Two-port network based bilateral control of a steer-bywire system

Steer-by-wire (SBW) system which is characterized by variable steering feel, better active safety, unmanned drive, has been widely studied to realize a distinctive driving experience. Control strategy acts as a key part of SBW system to achieve the goals. In this paper, a control strategy by bilateral control structure for steer-by-wire system is proposed. To make SBW system has the same function of conventional steering systems, the controller is designed to realize desired tracking control and realistic road feel feedback. The control of position and torque for each actuator is taken as two ports for the control network. Based on different control loop, two kinds of bilateral control is investigated respectively. The hardwarein- the-loop experiment platform of SBW is developed by the reconfiguration of electric power steering system. The test results are compared to show the performance of different control loops.     

Modelling and controlling of car-following behavior in real traffic flow using ARMAX identification and Model Predictive Control

Nowadays, car following models, as the most popular microscopic traffic flow modeling, are increasingly being used by transportation experts to evaluate new Intelligent Transportation System (ITS) and Advanced Driver Assistance Systems (ADAS) applications. The control of car following is essential due to its safety and its operational efficiency. For this purpose, this paper builds a model of car following behavior based on ARMAX structure from a real traffic data set and presents a Model Predictive Control (MPC) controller. An important advantage of this type of control is its ability to cope with constraints on controls. Since safety and operational efficiency are constraints for car following, therefore we have recruited this type of controller in this study to deal with these constraints. Based on the relative distance and relative acceleration of each instant, the MPC predicts the future behavior of the leader vehicle (LV) and according to this behavior, the acceleration of the follower vehicle (FV) is controlled. The MPC tries to control this acceleration in a way to keep the relative distance at a safe region. To investigate the performance of the designed controller, the result of the system is compared with the behavior of human drivers with similar initial conditions. Also, some other test performances were accomplished to investigate other features such as robustness and the stability of the designed MPC. The simulation results show that the MPC controller has a behavior much safer than that of real drivers and it can provide a pleasant trip for passengers.     

Comparative study between Korea and UK: relationship between driving style and real-world fuel consumption

It is known that differences in driving styles have a significant impact on fuel efficiency and driving styles are affected by various factors such as driver characteristics, street environment, traffic situation, vehicle performance, and weather conditions. However, existing knowledge about the relationship between driving style and fuel consumption is limited. Thus, the aim of this study was to analyze the relationship beteen driving style and fuel consumption. The analysis presented in this paper used data from three on-road experiments were conducted independently in two different countries, i.e. South Korea and the United Kingdom. In this study, 91 participants, consisting 44 UK drivers and 47 Korean drivers, were asked to drive approximately 28 km of UK road and 21 km of Korean road, respectively. Driving data, including real-time fuel consumption, vehicle speed, and acceleration pedal usage were collected. The results suggested that driving styles including average vehicle speed and average throttle position were highly correlated with the real-world fuel consumption, and the cultural factors, e.g. road environment, traffic design, and driver’s characteristics affected the driving styles and, consequently, fuel efficiency.     

一种有效近似建模方法及船舶耐波性代理模型构建

船舶耐波性能预报计算过程复杂,会受到诸多设计变量的影响;且采用高精度商业软件如CFD预报船舶性能的计算代价非常高。文章采用拉丁超立方方法进行了设计空间抽样。定义了一个新的综合衡准指标来表达船舶耐波性能,即短期和长期作用下船舶非工作时间百分数。考虑了船舶耐波性能中的五个运动方向：横摇、纵摇、转艏、横荡和升沉。为提高船舶耐波性能计算效率,一种有效的近似建模方法—单参数Lagrangian 支持向量回归算法被用于训练并构建代理模型以预报船舶耐波性能,且该算法是由作者在过去的研究工作中首次提出。以海洋平台支援船（OSV）为例,采用SPL-SVR算法预报船舶耐波性能,并与基于NAPA计算仿真结果、人工神经网络和经典支持向量回归算法进行对比。该文考虑OSV的两种速度,建立了海洋平台支援船短期作用下非工作时间百分数的耐波性能响应面模型,结果显示采用SPL-SVR算法建立的船舶耐波性能响应面模型比较适合船型初步设计的工程实际应用,并具有较高的计算效率。     

Panama Canal expansion: fuel economy and logistical risk

Since cargo capacity increases faster than fuel consumption, the significantly larger capacity fleets which will accompany expansion of the Panama Canal will introduce additional fuel economies and cost savings. Enabling larger, more fuel-efficient vessels to carry cargo the entire distance from Asia to US east-coast ports allows vessel operators to realize significant and meaningful savings compared with the alternatives of using smaller Panamax vessels for the whole distance, or sending the cargo over the US land bridge by train or truck. Fuel savings are quantified along with the monetary savings based on various assumptions for the price of fuel. These savings are dramatic and will increase directly with the price of crude petroleum. Finally, microeconomic theory is deployed to determine how cost savings will be distributed between shipping customers and vessel operators.     

