Experimental study and modeling of car-following behavior under high speed situation

To investigate the car-following behavior under high speed driving conditions, we performed a set of 11-car-platoon experiments on Hefei airport highway. The formation and growth of oscillations have been analyzed and compared with that in low speed situations. It was found that there is considerable heterogeneity for the same driver over different runs of the experiment. This intra-driver heterogeneity was quantitatively depicted by a new index and incorporated in an enhanced two-dimensional intelligent driver model. Using both the new high-speed and the previous low-speed experimental data, the new and three existing models were calibrated. Simulation results show that the enhanced model outperforms the three existing car-following models that do not take into account this intra-driver heterogeneity in reproducing the essential features of the traffic in the experiments.     

城市交通状态的空间依赖性和异质性分析

有关城市交通状态空间特征的研究相对匮乏。从空间角度分析城市宏观交通特征,首先,针对城市路网几何形态和交通数据的关系提出适合于城市交通数据分析的空间模型。然后,以从长期的浮动车数据中提取的路段行程速度作为描述交通状态的实验数据,分别采用空间自相关和核密度估计法定量分析路网行程速度的空间依赖性和空间异质性,并分析其在典型时段的空间分布特征。结果显示:城市交通状态的关联性在空间上随着路段间距的增长而衰减;城市交通状态的空间分布特征随时间变化,受路网结构和区域功能的影响在空间中呈现集聚特征。     

基于BIM的数字建造工业化平台中业务管理的多源数据集成关键技术研究

随着BIM技术的不断发展,BIM平台在施工全过程的应用逐渐丰富。集成整合平台背后全生命周期的工程数据,并将数据传递至工程建造各个环节当中进行应用,是BIM平台发挥作用的本质。如何在工程的全生命周期收集和整理工程数据库,并传递至各个工作流程中发挥作用,是开展BIM平台建设的重点。以乌鲁木齐市东进场高架道路工程为实例,重点研究BIM平台中工程数据库的建立,分析如何在项目的设计阶段和施工过程中采集工程数据,并将工程数据库应用于项目管理。     

基于多源轨迹数据的城市交通状态精细划分与识别

针对基于路段的城市交通状态分析方法的不足,本文利用公交车和出租车轨迹数据提出了城市交通状态精细划分和识别方法,实现城市交通状态分析.对两种轨迹点的速度值和空间位置值分别进行归一化处理,以此为属性数据,通过迭代计算轮廓系数确定k 值完成轨迹点聚类,结合二次处理方法对类簇进行拆分和融合以划分道路交通状态;在特征级建立多源数据融合方法,实现交通状态速度值计算;以归一化后的速度值为属性数据,通过聚类将样本分为4类对应4种城市交通流状态层级.实验表明,本文方法能够实现道路交通状态精细划分,能有效地识别出道路局部位置的交通状态,进而可为城市道路交通管理提供决策支持.     

基于大数据的大学校园停车系统规划 ——以大连理工大学凌水主校区为例

为解决大学校园停车系统混乱以及用于相关规划的基础数据样本量小、精度不高、时效性 差等问题,应用大学校园停车调查数据、各出入口车辆记录数据以及各院系教职工信息数据进行多源大数据分析,提出了一种基于大数据的大学校园停车系统规划方法。以大连理工大学凌水主 校区收集到的数据为例,首先从静态角度利用各出入口车辆记录数据和校园停车调查数据获取校园整体停车需求,进而利用各院系教职工信息数据分析各部门的停车需求。然后,从动态角度考虑停车位的周转问题,利用各出入口车辆记录数据分析校园出入车辆停车时段分布状况。最后,根据多源大数据分析所得校园停车系统现状,得出相应的校园停车系统规划结果。研究结果表 明：基于大数据的大学校园停车系统规划方法可有效解决传统方法中基础数据样本量小、精度不高、时效性差等问题,提高了规划结果的实用性和科学性。     

面向传染病疫情防控的公共交通运行管理决策支持研究

近年来全球新发重大传染病疫情不断出现，已成为人类社会必须防范应对的重大风险。公共交通在传染病疫情防控过程中承担着阻断病毒传播和保障复工复产的功能，疫情期间公共交通运行管理的决策需求和技术支撑体系与日常情况有显著差异。现有研究多针对公交日常运行决策需求展开，虽有少量针对突发公共事件的应急管理决策支持的研究，但多针对自然灾害和事故灾难场景，无法迁移应用于传染病疫情防控。基于此，以新型冠状病毒肺炎（COVID-19）疫情为例，综合考虑突发公共卫生事件应急管理流程和疫情防控实际情况，系统梳理疫情不同阶段的防控目标和决策需求，提出一种面向传染病疫情防控的公共交通运行管理决策支持系统框架，建立基于公共卫生事件案例库、多源数据融合库、公交数据分析技术库和公交防疫策略库的功能架构，并设计不同功能模块的算法模型。研究以厦门为例，对提出的决策支持系统的功能架构和算法模型进行验证。研究结果表明，构建公交乘客出行链的成功率为89.7%，并可应用于疫情不同阶段的关联客流分析、感染者同乘人员的追溯分析、医护人员等防疫人员的通勤出行识别、公交运行满载率监控等方面。研究成果不仅对传染病疫情防控有实用价值，而且对突发公共事件应急管理决策支持方法亦有理论贡献。     

