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.     

Integrated optimization of bus priority operations in connected vehicle environment

Most previous works associated with transit signal priority merely focus on the optimization of signal timings, ignoring both bus speed and dwell time at bus stops. This paper presents a novel approach to optimize the holding time at bus stops, signal timings, and bus speed to provide priority to buses at isolated intersections. The objective of the proposed model is to minimize the weighted average vehicle delays of the intersection, which includes both bus delay and impact on nearby intersection traffic, ensuring that buses clear these intersections without being stopped by a red light. A set of formulations are developed to explicitly capture the interaction between bus speed, bus holding time, and transit priority signal timings. Experimental analysis is used to show that the proposed model has minimal negative impacts on general traffic and outperforms the no priority, signal priority only, and signal priority with holding control strategies (no bus speed adjustment) in terms of reducing average bus delays and stops. A sensitivity analysis further demonstrates the potential of the proposed approach to be applied to bus priority control systems in real‐time under different traffic demands, bus stop locations, and maximum speed limits. Copyright © 2016 John Wiley & Sons, Ltd.     

Balanced strategy based on environment and user benefit-oriented carpooling service mode for commuting trips

Transportation - Besides saving money and providing convenience, carpooling can result in environmental benefits to society; therefore, it is important to promote and improve daily carpooling...     

低温热棒的检测

阐述热棒的工作原理以及在青藏铁路多年冻土区的应用。就热棒的主要检测内容进行了讨论,并对其修改完善提出了建议。     

戈壁铁路沿线风沙灾害特征与挡风沙措施及功效研究

为了掌握戈壁地区线路积沙规律以及戈壁地区铁路既有风沙防治工程措施的功效与不足,对新疆戈壁地区铁路沿线戈壁风沙地貌、线路沙害的表现形式、既有防风沙流工程措施功效进行实地调查分析与现场测试。根据戈壁铁路强风现场测试数据计算大风速率残余系数和遮蔽效应系数,分析挡风墙后的风速剖面变化与流场变化特征。结果表明:对于同一高度挡风墙,其遮蔽效应随着墙后距离的增加逐渐减弱,高点位高程的速度衰减快于低点位高程的风速衰减,3 m高挡风墙在墙后距离5 m以内存在低速涡旋积沙区;根据计算,当平均风速不大于41 m.s-1且上风区没有新的沙源补充时,通常设置的3 m高挡风墙基本可以阻挡风沙流的运动。     

船公司怎样实施和完善SMS

随着ISM规则的实施,船公司为满足这一国际强制性规则的要求,投入了大量的人力、物力以建立和完善自己的SMS.应当说,规则给船公司提高船舶安全和防止污染管理水平带来了机遇,但同时也提出了新的挑战.笔者想结合本公司的实际情况,就如何建立和完善SMS,促进安全管理,谈些想法.     

Short-Term Traffic Flow Forecasting for Freeway Incident-Induced Delay Estimation

Freeway incidents not only threaten travelers’ safety but also cause severe congestion. Incident-induced delay (IID) refers to the extra travel delay resulting from incidents on top of the recurrent congestion. Quantifying IID would help people better understand the real cost of incidents, maximize the benefit-cost ratio of investment on incident remedy actions, and develop active traffic management and integrated corridor management strategies. By combining a modified queuing diagram and short-term traffic flow forecasting techniques, this study proposes an approach to estimate the temporal IID for a roadway section, given that the incidents occurs between two traffic flow detectors. The approach separates IID from the total travel delay, estimates IID for each individual incident, and only takes volume as input for IID quantification, avoiding using speed data that are widely involved in previous algorithms yet are less available or prone to poor data quality. Therefore, this approach can be easily deployed to broader ranges where only volume data are available. To verify its estimation accuracy, this study captures two incident videos and extracts ground-truth IID data, which is rarely done by previous studies. The verification shows that the IID estimation errors of the proposed approach are within 6% for both cases. The approach has been implemented in a Web-based system, which enables quick, convenient, and reliable freeway IID estimation in the Puget Sound region in the state of Washington.     

边坡工程常用稳定性分析方法

本文对目前边坡工程中常用的一些稳定性分析方法进行了系统的总结,对它们各自的主要原理、特点及其优缺点等进行了阐述,为实际工程的边坡稳定性计算提供了指导意义。     

Short-term prediction of vehicle waiting queue at ferry terminal based on machine learning method

Ferry service plays an important role in several cities with waterfront areas. Transportation authorities often need to forecast volumes of vehicular traffic in queues waiting to board ships at ferry terminals to ensure sufficient capacity and establish schedules that meet demand. Several previous studies have developed models for long-term vehicle queue length prediction at ferry terminals using terminal operation data. Few studies, however, have been undertaken for short-term vehicular queue length prediction. In this study, machine learning methods including the artificial neural network (ANN) and support vector machine (SVM) are applied to predict vehicle waiting queue lengths at ferry terminals. Through time series analysis, the existence of a periodic queue-length pattern is established. Hence, methodologies used in this study take into account periodic features of vehicle queue data at terminals for prediction. To further consider the cyclical characteristics of vehicle queue data at ferry terminals, a prediction approach is proposed to decompose vehicle waiting queue length into two components: a periodic part and a dynamic part. A trigonometric regression function is introduced to capture the periodic component, and the dynamic part is modeled by SVM and ANN models. Moreover, an assembly technique for combining SVM and ANN models is proposed to aggregate multiple prediction models and in turn achieve better results than could be attained from a lone predictive method. The prediction results suggest that for multi-step ahead vehicle queue length prediction at ferry terminals, the ensemble model outperforms the separate prediction models and the hybrid models, especially as prediction step size increases. This research has important practical significance to both traffic service management interests and the travelers in cities along waterfront areas.