识别驾驶人意图的车道偏离防避有界控制

为了防止车辆偏离车道导致交通事故的发生和避免车道偏离防避系统（Lane Departure Avoidance Systems,LDAS）对驾驶人行为不必要的干预,提出基于中心区操纵特性阈值法和基于D-S（Dempster-Shafer）证据理论的车辆偏离车道驾驶人意图识别准则,并运用CarSim/Simulink联合仿真对比2种识别准则的有效性。建立转向盘角速度为输入的车路模型,设计LDAS滑模转向控制器,基于预瞄点的侧向偏移量和横摆角速度设计LDAS的期望横摆角速度观测器,并与基于道路曲率和预瞄点侧向偏移量的期望横摆角速度的LDAS进行性能对比。运用相平面法确定保证LDAS车辆稳定性的前轮转向角最大值,并基于CarSim/LabVIEW RT硬件在环试验平台验证基于BP神经网络训练获得D-S证据理论的初始概率赋值的驾驶人意图决策算法的有效性。结果表明：所提出的识别准则能够及时识别车辆偏离车道时的驾驶人意图,为LDAS控制器介入赢得了宝贵的时间,所设计的期望横摆角速度观测器具有很好的稳定性,所提出的方法能够有效避免车辆偏离车道。     

石灰粉煤灰混合料强度形成机理及提高早期强度的措施

分析石灰粉煤灰混合料强度的形成机理,并通过理论分析说明提高石灰粉煤灰混合料早期强度的措施,有助于归纳提高石灰粉煤灰混合料早期强度机理的方法。     

不同信息下的逐日路径选择行为实验与模型

为研究先进出行者信息系统(ATIS)对出行者逐日路径选择行为的影响,本文基于 Braess路网设计5组具有不同ATIS市场占有率(0、25%、50%、75%、100%)的行为实验.结果表明：3条路径的流量及新增路径保持选择的次数持续波动,随着ATIS市场占有率增大,路网平均行程时间趋于用户均衡,新增路径保持选择的次数呈现增长趋势,且被试对新增路径的选择性偏好增强,Braess悖论的效果也更明显.基于5组实验数据,分别建立普通Logit模型和基于面板数据的随机效应Logit模型刻画路径选择行为.结果表明：当ATIS市场占有率为0时,最佳模型为普通Logit模型;当ATIS市场占有率增大甚至达到100%时,最佳模型均为随机效应Logit模型;未配备ATIS的出行者的个体差异性比配备ATIS的小.     

铁路旅客感知的列车服务质量实证研究

探讨铁路客运列车旅客感知服务质量的构成与维度,及其与旅客感知消费价值、旅客满意度、旅客再乘意向以及正面口头传播意向之间的关系。本文以乘坐广深铁路"和谐号"列车的旅客为对象,共收集149份有效问卷,采用结构方程模型分析技术对数据进行分析。研究结果表明:旅客感知的列车服务质量包含3个维度,即硬质量、软质量、列车上所售商品质量;旅客感知的列车服务质量、票价合理性、列车旅行速度对旅客感知的消费价值有显著的正向影响;旅客感知的消费价值对旅客满意度有显著的正向影响;旅客满意度正向影响旅客的再乘意向及其正面口头传播意向。     

Assessing the impact of long-term mobility choice motivation and short-term mobility means connotation on the use intention of electric cars in rural areas

In this study several hypotheses comprising a heuristic framework derived from rational-choice (RC) premises and regarding some potentially influencing variables on future use intention of different vehicle types are tested with a rural area sample. Especially the differentiation between long-term vs. short-term as well as functional/rational vs. extra-functional/emotional motivators is assessed. Results suggest a predominance of functional motivators and rational connotations over extra-functional/emotional ones. The models to check whether short-term or long-term effects dominate did not clearly confirm a predominance of long-term factors as hypothesized. In several regression models a moderating effect of rational short-term connotations on different long-term motivators was found, thus contributing notably to the prediction of future vehicle use-intention. The need for further research and theory-driven modeling is briefly discussed.     

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.     

Relationships among service quality,corporate image,customer satisfaction,and behavioral intention for the elderly in high speed rail services

Since the Taiwan High Speed Rail operations, Taiwan's transportation market entered into a new era. Because of its competitive service of speed, convenience, environmental concerns and comfort, the High Speed Rail has not only made significant changes but has played a significant role in Taiwan's transportation. However, Taiwan now is an aging society. Due to the physical constraints among the elderly, demands to redesign the traffic system and maintain transportation safety are essential considerations. In the current market, Taiwan's transportation construction is facing fewer barriers; however, it must still improve, especially considering the health of the elderly. Thus, this study investigates elderly passengers' demands and further examined the relationships among service quality, corporate image, customer satisfaction, and behavioral intention. According to empirical analytical results based on structural equation modeling (N = 341), satisfaction directly affected travel behaviors, while service quality and corporate image played indirect roles. In addition, service quality plays a significant role on the effect of satisfaction. This study provides empirical evidence to indicate the quality of the accessible environment affects not only the effectiveness and efficiency of service quality, but also, the corporate image. The results provide valuable references for critically managing the elderly's usage of the high speed rail transportation service. Copyright © 2011 John Wiley & Sons, Ltd.     

论言外行为在大学英语教学中的运用

在英语教学中,学生往往只理解句子的表面意思,却不理解句子的言外之意,不能通过言内和言外的连贯作用把文章的深层含义理解透彻;而老师由于时间关系,可能无法详细讲解言外行为在英语中的作用,从而师生都忽视它的作用.本文从理论和实践相结合的角度分析言外行为在英语教学中的作用.     

面向混合交通流的智能网联车鸣笛意图识别模型

为使混合交通流(Mixed Traffic Stream，MTS)下智能网联车(Intelligent Connected Vehicle，ICV)实现鸣笛意图(Horn’s Intention，HI)识别，更好地遵循常规车辆(Manual Vehicle， MV)的驾驶意图，提出ICV 对MV 鸣笛声的“ 感知(Perception) — 定位(Location) — 识别 (Recognition)”模型(简称HI-PLR)，采用深度卷积—循环神经网络(Deep Convolution Recurrent Neural Network, DCRNN)算法感知鸣笛车辆(Horning Vehicles, HV)的鸣笛声；采用到达时差 (Time Difference of Arrival, TDOA)算法定位HV；再基于运动时间窗(Motion Time Window, MTW)的支持向量机(Support Vector Machine, SVM)算法识别HI.实验结果表明，HI-PLR可使 ICV 对混流中车辆的鸣笛声感知准确率达90.4%，定位角度估计误差小于5°，HI 识别率达 82.5%，为ICV在MTS中的智能驾驶决策提供依据.