A Trajectory-Oriented Carriageway-Based Road Network Data Model, Part 1: Background

This is the first of a three-part series of pape rs which introduces a general background of building trajectory-oriented road net work data models, including motivation, related works, and basic concepts. The p urpose of the series is to develop a trajectory-oriented road network data mode l, namely carriageway-based road network data model (CRNM). Part 1 deals with t he modeling background. Part 2 proposes the principle and architecture of the CR NM. Part 3 investigates the implementation of the CRNM in a case study. In the p resent paper, the challenges of managing trajectory data are discussed. Then, de veloping trajectory-oriented road network data models is proposed as a solution and existing road network data models are reviewed. Basic representation approa ches of a road network are introduced as well as its constitution.

A Trajectory-Oriented, Carriageway-Based Road Network Data Model,Part 2:Methodology

This is the second of a three-part series of papers which presents the principle and architecture of the CRNM, a trajectory-oriented, carriageway-based road network data model. The first part of the series has introduced a general background of building trajectory-oriented road network data models, including motivation, related works, and basic concepts. Based on it, this paper describs the CRNM in detail. At first, the notion of basic roadway entity is proposed and discussed. Secondly, carriageway is selected as the basic roadway entity after compared with other kinds of roadway, and approaches to representing other roadways with carriageways are introduced. At last, an overall architecture of the CRNM is proposed.

A Trajectory-Oriented Carriageway-Based Road Network Data Model, Part 3: Implementation

This is the final of a three-part series of papers which mainly discusses the implementation issues of the CRNM. The first two papers in the series have introduced the modeling background and methodology, respectively. An overall architecture of the CRNM has been proposed in the last paper. On the basis of the above discusses, a linear reference method (LRM) for providing spatial references for location points of a trajectory is developed. A case study is introduced to illustrate the application of the CRNM for modeling a road network in the real world is given. A comprehensive conclusion is given for the series of papers.

Design and Implementation of GIS Data Production System for Expressway Video and Road Infostructure

The expressway is necessary for the development of the modern transportation industry, and the level of expressway construction reflects the overall grade of national or regional economic development. In order to process the expressway road property data information, based on the current mainstream Windows operating system, this study utilizes Geographic Information System (GIS) development technology, road video processing technology, and spatial data mining method to design and develop an expressway video and road infostructure GIS data production system. The system designs a multi-layer distributed application model in accordance with the ideas and methods of GIS engineering and the characteristics of road production data. In addition, according to the characteristics and specification requirements of basic geographic data, the road production database of spatial data and attribute data integrated storage is constructed by combining database and spatial data engine. Through the development of the GIS data production system for expressway video and road infostructure, various functions such as generation of road property data, dynamic management of road infostructure, and visualization of spatial information have been realized. The system focuses on improving the production efficiency and automation level of expressway production data and meets the construction requirements for modernization, informatization, and intelligence of expressways.

Road Traffic Crash Data: An Overview on Sources, Problems, and Collection Methods

Road traffic crash data are useful tools to support the development, implementation, and assessment of highway safety programs that tend to reduce road traffic crashes. Collecting road traffic crash data aims at gaining a better understanding of road traffic operational problems, locating hazardous road sections, identifying risk factors, developing accurate diagnosis and remedial measures, and evaluating the effectiveness of road safety programs. Furthermore, they can be used by many agencies and businesses such as: law enforcements to identify persons at fault in road traffic crashes;insurers seeking facts about traffic crash claims;road safety researchers to access traffic crash reliable database;decision makers to develop long-term, statewide strategic plans for traffic and highway safety;and highway safety administrators to help educate the public. Given the practical importance of vehicle crash data, this paper presents an overview of the sources, trends and problems associated with road traffic crash data.

Assessing Factors for Occurrence of Road Accidents in Tanzania Using Panel Data Analysis: Road Safety Perspective

This study assessed critical factors for road traffic accidents and associated mitigation to reduce the accidents by the year 2030. The study was guided by research questions, what are the major causatives of road accidents and how to mitigate the problem. The study used secondary data collected from the repository database of traffic police at the division of Tanzania Road Safety Squad. Data were collected at the events of accident occurrences and reported annually by regions. Panel data analysis was used to allow for controlling variables which cannot be observed over time and across areas such as regions. Pooled Poisson model, fixed effect and random effect Poisson model was applied to assess factors for road traffic accidents. Fixed effect model was the best model with a reasonably good fit. Results indicated that all predictors are significant under fixed effect Poisson model with a p-value less than 0.05 but Passengers and Railway crossing road was found insignificant and dropped in the final model. Laws and regulatory frameworks should be formulated and enforced promptly for Tanzania may reach the target of 2nd decade of action for roads safety 2021-2030.

