EFD and CFD for KCS heaving and pitching in regular head waves

The KCS container ship was investigated in calm water and regular head seas by means of EFD and CFD. The experimental study was conducted in FORCE Technology’s towing tank in Denmark, and the CFD study was conducted using the URANS codes CFDSHIP-IOWA and Star-CCM+ plus the potential theory code AEGIR. Three speeds were covered and the wave conditions were chosen in order to study the ship’s response in waves under resonance and maximum exciting conditions. In the experiment, the heave and pitch motions and the resistance were measured together with wave elevation of the incoming wave. The model test was designed and conducted in order to enable UA assessment of the measured data. The results show that the ship responds strongly when the resonance and maximum exciting conditions are met. With respect to experimental uncertainty, the level for calm water is comparable to PMM uncertainties for maneuvering testing while the level is higher in waves. Concerning the CFD results, the computation shows a very complex and time-varying flow pattern. For the integral quantities, a comparison between EFD and CFD shows that the computed motions and resistance in calm water is in fair agreement with the measurement. In waves, the motions are still in fair agreement with measured data, but larger differences are observed for the resistance. The mean resistance is reasonable, but the first order amplitude of the resistance time history is underpredicted by CFD. Finally, it seems that the URANS codes are in closer agreement with the measurements compared to the potential theory.     

Are Longer and Heavier Vehicles (LHVs) Beneficial for Society? A Cost Benefit Analysis to Evaluate their Potential Implementation in Spain

Abstract

In this paper we carry out a thorough review of the current research related to the benefits and costs arising from the implementation of longer and heavier vehicles (LHVs). From this review we concluded that despite the many studies available, little has been said about the sensitivity of the benefits and costs to the ultimate performance of the key variables related to the evolution of the economy, road transport performance, safety, and so on. In order to fill this gap, we have designed a sensitivity approach based on a cost benefit analysis tool to determine which variables demonstrate the greatest influence on the benefits and costs stemming from the implementation of LHVs. In order to test the methodology, we have used it in an analysis of the Spanish trunk network. The results show that the benefits of LHVs for society are significant. Even in the least favorable scenario, the economic benefits are greater than €3500 million over 15 years, and the environment enhanced as well, for CO₂ emissions are reduced by 2 Million tonnes. Overall we noted how the results are not very sensitive to the evolution of key variables in determining the final outcome. However, we found that the variables that have the greatest affect on the final benefit, such as traffic growth and social discount rate, depend basically on the performance of the overall economy. Moreover, the private cost for haulers seems to be more important in determining the final benefit than externality costs.     

A Modeling Framework for Bus Rapid Transit Operations Evaluation and Service Planning

Abstract

In this paper, we present a dynamic traffic assignment-simulation modeling framework (DYNASMART-P) to support the evaluation and planning of Bus Rapid Transit (BRT) services in urban transportation networks. The model represents the different characteristics associated with BRT operations such as: exclusive right-of-way lanes, limited-stop service, signal prioritization at congested intersections, and enhanced bus stops to reduce passenger boarding times. A set of simulation experiments is conducted using the model to study the impact of introducing a hypothetical BRT service in the Knoxville area in the State of Tennessee. In these experiments, the different operational characteristics of BRT are evaluated in terms of potential impact on transit ridership and on the interacting auto traffic. The results illustrate the advantages of BRT for increasing transit ridership and improving overall system performance.     

Optimization of Fare Structure and Service Frequency for Maximum Profitability of Transit Systems

Abstract

Providing efficient public transportation has been recognized as a potential way of alleviating congestion, improving mobility, mitigating air pollution, and reducing energy consumption. Many people use public transportation systems for their daily commute, while others use different transportation modes (e.g. cars, taxis, carpools, etc.). Inexpensive fares with good transit service encourages ridership, and the resulting revenue may be used to provide better service. Optimization of transit service frequency and its associated fare structure is desirable in order to increase revenue at reasonable transit operating expenditure. The objective of the study reported here is to maximize profit subject to service capacity constraint, while elastic demand is considered. The solution methodology is developed and applied to solve the profit maximization problem in a case study based on Newark, NJ, USA. Numerical results, including optimal solutions and sensitivity analyses, are presented. It is found that an optimal temporal headway and differential fare structure that maximizes total profit for the studied subway system can be efficiently solved.     

