Total cost analysis: An alternative to benefit-cost analysis in evaluating transportation alternatives

This paper explains the theory in support of total cost analysis (TCA) to compare transportation system alternatives. The full costs of each alternative are first aggregated, including travel time costs and monetizable environmental and social costs. Many costs which are considered on the benefits side of the equation in benefit-cost analysis (BCA) as "cost savings" are brought over to the costs side. Total cost differences among alternatives are then traded off against their estimated non-monetized benefits or impacts, just as a consumer trades off product quality against cost before deciding which product he or she will buy. One advantage of TCA over traditional BCA is that the concept of "total cost" is more easily understood by the public and by political decision-makers than BCA concepts such as "net present worth", "benefit-cost ratio" and "internal rate of return". A second advantage is that there is no suggestion that all "benefits" have been considered; decision-makers are free to use their own value judgements to trade off total cost against non-monetizable social, environmental and economic impacts, just as they trade off quality and convenience against cost when purchasing goods and services in their roles as consumers. The TCA approach is demonstrated in this paper through a case study of two systemwide alternatives for the Baltimore, MD urban area.     

高速公路"透层"及"下封层"的防水功能和施工技术

对黑色沥青路面早期破坏的原因进行了分析,介绍了"封层"、"下封层"所使用的材料及施工工艺,强调了现代智能型沥青洒布车的特点及其作用.指出使用智能型沥青洒布设备,重视"透层"、"下封层"材料及其洒布施工工艺是提高沥青路面修建质量的一个重要环节.     

交通综合信息平台建设研究

建立一个基于GIS-T的交通综合信息平台。它能够接受、存储和处理多源异构数据．能够为各种应用子系统和公众提供良好的信息服务。同时，对平台的框架设计、功能构成以及平台实现的关键技术进行说明和分析。     

智能压路机控制系统数据通信的实现

介绍了CAN总线及CANopen协议的技术特点,详细阐述了基于CAN总线技术的智能压路机控制系统数据通信的实现,使之达到了智能压路机的设计要求.     

机器人生产线在船舶智能制造中的应用研究

智能制造是“中国制造2025”的主攻方向。本文先浅谈了智能船厂，并结合国内首个智能船厂试点对智能船厂的初级发展建设等进行初步探索，主要对船舶智能制造机器人生产线应用进行梳理分析，如工艺流程及布置、生产模式改进、提质增效和人员减配等。     

船舶甲板智能抛丸机器人设计

为解决在船舶外场涂装阶段除锈和拉毛施工效率低、质量不稳定、环境污染严重等问题,设计一款用于船舶甲板的智能抛丸机器人。简介该型机器人系统组成,阐述其抛丸分系统、除尘分系统和越障辅助机构的硬件设计及其软件设计,并设计手动遥控和自主导引操作方式。实船测试结果表明,该型机器人可满足船舶甲板除锈清理的工作要求。     

基于信令数据的出行强度影响因素分析模型

为探究城市交通出行强度影响因素及不同因素的影响程度，本文从土地利用与交通基础设施建设两方面出发，分析包括土地利用混合指数，职住混合率熵指数，公共交通站点 500 m覆盖率，路网可达性等17个指标与出行强度的相关关系；基于相关系数和拟合优度分析，提取7个与出行强度强相关指标，基于所识别指标构建北京市中心城区出行强度多元回归模型.模型结果表明，职住混合率熵指数对出行强度的影响最为显著，公共交通站点覆盖率对出行强度的影响比道路网密度和可达性更为明显.此外，给出单一土地利用/交通基础设施指标对出行强度拟合结果的离群特征分析方法，用于评估不同区域基础设施供给与交通出行需求之间的平衡关系.     

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。     

The identification and empirical characterization of vehicular (Lagrangian) fundamental diagrams in multilane traffic flow

Traditional macroscopic traffic flow modeling framework adopts the spatial–temporal coordinate system to analyze traffic flow dynamics. With such modeling and analysis paradigm, complications arise for traffic flow data collected from mobile sensors such as probe vehicles equipped with mobile phones, Bluetooth, and Global Positioning System devices. The vehicle‐based measurement technologies call for new modeling thoughts that address the unique features of moving measurements and explore their full potential. In this paper, we look into the concept of vehicular fundamental diagram (VFD) and discuss its engineering implications. VFD corresponds to a conventional fundamental diagram (FD) in the kinematic wave (KW) theory that adopts space–time coordinates. Similar to the regular FD in the KW theory, VFD encapsulates all traffic flow dynamics. In this paper, to demonstrate the full potential of VFD in interpreting multilane traffic flow dynamics, we generalize the classical Edie's formula and propose a direct approach of reconstructing VFD from traffic measurements in the vehicular coordinates. A smoothing algorithm is proposed to effectively reduce the nonphysical fluctuation of traffic states calculated from multilane vehicle trajectories. As an example, we apply the proposed methodology to explore the next‐generation simulation datasets and identify the existence and forms of shock waves in different coordinate systems. Our findings provide empirical justifications and further insight for the Lagrangian traffic flow theory and models when applied in practice. Copyright © 2015 John Wiley & Sons, Ltd.     

面向智能车辆的现役道路设施行驶适应性研究综述

为了总结面向智能车辆的现役道路设施行驶适应性，即现役道路基础设施承载智能车辆行驶的适宜程度，阐述自主智能驾驶定义与驾驶自动化等级分类，在此基础上剖析不同等级间的人机功能差异，并分别从感知层、感知-决策层、决策-控制层探讨与道路设计要素相关联的人机功能差异，通过归纳总结智能车辆与道路几何要素、路面性能及其他道路要素(如道路标线)的相互作用机制研究，从道路工程角度及其他道路要素方面回顾该领域的研究现状，指出存在的问题和未来发展方向。研究结果表明：相比传统车辆，配置高等级自动驾驶系统的智能车辆对现役道路设施行驶适应性最高，主动安全系统次之，而驾驶辅助及有条件自动驾驶系统适应性不足。而目前研究主要问题包括：难以归纳、标定不同驾驶自动化等级间的人机功能差异及其对于道路设计参数的需求设计值；测试道路场景条件过于理想，考虑的驾驶自动化等级单一，试验规模和样本有限；道路几何、路面性能以及道路标志、标线等道路要素与智能车辆间的相互作用机制研究不足，缺乏与不同道路场景相匹配的智能车辆驾驶特征数据的获取手段。因此建议：重视并推动与道路设计要素相关联的关键人机功能差异指标信息共享；联合高保真且可交互的道路场景、高精度感知传感器物理模型、车辆动力学模型及微观交通流模型，利用测试场景自动化生成、极限工况场景搜寻与泛化等技术开展智能驾驶虚拟测试，突破现有研究的深度和广度；探索反映不同等级智能车辆的道路行驶适应性特征指标与评价标准，精准、有效地评估预测复杂道路场景及不利道路条件下的行驶适应性。