Estimation of Sand Transportation Rate for Fixed and Semi-Fixed Dunes Using Meteorological Wind Data

Taibus County, Inner Mongolia, China, lies in a farming-pastoral ecotone, where severe wind erosion and various aeolian sand hazards are prevalent and fixed and semi-fixed sand dunes occur frequently. This study was conducted to investigate the relationships between sand transportation rate and wind speed for the fixed and semi-fixed sand dunes based on field measurements. The annual quantity of soil erosion by wind was estimated using meteorological wind data. The results indicated that the sand transportation rate in Taibus County in 2000 was 57.38 kg cm-1 year-1 for the semi-fixed dunes and 4.56 kg cm-1 year-1 for the fixed dunes. The total duration of erosive winds covered 12.5% of the time of the year, and spring posed the highest potential of sand transportation. Wind with low speed (≤ 17 m s-1) and high frequency plays a dominant role in sand transportation, while strong wind (≥ 17 m s-1) with low frequency significantly enhanced the sand transportation. Erosive wind speed, directions, and frequency were three crucial dynamic factors influencing sand hazards in the farming-pastoral ecotone. The dominant factors intensifying sand and dust storms in Taibus County might be related to the favorable wind condition in combination with the durable drought, which led to land desertification and vegetation degradation.

Security Model for Analyzing Data Privacy in Multipath Transport

In order to investigate the enhancement of data privacy by distributing data packets via multiple paths,this paper formulates a security model and analyzes the privacy problem in multipath scenarios leveraging information theoretic concept.Based on proposed model,a privacy function related to the path number is discussed.We heuristically recommend the optimal path number and analyze the tradeoff among the performance,resource consumption and privacy.For reducing the information leakage,the data schedule algorithms are also proposed.The analytical model can provide guidelines for the multipath protocol design.

Optimal estimation of zonal velocity and transport through Luzon Strait using variational data assimilation technique

A P-vector method was optimized using variational data assimilation technique, with which the vertical structures and seasonal variations of zonal velocities and transports were investigated. The results showed that westward and eastward flowes occur in the Luzon Strait in the same period in a year. However the net volume transport is westward. In the upper level (0m -500m),the westward flow exits in the middle and south of the Luzon Strait, and the eastward flow exits in the north. There are two centers of westward flow and one center of eastward flow. In the middle of the Luzon Strait, westward and eastward flowes appear alternately in vertical direction. The westward flow strengthens in winter and weakens in summer. The net volume transport is strong in winter (5.53 Sv) but weak in summer (0.29 Sv). Except in summer, the volume transport in the upper level accounts for more than half of the total volume transport (0m bottom). In summer, the net volume transport in the upper level is eastward (1.01 Sv), but westward underneath.

Big-Data Processing Techniques and Their Challenges in Transport Domain

This paper describes the fundamentals of cloud computing and current big-data key technologies. We categorize big-da- ta processing as batch-based, stream-based, graph-based, DAG-based, interactive-based, or visual-based according to the processing technique. We highlight the strengths and weaknesses of various big-data cloud processing techniques in order to help the big-data community select the appropri- ate processing technique. We also provide big data research challenges and future directions in aspect to transportation management systems.

Inversion of Evaporation and Water Vapor Transport Using HY-2 Multi-Sensor Data

HY-2 satellite is the first marine dynamic environment satellite of China.In this study,global evaporation and water vapor transport of the global sea surface are calculated on the basis of HY-2 multi-sensor data from April 1 to 30,2014.The algorithm of evaporation and water vapor transport is discussed in detail,and results are compared with other reanalysis data.The sea surface temperature of HY-2 is in good agreement with the ARGO buoy data.Two clusters are shown in the scatter plot of HY-2 and OAFlux evaporation due to the uneven global distribution of evaporation.To improve the calculation accuracy,we compared the different parameterization schemes and adopted the method of calibrating HY-2 precipitation data by SSM/I and Global Precipitation Climatology Project(GPCP)data.In calculating the water vapor transport,the adjustment scheme is proposed to match the balance of the water cycle for data in the low latitudes.

