Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions北大核心CSCD

［Objective ］ To meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. ［Method］On the basis of analyzing the characteristics of ship-shore cooperation, the proposed approach realizes autonomous perception of the environment with visual simulation at the core and navigation decision-making control based on deep reinforcement learning, and finally constructs an artificial intelligence system composed of image deep learning processing, navigation situation cognition, route steady-state control and other functions. Remote control and short-time autonomous navigation of operating ships are realized under inland waterway conditions, and remote control of container ships and ferries is carried out. ［Results］The proposed approach is capable of replacing manual work by remote orders or independent decision-making, as well as realizing independent obstacle avoidance, with a consistent deviation of less than 20 meters. ［Conclusions］The developed prototype system carries out the remote control operation demonstration of the above ship types in such waterways as the Changhu Canal Shenzhou line and the Yangtze River, proving that a complete set of algorithms with a CNN and reinforcement learning at the core can independently extract key navigation information, construct obstacle avoidance and control awareness, and lay the foundation for inland river intelligent navigation systems. © 2022 Journal of Clinical Hepatology. All rights reserved.     

Impacts of urban built environment on empty taxi trips using limited geolocation data

This study identifies the determinants of the empty taxi trip duration (ETTD) by combining three high-resolution databases—geolocation data in New York City, geodatabase of urban planning data, and transportation facilities data. Considering the nature of duration data, hazard-based duration model is proposed to explore the relationships between causal factors and ETTD, coupling with three variations of baseline hazard distribution, i.e., Weibull distribution with heterogeneity, Weibull distribution, and log-logistic. Furthermore, the likelihood ratio test is presented to implement comparisons of three baseline hazard distributions, as well as spatial and temporal transferability of causal factors. The results show significant complementary effects by subway system and competitive effects by city bus and bicycling system, as well as significant impacts of trip length, airport trip, average annual income, and employment rate. Urban built environment, for instance, density of road, public facilities, and recreational sites and ratio of green space, has various impacts on ETTD. The elasticity estimations confirm significant spatial and temporal heterogeneity in impacts on ETTD. In addition, the analysis on elasticity also reveals the considerable impacts of severe traffic congestion on ETTD within Manhattan. The modeling can assist stakeholders in understanding empty taxi movements and measuring taxi system efficiency in urban areas.     

Subjective-utility travel time budget modeling in the stochastic traffic network assignment

ABSTRACT

In this article, we propose a new model called subjective-utility travel time budget (SU-TTB) model to capture travelers' risk-averse route choices. In the travel time budget (TTB) and mean-excess travel time (METT) model, a predefined confidence level is needed to capture the risk-aversion in route choice. Due to the day-to-day route travel time variations, the exact confidence level is hard to be predicted. With the SU-TTB model, we assume travelers' confidence level belongs to an interval that they may comply with in the route choice. The two main components of SU-TTB are the utility function and the TTB model. We can show that the SU-TTB can be reduced to the TTB and METT model with proper utility function for the confidence levels. We can also prove its equivalence with our recently proposed nonlinear-expectation route travel time (NERTT) model in some cases and give some new interpretation on the NERTT with this equivalence. Finally, we formulate the SU-TTB model as a variational inequality (VI) problem to model the risk-averse user equilibrium (RAUE), termed as generalized RAUE (GRAUE). The GRAUE is solved via a heuristic gradient projection algorithm, and the model and solution algorithm are demonstrated with the Braess's traffic network and the Nguyen and Dupuis's traffic network.     

Effect of nozzle orifice diameter on diesel spray tip penetration according to various spray models for CFD simulation with widely varying back pressure

CFD simulations of spray tip penetration with the standard KIVA3V, ‘original gas jet’ and ‘Normal gas jet profile with breakup length formula’ (NGJBL) spray models were performed to investigate the effects of nozzle orifice size and ambient gas density combinations on the spray penetration. The accuracy of the CFD simulation results was estimated by comparing them with available experimental data. The ambient gas density was varied in 12 kg/m³ intervals from 12 to 69 kg/m³ for each nozzle orifice diameter. The nozzle orifice diameters used were 119, 140, 183 and 206 mm. A total of 20 cases in the CFD simulations were considered with combinations of the 4 nozzle orifice diameters and 5 ambient gas densities. CFD simulations with the NGJBL spray model were more accurate than those with either the standard KIVA3V or gas jet spray models as the nozzle orifice diameter and ambient gas density was increased. The NGJBL and original gas jet model is more effective in predicting the spray tip penetration near the nozzle tip region.     

Approximate optimal AUTOSAR software components deploying approach for automotive E/E system

The AUTOSAR has been developed as the worldwide standard for automotive E/E software systems, making the electronic components of different suppliers to be employed universally. However, as the number of component-based applications in modern automotive embedded systems grows rapidly and the hardware topology becomes increasingly complex, deploying such large number of components in automotive distributed system in manual way is over-dependent on experience of engineers which in turn is time consuming. Furthermore, the resource limitation and scheduling analysis make the problems more complex for developers to find out an approximate optimal deploying approach in system integration. In this paper, we propose a novel method to deploy the AUTOSAR components onto ECUs with the following features. First, a clustering algorithm is designed for deploying components automatically within relatively low time complexity. Second, a fitness function is designed to balance the ECUs load. The goal of our approach is to minimize the communication cost over all the runnable entities while meeting all corresponding timing constraints and balancing all the ECUs load. The experiment results show that our approach is efficient and has well performance by comparing with other existing methods in specific and synthetic data set.     

