Daily activity and travel sequences of students,faculty and staff at a large Canadian university

This paper examines the activity engagement, sequencing and timing of activities for student, faculty and staff commuter groups at the largest university in the Maritime Provinces of Canada. The daily activity patterns of all university community groups are modeled using the classification and regression tree classifier algorithm. The data used for this study are derived from the Environmentally Aware Travel Diary Survey (EnACT) conducted in spring 2016 at Dalhousie University, Nova Scotia. Results show that there are significant differences in activity and travel behavior between university population segments and the general population in the region, and between campus groups. For example, students participate in more recreation activities compared to faculty and staff. They also take more trips to and from campus, and are more flexible in their scheduling of trips. The insights gained from this study will provide helpful information for promoting sustainability across university campuses, and for development of campus-based travel demand management strategies.     

Tradable credits for managing car travel: a review of empirical research and relevant behavioural approaches

Recently, there has been a surge of interest in Tradable Credits (TC) as an alternative measure to manage the growth of personal car use. This paper summarises the results and methodologies of studies that have sought to anticipate the behavioural responses to several proposed TC schemes that target personal travel. In a critical reflection on this work and in an attempt to inspire future research, we argue that future empirical studies on TC behaviours can greatly benefit from insights from the fields of behavioural economics and cognitive psychology. Therefore, in the second part of the paper, we bring together behavioural concepts from these fields that are relevant in a TC decision-making context. Based on observations from current TC studies and the behavioural mechanisms identified in the second part of the paper, we propose promising directions for future research on understanding the impact of TC on personal car travel.     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Long-term impact of the Shinkansen on rail and air demand: analysis with data from Northeast Japan

This paper analyses how the high-speed rail construction in Northeast Japan (Tohoku) has affected total demand and interregional travel patterns. We use annual interregional passenger data from 1989 to 2012 and apply regression analysis with the demand between Tokyo and the Tohoku prefectures as the dependent variable. We distinguish particularly between the ‘Full-’ and the ‘Mini-’ Shinkansen, where the latter are branch services running with reduced speed. We find that the ‘Full-Shinkansen’ quickly increases rail and total public transport trips and generates additional rail demand year on year. The ‘Mini-Shinkansen’ impacts are less pronounced. Furthermore, our analysis shows that the Shinkansen has shifted some demand from air to rail once it started operation and increased rail share gradually. We therefore suggest that predictions of demand impacts should carefully distinguish immediate from gradual impacts. We also discuss differences in regional demand in that not all prefectures have gained equally from Shinkansen construction.     

Factors influencing travel mode choice among families with young children (aged 0–4): a review of the literature

Life events, such as the birth of a child, disrupt habitual travel behaviour and provide a valuable opportunity to influence the adoption of sustainable transport practices. However, in order for sustainable travel practices to be adopted, an understanding is required of the factors that influence travel mode choice among families with young children. Research in this field is particularly timely given many in the millennial generation, a comparably large cohort, are approaching this life stage. This comprehensive literature review develops a framework of factors influencing travel mode choice among families with young children. The findings reveal a multitude of factors influence decisions about mode choice, and, in particular, encourage travel by car, when travelling with young children. The paper concludes with an agenda for future research about travel among families with young children, a largely overlooked group of transport users.     

振华启东船厂产能升级布局规划

振华启东船厂前身为成立于2007年的道达船厂,针对厂区内各功能模块之间的能力匹配问题凸显、部分设施破损、部分设施严重制约厂区生产能力的问题,通过厂区现状平面布局、工艺流程系统梳理,根据企业发展定位和关键生产要素潜能制定科学合理的规划目标,以生产设施产能分析计算分析为理论支撑,提出一套各区域产能相匹配且适应未来规模化、精益化、规范化、安全化发展的产能升级布局规划方案,达到各功能模块布局合理、生产能力匹配、生产工艺流畅、生产设施规范的目的。针对既有港区的产能升级规划,采用以定量计算为支撑的规划方法,可供类似工程参考与借鉴。     

船舶稳定计算在浅水倒驳抛石中的应用

针对船舶施工安全稳定性问题,以马来西亚槟城吹填二期（STP2）工程为例,介绍特定条件限制下的浅水抛石施工方法,以施工过程中的船舶稳定性验算为理论基础,判定了船舶的横倾角并通过工程实例验证,为类似工程提供相对简单、实用的船舶安全验算基础。     

汽油机燃烧室紧凑性评价参数分析

对燃烧室紧凑性评价参数面容比A/V值进行了分析,讨论了其局限性。提出了新的内燃机燃烧室紧凑性的衡量方法,即面面比S/A,在等容积条件下,进行了各种燃烧室紧凑性及火焰传播距离的比较。     

西南公路出海(辅助)通道物流运作模式及政策研究

为了优化资源,降低物流成本,提高物流运输可靠度和速度,需要建立恰当的西南公路出海(辅助)通道的物流运作模式,以充分发挥出西南公路出海(辅助)通道基础建设的效益.     

基于客观测度与主观估算的出行疲劳研究

出行舒适度是影响交通方式选择的要素之一,但由于缺少合理的量化方法,其评价长期停滞于定性描述,难以科学反映不同交通方式的服务水平差异。就典型出行环节进行疲劳测定实验,采集不同情况下出行者在单位时间内的客观体能消耗及其对出行疲劳的主观感受;采用自由模量幅度估计估算出行疲劳的主观感受,并与客观体能消耗进行对比。结果显示,车辆行进方式、乘车姿势、乘客负重、车内拥挤程度等均对体能消耗有显著影响,且客观体能消耗与主观感受之间存在显著差异。最后,利用实验结果以北京市和中山市为例进行案例分析,结果表明,在交通方式选择过程中,体能消耗对出行者产生的影响不亚于出行时耗。