Assessing air quality and health benefits of the Clean Truck Program in the Alameda corridor,CA

In this paper, vehicle microscopic simulation and emission models were combined with an air pollutant dispersion model and a health assessment tool to quantify some social costs resulting from urban freight transportation in the Alameda corridor that links the Ports of Los Angeles and Long Beach to downtown Los Angeles. Traffic on two busy freeways, the I-710 and the I-110, and some heavily trafficked arterial roads was analyzed to estimate the health impacts caused by drayage truck emissions of particulate matter (PM) for four different years: 2005, which serves as a baseline for various pollution inventories, as well as 2008, 2010 and 2012. These years correspond to deadlines for the Clean Truck Program (CTP), which was put in place to improve air quality in the Alameda corridor. Results show that the health costs from particulate matter (PM) emitted by drayage trucks exceeded 440 million dollars in 2005. However, these costs decreased by 36%, 90%, and 96% after accounting for the requirements of the 2008, 2010, and 2012 CTP deadlines. These results quantify the magnitude of the social costs generated by drayage trucks in the Alameda corridor, suggest that these costs justified replacing drayage trucks operating there, and indicate that the Clean Truck Program likely exceeded its target.     

Design of a survey to assess prospects for consumer electric mobility in Canada: a retrospective appraisal

Transportation - This paper reviews the process that led to the development of a national survey instrument used to gather over 20,000 observations across Canada. This survey captured aspects of...     

The role of socio-economic,built environment and psychological factors in parental mode choice for their children in an Iranian setting

This research investigated the role of parental psychological and socio-economic factors as well as built environment for the choice of their children’s (primary school pupils, aged 7–9 years) travel mode to school in Rasht, Iran. A total of 1078 questionnaires were distributed (return rate of 80 percent) among pupils in nine primary schools in January 2014. A mixed logit (ML) model was employed due to its ability to test heterogeneity among parents and also to determine its possible sources. Results of random coefficient ML modelling showed that several psychological, socio-economic and built environment characteristics were significant factors in parental mode choice. Only walking time perception to school had a significant random normal distribution coefficient and no other psychological and socio-economic variable had a random effect. Further investigation by random coefficient analysis showed that the possible source of household preference heterogeneity could be to own two or more cars. Regarding psychological variables, strong parental worry about their children walking alone to school had a negative impact on allowing them to walk to school. Parents who evaluated poor contextual and design preconditions for walking tended to choose school service more than private car and walking. Parents with stronger environmental personal norms were more willing to allow their children to walk. The findings suggest that infrastructural measures, such as sidewalk facilities, neighborhood security and safety, encourage parents to allow children to walk to school. Information campaigns targeting environmental norms may increase walking among pupils in an Iranian setting.     

A behavioral choice model of the use of car-sharing and ride-sourcing services

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014–2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There are significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand services.     

Proficiency improvement method in maritime education

The research conducted by the International Maritime Organization (IMO) shows that maritime education not always reaches its pre-established goal. One of the aspects in maritime education development process with the aim to prepare ship officers and other specialists is a thorough selection of the learning content according to real life necessities. Structuring the learning content of the subjects, both significant to profession and conforming to the requirements set by professional bodies, is one of the key issues addressed by curriculum developers. The aim of this research is to create a model for the curriculum development in scientific subjects for outcome-based maritime education. The main criterion which determines the significance/contribution level of the included topic in the curriculum is the anticipated learning outcome increasing the level of proficiency in students. Thus, the present research unveils the necessary steps for the evaluation of the proposed topics in the context of teaching/learning and gives grounds for their selection and the arrangement of topics in a logical order for further implementation in teaching/learning process. The present research is illustrated by a case study concerning the development of teaching/learning content for chemistry curriculum as a study subject in the secondary vocational maritime education programme.     

Analysis of ship drifting in a narrow channel using Automatic Identification System (AIS) data

With maritime transportation has played an important role in global economy development, ship traffic has become more congested. Therefore, ships navigate under risk conditions, and thus maritime accidents have occurred frequently. Especially, ship passing through a narrow channel is even more dangerous. Because, the ships are easy to be affected by external forces such as wind and currents that can cause ship drifts. Many latent risks are present during navigation. In order for the development of a sensible and appropriate traffic model for the safety and efficiency ship navigation, this study has focused on the actual ship behavior to understand the ship drift in the Kurushima Strait, Japan, which is one of the most dangerous routes in Japan. The analysis of ship behavior was carried out using the Automatic Identification System (AIS) data. As a result, the ships drift was understood in detail, and the latent risk was unveiled when ships pass through the narrow route. Moreover, the risk areas were obtained and visualized by the ship drift behavior analysis. The obtained results can be applied to ensure safe navigation and the development of an eco-friendly and economy efficient for ship navigation.     

