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.     

Adoption of alternative fuel vehicles: Influence from neighbors,family and coworkers

During the last years, many governments have set targets for increasing the share of biofuels in the transportation sector. Understanding consumer behavior is essential in designing policies that efficiently increase the uptake of cleaner technologies. In this paper we analyze adopters and non-adopters of alternative fuel vehicles (AFVs). We use diffusion of innovation theory and the established notion that the social system and interpersonal influence play important roles in adoption. Based on a nationwide database of car owners we analyze interpersonal influence on adoption from three social domains: neighbors, family and coworkers. The results point primarily at a neighbor effect in that AFV adoption is more likely if neighbors also have adopted. The results also point at significant effects of interpersonal influence from coworkers and family members but these effects weaken or disappear when income, education level, marriage, age, gender and green party votes are controlled for. The results extend the diffusion of innovation and AFV literature with empirical support for interpersonal influence based on objective data where response bias is not a factor. Implications for further research, environmental and transport policy, and practitioners are discussed.     

Liner shipping network design with emission control areas: A genetic algorithm-based approach

To curb emissions, containerized shipping lines face the traditional trade-off between cost and emissions (CO₂ and SO_x) reduction. This paper considers this element in the context of liner service design and proposes a mixed integer linear programming (MILP) model based on a multi-commodity pickup and delivery arc-flow formulation. The objective is to maximize the profit by selecting the ports to be visited, the sequence of port visit, the cargo flows between ports, as well as the number/operating speeds of vessels on each arc of the selected route. The problem also considers that Emission Control Areas (ECAs) exist in the liner network and accounts for the vessel carrying capacity. In addition to using the MILP solver of CPLEX, we develop in the paper a specific genetic algorithm (GA) based heuristic and show that it gives the possibility to reach an optimal solution when solving large size instances.     

桨-舵间距对其组合系统水动力性能的影响

本文通过CFD方法对敞水桨、桨-舵组合以及优化间距的桨-舵组合装置开展了数值仿真研究，分析了桨-舵间距对其组合系统的水动力性能影响。螺旋桨敞水工况的计算值与物理模型试验值吻合良好，验证了数值计算方法的可行性。通过对比桨-舵间距大于推荐值的三个工况，发现在较低进阶系数下系统的节能效率有稍许增加，然而随着间距的增大，节能效率呈现降低的趋势；在高进阶系数下，随间距增大节能效率逐步降低。适当减小桨-舵间距，在较低和中等进阶系数下，随间距减小节能效率呈现逐步升高的趋势，在间距减少10mm时，组合体的节能效率最大可增加1.937%；不过在高进阶系数下，随间距减小节能效率却有下降趋势。     

基于CFD的中低速Wigley船模黏性阻力

船舶阻力性能对船型参数的确定、船体结构的设计有重要影响。本文以Wigley船模为研究对象，采用CFD方法建立了行船阻力分析系统，以实际海况数据为依据，确定较准确的参数和边界条件，分析了不同航速（傅汝德数）下的低速行船阻力，并与理论公式对比分析。仿真测试结果表明：在实际海况数据下，CFD数值模拟阻力与理论ITTC公式计算的阻力误差在2%以内且发展趋势一致。本文的研究为采用CFD研究行船阻力奠定基础。     

Extreme hawser tension assessment for FPSO vessel during offloading operation in Bohai bay

The Floating Production Storage and Offloading Unit (FPSO) is an offshore vessel that produces and stores crude oil prior to tanker transport.Robust prediction of extreme hawser tensions during Floating Production Storage and Offloading (FPSO) operation is an important safety concern. Excessive hawser tension may occur during offloading operations, posing an operational risk. In this paper, AQWA has been used to analyze vessel response due to hydrodynamic wave loads, acting on a specific FPSO vessel under actual sea conditions. Experimental validation of numerical results has been discussed as well.This paper advocates methodology for estimating extreme response statistics, based on simulations (or measurements). The modified ACER (averaged conditional exceedance rate) method is presented in brief detail. Proposed methodology provides an accurate extreme value prediction, utilizing all available data efficiently. In this study the estimated return level values, obtained by ACER method, are compared to the corresponding return level values obtained by Gumbel method. Based on the overall performance of the proposed method, it is concluded that the improved ACER method can provide more robust and accurate prediction of the extreme hawser tension.Data declustering issue has been addressed. Paper highlights ability of ACER method to account for a set of varying sea state probabilities, as required in engineering long term statistical analysis.Described approach may be well used at the vessel design stage, while defining optimal vessel parameters that would minimize potential FPSO hawser tension.     

