Transportation mode detection – an in-depth review of applicability and reliability

The wide adoption of location-enabled devices, together with the acceptance of services that leverage (personal) data as payment, allows scientists to push through some of the previous barriers imposed by data insufficiency, ethics and privacy skepticism. The research problems whose study require hard-to-obtain data (e.g. transportation mode detection, service contextualisation, etc.) have now become more accessible to scientists because of the availability of data collecting outlets. One such problem is the detection of a user's transportation mode. Different fields have approached the problem of transportation mode detection with different aims: Location-Based Services (LBS) is a field that focuses on understanding the transportation mode in real-time, Transportation Science is a field that focuses on measuring the daily travel patterns of individuals or groups of individuals, and Human Geography is a field that focuses on enriching a trajectory by adding domain-specific semantics. While different fields providing solutions to the same problem could be viewed as a positive outcome, it is difficult to compare these solutions because the reported performance indicators depend on the type of approach and its aim (e.g. the real-time availability of LBS requires the performance to be computed on each classified location). The contributions of this paper are three fold. First, the paper reviews the critical aspects desired by each research field when providing solutions to the transportation mode detection problem. Second, it proposes three dimensions that separate three branches of science based on their main interest. Finally, it identifies important gaps in research and future directions, that is, proposing: widely accepted error measures meaningful for all disciplines, methods robust to new data sets and a benchmark data set for performance validation.     

Effects of intake flow on the spray structure of a multi-hole injector in a DISI engine

The spray characteristics of a 6-hole injector were examined in a single cylinder optical direct injection spark ignition engine. The effects of injection timing, in-cylinder charge motion, fuel injection pressure, and coolant temperature were investigated using the 2-dimensional Mie scattering technique. It was confirmed that the in-cylinder charge motion played a major role in the fuel spray distribution during the induction stroke while injection timing had to be carefully considered at high injection pressures during the compression stroke to prevent spray impingement on the piston.     

Strategies for improving the mode transition in a sequential parallel turbocharged automotive diesel engine

Parallel sequential turbocharging systems are able to operate in different modes, which are defined according to the turbochargers that simultaneously boost the engine, and are controlled by means of specific valves. In order to cover the full engine operating range, a smooth transition between turbocharging operating modes must be ensured. However, important disturbances affect both boost and exhaust pressure when shifting the operation mode, thus causing non-negligible torque oscillations. This paper presents different methods for smoothing such undesirable effects during mode transition. Strategies covering optimal synchronization of the control valves, control of the valves’ position, and correction of the injected fuel during the transition are analysed. A fully instrumented passenger car engine is used for illustrating the different torque smoothing methods, and experimental results for transitions during both steady operation and engine accelerations are shown.     

Development of a knowledge-based hybrid failure diagnosis system for urban transit

Urban transit is a complex system that contains both electrical and mechanical entities; therefore, it is necessary to construct a maintenance system for ensuring safety during high-speed driving. Expert systems are computer programs that use numerical or non-numerical domain-specific knowledge to solve problems. This research aims to develop an expert system that diagnoses the causes of failures quickly and displays measures to correct them. For the development of this expert system, the standardization of a failure code classification and the creation of a Bill of Materials (BOM) were first performed. Through the analysis of both failure history and maintenance manuals, a knowledge base has been constructed. Also, for retrieving the procedure of failure diagnosis and repair linking with the knowledge base, we have built a Rule-Based Reasoning (RRB) engine with a pattern matching technique and a Case-Based Reasoning (CBR) engine with a similar search method. Finally, this system has been developed as web based in order to maximize accessibility.     

北美铁路经历的车轴故障

对北美铁路重载货车的车轴故障、车轴疲劳试验和车轴应力进行了研究,并介绍了几种解决车轴故障的措施.     

Nature of influence of out‐of‐vehicle time‐related attributes on transit attractiveness: a random parameters logit model analysis

This paper describes the nature of the impacts of walking distances and waiting time on transit use. The relative trade‐offs of walking and transfer components with other transit service attributes are also discussed. A total of 449 completed stated‐preference interviews were collected; with six observations from each respondent, the total number of observations was 2694. This data set was used to estimate the coefficients in different utility functions using a random parameters logit model. The results demonstrated that walking distances to and from transit stops have important and significant nonlinear negative influences on the attractiveness of transit. Transfer waiting time was also shown to have a significant nonlinear negative impact on transit attractiveness. The random parameters logit model had a better model fit than the standard logit model. Some of the findings obtained here are novel, while others are consistent with previous works. These findings have implications for both theory and practice. Copyright © 2014 John Wiley & Sons, Ltd.     

Bayesian committee of neural networks to predict travel times with confidence intervals

Short-term prediction of travel time is one of the central topics in current transportation research and practice. Among the more successful travel time prediction approaches are neural networks and combined prediction models (a ‘committee’). However, both approaches have disadvantages. Usually many candidate neural networks are trained and the best performing one is selected. However, it is difficult and arbitrary to select the optimal network. In committee approaches a principled and mathematically sound framework to combine travel time predictions is lacking. This paper overcomes the drawbacks of both approaches by combining neural networks in a committee using Bayesian inference theory. An ‘evidence’ factor can be calculated for each model, which can be used as a stopping criterion during training, and as a tool to select and combine different neural networks. Along with higher prediction accuracy, this approach allows for accurate estimation of confidence intervals for the predictions. When comparing the committee predictions to single neural network predictions on the A12 motorway in the Netherlands it is concluded that the approach indeed leads to improved travel time prediction accuracy.     

从全球角度透视巴拿马运河扩建及海运业的发展(英文)

2007年6月13日,巴拿马运河管理局在上海浦东香格里拉大酒店举办“巴拿马海运日”,巴拿马运河管理局国际顾问委员会主席、国际海事组织(IMO)前秘书长威廉·A·奥尼尔先生在开幕仪式上发表了演讲。奥尼尔先生的讲话着重强调海运在当代经济和社会发展中不可替代的巨大作用,集装箱化又是影响最大的因素之一,而且在可持续发展大趋势下,海运又是能效最高、对生态环境最友好的运输方式。演讲还指出海运事业广泛的国际性以及各国政府在政策法规等方面合作和协调对发展全球海运业的重要意义。奥尼尔先生高度赞扬巴拿马运河回归后的出色管理,以及运河在21世纪,尤其是在扩建计划完成后,对世界航运业的重大贡献。应本刊之约,讲演稿由作者修改后发表如下。     

Hybridation of generation propagation models and SPH model to study severe sea states in Galician Coast

The Atlantic and Cantabrian coasts of the Iberian Peninsula suffer the periodic passage of storms which give rise to severe sea states. Standard generation- propagation models (WAM, WAVEWATCH, SWAN) are commonly used for operational oceanography purposes with satisfactory results both in the open ocean and in near shore areas but they do not provide information about the possibility of flooding in coastal areas. A 2D HV version of SPH (Smoothed Particle Hydrodynamics) model is considered to propagate the signal provided by generation- propagation models to the coast and to analyze the nature of coastal structures overtopping as a tool to create maps of risk. SPH is shown to provide valuable information about overtopping (maximum water height and water velocity) under the stormy conditions suffered by the Galician coast on February 17, 2006.