Road2vec:一种基于出租车轨迹数据的城市道路可视分析方法

发掘轨迹数据的时空连续性对分析路网结构和人类移动模式的非常重要,基于出租车GPS数据,提出一种城市道路的可视分析方法——road2vec.首先利用词嵌入技术将轨迹数据视为文本进行建模,得到道路的向量表示形式;然后计算得到道路向量在向量空间中的位置关系,并用这种位置关系来表示道路向量之间的相似性;最后根据相似性来探索道路在轨迹中的位置信息和连接关系.文中还设计了一套可视分析系统,以支持用road2vec方法探索城市道路相关信息.基于温州市出租车GPS数据的案例分析表明,该方法可以有效地反映人群在城市路网中的移动模式.

Zero Truncated Bivariate Poisson Model: Marginal-Conditional Modeling Approach with an Application to Traffic Accident Data

A new covariate dependent zero-truncated bivariate Poisson model is proposed in this paper employing generalized linear model. A marginal-conditional approach is used to show the bivariate model. The proposed model with estimation procedure and tests for goodness-of-fit and under (or over) dispersion are shown and applied to road safety data. Two correlated outcome variables considered in this study are number of cars involved in an accident and number of casualties for given number of cars.

“天地图·北京”多源道路数据融合关键技术研究

“天地图”是“数字中国”建设的重要内容,是面向公众的地理信息公共服务平台,可为用户提供北京市地理信息“一站式”协同服务。为了给用户提供更加准确的地理信息,亟须高效的数据融合技术,将不同来源、不同模式、不同媒质、不同时间、不同表示的信息进行结合,实现对被感知对象的更精确的描述。道路数据作为“天地图”的基础数据之一,其几何与属性特征的复杂性给矢量数据融合技术增加了挑战。本文围绕“天地图·北京”多源道路数据融合的分析、提取与融合过程,通过对比导航数据、主节点数据、交通委数据的属性、现势性、精度、权威性等具体情况,分析道路数据融合的技术特点,对多源道路数据融合的关键技术进行了研究并设计开发出两项工具,提高了数据融合的效率和准确度。

基于网络开放数据的区域消防救援总体有效覆盖率评估

高效准确地掌握消防救援有效覆盖率是优化消防站点资源配置的前提。将判断是否有效覆盖的消防救援行程时间阈值定为240 s,建立了基于时间加权的区域消防救援总体有效覆盖率评估模型。基于网络开放数据收集了长沙的50座消防站作为消防救援供给点、5746家被抽查到的社会单位作为消防救援需求点,并调用网络地图应用程序编程接口基于实时路况来仿真消防救援行程时间。在连续7 d内设置197个评估场景,共获得了1131962个有效样本,进而得出:长沙消防救援总体有效覆盖率为21.22%,结果等级为“C”,消防救援水平一般,需加强消防站建设。这种基于网络开放数据的区域消防救援有效覆盖率评估,具备高效和准确的特点,可为优化消防站点资源配置、提升公共安全水平提供关键理论和方法支撑。

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。

基于多尺度特征融合和注意力机制的矿区道路障碍检测

为解决复杂露天矿区背景下的行车障碍检测问题,提出一种基于改进跨尺度特征融合的矿区道路障碍检测算法。首先,针对原始矿山数据集中小目标样本类别不平衡的问题,采用一种基于几何变换和加权泊松融合的数据增强方法扩大样本数量;其次,在特征提取阶段提出更适用于障碍检测的跨阶段连接网络,以增大检测尺度,提高算法对小目标特征的学习能力;然后,在特征融合阶段提出基于3D无参注意力(SimAM)和去权重的双向特征融合金字塔网络(Bi-FPN),通过扩大预测特征图和特征感受野,提升多尺度检测性能;最后,针对训练中样本不均衡和障碍物边界框定位不精准问题,引入质量焦点损失函数(QFL)和可扩展的交并比损失函数(SIoU),将分类得分与位置的质量预测结合,提高对密集遮挡目标的定位精度。结果表明:改进方法能有效识别复杂背景下露天矿区非结构化道路障碍物,在实际应用中,检测精度达到91.88%,检测速度达到68.7帧/s,相较于主流检测方法有着更好的小目标和多尺度检测性能,可满足露天矿区无人矿卡行进中的障碍安全检测要求。