Analyzing the dispersion of cargo vapors around a ship’s superstructure by means of wind tunnel experiments

In a previous study, it was found that cargo tank operations like cleaning and venting, lead to higher cargo vapor concentrations around the ship’s superstructure. Can wind tunnel experiments confirm these findings? Is there an improvement when using higher outlets at high velocities compared to lower outlets with a low outlet velocity? Is there a relation between relative wind speed and measured concentration? These questions were investigated in the Peutz wind tunnel. By using a tracer gas for the wind tunnel experiments, concentration coefficients have been calculated for various settings. The study shows that using high-velocity outlets is an efficient way to keep concentrations as low as possible. The only exception is for relative wind directions from the bow. In this last case using a manhole as ventilation outlet leads to lower concentrations. With increasing wind speeds the building downwash effect resulted in higher concentration coefficients near the main deck. This study confirms our on-board measurements and suggests the lowering of the ventilation inlet of the accommodation, so that the high-velocity outlet can be used safely at all times.     

Optimization of integrated scheduling of handling and storage operations at automated container terminals

Increasing demand for containerization compels container terminals to improve their performance. Uncoordinated scheduling of operations is one of the main factors accounting for poor performance at automated container terminals (ACTs). To increase land utilization efficiency and lower operational times, a new storage system called the split-platform automated storage/retrieval system (SP-AS/RS) has been introduced for temporary storage of containers. This paper describes a multi-objective mixed-integer programming (MIP) model that is based on a combination of multiple interacting sub-tasks. It is aimed at optimizing the integrated scheduling of handling and storage operations in ACTs. The MIP model objective function is to minimize delays in the loading/unloading tasks of the cranes and the travel time of vehicles and platforms in the SP-AS/RS. At the same time, a simulated annealing algorithm (SAA) that provides near-optimal solutions for the problem in a reasonable computation time is appraised. The results of this study show that the objective function of the MIP model is, on average, 58 % lower than that of the non-integrated scheduling method. On the other hand, the best objective function values obtained by the SAA indicate only a 3.7 % disadvantage in comparison with optimal values determined by the MIP model, demonstrating that the SAA is able to provide near-optimal solutions for the integrated scheduling of handling and storage operations.     

Robust principal component analysis via truncated nuclear norm minimization

Robust principal component analysis(PCA) is widely used in many applications, such as image processing, data mining and bioinformatics. The existing methods for solving the robust PCA are mostly based on nuclear norm minimization. Those methods simultaneously minimize all the singular values, and thus the rank cannot be well approximated in practice. We extend the idea of truncated nuclear norm regularization(TNNR) to the robust PCA and consider truncated nuclear norm minimization(TNNM) instead of nuclear norm minimization(NNM). This method only minimizes the smallest N-r singular values to preserve the low-rank components, where N is the number of singular values and r is the matrix rank. Moreover, we propose an effective way to determine r via the shrinkage operator. Then we develop an effective iterative algorithm based on the alternating direction method to solve this optimization problem. Experimental results demonstrate the efficiency and accuracy of the TNNM method. Moreover, this method is much more robust in terms of the rank of the reconstructed matrix and the sparsity of the error.     

基于CML的级联失效下异质多层交通网络节点抵抗特性研究

为了有效刻画拟合实际的多层交通网络级联失效过程，识别多层网络中对整体韧性安全影响显著的对象，提升交通网络抵抗失效的能力，建立一种基于耦合映象格子（Coupled Map Lattice， CML）的级联失效模型。首先，将交通管控措施赋予交通网络节点额外的容纳能力引申为节点抵抗特性，通过为CML添加抵抗参数H，形成考虑抵抗特性的级联失效（HCML）模型，沿常值-拓扑关联-时变拓扑关联的路径深化H的表征方式，并在小世界（Small World， SW）网络上对比3类表征方式的优劣；其次，应用Space H方法建立异质3层公共交通网络，对比度值与介数2种时变拓扑指标关联的抵抗效果，探究不同交通层抵抗系数对网络失效的影响程度；最后，在6组不同的网络结构上进行HCML模型与传统模型的对比，讨论建网方法、网络规模等不同网络性质的差异对模型有效性的影响，并结合实际客运数据验证HCML模型优越性。研究结果表明：3类表征方式中时变拓扑关联可以兼顾其余2类的优点；同等条件中网络在介数关联的抵抗特性作用下失效增速更缓，模型识别得到的对网络整体失效影响更大交通方式符合客流量实际；HCML模型在多种不同类型的多层交通网络中均可以有效实施，相比于传统模型，HCML模型的最终失效比例平均下降了5.78%，与实际交通级联失效过程更加拟合。