Analysis of the Relevance of Spatial Distribution Between Urban Parks and Transportation Infrastructure in Beijing Based on POI Data

In this paper,the relevance of spatial distribution between urban parks and transportation infrastructure in Beijing was studied grounded on POI data to guarantee the accuracy and scientificity.This paper focused on three aspects.Firstly,based on vector data of Beijing and POI data,the distribution of bus stations,subway stations,and parking lots as well as the road network density in the radiating region of each main entrance in urban parks were analyzed to assess traffic service ability in surrounding area of urban parks.Secondly,coupling relationship of spatial distribution between urban parks and transportation network in Beijing was analyzed using Kernel Density tools.Thirdly,Arc GIS was used to explore space pattern characteristics of large parks and association models between large parks and main transportation network,including two types of intersected and non-intersected and seven models.Finally,according to the comprehensive analysis of POI data,there was a contradictory relationship of interdependency and interaction between space pattern of urban parks and transportation infrastructure construction in Beijing,contributing to the scientific judgment of spatial characteristics of urban parks and transportation infrastructure as well as traffic accessibility and convenience.Quantified conclusions were thus obtained to explore coordinated development strategies for two systems of park green space and transportation network,thereby providing new ideas for the construction of harmonious and livable environment in Beijing.

The relation between ambulance transports due to heat stroke and air temperature using daily data in Okayama prefecture, Japan

The aim of this study was to investigate the link between ambulance transports due to heat stroke and air temperature by using daily data of ambulance transports in Okayama prefecture, Japan. Daily observations for ambulance transports due to heat stroke from July to September in 2010 in Okayama prefecture, Japan were obtained from Fire and Disaster Management Agency in Japan. Data of meteorological parameters in Okayama prefecture, Japan were also obtained from Japan Meteorological Agency. Effect of meteorological parameters on ambulance transports due to heat stroke was analyzed. A total of 1133 ambulance transports due to heat stroke were observed in from July to September of 2010 in Okayama prefecture, Japan. Ambulance transports due to heat stroke was significantly correlated with air temperature. In addition, number of subjects with ambulance transports due to heat stroke over 34°C in the highest air temperature was 21.2 ± 9.8 per day. Higher air temperature was closely associated with higher ambulance transports due to heat stroke by using daily data in Okayama, prefecture, Japan.

考虑载客状态的改进孤立森林浮动车异常数据检测算法

为提高浮动车数据中异常数据检测能力及不同载客状态下的模型检测分析能力,提出基于S-DTA-IIForest(Summation&Difference Third Order Average&Improvement-Isolation Forest)的浮动车数据异常检测算法。构建由相邻两项求和(S)、三阶求和平均差分(DTA)的二维度空间SDTA特征向量;提出差额累计更新和动态区分辨识的改进孤立森林IIForest算法,通过设置停止阈值参数,避免当出现新样本异常值分数大于停止阈值时,仅更新样本不更新孤立森林模型的问题,设计每个二叉树区分辨识度参数,区分辨识度位于停止区间时停止二叉树生长,提高算法收敛性能,以ROC(Receiver Operating Characteristic)曲线下面积AUC(Area Under ROC Cure)、F1-score为指标对模型精度进行对比分析,并以重庆市中心城区学府大道开展实例验证。结果表明:本文S-DTA-IIForest组合算法AUC、F1-score分别为86.63%、0.89,AUC较传统孤立森林IForest(Isolation Forest)提高32.4%,运行效率提高1.29%,具有收敛速度更快、精度更高的优势,载客条件下模型AUC、F1-score较未载客分别提高7.7%、10.8%,组合算法对载客数据有更高的检测精度,且未载客状态数据异常率较载客状态增加71.4%,未载客数据异常率更高。

循环神经网络模型下道路碳排放浓度预测

以湖南省永州市永州大道基本路段CO_(2)浓度时序数据为研究对象,旨在实现道路CO_(2)浓度的实时预测。测得用于模型训练和预测精度计算的路段CO_(2)浓度数据,利用Savitzky-Golay滤波器对数据进行平滑去噪,在调试并建立循环神经网络最优模型结构的基础上,引入多元预测模型(MLR、SVR、BP)和时序预测模型(BP、RF、RNN、LSTM、GRU)进行预测性能对比,为路段CO_(2)浓度的实时预测提供参照。结果表明:时序预测模型相比于多元预测模型具有更好的预测效果,特别是循环神经网络模型中的GRU表现出较高的预测精度,其次是LSTM,最后是RNN;循环神经网络模型在处理路段CO_(2)浓度时序数据的训练和预测任务中具备突出性能,能够实时且精准预测道路路段CO_(2)浓度。