Generation of synthetic datasets for discrete choice analysis

Despite the widespread use of synthetic data in discrete choice analysis, little is known about how the methodology used to generate synthetic datasets influences the properties of parameter estimates and the validity of results based on these estimates. That is, there are two potential sources of biases when using synthetic discrete choice data: (1) bias due to the method used to generate the dataset; and, (2) bias due to parameter estimation. The primary objective of this study is to examine bias due to the underlying data generation method. This study compares three methods for generating synthetic datasets and uses design of experiments and analysis of variance methods to investigate the ability to recover estimates for “true” logsum parameters for nested logit models. The method that uses nested logit probabilities to generate the chosen alternative results in unbiased parameter estimates. The method that is based on Gumbel error component approximations reveals that while the error components themselves are unbiased, subtle empirical identification problems can arise when these error components are combined with synthetically generated utility functions. The method that is based on normal error component approximations reveals that all logsum coefficients are biased upwards; the bias dramatically increases for those nests that have a low choice frequency and is most pronounced for those nests with high correlations among alternatives. Based on the results of the analysis, several recommendations for the generation of synthetic datasets for discrete choice analyses are provided.     

Analysis of the continuous berth allocation problem in container ports using a genetic algorithm

The optimal usage of berths plays a key role in raising the efficiency of container terminals. The berth allocation problem in a container terminal is defined as the feasible allocation of berths to incoming ships such that the total time that elapses between the arrival of the ships to their exit from their berths is minimized. In the transportation literature, the latter problem is usually formulated as a mixed integer programming model. Optimization methods, like the branch and bound algorithm, are efficient ways to solve this model but become absolutely unusable when the size of the problem increases. An advanced search method such as GA may be suited to such a situation. In this paper, a genetic-based algorithm is proposed for the problem. Computational results for two test problems (a small and a large-sized problem) are also presented. The results from the small test are also compared with the results obtained from the branch and bound algorithm.     

Assessment of work-related risk criteria onboard a ship as an aid to designing its onboard environment

The environment onboard a ship presents a typical example of a severe environment, displaying extreme conditions of temperature and relative humidity, especially in the engine room. Datasheets, the international labour organization, and standards do not provide clear information about the suitable ambience of the engine room, its design conditions, and the role of marine engineers in preventing work-related risk. In this study, air temperature and relative humidity were monitored at several locations onboard a merchant ship. These real monitored data were then compared with the ISO design indications to obtain an effective work risk analysis. From these indoor temperature and relative humidity data, the corresponding parameters of thermal comfort in the engine control room and the heat stress and sweating index of a worker in the engine room were determined. As a function of these indices, the maximum time that a worker can stay in the engine room and the time for which he must rest in the control room were also calculated in the present study. Some design corrections are also proposed herein to improve these environments.     

Estimation of CO2 reduction for Japanese domestic container transportation based on mathematical models

This research discusses domestic feeder container transportation connected with international trades in Japan. Optimal round trip courses of container ship fleet from the perspective of CO₂ emission reduction are calculated and analyzed to obtain basic knowledge about CO₂ emission reduction in the container feeder transportation system. Specifically, based on the weekly origin–destination (OD) data at a hub port (Kobe) and other related transportation data, the ship routes are designed by employing a mathematical modeling approach. First, a mixed integer programming model is formulated and solved by using an optimization software that employs branch and bound algorithm. The objective function of the model is to minimize the CO₂ emission subject to necessary (and partially simplified) constraints. The model is then tested on various types of ships with different speed and capacity. Moreover, it is also tested on various waiting times at hub port to investigate the effect in CO₂ emission of the designated fleet. Both the assessment method of container feeder transportation and the transportation’s basic insights in view of CO₂ emission are shown through the analysis.     

Recent Results on Weakly Compact Operators on Banach Lattices

There have been many really positive results concerning the weakly compact operators on Banach lattices in terms of their order structure as well as in many respects. This paper will survey some known recent results in this area.