Incorporating the extended theory of planned behavior in a school travel mode choice model: a case study of Shaoxing,China

Travel to and from school can have social, economic, and environmental implications for students and their parents. Therefore, understanding school travel mode choice behavior is essential to find policy-oriented approaches to optimizing school travel mode share. Recent research suggests that psychological factors of parents play a significant role in school travel mode choice behavior and the Multiple Indicators and Multiple Causes (MIMIC) model has been used to test the effect of psychological constructs on mode choice behavior. However, little research has used a systematic framework of behavioral theory to organize these psychological factors and investigate their internal relationships. This paper proposes an extended theory of planned behavior (ETPB) to delve into the psychological factors caused by the effects of adults’ cognition and behavioral habits and explores the factors’ relationship paradigm. A theoretical framework of travel mode choice behavior for students in China is constructed. We established the MIMIC model that accommodates latent variables from ETPB. We found that not all the psychological latent variables have significant effects on school travel mode choice behavior, but habit can play an essential role. The results provide theoretical support for demand policies for school travel.     

Does crowding affect the path choice of metro passengers?

This paper investigates crowding effect on the path choice of metro passengers. We show people reroute not only to avoid the delay from crowding but also to evade crowding itself. More specifically, a logit model fits best when it uses the transit delay from crowding as well as the passenger load of a connection in addition to the conventional explanatory variables. Also, we demonstrate that crowding decreases the overall welfare of metro passengers. The model is tested on the real path choice data acquired by the recent algorithm by Hong et al. (2015) known to detect the real path choice from Smart Card data in more than 90% of the cases.     

大跨度钢箱梁斜拉桥中跨合龙关键技术

以4座主跨超过400 m的钢箱梁斜拉桥中跨合龙控制为背景,对大跨度钢箱梁斜拉桥中跨合龙的2种方法进行对比分析,对合龙各主要工序的关键技术进行研究。提出了合龙段配切长度的计算公式和合龙口宽度连续观测的测点布置方式。建议:在调整好合龙口姿态后可不加压重,也可不采用临时劲性骨架锁定;采用无线采集设备采集合龙口结构的温度场,用激光测距仪测量合龙口宽度以提高观测效率和安全性;在悬臂施工阶段关注梁长累计误差并通过调整后续梁段的制造长度消除之。     

Local joint flexibility of tubular X-joints stiffened with external ring or external plates

In the present paper, the Local Joint Flexibility (LJF) of the ring-stiffened X-joints and plate-stiffened X-joints under compressive load is investigated. In the first phase, a finite element (FE) model was generated and verified with the results of available experimental tests and equations. In the next phase, a set number of 234 FE models were created to evaluate the role of the external ring size (β_r and τ_r), the external plate size (β_p and τ_p), and the connection geometry (γ, τ, and β) on the LJF factor (f_LJF). In these FE models, the weld connecting the chord and brace members was generated. The results indicated that the f_LJF of a plate stiffened joint can be down to 76% of the f_LJF of the corresponding un-stiffened joint. Also, the effect of the ring size on the f_LJF was more than the effect of the plate size on the f_LJF, because of the stiffener position. Despite the notable effect of the ring and the plate on the f_LJF, there is not any study or formula on tubular connections stiffened with ring or plate. Therefore, the FE results were used to propose two parametric formulas for determining the f_LJF in X-joints with external ring or external plate under brace compressive load. Moreover, the derived formulas were checked based on the UK DoE acceptance criteria.     

Human-like autonomous car-following model with deep reinforcement learning

This study proposes a framework for human-like autonomous car-following planning based on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation environment where an RL agent learns from trial and error interactions based on a reward function that signals how much the agent deviates from the empirical data. Through these interactions, an optimal policy, or car-following model that maps in a human-like way from speed, relative speed between a lead and following vehicle, and inter-vehicle spacing to acceleration of a following vehicle is finally obtained. The model can be continuously updated when more data are fed in. Two thousand car-following periods extracted from the 2015 Shanghai Naturalistic Driving Study were used to train the model and compare its performance with that of traditional and recent data-driven car-following models. As shown by this study’s results, a deep deterministic policy gradient car-following model that uses disparity between simulated and observed speed as the reward function and considers a reaction delay of 1 s, denoted as DDPGvRT, can reproduce human-like car-following behavior with higher accuracy than traditional and recent data-driven car-following models. Specifically, the DDPGvRT model has a spacing validation error of 18% and speed validation error of 5%, which are less than those of other models, including the intelligent driver model, models based on locally weighted regression, and conventional neural network-based models. Moreover, the DDPGvRT demonstrates good capability of generalization to various driving situations and can adapt to different drivers by continuously learning. This study demonstrates that reinforcement learning methodology can offer insight into driver behavior and can contribute to the development of human-like autonomous driving algorithms and traffic-flow models.     

A Delphi analysis on green performance evaluation indices for ports in China

This study identified a set of applicable and practical green performance evaluation indices for Chinese ports using the Delphi technique. The research was conducted by targeting three representative Chinese ports in Eastern China: the Shanghai Port, Ningbo Port, and Qingdao Port. An effective expert panel was structured with direct stakeholders related to green performance, which was based on a sufficient consideration of the unique and the special decision-making system for Chinese ports. Twenty-one green performance indices in six dimensions (i.e. liquid pollution management, air pollution management, noise control, low carbon regulations and energy savings, marine biology preservation, and organization and management) were eventually identified through three rounds of iterations. The identified green performance indices for Chinese ports are highly consistent with the Chinese Government’s environmental policies. Compared with European ports, the green port performance indicators in China are not as comprehensive. The indicators that are strictly consistent with national macro policies and the factors that are more easily seen, heard, and felt were perceived to be more important. From an academic perspective, this study offers a new approach for system establishment and green practice criteria exploration and thus provides a significant basis for further green port studies.     

Empirical analysis of short period traffic counts and their efficiency: the case of Indian traffic

Short period traffic counts (SPTCs) are conducted routinely to estimate the annual average daily traffic (AADT) at a particular site. This paper uses Indian traffic volume data to methodically and extensively study the effect of four aspects related to the design of SPTCs. These four aspects are: (i) for how long, (ii) on which days should SPTCs be carried out, (iii) how many times, and (iv) on which months should SPTCs be carried out? The analyses indicate that the best durations for conducting SPTCs are 3 days (starting with a Thursday) and 7 days, for total traffic and truck traffic, respectively. Further, these counts should be repeated twice a year keeping a separation of two months between the counts to obtain good estimates of AADT at minimal cost. An additional outcome of this study has been the determination of seasonal factor values for roads in developing economies, like India.     

船舶通信英语口语与听力课程标准

结合船舶驾驶员的岗位职责,依照现代职业教育理论和成果,设计了船舶通信英语口语与听力课程标准.对该课程的课程概述、培养目标、与前后课程的联系、教学内容与学时分配、学习资源、教师要求、学习场地与设施要求、考核方式与标准、学习情境设计进行了设计和描述,将船舶通信中典型工作任务转化为学习型任务.     

加强教风学风建设 不断提高人才培养质量

在改革不断深入、经济社会深度转型的当下,大学生群体呈现出新的特点和个性。在新的形势下,要加强高校教风学风建设,更好的发挥高校培养人才的作用,促使人才培养质量提升。本文以辽宁省交通高等专科学校为例,着重从文化建设、教师育人能力提升、学生职业梦想等角度入手,提出了加强教风学风建设的具体举措和途径。