EU maritime transport

The purpose of this paper is to summarize the European maritime transport policy within the context of maritime politics at large. At the outset the legal framework conditions and supportive instruments for the shipping and port industries are presented. Against the background of recent accidents at sea, such as the sinking of ERIKA and PRESTIGE, the EU legislation on maritime safety is of particular interest as it is both complex and rapid in reaction to environmental needs and political pressure. Finally, the sensible relationship between the EU as a regional organization and the IMO as “the competent international organization” is discussed with a view to reconcile possible rivalry and to suggest a complementary cooperation between the two organizations.     

Crystallographic structure of sea ice along a salinity gradient and environmental control of microalgae in the brine cells

Duplicate ice cores were taken in southeastern Hudson Bay (Canadian Arctic), at 8 stations along a transect, from the mouth of the Great Whale River to saline waters 25 km offshore. One core from each station was cut into 10-cm sections, which were melted at room temperature for determinations of salinity, nutrients, algal pigments and taxonomic composition of the microalgal assemblages. On the second core, thin sections were cut every 2 cm to optically determine the ratio of brine/gas pockets to the total sections. Relative volumes of brine in melted samples were computed from the observed ratios and calculated values, and used to convert per unit brine volume the concentrations of pigments, nutrients and algal cells, initially measured per unit volume of melted sample.Salinity of the melted samples indicate the presence of freshwater beneath the sea ice close to shore throughout the growth season, and the vertical salinity profiles suggest intermittent intrusions of freshwater. Nutrient concentrations in the brine were high, suggesting that microalgae in the brine cells were generally not nutrient limited. Concentrations of ice algae in the brine cells reached relatively high values, that are often of the same order as those reported for eutrophic marine waters. Statistical analyses identified the rate of ice growth as the most important factor controlling the vertical and horizontal distributions of algal biomass and taxonomic composition in the sea ice, along the salinity gradient. Higher biomasses were generally associated with slower ice growth and also possibly lower grazing activity. In addition, the rate of ice growth influenced the distribution of microalgal assemblages, with nitrogen limitation potentially playing a secondary role in some instances.     

Shipping and the competitive advantage of nations: the role of international ship registers

This paper argues that the creation of international ship registries by traditional maritime countries will not sufficient to halt the decline of their fleets. Over the last two decades shipping has undergone profound restructuring, characterized by a trend towards globalization and a search for a more efficient factor input combination. While shipowners from OECD countries have relied increasingly on flags of convenience, new maritime countries, particularly from Pacific Asia, have emerged, taking advantage of low-cost inputs and supportive national national environments. In the late 1980s the traditional maritime countries responded to the challenge by introducing international ship resistries. The Norwegian International Ship Registry is the most liberal and has the greatest success. Other new registries have limited impact. It appears that an international ship registry per seis not sufficient to reverse declining national fleets.     

Implications of path tolerance and path characteristics on critical vehicle manoeuvres

Path planning and path following are core components in safe autonomous driving. Typically, a path planner provides a path with some tolerance on how tightly the path should be followed. Based on that, and other path characteristics, for example, sharpness of curves, a speed profile needs to be assigned so that the vehicle can stay within the given tolerance without going unnecessarily slow. Here, such trajectory planning is based on optimal control formulations where critical cases arise as on-the-limit solutions. The study focuses on heavy commercial vehicles, causing rollover to be of a major concern, due to the relatively high centre of gravity. Several results are obtained on required model complexity depending on path characteristics, for example, quantification of required path tolerance for a simple model to be sufficient, quantification of when yaw inertia needs to be considered in more detail, and how the curvature rate of change interplays with available friction. Overall, in situations where the vehicle is subject to a wide range of driving conditions, from good transport roads to more tricky avoidance manoeuvres, the requirements on the path following will vary. For this, the provided results form a basis for real-time path following.     

Fatigue and buckling analysis of automotive components considering forming and welding effects

Some vehicle components are developed by setting target weights to the gram level at their design stages to accomplish a lightweight design. Recently, there have been many studies that have focused on lightweight design through the use of ultra-high-strength steels. However, a lightweight design can face many challenges if the reliability of the analysis is not also secured at the design stage. Such challenges include difficulties in coupled analyses when the file formats are different among PAM-STAMP, ABAQUS, and NASTRAN. In this study, we developed a mapping interface that enables mapping between the file formats of various software programs. Buckling analysis was coupled to the forming analysis, in which pre-strain test data were applied in considering the material’s strain hardening, to evaluate the rigidity of the front lower control arm that controls the wheels and transfers loads. The influence of forming effects on endurance was evaluated, and residual stresses around the weld zone were calculated. A comparison of experimental and analytical results indicated that the proposed analysis was highly reliable.     

Estimation of lateral offset and drift angle for application in secondary collision avoidance system

Recent reports show that the secondary collision on the road gives much higher fatality rate than the other traffic accidents. Many studies have been carried out to prevent the secondary accidents and as a result automotive companies began to introduce brake-based secondary collision avoidance systems. To prevent the secondary accidents it is important to monitor and control the lateral deviation of the vehicle after the primary collision. An estimator for the vehicle’s lateral offset and drift angle based on the in-vehicle sensors and the camera was developed in this paper. By employing sensor fusion scheme and applying extended Kalman filter, the estimator has been designed so that it works even when the camera loses the image of the lanes due to sudden change of the vehicle’s heading angle. For validation of the estimator, simulation has been carried out on various collision scenarios. The simulation results indicated that the estimator of this paper could calculate the vehicle’s lateral deviation with robustness that may be required for application in the secondary collision avoidance systems.     