Vibration reduction of H/Shaft using an electromagnetic damper with mode change

The objective of this study is to develop a damper that can reduce the amplitude of vibration in various frequency ranges. Previous H/Shaft vibration reduction methods work in a passive way. A dynamic damper reduces the amplitude of vibration at its first mode, but vibration still appears at the second mode. A mass damper or hollow shaft can shift the natural frequency to a lower or higher region. The fixed operating frequency prevents vibration from being reduced outside the operating frequency range. The proposed damper uses electromagnets as either masses or actuators to change the damper mode between dynamic damper mode and mass damper mode. The electromagnetic damper (EMD) can change its mode to respond to the vibration excitation at both low and high frequencies. The vibration reduction performance was evaluated by FRF tests in laboratory and vehicle conditions. The results were compared with those of a dynamic damper and indicate that the amplitude of vibration is reduced by 95.6 % when the EMD is implemented on an H/Shaft, whereas only 61.9 % vibration reduction is achieved by the dynamic damper.     

Rapid first-stage tests of on-ship infection

Protection against on-ship infectious disease—whether due to mishap or to harmful purpose—faces special situational problems. Sometimes, when infection levels on board have reached threshold levels, emergency actions are required. Often, the most thorough strategies for responding to threat are not feasible. A rapid first-stage test (RFT) is a fast, minimally invasive procedure used to rule out from possible infection a large percentage of an infection-threatened group. Prevention and control of on-ship infection need to combine various interconnected tactics. When timely criterion tests are not possible, the medical team must adopt fast alternative measures. The methods used to summarize protection against on-ship infectious agents included a scientific literature review and a web search. The fields of the review were maritime, health, and technology sources. Special attention was paid to material dealing with risks and threats of on-ship penetration by infectious agents, on-ship infection prevalence thresholds, and rapid diagnostic screens. The Bayes rule and the law of large numbers were applied to the analysis, for large on-ship populations, of RFT indications of crossing of an infection prevalence threshold. The increasing risk of serious on-ship infection—either accidental or purposeful—calls for a multi-layered protection approach. RFTs are a key part of the outer layer of such a defense. Well-designed and well-administered RFTs provide several advantages for defense against on-ship infection: low-cost, non-invasive, fast, and focuses on a drastically smaller number of infection possibilities.     

Characteristics of premium transit services that affect mode choice

This research seeks to improve the understanding of the full range of determinants for mode choice behavior and to offer practical solutions to practitioners on representing and distinguishing these characteristics in travel demand forecasting models. The principal findings were that the representation of awareness of transit services is significantly different than the underlying assumption of mode choice and forecasting models that there is perfect awareness and consideration of all modes. Furthermore, inclusion of non-traditional transit attributes and attitudes can improve mode choice models and reduce bias constants. Additional methods and analyses are necessary to bring these results into practice. The work is being conducted in two phases. This paper documents the results of Phase I, which included data collection for one case study city (Salt Lake City), research and analysis of non-traditional transit attributes in mode choice models, awareness of transit services, and recommendations for bringing these analyses into practice. Phase II will include data collection for two additional case study cities (Chicago and Charlotte) with minor modifications based on limitations identified in Phase I, additional analyses where Phase I results indicated a need, and a demonstration of the research in practice for at least one case study city.     

Assessing a maritime service website prototype in a ship bridge simulator: navigators’ experiences and perceptions of novel e-Navigation solutions

The aim of this study was to assess proof of concept and usability of a maritime service website prototype in a full-mission ship bridge simulator through Swedish mariners’ experiences and perceptions. This test was part of the European Commission’s EfficienSea2 project for e-navigation. The prototype was intended as an aid to existing standard systems and methodologies for planning, executing and monitoring voyages. The study began with 5 days of simulator trials focused on today’s standard practices. This served as a baseline to compare to subsequent 4 days of simulator trials testing the prototype. For data collection, observations, video footage, interviews, and eye tracking were used. Data analysis included breaking apart the qualitative data to capture the perceptions of the participants, and a preliminary analysis of eye-tracking data as a complement. The results suggested that the prototype could be more suitable for a route planning stage, that the participants were familiar with similar existing solutions from other manufacturers, and that the contents of the tool would be most beneficial if integrated within the Electronic Chart Display and Information Systems (ECDIS). There is a pressing need for the novel solutions to be user needs-driven, integrated with the existing technologies, and standardized across the domain, and these processes must go hand-in-hand with accounting for all involved stakeholders, procedures, regulations, and training, as this will alter the course of shipping.     

An analysis of the determinants of children’s weekend physical activity participation

This paper examines the out-of-home, weekend, time-use patterns of children aged 5–17 years, with a specific emphasis on their physical activity participation. The impact of several types of factors, including individual and household demographics, neighborhood demographics, built environment characteristics, and activity day variables, on physical activity participation is analyzed using a joint nested multiple discrete–continuous extreme value-binary choice model. The sample for analysis is drawn from the 2000 San Francisco Bay Area Travel Survey. The model developed in the paper can be used to assess the impacts of changing demographics and built environment characteristics on children’s physical activity levels.