Commuters’ willingness-to-pay for improvement of transfer facilities in and around metro stations – A case study in Kolkata

Although several cities in India are developing the metro system, there are lacunas associated with transfer facilities in and around metro stations. The present work aims to investigate the perception of commuters of Kolkata city, India in terms of their willingness-to-pay (WTP) for improvement of transfer facilities. A stated preference survey instrument was designed to collect choice responses from metro commuters and the database was analysed by developing random parameter logit (RPL) models. The decomposition effects of various socioeconomic and trip characteristics on mean estimates were also investigated in random parameter logit models with heterogeneity. The work indicates significantly high WTP of metro commuters as compared to the average metro fare for improvement of various qualitative attributes of transfer facility such as ‘facility for level change’, ‘visual communication’, ‘pedestrian crossing’, and ‘pedestrian environment’. The WTP values are also found to vary across different groups of commuter formed on the basis of ‘trip purpose’, ‘monthly household income’, ‘station type’ and ‘metro fare’. ‘Work trip’ commuters are found to have higher WTP for improvement of access time, pedestrian environment and use of an escalator over the elevator. On the other hand, ‘high-income group’ commuters have shown higher WTP for improvement of access time, pedestrian crossing, and pedestrian environment. While ‘high fare group’ commuters have higher WTP for access time and pedestrian environment, heterogeneity is also observed in WTP for facility for level change, pedestrian crossing, and pedestrian environment across commuters using different ‘station type’ (underground, at-grade, and elevated). The findings from the study provide a basis for formulating policies for the improvement of transfer facilities in and around metro stations giving due attention to the preference of commuters having different socioeconomic and trip characteristics.     

Shockwave-based queue estimation approach for undersaturated and oversaturated signalized intersections using multi-source detection data

With the progress of information and sensing technologies, estimating vehicular queue length at signalized intersections becomes feasible and has attracted considerable attention. The existing studies provided a solid theoretical foundation for the estimation; however, the studies have some restrictions or limitations more or less. This paper presents a new methodology for estimating vehicular queue length at signalized intersections using multi-source detection data under both undersaturated and oversaturated conditions. The methodology applies the shockwave theory to model queue dynamics. Using data from probe vehicles and point detectors, analytical formulations for calculating the maximum and minimum (residual) queue lengths of each cycle are developed. Ground truth data were collected from numerical experiments conducted at two intersections in Shanghai, China, to verify the proposed methodology. It is found that the methodology has mean absolute percentage errors of 17.09% and 12.28%, respectively, for maximum queue length estimation in two tests, which are reasonably effective. However, the methodology is unsatisfactory in estimating the residual queue length. Other limitations of the proposed models and algorithms are also discussed in the paper.     

无核密度仪在沥青路面工程质量控制中的应用技术研究

无核密度仪是一种可实现大样本、高效、实时、无损、安全测定沥青面层压实度和非均匀性的新型检测仪器.根据无核密度仪检测方法的基本原理,分析该法测值精确度的影响因素,并提出现场检测时的操作建议及注意事项.阐述无核密度仪在沥青路面压实过程中的压实控制、压实效果评价、压实方案和工艺比选,提出改善沥青面层压实效果的措施,并探讨无核密度仪在沥青面层非均匀性检测中的应用技术.     

共享单车出行空间异质性特征及驱动因素研究

为实现基于轨迹数据挖掘的共享单车出行空间异质性特征及其驱动因素评估，本文应用核密度分析和热点探测，获取采样分析区域并以热力值表征共享单车出行发生量，减少尺度效应的干扰；引入空间统计学的半变异函数模拟共享单车出行发生量的结构性和随机性变化规律，挖掘空间异质性特征，确定邻域效应的尺度范围；利用空间序列的斜率表征变化趋势，同时，结合改进的空间滞后和残差模型，区分土地利用、邻域效应和其他建成环境各自对共享单车出行空间异质性特征的驱动力。以北京市为案例进行分析，结果表明：北京市的共享单车出行存在中等的、 正的空间自相关性，空间异质性特征的最佳拟合模型为指数模型；空间自相关性的衰减半径为 1860 m，大于此距离时邻域效应消失；建成环境对空间异质性特征的相对驱动力最大，邻域效应对其的相对驱动力则处于中间水平，而土地利用对其的相对驱动力最小。