Monitoring Mongolia Gobi dust transport using OMI data

The characteristics of long-distance dust transport from Asia to the United States over the Pacific Ocean are statistically analyzed using OMI AI （Ozone Monitoring Instrument Aerosol Index） data during 2005-007. The results show that there is a high correla- tion of At （the correlation coefficients are as high as 0.83 in March, 0.62 in April and 054 in May） between the Mongolia Gobi Desert and the west coast region of the United States （40°-50°N, 120°- 130°W）, indicating a strong source-receptor area relationship. Through calculating the lag correlation coefficient of the dust propagation time, we determined that the dust propagation lime fi＇om the Mongolia Gobi Desert to the west coast of the United States is about 6-7 days at the 99% confidence level.

公路交通数据要素价值释放:机理路径、重点方向与发展建议

为促进公路交通数据要素深度应用,赋能公路交通数字化转型和高质量发展,对公路交通数据要素价值释放的机理路径、重点方向进行了探索。首先通过资料分析、理论凝练,提出了公路交通数据要素的内涵和特征,梳理并总结了公路交通数据要素的主要类型。然后介绍了数据要素叠加、倍增、替代效应等价值释放机理,提出了数据资源盘点、数据要素管理、要素价值发现、数据开发利用的价值释放路径。再围绕公路交通全寿命周期应用及跨行业延伸应用两大领域,提出了公路交通数据要素应用的重点方向。最后针对公路交通数据要素应用面临的挑战,提出了加强标准体系建设实施、健全数据要素流通机制、推进数字化技术推广应用、加强复合型人才培育等发展建议,以期为公路交通数据要素价值释放提供参考。

区块链在城市道路智能交通中的应用综述

从安全、共享、运营三个方面介绍了区块链在城市道路智能交通中的应用。在安全方面,区块链的去中心化和不可篡改的特性能够保护数据信息安全和用户隐私安全;在共享方面,区块链的激励机制促进了车辆计算资源和交通信息的共享;在运营方面,区块链的不可篡改和可追溯性保证了运营中对交通违章准确有效的溯源,利用共识机制让交通信号灯配时更加高效。此外,分析了区块链在城市道路智能交通应用中存在的不足,并展望了区块链在城市道路智能交通领域的未来发展方向。

思政背景下交通大数据技术及应用课程设计探讨

系统分析高校交通大数据技术及应用课程在思政教育过程中存在的问题,提出交通大数据技术及应用课程的理论知识内容和发展方向,给出思政教育与专业知识相融合的教学模式。以数据安全、国家安全、软件国产化、社会大事件和芯片“卡脖子”等为例,激发学生的学习兴趣,调动学生的学习积极性,实现与思政教育的深度融合。

基于赛教融合的智能交通课程实践教学研究

结合全国大学生智能汽车竞赛百度智慧交通创意组竞赛项目,设计智能交通课程实践教学内容,从竞赛内容凝练与课程知识点结合的教学案例和实验项目,实现赛教资源融合和赛教一体化实践平台共享。设计的实验教学项目融合了图像处理、数据分析、人工智能、智能车硬件平台等内容,包括数据采集、数据分析、数据集构建,深度学习模型建立与智能车平台部署等实践环节。学生从编写简单程序开始,不断提高,到构建复杂的深度学习模型实现智能车自动巡航控制实验。将竞赛任务具有挑战性和对抗性的特点融入课程教学,吸引学生兴趣,增强学生求知欲,提升学生创新能力和工程实践能力。