In-vehicle technology for self-driving cars: Advantages and challenges for aging drivers

The development of self-driving cars or autonomous vehicles has progressed at an unanticipated pace. Ironically, the driver or the driver-vehicle interaction is a largely neglected factor in the development of enabling technologies for autonomous vehicles. Therefore, this paper discusses the advantages and challenges faced by aging drivers with reference to in-vehicle technology for self-driving cars, on the basis of findings of recent studies. We summarize age-related characteristics of sensory, motor, and cognitive functions on the basis of extensive age-related research, which can provide a familiar to better aging drivers. Furthermore, we discuss some key aspects that need to be considered, such as familar to learnability, acceptance, and net effectiveness of new in-vehicle technology, as addressed in relevant studies. In addition, we present research-based examples on aging drivers and advanced technology, including a holistic approach that is being developed by MIT AgeLab, advanced navigation systems, and health monitoring systems. This paper anticipates many questions that may arise owing to the interaction of autonomous technologies with an older driver population. We expect the results of our study to be a foundation for further developments toward the consideration of needs of aging drivers while designing self-driving vehicles.     

A long panel survey to elicit variation in preferences and attitudes in the choice of electric vehicles

This paper describes the methodology we set up to gather appropriate data to study the impact of real life experience with electric vehicles (EVs) over a relatively long period of time on individual preferences and attitudes. We used stated choices (SC) to elicit individual preferences because EVs and their associated charging infrastructure are not yet fully integrated onto the market. Furthermore, to measure the extent to which the experience of using an EV may affect individual preferences and attitudes, we set up a “long panel” survey, where data was gathered before and after individuals experienced an EV in real life during a three-month period. We also measured attitudinal effects (AE) that might affect the choice of an EV by individuals. To our knowledge, this represents the first example of a “long panel” SC/AE and the first attempt to measure the formation of preferences and attitudes for this emerging product. Our results show that preferences and attitudes are indeed affected by real life experience. In the SC experiment, the respondents only chose the EV half as often as compared to the situation where they had not yet tried it. Furthermore, we measured a change in attitude for statements regarding the use of EVs. On the whole, respondents got a more positive view of the EV driving performance and this change is significantly greater for women than for men. However, respondents expressed more concern about being able to maintain current mobility with an EV. The data gathered in this survey should also serve to analyse the changes generated by direct experience with EVs, and eventually to formulate and estimate advanced discrete choice models that allow insights into factors relevant for improved understanding of market behaviour.     

Development of an intelligent CAE system for auto-body concept design

The concept design phase is a critical step in auto-body design, as it has a great effect on later design work. This paper describes the implementation of an auto-body structure design in the early stages of a new auto-body developing program. In order to reduce the long design period and analysis error that plagues traditional auto-body concept design, an intelligent CAE system has been successfully developed and implemented based on the UGS NX/API opening platform. This system, the so-called ACD-ICAE (Auto-body concept design-intelligent computer aided engineering) System that means concept design-intelligent computer aided engineering system, employs a fully parametrized template method to build the conceptual auto-body geometry model and FEM model quickly and easily. It also integrates auto-body modeling, analysis and optimization on only one CAD platform via a parametric variables database. Moreover, all parametric variables are shared and updated in different phases of the ACD-ICAE System. A wizard User Interface (UI) based on knowledge of auto-body engineering was developed and used in this system. The procedures implementing the functional diagram of the ACD-ICAE system are also provided. A typical example of a car body concept design with four doors shows that the ACD-ICAE system is efficient and accurate.     

区域公共物流中心规模和选址问题

阐述了中国发展区域公共物流中心（Region Public Logistics Center,RPLC)的必要性和必然性,即区域经济的发展将增加不同区域间的物流量,同时它也会大大促进城市化进程,从而产生区域内部的交通和环境问题,进而限制区域经济的发展和降低人民的生活质量,RPLC的建设有益于形成高效的物流系统体系和有利于信息流的管理利用。给出了优化RPLC规模和选址的数学模型,并采用非线性规划和排队理论对模型进行了推导,最后给出了求解该问题的遗传模拟退火算法和应用实例。     

Getting the best of both worlds: a framework for combining disaggregate travel survey data and aggregate mobile phone data for trip generation modelling

Transportation - Traditional approaches to travel behaviour modelling primarily rely on household travel survey data, which is expensive to collect, resulting in small sample sizes and infrequent...