基于交通大数据的移动模式分析综述

交通大数据可为揭示交通主体显性出行行为背后的深层规律（即移动模式）提供重要基础。精确掌握大数据驱动下交通主体的移动模式，可为需求预测、客流组织、土地利用、事件管理等应用提供理论依据。交通大数据主体繁多、时空多态、关联性复杂的特性迫使小数据时代下的移动模式分析方法转型和升级，但仍可能遇到移动模式一致性表达难、异常类型检测难、复杂关联性表达难、时空多态性建模难、一体可视化分析难等普遍问题。针对这些问题，利用科学知识图谱，对2010~2020年期间3 747篇文献的热点关键词分布、发表趋势分布、出版刊物分布等特点进行归纳总结，结合常见的移动模式分析数据集，系统综述现有研究在移动模式常态分析、非常态分析、关联分析、预测分析和可视化分析方向上的阶段性进展。其中，移动模式常态分析综述了个体活动特性分析、出行类别划分、特定群体分析等应用的研究进展。移动模式非常态分析综述了基于模板匹配和数据驱动的非常态事件检测方法的发展脉络。移动模式关联分析综述了面向不同数据源的关联特性检测方法的发展近况。移动模式预测分析综述了基于数理统计和数据驱动的交通属性预测方法的发展状况。移动模式可视化分析综述了用户交互设计、移动模式宏观可视化、微观可视化和整体可视化的发展近况。最后，系统总结各个分支方向面临的主要问题与挑战，并从数据整合、模型创新、机制变革等角度提炼移动模式分析研究的未来发展趋势，期望为后续研究采用新理论技术开展移动模式分析提供参考。     

A discounted recursive logit model for dynamic gridlock network analysis

Emerging sensing technologies such as probe vehicles equipped with Global Positioning System (GPS) devices on board provide us real-time vehicle trajectories. They are helpful for the understanding of the cases that are significant but difficult to observe because of the infrequency, such as gridlock networks. On the premise of this type of emerging technology, this paper propose a sequential route choice model that describes route choice behavior, both in ordinary networks, where drivers acquire spatial knowledge of networks through their experiences, and in extraordinary networks, which are situations that drivers rarely experience, and applicable to real-time traffic simulations. In extraordinary networks, drivers do not have any experience or appropriate information. In such a context, drivers have little spatial knowledge of networks and choose routes based on dynamic decision making, which is sequential and somewhat forward-looking. In order to model these decision-making dynamics, we propose a discounted recursive logit model, which is a sequential route choice model with the discount factor of expected future utility. Through illustrative examples, we show that the discount factor reflects drivers’ decision-making dynamics, and myopic decisions can confound the network congestion level. We also estimate the parameters of the proposed model using a probe taxis’ trajectory data collected on March 4, 2011 and on March 11, 2011, when the Great East Japan Earthquake occurred in the Tokyo Metropolitan area. The results show that the discount factor has a lower value in gridlock networks than in ordinary networks.     

Visitor Preferences for Public Beach Amenities and Beach Restoration in South Florida

Coastal erosion threatens many sandy beaches and the ecological, economic, social and cultural amenities they provide. The problem is especially chronic in South Florida. A frequent solution for beach restoration involves sand replacement, or nourishment, but is temporary, expensive, and has usually been funded by governmental sources. However, as such agencies reduce their share and require more local funding, beach nourishment must rely on other funding sources, including beach recreationists. Our study characterized three South Florida beaches and probed visitor willingness-to-pay for beach nourishment. We found that even beaches within close proximity attract different user types. Users are amenable to higher fees if they lead to greater resource protection.     

手机数据在交通调查和交通规划中的应用

手机作为一种理想的交通探测器,为居民出行信息分析提供了很好的技术选择。将手机数据映射至交通分析单元,并经信息预处理、匹配分析、交通模型分析处理、数据去噪、扩样等一系列海量数据运算处理,最终可获得居民出行特征数据。利用长期历史手机话单数据,可分析常住人口和就业人口分布、通勤出行特征、大区间OD、特定区域出行特征、流动人口出行特征等。手机信令数据能够较完整地识别手机用户的出行轨迹,可进一步应用于分析城市人口时空动态分布、特定区域客流集散、查核线断面或关键通道客流、轨道交通客流特征、出行时耗、出行距离、出行强度、道路交通状态等。根据天津手机话单数据应用案例及上海手机信令数据应用案例,验证了技术可行性。     