基于频繁序列挖掘的出租车轨迹特性分析

为进一步厘清不同出租车路径选择行为的差异性,采用频繁序列挖掘方法提取了同一个OD对间的频繁路径,构建路径选择集,分别从静态和动态两个角度分析路径集的相似特性。以西安市出租车的轨迹数据为研究对象,通过栅格划分与路网匹配,获得了不同OD对之间的路径集合。重新定义了频繁路径,采用PrefixSpan演变算法,在得到频繁子序列的基础上引入动态阈值和频繁度指标挖掘频繁路径,提取了最短路径和其他路径,完成了3类有效路径集的构建,并分析了路径集的一般属性。其后,将路径上二维时间序列(轨迹)间的相似度表示为动态相似度,将一维有向序列(路段)间的相似度表示为静态相似度,基于改进的最长公共子序列和动态时间规整算法对3类路径进行了相似性分析。结果表明:频繁路径与最短路径的相似度较高,意味着大多数出租车仍然选择具有最低出行时间的路段,但不一定会选择最短路径;时间和距离仍是出行者选择路径时主要考虑的因素,但出行者并不完全追求时间最短或距离最短;试验得到的动态相似度计算结果显著高于静态相似度计算结果,说明路径上的二维时序相似度高于一维形状相似度;两种方法下频繁路径和最短路径的相似度均最高,最短路径和其他路径的相似度均最低,比较结果的一致性说明可以用动态轨迹的相似度来大致度量静态路径的相似度。文中的频繁路径挖掘算法具有一定的可靠性,可为城市交通管理者进行路径推荐、道路规划等提供支持。

随机矩阵理论在高速路关键路径辨识中的应用

高速公路网络是我国各地区相互连接的重要纽带,高速公路网络关键路径辨识对确保高速网络的可靠运行具有重要意义。传统的关键路径分析方法基于拓扑结构,未考虑交通网络的运输量特性;而现有的基于运输量数据的分析方法只考虑部分路径的运输量特性,难以反映交通网络的实际运行情况。利用路径运输量数据,搭建运输量随机矩阵模型,针对高速公路网络异常后的运输量变化特性,定义关键路径评估指数,实现异常影响程度的量化评估,在此基础上提出一种基于数据驱动的高速公路网络关键路径辨识方法。最后,采用辽宁省高速公路网络进行分析,验证了所提方法的合理性和有效性,并将该方法应用于城市路网案例中,进一步证明该方法具有普适性。

基于谱域超图卷积网络的交通流预测模型

针对传统图结构难以对节点间的隐含复杂关联关系建模的问题,利用超图对交通流数据进行高阶表示,提出基于谱域超图卷积网络的交通流预测方法。首先,通过动态超边刻画数据特征层面的关系,利用谱域超图卷积,包括基于傅里叶和图小波的超图卷积及门控时序卷积,在多尺度上提取交通流的时空特征,实现端到端的节点级交通流预测。然后,采用北京市以及美国加利福尼亚州真实历史数据集进行预测实验。消融实验通过孤立和重构网络模型验证了所提方法的有效性。全时段和早高峰交通流预测的实验结果表明,该方法预测准确率高于目前主流交通流预测模型。

“数据要素×”背景下交通领域新基建投融资分析

《“数据要素×”三年行动计划(2024—2026年)》对充分发挥数据要素乘数效应,推动高质量发展做出了具体要求。现阶段,交通新基建投融资主要存在传统投融资渠道难以满足资金需求、尚未形成可持续投资收益闭环、缺乏相应配套制度和规则、政府功能定位不明确等突出问题。为加快完善可持续的交通新基建资金保障体系,推动交通新基建赋能经济社会发展,从数字化产品视角深入理解交通新基建的内涵及投资特征,探明交通新基建赋能经济高质量发展的机理,揭示新阶段交通新基建投融资困境,才有可能找到“数据要素×”背景下创新交通新基建投融资渠道的现实路径。研究发现,交通新基建是适应新一轮科技革命和产业变革,在传统设施基础上融入新要素,具备新功能,呈现新形态,促进交通网、运输服务网、能源网和信息网融合发展的现代化交通基础设施体系,是“数据要素×交通运输”的典型应用场景,其投资具有规模更具差异化、主体更具多元化、乘数效应更显著、运营更具市场化等特征,成为促投资、稳增长、推动经济高质量发展的新引擎。研究表明,创新交通新基建投融资模式,建立可持续资金保障体系,要立足“数据要素×”视角,明确交通新基建服务对象、核心产品及价值,支持交通新基建“向数据要收益”,打造可持续投资收益闭环,畅通场景创新应用渠道,探索投资体制机制创新,强化交通领域新基建顶层设计,做好配套政策制度支持保障。