Motivating small-displacement car purchasing in China

Due to the rapid development of the automobile industry and the ever-increasing quantities of produced and sold automobiles in China, many problems such as fuel scarcity and air pollution have emerged. To alleviate such problems, one solution is to promote households to purchase small-displacement (engine) cars (SDCs). Based on the theory of planned behavior, we develop a theoretical framework to examine how influencing factors such as environmental attitude, subjective norm, self-image and environmental knowledge motivate SDC purchasing behavior through SDC purchasing intention in China. We further extend the research framework to examine whether the factor of economic incentives moderates the relationships between SDC purchasing intention and behaviors. Using an empirical study with 232 usable questionnaire responses, we observe that SDC purchasing intention partly mediates the relationship between three of four influencing factors (environmental attitude, self-image, environmental knowledge) and SDC purchasing behavior. Statistical results also show that the factor of economic incentives moderates the relationship between SDC purchasing intention and behavior. Our results indicate that three of four influencing factors can yield SDC purchasing behavior, especially when SDC purchasing intention exists. Economic incentives such as financial support from the government could promote SDC purchasing intention to transform into purchasing behavior.     

通信信号调制样式的自动识别

针对卫星通信信号中常用的数字信号调制样式的自动识别问题,提出一种基于人工神经网络（ArtificialNeuralNet,ANN）的识别算法,该算法在几乎没有先验信息的条件下,以几种调相信号为基本模型,通过双隐层人工神经网络获取频谱特征,进而判别出不同信号的调制样式。仿真及实测数据验证表明,该算法在低信噪比条件下,随着神经元组合数量的增加,数字调制样识别的正确率有明显提高。     

故障快速识别技术在电力系统保护中的应用

本文阐述了一种故障快速识别的技术,主要从直流传感器的选择,故障检测方法研究,滤波器的设计等方面对故障快速识别技术进行论述,提出了一种故障快速识别装置的实现方法,具有创新性,可操作性强,具有实用意义.     

A microscopic analysis of speed deviation impacts on lane-changing behavior

Driving behavior models that capture drivers’ tactical maneuvering decisions in different traffic conditions are essential to microscopic traffic simulation systems. This paper focuses on a parameter that has a great impact on road users’ aggressive overtaking maneuvers and directly affects lane-changing models (an integral part of microscopic traffic simulation models), namely, speed deviation. The objective of this research is to investigate the impacts of speed deviation in terms of performance measures (delay time, network mean speed, and travel time duration) and the number of lane-change maneuvers using the Aimsun traffic simulator. Following calibration of the model for a section of urban highway in Tehran, this paper explores the sensitivity of lane-changing maneuvers during different speed deviations by conducting two types of test. Simulation results show that, by decreasing speed deviation, the number of lane changes reduces remarkably and so network safety increases, thus reducing travel time due to an increase in network mean speed.     

Commuter impacts and behavior changes during a temporary freeway closure: the ‘Fix I-5’ project in Sacramento,California

One mile of Interstate 5 (I-5) in downtown Sacramento, California was closed intermittently for reconstruction (‘the Fix project’) over nine weeks in 2008. We analyze the impacts of the Fix on commuters’ travel behavior, as measured through two contemporaneous Internet-based surveys. The impacts of the Fix on traffic conditions do not appear to have been excessive: majorities in all relevant subsamples did not find conditions worse than usual, and sizable minorities actually found them to be better. Among the active changes to commute trips, the easiest options – avoiding rush hour and changing route – were the most common (adopted by 48% and 44%, respectively). Among the changes that reduced vehicle-miles traveled, increasing transit use and increasing telecommuting (TC) were the most common (each adopted by 5–6% of the relevant subsample). Binary logit models of these two choices suggest that persuading current adopters to increase their frequency of use is easier than convincing nonadopters to start TC or switch to transit. Women and those in larger households were found to be more likely to increase TC and transit use. Employer support of commute alternatives significantly influenced the adoption of both strategies.     

桥梁工程施工风险综合识别与评估方法

风险评估方法种类繁多,且各有优缺点,单一的方法无法满足实际的需求.根据桥梁工程施工的特点,提出了事故总结、结构分析、现场调研和专家调查四种方法相结合的桥梁施工风险综合识别方法,以及提出基于分级评判的桥梁施工风险综合评估方法.提出的桥梁施工风险综合识别与评估方法具有较强的实用性和有效性,可供桥梁工程施工风险评估参考.     

联网高速公路路径射频识别系统理论误差分析

射频技术是解决联网高速公路路径识别的一种可行技术.目前,国内已有个别省份采用该技术解决路径识别问题,但未进行国内大范围的推广.从射频设备的准确率、标识站点的设置方式、标识站与收费站的位置关系、收费站点间交通流分布等几个方面,分析整个识别系统中可能产生的理论误差,并引入综合误差度的概念对系统误差做统一标定.     

基于广义回归神经网络的磁流变减振器模型辨识

根据磁流变减振器的非线性特性,提出磁流变减振器广义回归神经网络(GRNN)模型辨识方法,利用台架试验获取的力学特性数据,建立磁流变减振器广义回归神经网络正、逆模型,并与反向传播神经网络(BPNN)模型进行比较.结果表明:通过合理选取网络变量并优化光滑因子,GRNN模型能准确预测磁流变减振器的阻尼力和控制电流,其正、逆模型辨识精度优于BPNN模型.此外,GRNN还具有结构简单、快速收敛等特点,为磁流变减振器的准确建模与控制提供了重要手段.     

基于云模型的城市快速路交通状态评价方法研究

交通状态具有模糊性和随机性的特点。基于北京市快速路检测线圈数据,引入了基于云模型的模糊系统来评价快速路交通状态。在充分分析交通流特性的基础上,提出了交通状态划分原则、依据,评价指标,以及基于云模型的模糊综合评价方法的算法流程。为实施交通信息发布以及后期交通状态的改善提供依据。最后,以北京市快速路系统为例,进行实证研究。     

城市快速路交通流特性分析

城市快速路是城市道路网的主骨架,对交通状态进行状态划分及稳定性分析,结合城市快速路交通信息采集系统的交通流检测数据,对速度一流量关系模型进行分析,建立了城市快速路快速交通流流量、速度、占有率关系模型,并进行交通流基本参数时变特性和空间特性分析。首先利用基本图理论,对3种城市快速路交通流状态进行稳定性分析。随后,结合北京市典型路段实测数据散点图,对各种速度一流量关系模型的适用范围和适用程度进行对比分析,从而得出Greenshields模型的拟合效果最好。最后分析交通状态转换过程中的交通流参数时变特性和空间特性,对实际交通疏导有指导意义。