Heteroscedastic Gaussian processes for uncertainty modeling in large-scale crowdsourced traffic data

Accurately modeling traffic speeds is a fundamental part of efficient intelligent transportation systems. Nowadays, with the widespread deployment of GPS-enabled devices, it has become possible to crowdsource the collection of speed information to road users (e.g. through mobile applications or dedicated in-vehicle devices). Despite its rather wide spatial coverage, crowdsourced speed data also brings very important challenges, such as the highly variable measurement noise in the data due to a variety of driving behaviors and sample sizes. When not properly accounted for, this noise can severely compromise any application that relies on accurate traffic data. In this article, we propose the use of heteroscedastic Gaussian processes (HGP) to model the time-varying uncertainty in large-scale crowdsourced traffic data. Furthermore, we develop a HGP conditioned on sample size and traffic regime (SSRC-HGP), which makes use of sample size information (probe vehicles per minute) as well as previous observed speeds, in order to more accurately model the uncertainty in observed speeds. Using 6 months of crowdsourced traffic data from Copenhagen, we empirically show that the proposed heteroscedastic models produce significantly better predictive distributions when compared to current state-of-the-art methods for both speed imputation and short-term forecasting tasks.     

高性能排水板在淤泥地基筑堤工程中的应用效果

为验证采用高性能排水板作为淤泥质土径向排水通道的适用性和效果,在连云港徐圩港区设置一段高性能排水板试验段,埋设部分原位观测仪器。通过高性能排水板和普通排水板标段地基固结度和深层水平位移的对比来研究高性能排水板的应用效果。对比结果表明:高性能排水板应用效果良好;同样工期内,高性能排水板地基比普通排水板试验段地基的固结度高,深层水平位移小。     

交通大数据视角看广佛同城

广佛同城发展由来已久,是中国城市群中同城化程度最高的区域。简要分析广佛同城的交通基础设施发展演变历程,并基于模糊大数据(手机信令数据)和准确大数据(运行监测数据)对广佛通勤交通特征进行分析。结合手机信令数据对广州南站的客流组成及空间分布进行研究,对广州南站选址偏远问题进行解析。结果表明:广佛同城具有双向对等性的联系;地铁在同城化推进过程中起到重要的促进作用,拓展同城化活动范围;广州市机动车交通需求管理政策不够系统,非广佛车牌在通勤小汽车中比例超过40%,需要引起足够的关注;广州南站服务的客流中广州客流与佛山客流比为7:3,与对应的常住人口规模比例相当,初步实现了交通战略规划提出的共享理念。     

A model for the visualization and analysis of elevator traffic

ABSTRACT

Analysis of elevator traffic in high rise buildings is critical to the performance evaluation of elevator group control systems (EGCS). Elevator dispatching methods or parking algorithms in an EGCS can be designed or modified according to analyses of traffic flow. However, interpretation of traffic flow based solely on numerical data may not be explicit and transparent for EGCS experts as well as for other non-expert building administration. In this study, we present a model for visualization and analysis of elevator traffic. First, we present an alternative approach for traffic analysis which we call route visualization. In the proposed approach, we initially decompose elevator traffic into its component parts and investigate each component independently. Then, using superposition of components we obtain a reconstructed model of overall traffic. This modeling approach provides component-based traffic analysis and representation of routes with intensities through data visualization. In the second part we introduce a multi-dimensional analysis of time parameters in ECGS. This approach provides a comparative analysis of several control algorithms such as dispatch or park algorithms for different combinations of traffic components.     

