Air pollution is one of the emerging problems in our society. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce emissions as well as total cost of ownership (TCO) for public transport vehicles (e.g. bus application). In this context, typically diesel engines are used to form the hybrid propulsion system of the vehicle. Gaseous fuels represent an attractive alternative to diesel for both ecologic and economic reasons. In the framework of the research project “Optimised Real-world Cost-Competitive Modular Hybrid Architecture” (ORCA), which was funded by the EU, two different hybrid electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG engine. The aim of the current study is to analyse specific benefits for the aforementioned hybrid propulsion systems for representative driving scenarios with regard to emissions (e.g. NOx and CO2) and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed to estimate the emissions from engine torque and rotational speed. For designing optimal energy management strategies for each propulsion system, maps-driven quasi-static models for specific engine types are used in this study. This paper compares the two aforementioned propulsion concepts regarding their CO2 and NOxemissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid propulsion concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO2 emissions are 13% lower and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.
Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR) which are tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. Paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C-Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases including image acquisition, processing, and extraction of features. A digital camera, (Gopro) camera with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807 which is considered in the linear regression model to be ‘large positive linear association’.
Abstract — Virtual Container Yard (VCY) is a modern concept that helps to reduce the empty container repositioning cost of carriers. The concept of VCY is based on container interchange between shipping lines. Although this mechanism has been theoretically accepted by the shipping community as a feasible solution, it has not yet achieved the necessary momentum among container shipping lines (CSL). This paper investigates whether there is any legal influence on this industry myopia about the VCY. It is believed that this is the first publication that focuses on the legal aspects of container exchange between carriers. Not much literature on this subject is available. This study establishes with statistical evidence that there is a phobia prevailing in the shipping industry that exchanging containers with other carriers may lead to various legal implications. The complexity of exchange is two faceted. CSLs assume that offering a container to another carrier (obviously, a competitor in terms of commercial context) or using a container offered by another carrier may lead to undue legal implications. This research reveals that this fear is reflected through four types of perceived components, namely: shipping associate; warehouse associate; network associate; and trading associate. These components carry eighteen subcomponents that comprehensively cover the entire process of a container shipment. The statistical explanation has been supported through regression analysis; INCO terms were used to illustrate the shipping process.
Based on activity method, this paper focuses on morning commuting behavior when commuters travel with autonomous vehicles (AVs). Firstly, a net utility function of commuters is constructed by the activity utility of commuters at home, in car and at workplace, and the disutility of travel time cost and that of schedule delay cost. Then, this net utility function is applied to build an equilibrium model. Finally, under the assumption of constant marginal activity utility, the properties of equilibrium are analyzed. The results show that, in autonomous driving, the starting and ending time of morning peak and the number of commuters who arrive early and late at workplace are the same as those in manual driving. In automatic driving, however, the departure rate of arriving early at workplace is higher than that of manual driving, while the departure rate of arriving late is just the opposite. In addition, compared with manual driving, the departure time of arriving at workplace on time is earlier and the number of people queuing at the bottleneck is larger in automatic driving. However, the net utility of commuters and the total net utility of system in automatic driving are greater than those in manual driving. Keywords—Autonomous cars, bottleneck model, activity utility, user equilibrium.
