产生的冲击波会对隧道内的人员及机械设备安全产生较大影响,造成重大安全事故和财产损失。本文主要介绍了冲击波在隧道内传播会形成超压,且随着传播距离增加超压峰值逐渐衰减到大气压范围内;基于超压准则评估了冲击波对人体、隧道内设施及周边建筑物的危害程度;通过在隧道内安装简易的冲击波缓冲装置及加强监测、设置安全警戒线等控制措施,减弱了爆破冲击波的危害,从而达到安全快速施工的目的。     

Highway voting system: Embracing a possible paradigm shift in traffic data acquisition

The integration of internet and mobile phones has opened the door to a new wave of utilizing private vehicles as probes not only for performance evaluation but for traffic control as well, gradually replacing the role of traffic surveillance systems as the dominant source of traffic data. To prepare for such a paradigm shift, one needs to overcome some key institutional barriers, in particular, the privacy issue. A Highway Voting System (HVS) is proposed to address this issue in which drivers provide link- and/or path-based vehicle data to the traffic management system in the form of “votes” in order to receive favorable service from traffic control. The proposed HVS offers a platform that links data from individual vehicles directly with traffic control. In the system, traffic control responds to voting vehicles in a way similar to the current system responding to prioritized vehicles and providing the requested services accordingly. We show in the paper that the proposed “voting” system can effectively resolve the privacy issue which often hampers traffic engineers from getting detailed data from drivers. Strategies to entice drivers into “voting” so as to increase the market penetration level under all traffic conditions are discussed. Though the focus of the paper is on addressing the institutional issues associated with data acquisition from individual vehicles, other research topics associated with the proposed system are identified. Two examples are given to demonstrate the impact of the proposed system on algorithm development and traffic control.     

基于深度强化学习的智能船舶航迹跟踪控制

[目的]智能船舶的航迹跟踪控制问题往往面临着控制环境复杂、控制器稳定性不高以及大量的算法计算等问题。为实现对航迹跟踪的精准控制,提出一种引入深度强化学习技术的航向控制器。[方法]首先,结合视线(LOS)算法制导,以船舶的操纵特性和控制要求为基础,将航迹跟踪问题建模成马尔可夫决策过程,设计其状态空间、动作空间、奖励函数;然后,使用深度确定性策略梯度(DDPG)算法作为控制器的实现,采用离线学习方法对控制器进行训练;最后,将训练完成的控制器与BP-PID控制器进行对比研究,分析控制效果。[结果]仿真结果表明,设计的深度强化学习控制器可以从训练学习过程中快速收敛达到控制要求,训练后的网络与BP-PID控制器相比跟踪迅速,具有偏航误差小、舵角变化频率小等优点。[结论]研究成果可为智能船舶航迹跟踪控制提供参考。     

Achieving transport modal split targets at intermodal freight hubs using a model predictive approach

The increase of international freight commerce is creating pressure on the existing transport network. Cooperation between the different transport parties (e.g., terminal managers, forwarders and transport providers) is required to increase the network throughput using the same infrastructure. The intermodal hubs are locations where cargo is stored and can switch transport modality while approaching the final destination. Decisions regarding cargo assignment are based on cargo properties. Cargo properties can be fixed (e.g., destination, volume, weight) or time varying (remaining time until due time or goods expiration date). The intermodal hub manager, with access to certain cargo information, can promote cooperation with and among different transport providers that pick up and deliver cargo at the hub. In this paper, cargo evolution at intermodal hubs is modeled based on a mass balance, taking into account hub cargo inflows and outflows, plus an update of the remaining time until cargo due time. Using this model, written in a state-space representation, we propose a model predictive approach to address the Modal Split Aware – Cargo Assignment Problem (MSA–CAP). The MSA–CAP concerns the cargo assignment to the available transport capacity such that the final destination can be reached on time while taking into consideration the transport modality used. The model predictive approach can anticipate cargo peaks at the hub and assigns cargo in advance, following a push of cargo towards the final destination approach. Through the addition of a modal split constraint it is possible to guide the daily cargo assignment to achieve a transport modal split target over a defined period of time. Numerical experiments illustrate the validity of these statements.     

