Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.     

囊式空气弹簧机械阻抗特性研究

根据小幅振动的线性叠加原理将囊式空气弹簧分成几个简单的可解析计算的规则区域,结合线性空气波动理论求解出空气弹簧内部声压场的分布。根据弹性薄壳无矩理论推导出旋转壳体状态向量的一阶常微分矩阵方程,利用齐次扩容精细积分法推导出壳体的传递矩阵,结合动力平衡方程求出空气弹簧在位移谐波激励下所受到的激励力,进而得出其机械阻抗。算例结果表明该方法合理可行,为运用近似解析法分析空气弹簧的阻抗特性提供了一种新的思路。     

变邻域搜索求解公共交通乘务调度问题

公共交通乘务调度问题是一个将车辆工作切分为一组合法班次的过程,它是NP难问题,许多求解方法的效率都与班次评价密不可分,本文通过裁剪TOPSIS方法(Technique for Order Preference by Similarity to an Ideal Solution)设计了TOPSIS班次评价方法.此外,通过裁剪变邻域搜索算法使之适合求解乘务调度问题,提出了基于变邻域搜索的乘务调度方法(Crew Scheduling Approach Based on Variable Neighbourhood Search,VNS),其中,并入了TOPSIS班次评价方法在调度过程中进行班次评价,设计了两种带概率的复合邻域结构以增加搜索的多样性,帮助跳出局部最优,在VNS中利用模拟退火算法进行局部搜索.利用中国公共交通中的11组实例进行了测试,测试结果表明,VNS优于两种新近提出的乘务调度方法,且其结果关于班次数接近于下界.     

基于混合选择模型的汽车共享选择行为研究

为了深入分析出行者的汽车共享选择行为,首先以技术接受模型和计划行为理论为框架,将对汽车共享选择行为具有影响的心理因素整合到传统的离散选择模型之中,形成混合选择模型.然后,基于南京市的实证调查数据,运用混合选择模型对出行者的汽车共享选择行为进行研究.结果表明,出行者对于汽车共享的感知有用性、感知易用性、行为态度、知觉行为控制等心理态度潜变量对其选择行为产生显著的正向影响,混合选择模型比传统不带潜变量MNL模型对实证数据具有更高的拟合度.     

A novel approach for the modelling of air quality dynamics in underground railway stations

Indoor air quality in subterranean train stations is a concern in many places around the globe. However, due to the specificity of each case, numerous parameters of the problem remain unknown, such as the braking discs particle emission rate, the ventilation rate of the station or the complete particle size distribution of the emitted particles. In this study the problem of modelling PM₁₀ concentration evolution in relation with train traffic is hence addressed with a particle-mass conservation model which parameters are fitted using a genetic algorithm. The parameters of the model allow to reproduce the dynamics and amplitude of four field data sets from the French and Swedish underground contexts and comply with realistic bounds in terms of emissions, deposition and ventilation rate.     

Evaluating the effects of green port policy: Case study of Kaohsiung harbor in Taiwan

The paper evaluates the effectiveness of strategies designed to reduce these pollutants in port areas, based on a newly developed assessment model to calculate emissions. The case study found that the strategy of reducing the ship’s speed to 12 knots is most effective in cutting fuel consumption and costs, as well as emissions. Adopting an onshore power supply system could reduce CO₂ emission by 57.16% and PM by 39.4%. By adopting the strategies of both reduced speed and cold ironing emissions control, a reduction in emissions of 71% to 91% can be achieved with a 20 nautical mile reduced speed zone. Therefore, the goals of reductions in emissions to improve port areas air quality could be achieved through adopting a green port policy in the future.     

快速路可变限速与匝道控制协同优化策略

可变限速控制和匝道控制是快速路交通控制的主要手段,本文对两者的协同优化策略进行了研究.借助智能车路协同系统强大的信息感知能力,通过引入微观交通流信息,对经典METANET模型进行了改造,构建了可变限速控制影响下的微观METANET模型,实现了一种新的可变限速控制策略,同时,采用ALINEA算法,对入口匝道进行了优化控制,实现了两者的协同优化.最后,基于实际道路和交通流数据搭建了仿真平台,对微观METANET模型和协同优化策略的有效性进行了验证.仿真结果表明,微观METANET模型具有良好的交通流预测效果,协同优化策略能有效地改善快速路交通流状态.     

船用厨房和具有烹调设备的配餐室的通风计算及空气处理方法

本文介绍了ISO 9943-2009国际标准和GBT 20846-2007中国国家标准中对船用厨房和具有烹调设备的配餐室的通风计算及空气处理中提出的送风量的计算方法，提出另一种更易于大家理解和接受的简易计算方法和空气处理过程，供工程技术及设计研究人员参考。     

新型负阶跃动态扭矩校准装置

针对扭矩传感器静态校准无法完全满足实际需要的难题,设计一种新型100 N·m负阶跃动态扭矩校准装置,并阐述该装置的工作原理和关键技术。校准装置由扭矩产生装置、连接系统、制动系统、信号处理控制系统和空气轴承系统组成,利用火工拔销器产生负阶跃动态扭矩,较大程度上降低负阶跃动态扭矩的下降时间,并采用空气轴承的支承方式提高动态扭矩的传递精度。通过对试验数据进行分析和处理,结果表明该装置负阶跃扭矩产生时间低于0.1 ms。不确定度分析结果显示,该装置的扩展不确定度U为4.22%,扩展因子k为2。