Competitiveness of container terminal operating companies in South Korea and the industry–university–government network

Burgeoning container port facilities have fostered intensified competition among container terminal operating companies (CTOCs). However, despite research into their survival strategies which identified antecedents of competitiveness including hard factors such as facilities, available cargo and cargo processing ability, softer factors spanning human resource management, networks and strategic alliances with universities and government agencies in industry–university–government (I–U–G) networks have been overlooked. This study aims to examine both hard and softer antecedents of competitiveness as perceived by 152 professionals in South Korean CTOCs; empirical relationships among these antecedents, I–U–G networks, and competitiveness itself; and the significance of the I–U–G network in establishing and improving competitiveness. Posited antecedents of competitiveness included human resources, facilities, service quality, customer orientation, reputation, and government support policy as independent variables; the I–U–G network as a moderating variable; and competitiveness as a dependent variable. Empirical structural relationships revealed that excepting government support policy, each variable significantly affected CTOC competitiveness. Further, the I–U–G network moderated the relationships between the antecedents of competitiveness and competitiveness. Because an effective I–U–G network was pivotal in controlling CTOC competitiveness, improved competitiveness requires not only differentiation of human resources, facilities, service quality, customer orientation, and reputation factors but also I–U–G network developments.     

Controller design for gating traffic control in presence of time-delay in urban road networks

Recent studies demonstrated the efficiency of feedback-based gating control in mitigating congestion in urban networks by exploiting the notion of macroscopic or network fundamental diagram (MFD or NFD). The employed feedback regulator of proportional-integral (PI)-type targets an operating NFD point of maximum throughput to enhance the mobility in the urban road network during the peak period, under saturated traffic conditions. In previous studies, gating was applied directly at the border of the protected network (PN), i.e. the network part to be protected from over-saturation. In this work, the recently developed feedback-based gating concept is applied at junctions located further upstream of the PN. This induces a time-delay, which corresponds to the travel time needed for gated vehicles to approach the PN. The resulting extended feedback control problem can be also tackled by use of a PI-type regulator, albeit with different gain values compared to the case without time-delay. Detailed procedures regarding the appropriate design of related feedback regulators are provided. In addition, the developed feedback concept is shown to work properly with very long time-steps as well. A large part of the Chania, Greece, urban network, modelled in a microscopic simulation environment under realistic traffic conditions, is used as test-bed in this study. The reported results demonstrate a stable and efficient behaviour and improved mobility of the overall network in terms of mean speed and travel time.     

Evaluating determinants of attractiveness and their cause-effect relationships for container ports in Taiwan: users’ perspectives

The attractiveness of ports is usually a pre-requisite and necessary condition for ports to achieve competitiveness, as well as the springboard to explore the competitive advantages of ports. To determine whether a port is competitive, it is necessary to explore whether it boasts certain factors that make the port attractive to users. The main purpose of this article is to apply the Analytic Hierarchy Process (AHP) method and the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique to evaluate key determinants of attractiveness and their cause/effect relationships for container ports in Taiwan. The empirical results showed that: (1) Top six determinates of attractiveness for container ports are ‘ample cargo sources,’ ‘favorable port charges,’ ‘dense ship network and routes,’ ‘low transshipment costs,’ ‘efficient wharf operations,’ and ‘adequate wharfs and back-line land,’ respectively. (2) Among the above six determinants of attractiveness, ‘ample cargo sources’ is the cause determinant. Three determinants of port attractiveness, ‘favorable port charges,’ ‘dense ship network and routes,’ ‘low transshipment costs,’ which are the effect determinants. They are affected by the determinants of attractiveness of ‘ample cargo sources’. In addition, this study discusses the above findings and expects to provide the study results to Taiwan’s port authorities for reference.     

基于光纤传感系统的德国列车实时精确定位技术

实时、精确地获取列车位置信息是保证列车安全有效运行、发挥效率、提供最佳服务的前提。而轨旁传感器将在进行高效、可靠的列车跟踪和定位方面发挥重要作用。文章介绍德国基于光纤传感系统的列车实时精确定位技术,这是一种全新的解决方案,具有独特的优势和可能性。