Design factor optimization of 3D flash lidar sensor based on geometrical model for automated vehicle and advanced driver assistance system applications

Sensor technologies have been innovated and enhanced rapidly for highly automated vehicle and advanced driver assistance systems (ADAS) in automotive industry; however, in order to adopt sensors into mass production vehicle in near future, various requirements should be satisfied such as cost, durability, and maintainance without any loss of overall performance of the sensors. In this sense, a 3D flash lidar is one of primising range sensors because of no moving parts, compact package, and precise measure for distance by using a laser. In spite of the several advantages, the 3D flash lidar is not commonly used in automotive industry because it is quite expensive for adoption and it is manufactured with only general purpose currently; therefore, the cost reduction and optimal design to satisfy various purposes of ADAS or autonomous driving should be accomplished. In this paper, we propose a novel approach for design factor optimization of the 3D flash lidar based on a geometrical model by using structural similarity between the 3D flash lidar and 2D digital camera. In particular, focal length and area of a receiver (focal plane array and read-out integrated circuit) which directly affect on sensor performance (field of view and maximum detection range) are optimized as the design factors. From the optimization results in simulation, we show that optimal design factors according to various purposes required in ADAS could be easily determined and the sensor performances could be evaluated before manufacturing. It will reduce temporal and economic burdens for design and manufacturing in development process.     

Gain scheduled linear quadratic tracking system tuned optimally by covariance matrix adaption evolutionary strategy for automotive engine coldstart control

In this paper, a gain scheduled linear quadratic tracking system (LQTS) tuned optimally by an evolutionary strategy (ES) is devised to reduce the total tailpipe hydrocarbon (HC) emissions of an automotive engine over the coldstart period. As the engine’s behavior during coldstart operations is nonlinear, the system dynamics is clearly analyzed and represented by a number of separate linear models generated based on a coldstart model verified by experimental data. An independent LQTS is then implemented for each of these linear models. In this way, several control laws are created, and the corresponding gains are calculated for each of the independent control laws. ES is then used to tune the adjustable parameters of LQTSs to calculate the control inputs, namely air/fuel ratio (AFR) and spark timing (Δ), such that the resulting exhaust gas temperature (T _exh) and engine-out HC emissions (HC _raw) be close to a set of optimum profiles. This enables the controller reduce the cumulative tailpipe hydrocarbon emissions (HC _cum) to the highest possible extent. To demonstrate the acceptable performance of the proposed controller, an optimal controller derived from the Pontryagin’s minimum principle (PMP) is also taken into account. Based on the results of the conducted comparative study, it is shown that the proposed control technique has a very good performance, and also, can be easily used for real-time applications, as it consumes a remarkably trivial computational time for calculating the controlling commands.     

Pedaling torque sensor-less power assist control of an electric bike via model-based impedance control

This paper proposes a method to assist human force acting on electric bike without using costly torque sensors via a model-based impedance control technique. In general, electric bikes are classified into two categories, i.e., pedelec electric bikes and throttle electric bikes. We focus on the system called a pedelec electric bike. It assists human pedaling force using the pedaling information, e.g., pedaling force or speed. To obtain the human’s pedaling information in real-time, it needs physical sensors such as a torque sensor and a velocity sensor. But, these sensors are expensive and weak against external loads. Also, since these sensors are fixed directly to the forced component in a bike system, there are the risks of damage. For these reasons, sensor-less control methods based on a disturbance observer have been studied so far. In this paper, we have proposed a pedaling torque sensor-less power assist method and have applied it to the experimental pedelec electric bike. A power assist control algorithm, designed by employing an impedance model, consists of a PI-type feedback controller, an inverse model-based feedforward controller, and a pedaling torque observer. Finally, we performed experiments and confirmed the effectiveness of a proposed power assist control method.     

Drowsy behavior detection based on driving information

Drowsy behavior is more likely to occur in sleep-deprived drivers. Individuals’ drowsy behavior detection technology should be developed to prevent drowsiness related crashes. Driving information such as acceleration, steering angle and velocity, and physiological signals of drivers such as electroencephalogram (EEG), and eye tracking are adopted in present drowsy behavior detection technologies. However, it is difficult to measure physiological signal, and eye tracking requires complex experiment equipment. As a result, driving information is adopted for drowsy driving detection. In order to achieve this purpose, driving experiment is performed for obtaining driving information through driving simulator. Moreover, this paper investigates effects of using different input parameter combinations, which is consisted of lateral acceleration, longitudinal acceleration, and steering angles with different time window sizes (i.e. 4 s, 10 s, 20 s, 30 s, 60 s), on drowsy driving detection using random forest algorithm. 20 s-size datasets using parameter combination of accelerations in lateral and longitudinal directions, compared to the other combination cases of driving information such as steering angles combined with lateral and longitudinal acceleration, steering angles only, longitudinal acceleration only, and lateral acceleration only, is considered the most effective information for drivers’ drowsy behavior detection. Moreover, comparing to ANN algorithm, RF algorithm performs better on processing complex input data for drowsy behavior detection. The results, which reveal high accuracy 84.8 % on drowsy driving behavior detection, can be applied on condition of operating real vehicles.