交通模型的价值

在既有规划编制导则中,已经明确交通模型和交通需求分析是综合交通体系规划、轨道交通线网规划的重要工作内容。交通模型的价值并非仅仅体现在预测结果和精度上,更在于编制过程中对交通特征和供需关系的分析,对战略方案、系统方案的指导、解释、论证的作用上。但在现实规划编制中,模型的地位和价值在丧失,日益成为项目成果中的摆设品,难以支撑交通需求深入分析,并与战略构思、方案制定相脱节。与此同时,规划实践、大数据、交通模型的发展趋势,亟须重新审视模型的价值,提升模型精细化的定量分析水平。最后,从机制保障、应用推广、功能拓展、科研攻关等方面,提出促进模型价值提升的相关建议。     

Empirical analysis of short period traffic counts and their efficiency: the case of Indian traffic

Short period traffic counts (SPTCs) are conducted routinely to estimate the annual average daily traffic (AADT) at a particular site. This paper uses Indian traffic volume data to methodically and extensively study the effect of four aspects related to the design of SPTCs. These four aspects are: (i) for how long, (ii) on which days should SPTCs be carried out, (iii) how many times, and (iv) on which months should SPTCs be carried out? The analyses indicate that the best durations for conducting SPTCs are 3 days (starting with a Thursday) and 7 days, for total traffic and truck traffic, respectively. Further, these counts should be repeated twice a year keeping a separation of two months between the counts to obtain good estimates of AADT at minimal cost. An additional outcome of this study has been the determination of seasonal factor values for roads in developing economies, like India.     

客货滚装码头车辆定位系统需求分析和技术实现

针对某客货滚装码头中车辆运输的智能化调度需求,进行车辆位置智能感知的研究,采用物联网感知和计算机视觉技术,得出一种基于视频监控的车辆定位系统方案。该系统能够实时监控码头内进出港车辆,跟踪和记录其路径,支持越界报警,为智能化调度和安全监控提供基础数据。     

隧道工程建设地质预报及信息化技术的主要进展及发展方向

复杂的不良地质条件是制约隧道安全高效建设的主要因素,要实现隧道工程的安全高效建设,首先要提高地质预测预报技术水平及其信息化程度。1)介绍我国复杂不良地质隧道超前预报的方法进展及其应用,包括突水突泥灾害源超前探测方法与设备、断层破碎带超前预报、城市地铁溶洞和孤石等探测的进展及应用等;2)介绍我国隧道岩爆监测预警方法及其应用,预报清楚之后就要加强安全风险过程监控;3)介绍基于BIM技术的建筑物(隧道工程)安全风险监控最新进展,包括安全风险实时感知系统和实时预警系统;4)指出隧道工程建设信息化技术的发展方向,包括开展基于大数据技术的TBM/盾构施工的分析与控制研究以及数字隧道向智慧隧道(建设和运营维护)的发展。     

基于GPS载波相位信号确定运动体姿态的关键技术

应用GPS载波相位信号确定运动体姿态,针对二维两天线系统情况,设计了姿态测量系统的硬件结构及算法流程框图,文章介绍了GPS姿态测量的关键技术：GPS姿态观测方程、整周模糊度的解算、误差的消除。从系统设计角度证明了技术的可行性。     

A data model applied to the knowledge-based ICAS

Image-guided computer aided surgery system (ICAS) contributes to safeness and success of surgery operations by means of displaying anatomical structures and showing correlative information to surgeons in the process of operation. Based on analysis of requirements for ICAS, a new concept of clinical knowledge-based ICAS was proposed. Designing a reasonable data structure model is essential for realizing this new concept. The traditional data structure is limited in expressing and reusing the clinical knowledge such as locating an anatomical object, topological relations of anatomical objects and correlative clinical attributes. A data structure model called mixed adjacency lists by octree-path-chain (MALOC) was outlined, which can combine patient's images with clinical knowledge, as well as efficiently locate the instrument and search the objects' information. The efficiency of data structures was analyzed and experimental results were given in comparison to other traditional data structures. The result of the nasal surgery experiment proves that MALOC is a proper model for clinical knowledge-based ICAS that has advantages in not only locating the operative instrument precisely but also proving surgeons with real-time operation-correlative information. It is shown that the clinical knowledge-based ICAS with MALOC model has advantages in terms of safety and success of surgical operations, and help in accurately locating the operative instrument and providing operation-correlative knowledge and information to surgeons in the process of operations.