Dynamic traffic metering in urban street networks: Formulation and solution algorithm

Traffic metering offers great potential to reduce congestion and enhance network performance in oversaturated urban street networks. This paper presents an optimization program for dynamic traffic metering in urban street networks based on the Cell Transmission Model (CTM). We have formulated the problem as a Mixed-Integer Linear Program (MILP) capable of metering traffic at network gates with given signal timing parameters at signalized intersections. Due to the complexities of the MILP model, we have developed a novel and efficient solution approach that solves the problem by converting the MILP to a linear program and several CTM simulation runs. The solution algorithm is applied to two case studies under different conditions. The proposed solution technique finds solutions that have a maximum gap of 1% of the true optimal solution and guarantee the maximum throughput by keeping some vehicles at network gates and only allowing enough vehicles to enter the network to prevent gridlocks. This is confirmed by comparing the case studies with and without traffic metering. The results in an adapted real-world case study network show that traffic metering can increase network throughput by 4.9–38.9% and enhance network performance.     

Vegetation cover at right of way locations

This research evaluated the status of vegetation cover at right of way locations. Site factors that contributed to low and high ground cover along roadsides and medians were identified. Twenty-nine roadside and median study sites incorporated variability in soil type, elevation, vegetation establishment and cover, seed mixture, slope, aspect, time since planting, and climate. Vegetation cover was measured, and species distribution was identified. Slopes, aspects of the sloping face, and elevations were recorded. Soil samples were tested for nutrients, minerals, texture, and pH. Approximately 50% of the test sites met the 70% cover criteria. Locations of the worst cover (<50%) had soils with high soluble salt content (0.36–1.54 mmhos/cm) or low organic matter values (<1.7%). Vegetation cover was dominated by tall fescue (Festuca arundinacea) and crownvetch (Coronilla varia L.), two species that were included in the current seeding mixture and are considered invasive. To further promote revegetation success and persistence, both maintenance and site specific seed mixtures are needed.     

船舶电缆自动化敷设系统设计与实现

在船舶电缆敷设过程中,很难借助有效的工装提高劳动效率,低空间的高强度作业存在严重的安全风险。以船舶电缆自动化敷设系统为分析对象,介绍系统组成和系统接口,采用比例积分微分(Proportion Integration Differentiation,PID)算法计算系统行程,通过PROFINET总线完成数据传输,以人机界面(Human Machine Interface,HMI)实现系统性能要求。在风电安装平台上的实际运用表明,该系统可解决造船行业劳动力成本高和安全风险大的问题。     

基于模糊综合评价法的城市综合管廊结构健康评价方法研究

为解决城市综合管廊结构健康状况评估结果无法量化和指导运维的问题，通过分析模糊综合评价理论在交通隧道结构健康评价方法研究中的应用，依照类比思想，利用该理论建立城市综合管廊结构健康状况评价体系。首先，依据有关养护规定和调研结果，基于不同需求分别建立管廊结构的本体完好状况和本体结构状况评价指标体系； 其次，以交通隧道和综合管廊养护经验为基础，划分各指标的分级判定标准； 然后，采用层次分析法，计算评价指标的权重分配； 最后，采用柯西分布型隶属函数和矩阵型隶属函数确定各指标的隶属度，建立一级和二级模糊综合评价模型，赋予评价向量中各评语相应分值，将评价向量单值化，判定管廊结构健康状况。采用所提出的评价方法应用于实际工程，所得评价结果与经验评判得到的结果相同。     

A real-time adaptive signal control in a connected vehicle environment

The state of the practice traffic signal control strategies mainly rely on infrastructure based vehicle detector data as the input for the control logic. The infrastructure based detectors are generally point detectors which cannot directly provide measurement of vehicle location and speed. With the advances in wireless communication technology, vehicles are able to communicate with each other and with the infrastructure in the emerging connected vehicle system. Data collected from connected vehicles provides a much more complete picture of the traffic states near an intersection and can be utilized for signal control. This paper presents a real-time adaptive signal phase allocation algorithm using connected vehicle data. The proposed algorithm optimizes the phase sequence and duration by solving a two-level optimization problem. Two objective functions are considered: minimization of total vehicle delay and minimization of queue length. Due to the low penetration rate of the connected vehicles, an algorithm that estimates the states of unequipped vehicle based on connected vehicle data is developed to construct a complete arrival table for the phase allocation algorithm. A real-world intersection is modeled in VISSIM to validate the algorithms. Results with a variety of connected vehicle market penetration rates and demand levels are compared to well-tuned fully actuated control. In general, the proposed control algorithm outperforms actuated control by reducing total delay by as much as 16.33% in a high penetration rate case and similar delay in a low penetration rate case. Different objective functions result in different behaviors of signal timing. The minimization of total vehicle delay usually generates lower total vehicle delay, while minimization of queue length serves all phases in a more balanced way.