电气化公路技术研究

交通是能源消纳的重要领域，其对社会能源结构的调整和节能减排具有重要的影响和带动作用。在陆路交通方面，轨道交通和小型客运车辆的电气化发展方向相对清晰，而公路货运尚无明确的技术路线。为充分利用清洁能源，减少化石能源在交通领域中的使用，发展并推广电气化公路技术，对重载卡车的蓄电池、燃料电池、混合动力3种电气化方案进行对比分析，结合卡车负载的特点，对不同电气化方案进行评估。研究融合新能源发电及并网、混合动力技术、智能驾驶技术的电气化公路技术，从车辆动力技术、供电线路、受电弓与计费、新能源并网、编组智能驾驶运行5个方面对电气化公路方案进行介绍，可以实现公路货运系统的绿色、安全、高效运行。以10公里线路电气化为例，进行规划和成本估算，构建单车和区域（或路段）电气化的运营成本计算模型，基于燃油消耗和阻力分析2种方法进行计算。对车辆购置及改装、基础设施建设、可再生能源发电、系统环保效益等4个方面进行技术分析与成本测算。从供能技术变革、商业模式和推广路线3个角度对电气化公路技术的未来推广进行论证展望。研究结果表明：电气化公路技术的应用与规模化能够带来巨大的经济与环境收益，其中的混合动力方案与架空线输电方案为面对未来可能的储能技术变革与无线输电普及打下重要的基础，提供了拓展空间，也是重载货车实现智能驾驶的重要步骤；与燃油驱动相比，电驱动百公里成本减少96元，单一重卡年运营成本减少18.8万元，百公里污染物（如：碳氧化物、氮氧化物等）均减少50%以上。     

论公路隧道提质升级

与欧洲和日本等发达国家相比，我国公路隧道工程品质亟待提升。从国家战略、行业需求和人民需要3个维度分析开展公路隧道提质升级行动的时代背景，从8个方面解读其深刻内涵，并详尽阐述公路隧道提质升级的总体思路和技术要点。强调应关注的重点区域是隧道洞口、洞身和路面，最需要补齐的短板是通风、照明、消防、逃生疏散、交通安全设施以及智能化管养平台，并提出“设施是基础、安全是根本、养护是关键、管控是核心、预案是保障、品质是追求”，建议大力推进公路隧道建设、管理、养护、运营、安全、服务协调发展，打造安全、绿色、智能的公路隧道，助力我国由“公路隧道大国”迈向“公路隧道强国”。     

城市交通能耗区的识别及等级划分方法研究

随着社会经济的发展，机动车保有量急剧增长，城市化过程中交通拥堵问题日趋严重，交通能源消耗加剧。为了降低由此带来的损失，需要及时探明路网中交通效率低、能耗高的区域，并采取有效的交通管理措施。通过研究交通状态与能耗的关系，进行相应的交通参数分析，建立能耗区识别及等级划分模型，计算得到3个等级能耗区的界定阈值分别为0．411和0．678。     

Real-time traffic state estimation in urban corridors from heterogeneous data

In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.     

Multi-step prediction of experienced travel times using agent-based modeling

This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60 min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.     

车辆侧翻的运动力学分析及预防措施

车辆转弯发生侧翻是最常见、最严重的交通事故之一。对车辆转弯的4种运动状态进行了力学分析，对“车轮下的奇迹”进行科学的压力测算，提出了防止车辆侧翻的具体措施。     

人的失误模型在船舶溢油事故应急中的应用分析

船舶交通事故问题的预测一直是业内研究人员十分重视的研究课题。分别采用回归预测法、时间序列预测法、灰色理论预测法和贝叶斯统计预测法等不同方法,结合国内某港引航站近十多年来船舶引航总量和事故的实际情况,进行了比较分析和对未来情况予以预测。着重就贝叶斯方法在港口船舶引航风险预测中的运用进行了探讨。结论证明贝叶斯估计方法得到的结果具有良好的预测效果。     

CFC复频电导法与TEM瞬变电磁法在某隧道中的应用对比

CFC复频电导法与TEM瞬变电磁法是我国目前较为先进的隧道超前探水技术。以CFC与TEM在我国某铁路隧道中的应用为例,简述CFC与TEM的方法原理,并结合开挖实际情况进行对比。试验对比表明,CFC探水技术抗干扰能力更强,探水预报结果更为准确,特别是在电磁环境复杂的隧道。