基于ERA5再分析系统海上丝绸之路海况及波高周期联合分布特征

利用欧洲中期天气预报中心的ERA5再分析系统,基于2012—2022年时间分辨率为1 h的全球气象资料,对海上丝绸之路沿线典型海域进行海况分析。利用我国东南海域、孟加拉湾海域和阿拉伯海域的实测数据验证ERA5资料的有效性和准确性,获得该目标海域风、浪共同限制条件下各季节海况情况。统计得到各季节平均多年海上丝绸之路沿线波浪特征分布规律,并统计分析我国南海、孟加拉湾和阿拉伯海各典型海域的有效波高与谱峰周期联合分布概率。研究结果表明,ERA5数据能较好地反映目标海域的海况特征;工程施工过程中需重点关注夏季波浪波高及全年长周期波浪的影响;我国东南沿海和阿拉伯海整体海况条件较好,孟加拉湾海况较为复杂,有效波高在1.5 m与谱峰周期在10s以上在85%以上,在前期投资规划时需重点关注。

数据驱动的学校周边道路拥堵识别

为定量分析多个中小学周边道路拥堵情况,针对性地改善学校周边拥堵状况,对比通学时期与非通学时期的交通拥堵数据.建立学校周边道路拥堵指标,通过拥堵评价函数,分析各道路受周边学校出行影响的程度,识别重点拥堵道路.提出了一种基于地图开放平台获取交通大数据的算法,对南京主城区79所中小学周边道路进行实例分析,给出了各道路受学校出行影响的拥堵值.结果表明:在通学期间交通整体拥堵程度高于非通学时期,通学时期平均拥堵指数为1.973,非通学时期平均拥堵指数为1.664,通学时期比非通学时期平均拥堵指数提高了18.57%.

City Routing Velocity Estimation Model under theEnvironment of Lack of Floating Car Data

After introducing the principle of float car data (FCD), this paper gives the primary flow of pre-handing and map- matching of the FCD. After analyzing the percentage of coverage of FCD on the road network, large quantity of heritage database of routing status is used to estimate the routing velocity when lack of FCD on parts road segments. Multi liner regression model is then put forwarded by considering the spatial correlativity among the road network, and some model parameters are deduced when time series is classified in day and week. Besides, error of velocity probability and error of status probability are achieved based on the result from field testing while the feasibility and reliability of the velocity estimation model is obtained as well. Finally, as a case study in Shanghai center area, the whole routing velocity in the road network is estimated and published in real time.

基于ReliefF-RBF的路面不平度识别算法研究

路面不平度对道路车辆行驶安全性及车辆动力学响应具有重要影响。通过将路面不平度识别与先进悬架控制结合,有望能进一步提升乘员舒适性和车辆的操纵稳定性。现有基于数据驱动的路面分类方法难以高效处理时变参数与车速,现有基于模型的路面识别算法需要已知精确车辆模型,在实际应用中面临车辆物理参数难以获得的问题。提出一种融合模型和数据驱动的路面分类算法,采用基于模型的方法反算等效路面轮廓,结合数据预处理方法,对车辆响应和反算等效路面轮廓数据进行滤波;对等效路面轮廓和响应信息进行时域频域特征计算,采用ReliefF算法进行关键特征提取,构建基于径向基函数神经网络的路面分类器,进行路面分级识别;通过仿真试验和实车试验验证了不同车辆参数和车速下所提出的算法鲁棒性。

路面结冰检测技术发展研究

开展路面结冰检测是预防和减少交通事故的重要手段。首先,从气候条件、环境、道路基础设施这三个方面对路面结冰的影响因素进行了介绍;其次,分析了路面结冰的常见检测技术,包括基于气象数据的预测方法、基于路面状况的检测方法、基于遥感技术应用、基于人工智能与大数据技术融合应用,并从技术原理、常见应用等方面进行检测技术的探讨,每项技术都有其优势和缺点,多技术结合可有效提升结冰检测的精度和可靠性。

优化中国(新疆)自由贸易试验区法治保障研究

中国(新疆)自贸试验区法治建设,应坚持人民群众高品质生活、促进人的现代化和人的全面发展,深刻把握高质量发展,坚持以人民为中心的价值导向。着力抓主要矛盾、重点领域、关键环节,聚焦高标准的法治要求建设新疆自贸试验区,要从维护政治安全和更好统筹发展和安全、开放与稳定和促进新质生产力发展的高度把握新疆自贸试验区法治建设的时代方位及形势任务,统筹加强涉外法治,主动精准对接国际规则,努力以法治建设现代化支撑和服务中国式现代化的自贸试验区建设实践,确保更好发挥法治固根本、稳预期、利长远的重要保障作用,持续拓展自贸试验区安全、稳定、高效的发展空间。