自行车流视频识别判断方法研究

考虑算法的实时性,交通流个体识别往往采用轮廓特征来描述。由于自行车与行人的很多轮廓特征值相近,在复杂城市交通环境中,从慢行交通流中准确地识别出自行车是目前采用视频检测交通流的难点之一。通过现场视频检测获取足够的样本外轮廓数据,分析检测目标轮廓的高、宽、高宽比、面积等典型轮廓特征,发现目标轮廓高宽比特征能较好地识别出行人、自行车等慢行交通,并给出合适的取值范围。研究表明自行车高宽比能够较好地成为视频识别的依据,为自行车视频识别提供数据。     

甘泉铁路区间通过能力研究

阐述甘泉铁路车站分布和运量发展情况及货运量增加后区间通过能力不足的问题,介绍甘泉铁路行车组织和区间通过能力计算方法,计算各区间的通过能力,结合近期货物运量500万t、700万t、1000万t三种情况,计算需求通过能力,并给出提高通过能力的具体方案,为下一步货运量的增加做准备。     

使用有限元分析以改善重载运输车轴

分析了北美铁路货运发生的车轴故障,介绍了使用有限元对F级和K级车轴进行应力分析计算,研究车轴尺寸变化对应力的影响,并提出了改善重载车轴设计的建议.     

Are we ready to embrace connected and self-driving vehicles? A case study of Texans

While connected, highly automated, and autonomous vehicles (CAVs) will eventually hit the roads, their success and market penetration rates depend largely on public opinions regarding benefits, concerns, and adoption of these technologies. Additionally, the introduction of these technologies is accompanied by uncertainties in their effects on the carsharing market and land use patterns, and raises the need for tolling policies to appease the travel demand induced due to the increased convenience. To these ends, this study surveyed 1088 respondents across Texas to understand their opinions about smart vehicle technologies and related decisions. The key summary statistics indicate that Texans are willing to pay (WTP) $2910, $4607, $7589, and $127 for Level 2, Level 3, and Level 4 automation and connectivity, respectively, on average. Moreover, affordability and equipment failure are Texans’ top two concerns regarding AVs. This study also estimates interval regression and ordered probit models to understand the multivariate correlation between explanatory variables, such as demographics, built-environment attributes, travel patterns, and crash histories, and response variables, including willingness to pay for CAV technologies, adoption rates of shared AVs at different pricing points, home location shift decisions, adoption timing of automation technologies, and opinions about various tolling policies. The practically significant relationships indicate that more experienced licensed drivers and older people associate lower WTP values with all new vehicle technologies. Such parameter estimates help not only in forecasting long-term adoption of CAV technologies, but also help transportation planners in understanding the characteristics of regions with high or low future-year CAV adoption levels, and subsequently, develop smart strategies in respective regions.     

Evaluating air emission inventories and indicators from cruise vessels at ports

This paper provides an estimation of air emissions (CO₂, NO_X, SO_X and PM) released by cruise vessels at the port level. The methodology is based on the “full bottom-up” approach and starts by evaluating the fuel consumed by each vessel on the basis of its individual port activities (manoeuvring, berthing and hoteling). The Port of Barcelona was selected as the site at which to perform the analysis, in which 125 calls of 30 cruise vessels were monitored. Real-time data from the automatic identification system (AIS), factor emissions from engine certificates and vessel characteristics from IHS Sea-web database were also collected for the analysis. The research findings show that the most appropriate indicators are inventory emissions per “port-time gross tonnage”, “port-time passenger” and “port time”. These emission indicators improve our understanding of cruise emissions and will facilitate the work that aims to estimate reliably and quickly the in-port ship emission inventories of cruise ports.     

An activity-based approach of investigating travel behaviour of older people

The paper presents the results of an investigation on daily activity-travel scheduling behaviour of older people by using an advanced econometric model and a household travel survey, collected in the National Capital Region (NCR) of Canada in 2011. The activity-travel scheduling model considers a dynamic time–space constrained scheduling process. The key contribution of the paper is to reveal daily activity-travel scheduling behaviour through a comprehensive econometric framework. The resulting empirical model reveals many behavioural details. These include the role that income plays in moderating out-of-home time expenditure choices of older people. Older people in the highest and lowest income categories tend to have lower variations in time expenditure choices than those in middle-income categories. Overall, the time expenditure choices become more stable with increasing age, indicating that longer activity durations and lower activity frequency become more prevalent with increasing age. Daily activity type and location choices reveal a clear random utility-maximizing rational behaviour of older people. It is clear that increasing spatial accessibility to various activity locations is a crucial factor in defining daily out-of-home activity participation of older people. It is also clear that the diversity of out-of-home activity type choices reduces with increasing age and older people are more sensitive to auto travel time than to transit or non-motorized travel time.     

Intermittent automatic train protection using an infrared system

Automatic train protection (ATP) is a vital part of the signalling system that prevents collisions between trains, especially on densely trafficked lines. Conventionally, ATP uses a transponder to communicate between an onboard train device and a trackside device. In Indonesia, ATP is not yet implemented and all trains are currently operated by drivers. It has now become a necessity to install ATP in Indonesia in order to protect train operations. However, as in many tropical and developing countries there are some environmental problems, especially heavy rain, as well as the theft of trackside equipment that influences performance. Installed trackside devices must therefore meet certain criteria such as low-cost configuration, minimalized devices on the track, ease of maintenance, etc. To address the necessity of ATP and to meet these criteria for trackside devices, we develop ATP using an infrared system. This type of ATP – the intermittent ATP system – consists of onboard devices and infrared sensors as trackside equipment. This approach to ATP offers a cost-effective solution and ensures the safety of train movements.     

The Bid-rent Land Use Model of the simple,efficient, elegant,and effective model of land use and transportation

Integrated land use/transportation forecasting models add significant policy and infrastructure alternatives analysis capabilities to the urban planning process. The financial, time, and staff requirements to develop these models has put them beyond the reach of most small to medium sized urban areas. This paper presents the land use allocation submodel of the Simple, Efficient, Elegant, and Effective model of land use and transportation (SE³M), an integrated land use and transportation forecasting model founded upon Economic Base Theory and Bid-rent Theory. The Bid-rent Land Use Model (BLUM) is an agent based, spatial competition model utilizing unique utility curves for willingness to pay and incomes for budget constrained abilities to pay for each agent. The model structure, estimation, calibration, implementation, and validation are presented. With a single year of land use data available, the validation approach used the Kappa Index of Agreement to spatially check model outputs against base year control data while controlling for agreement by chance. The U.S. territory of Guam is used as the case study/proof of concept implementation for this model framework. Once calibrated, BLUM could solve the spatial competition problem on Guam in less than two minutes of processing time with over 90% accuracy.     

Genetics of traffic assignment models for strategic transport planning

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models.