Investigating heterogeneity in social influence by social distance in car-sharing decisions under uncertainty: A regret-minimizing hybrid choice model framework based on sequential stated adaptation experiments

The present study is designed to investigate social influence in car-sharing decisions under uncertainty. Social influence indicates that individuals’ decisions are influenced by the choices made by members of their social networks. An individual may experience different degrees of influence depending on social distance, i.e. the strength of the social relationship between individuals. Such heterogeneity in social influence has been largely ignored in the previous travel behavior research. The data used in this study stems from an egocentric social network survey, which measures the strength of the social relationships of each respondent. In addition, a sequential stated adaptation experiment was developed to capture more explicitly the effect of social network choices on the individual decision-making process. Social distance is regarded as a random latent variable. The estimated social distance and social network choices are incorporated into a social influence variable, which is treated as an explanatory variable in the car-sharing decision model. To simultaneously estimate latent social distance and the effects of social influence on the car-sharing decision, we expand the hybrid choice framework to incorporate the latent social distance model into discrete choice analysis. The estimation results show substantial social influence in car-sharing decisions. The magnitude of social influence varies according to the type of relationship, similarity of socio-demographics and the number of social interactions.     

LNG运输船作为浮式储存装置的适应性评估研究

采用OCIMF方法和水动力分析法,对3万方LNG运输船靠泊码头作为FSU适应性评估进行了研究,运用AQWA软件并结合码头实际情况对已有系泊方案进行了优化设计。从碰垫选型、系泊方案分析、总管与软管连接兼容性和设备维护保养等方面评估了该轮作为FSU的适应性,并结合船舶、码头实际配备情况提出相应的建议措施,为作为FSU安全作业提供保障。     

基于LMS算法的自适应前馈

作为通信系统核心器件的功率放大器的线性度直接影响了整个系统的通信质量,而前馈线性化技术综合性能较好,一直以来都是研究的热点.论文基于自适应前馈电路的原理,引入了一种改进的LMS算法,通过计算机软件仿真,表明该算法可以很好地改善系统的线性度.     

语用顺应论在口译介绍语类中的研究

语言顺应论认为语言的使用即选择。语言的使用要顺应不同的交际对象和环境。本文从顺应论的四个角度,即:语言的语境顺应、语言结构顺应、动态顺应以及顺应过程的突显性,探讨了介绍语类的口译过程。在这个过程中,译员要动态地选择顺应对象和口译策略,最大限度地实现相应的语言顺应。     

Intelligent speed adaptation: Preliminary results of on-road study in Penang,Malaysia

The first field experiment with intelligent speed adaptation (ISA) in Malaysia was held in December 2010 in the State of Penang. Eleven private cars were instrumented with an advisory system. The system used in the present study included a vocal warning message and a visual text message that is activated when the driver attempts to exceed the speed limit. When the driver decreases the speed, the warning stops; otherwise it is continuously repeated. The test drivers drove the vehicles for three months with the installed system, and the speed was continuously logged in all vehicles. The warning was however only activated in the second month of the three month period. The present study aimed to evaluate the effects of an advisory ISA on driving speed, traffic safety, and drivers' attitude, behavior, and acceptance of the system. To examine these effects, both the survey and the logged speed data were analyzed and explored. The results show a significant reduction in the mean, maximum and 85th percentile speed due to the use of the system. However, there was no long-lasting effect on the speed when the system was deactivated. In the post-trial survey, drivers declared that the system helped them well in following the speed limits and that it assisted them in driving more comfortably. Furthermore, the warning method was more accepted compared to a supportive system, such as active accelerator pedal (AAP). After the trial, most drivers were willing to keep an ISA system.     

Exploring the Knowledge Dynamics Associated with Coastal Adaptation Planning

Scientific projections for climate change induced sea-level-rise highlight current and potential future consequences for low lying coastal areas. In response considerable attention has been directed toward the task of coastal adaptation planning. Experience to date indicates that adaptation planning is more complex and contested than anticipated. We argue that this is partly due to the constrained way adaptation planning is conceptualized, whereby limited attention is directed toward understanding coastal adaptation planning as a site of complex and contested knowledge dynamics. Consequently, we use a knowledge systems perspective to explore coastal adaptation planning in order to highlight some of the knowledge exchange dynamics involved. In doing so we draw on views expressed in semi-structured interviews with a diverse range of stakeholders with an interest in coastal management in Victoria, Australia. While the focus is on coastal adaptation planning in Victoria, the insights generated are intended to contribute to broadening the way in which adaptation is conceptualized.     

基于视觉适应性的公路隧道限速研究

通过分析隧道对驾驶员视觉、心理的影响,得出车辆通过隧道时车速的变化情况,进而确定了隧道限速段的长度。利用瞳孔面积变化速度与行车安全关系的定量分析,得出基于视觉适应能力的隧道进出口安全行车的临界速度,结合车辆在隧道限速段内的速度变化情况及隧道本身条件确定了保证行车安全的隧道限速值。     

基于改进的BP人工神经网络的物流需求规模预测

为了对物流需求规模进行准确预测,探讨了用于物流需求规模预测的经济指标和物流需求规模的度量指标,再应用粗糙集理论、适应度函数和BP人工神经网络理论建立了用于物流需求规模预测的模型,即改进的BP人工神经网络模型。该模型首先应用粗糙集对BP人工神经网络的输入层进行指标知识约简,以减少BP人工神经网络的复杂度,再在BP人工神经网络中引入适应度函数,以克服传统BP人工神经网络算法易陷入局部最优、训练速度较慢等缺陷,最后,将该模型应用在案例分析中。结果表明,该模型使预测精度得到很大提高;该方法为以后物流需求规模的预测提供了一种新的思路和方法。     

Energy and emissions impacts of a freeway-based dynamic eco-driving system

Surface transportation consumes a vast quantity of fuel and accounts for about a third of the US CO₂ emissions. In addition to the use of more fuel-efficient vehicles and carbon-neutral alternative fuels, fuel consumption and CO₂ emissions can be lowered through a variety of strategies that reduce congestion, smooth traffic flow, and reduce excessive vehicle speeds. Eco-driving is one such strategy. It typically consists of changing a person’s driving behavior by providing general static advice to the driver (e.g. do not accelerate too quickly, reduce speeds, etc.). In this study, we investigate the concept of dynamic eco-driving, where advice is given in real-time to drivers changing traffic conditions in the vehicle’s vicinity. This dynamic strategy takes advantage of real-time traffic sensing and telematics, allowing for a traffic management system to monitor traffic speed, density, and flow, and then communicates advice in real-time back to the vehicles. By providing dynamic advice to drivers, approximately 10–20% in fuel savings and lower CO₂ emissions are possible without a significant increase in travel time. Based on simulations, it was found that in general, higher percentage reductions in fuel consumption and CO₂ emission occur during severe compared to less congested scenarios. Real-world experiments have also been carried out, showing similar reductions but to a slightly smaller degree.