数据存储和GPS定位在冷藏机组控制器中的应用

本文研究了一种基于ATMEGA644PA-AU单片机的具有数据存储和GPS定位功能的冷藏机组控制器,其将冷藏运输车辆在运行过程中冷藏箱体内温度、冷藏制冷机组运行时各参数、GPS定位信息以逗号分隔文档的形式存储于USB闪存盘中,用以实现冷藏机组运行时的全过程参数的存储与查询,为冷藏机组的维修、运输货物的保存、品质的查询提供详实、可靠数据。     

Exploiting floating car data for time-dependent Origin–Destination matrices estimation

The study evaluates the added value generated by estimating dynamic demand matrices by information gathered from Floating Car Data (FCD).

Firstly, adopting a large dataset of FCD collected in Rome, Italy, during May 2010, all the monitored trips on a specific district of the city (Eur district) have been collected and analysed in terms of (i) spatial and temporal distribution; (ii) actual route choices and travel times. The data analysis showed that demand data from FCD are usually not suitable to retrieve directly demand matrices, due to a strong dependence of this information from the penetration rate of the monitoring device. Instead, origin–destination travel times and route choice probabilities from FCD are a much more reliable and powerful information with respect to FCD origin–destination flows, since they represent the traffic conditions and behaviors that vehicles experiment along the path.

Thus, several synthetic experiments have been conducted adopting both travel times and route choice probabilities as additional information, with respect to standard link measurements, in the dynamic demand estimation problem. Results demonstrated the strength and robustness associated to these network based data, while link measurements alone are not able to define the real traffic pattern. Adopting both the information of origin–destination travel times and route choice probabilities during the demand estimation process, the spatial and temporal reliability of the estimated demand matrices consistently increases.     

基于多尺度方法的道路隧道温度场特征研究

隧道火灾往往会造成严重后果。为实现快速准确的火灾报警,以大连路隧道、青浦隧道、白茫雪山隧道正常运营及火灾试验工况下采集的大量正常运营工况温度数据和火灾工况温度数据为对象,使用多尺度分析方法,研究道路隧道火灾工况和正常运营工况不同尺寸下的温度场特征。结合隧道光纤光栅温度系统采集的数据,对隧道火源及其邻域的温度、温度梯度和温度二阶导数进行大量统计描述分析; 同时对火灾时隧道内温度场的波动特征进行论述。通过分析,得出隧道火灾时的温度场具有强烈波动特征,建议使用单位时间内温度的标准差、离散系数来表征隧道温度的波动程度;使用单位时间内温度一阶导数的标准差、离散系数（均值大于0.1）来表征温升的波动程度,并给出常规工况下单位内时间温度标准差的建议取值。最后,通过识别火源点及其邻域的温度波动特征可判断火灾是否发生。     

船舶营运大数据挖掘与应用思考

船舶营运大数据来源于航运信息平台和营运船舶监测,通过对这些海量数据的分析与挖掘,能发现很多有价值的信息与规律,可应用于多载况下船舶功率与航速评估、船舶能效设计指数(EEDI)实船验证方法的完善、MRV机制实施的技术支持;风浪对航速的影响研究;节能技术的节能效果评价;船舶进坞清污最佳时机分析;船舶设备运行的精细化管理等,对于促进造船和航运业的技术进步具有重要的意义。     

海面分布式传感器多信息融合技术

在海上军事指挥系统及其目标识别中,基于分布式的多传感器信息融合技术一直是海上作战体系中的重要研究课题。由于受海面环境噪声等因素影响,单个传感器对目标物数据的采集往往精度比较低甚至会出现误差。本文重点研究信息融合技术中的数据关联算法,提出一种联合概率数据关联算法,较好的克服了在海面噪声干扰及多径信道干扰条件下的多目标定位跟踪的精度。最后对算法进行实验仿真,通过分析得出此算法的有效性。     

一种嵌入式航海数据采集系统方案设计

本文首先研究了基于无线传感器组网的数据采集系统以及其中的技术逻辑,分析了航海雷达数据的特性。针对雷达数据的高频采样率,本文设计一种新的多通道组网方式来处理航海雷达回波的数据采集方案,并给出雷达数据的采集汇聚算法,该算法对舰队组网中的节点进行规划,通过相邻节点组成簇,来提高数据采集的实时性。最后基于此系统所采用的多通道组网方式以及汇聚算法设计了基于DSP的嵌入式仿真系统,验证了该多通道组网方式以及汇聚算法的有效性。