The transport of goods and persons with two or more transport carriers (road, rail, air, inland waterway, or sea) results in multipartite transport chains whose profitability depends on the cost-effectiveness of the transport carriers involved as well as on the capability of multimodal transport management. Currently, differences with regard to the technical equipment used and infrastructural facilities available as well as administrative and public organizational structures in place are the major obstacles to comprehensive multimodal transport management within and beyond European Union borders. Though information and communication technologies (ICT) have entered into all traffic and transport systems, the levels of ICT penetration achieved in controlling, monitoring, and managing of system operation and processes are currently quite different [1-5]. One of the reasons for that is the lack of homogenous ICT standards and, as a result, the technological barriers for interconnectivity between different systems, processes, applications, and stakeholders [2]. The proposed trajectory-based concept is considered as suitable approach to perform the smart and adaptable planning, operation, and management of systems with dissimilar structures, a wide diversity of actors, and distributed responsibilities. It is therefore expected that it will be especially well suited to facilitate multimodal transport management for future Intelligent Transport Systems (ITS). Based on the “transport trajectory” formulation introduced here, it will be shown that a trajectory-based status description is generally possible for all transport-relevant components and processes. The expected benefit of the trajectory-based transport management is illustrated by means of selected transportation scenarios.
Collision avoidance is one of the high-level safety objectives and requires a complete and reliable description of the maritime traffic situation. The radar is specified by the IMO as the primary sensor for collision avoidance. In this paper we study the performance of multi-target tracking based on radar imagery to refine the maritime traffic situation awareness. In order to achieve this we simulate synthetic radar images and evaluate the tracking performance of different Bayesian multi-target trackers (MTTs), such as particle and JPDA filters. For the simulated tracks, the target state estimates in position, speed and course over ground will be compared to the reference data. The performance of the MTTs will be assessed via the OSPA metric by comparing the estimated multi-object state vector to the reference. This approach allows a fair performance analysis of different tracking algorithms based on radar images for a simulated maritime scenario.
The highest priority for safe ship navigation is the avoidance of collisions and groundings. For this purpose, the concept of ship domain has been introduced to describe the surrounding effective, waters which should be kept clear of other ships and obstacles. In the last decades, a large variety of ship domains have been developed differing in the applied method of their determination as well as in the modelled shape, size, and safety areas. However, a ship domain should be adjusted in real time to enable a reliable evaluation of collision risks by the officers of the watch. Until today in discussions about modelling and utilization of ship domains, it has been mostly unnoticed that the performance of vessel’s position (P), navigation (N), and timing data (T) ultimately determines the accuracy and integrity of indicated ship domain. This paper addresses this question, and starts with a comprehensive analysis of AIS data to prove the violation of ship domains in the maritime practice. A simulation system has been developed to enable, for the first time, investigation into the extent inaccuracies in PNT data result to a faulty evaluation of collision risks. The simulation results have shown that there is a non-negligible risk of not detecting a collision, if inaccuracies of sensor data remain unnoticed.
PL
Zapobieganiu wypadkom na morzu przyznaje się najwyższy priorytet w ramach bezpiecznego prowadzenia statku. Dla poprawy bezpieczeństwa żeglugi stworzono koncepcję domeny statku. Definiuje ona taki obszar wokół jednostki pływającej, w którym nie powinno być ani żadnych innych uczestników ruchu morskiego, ani przeszkód. Na przestrzeni minionych dziesięcioleci powstały rozmaite domeny statku różniące się między sobą sposobem ich definiowania, modelowaniem kształtu, rozmiarem czy strefami bezpieczeństwa. Istotnym warunkiem do należytej oceny ryzyka kolizji jest umożliwienie oficerowi wachtowemu dopasowania w czasie rzeczywistym domeny statku do panujących warunków. W dotychczasowych dyskusjach na temat modelowania i stosowania domeny statku przeważnie pomijano istotną zależność pomiędzy dokładnością pozycji statku (P), wektora ruchu (N) oraz znacznika czasu (T) a dokładnością i spójnością domeny statku. W niniejszym artykule poruszono kwestię powyższego związku. Na wstępie przeprowadzono dogłębną analizę danych AIS i dowiedziono się, że naruszanie domeny statku ma miejsce w praktyce żeglugowej. Ponadto opracowano system symulacyjny, który po raz pierwszy umożliwia badanie wpływu niedokładności danych PNT na błędność oceny ryzyka kolizji. Wyniki symulacji potwierdziły, że istnieje poważna możliwość niewykrycia groźnej sytuacji zbliżeniowej, jeżeli pozostanie niedostateczna dokładność czujników pokładowych niezauważona.
The Automatic Identification System (AIS) is widely used for reporting vessel movements and broadcasting additional information related to the current voyage or constant parameters like the IMO number or the overall dimension of the hull. Since dynamic AIS data is shared mostly without human interaction, and is not flawless, the static AIS content edited manually is vulnerable to human error. This work introduces a simple vessel motion pattern approach that determines the probable foredeck/afterdeck location of the GNSS reference used by the AIS transponder, and compares it to the hull parameters obtained from the static AIS data, to find observable errors in the static AIS configuration of the mount point of the GNSS reference antenna.
Collision avoidance is one of the high-level safety objectives and requires a complete and reliable description of maritime traffic situation. A combined use of data provided by independent data sources is an approach to improve the accuracy and integrity of traffic situation related information. In this paper we study the usage of radar images for automatic identification system (AIS) and radar fusion. Therefore we simulate synthetic radar images and evaluate the tracking performance of the particle filter algorithm as the most promising filter approach. During the filter process the algorithm estimates the target position and velocity which we finally compare with the known position of the simulation. This approach allows the performance analysis of the particle filter for vessel tracking on radar images. In a second extended simulation we add the respective AIS information of the target vessel and study the gained level of improvement for the particle filter approach. The work of this paper is integrated in the research and development activities of DLR Institute of Communications and Navigation dealing with the introduction of data and system integrity into the maritime traffic system. One of the aimed objectives is the automatic assessment of the traffic situation aboard a vessel including integrity information.
Since its deployment in 2004, the Automatic Identification System (AIS) has been considered a significant improvement of watchkeeping duties at sea. According to current regulations, AIS has not been recognised as an approved anticollision instrument yet. However, it would be difficult to rule out a possibility that AIS, being an essential part of the onboard SOLAS — compliant configuration, is unaidedly used for collision avoidance tasks. Recent research activities of DLR’s Department of Nautical Systems have shown that AIS transmissions may contain a lot of incomplete data and the system does not have any dependable information on its data integrity. For that reason, the computation of the closest point of approach (CPA) and the time to the CPA (TCPA) are analysed based on AIS data involving multiple vessels, in order to compare the predictions with factual approaches between vessels and to evaluate the usability of AIS data, in its present form, for the appraisal of the traffic situation around each vessel.
PL
System automatycznej identyfikacji (AIS) rozwinął się w 2004 roku i odtąd jest uważany za istotny czynnik poprawiający jakość pełnienia wachty morskiej. W aktualnych regulacjach AIS nie jest uznawany za urządzenie antykolizyjne, jednak trudno nie dostrzec możliwości, jakie ma ten — wedle konwencji SOLAS — zasadniczy element obowiązkowego wyposażenia. Badania prowadzone w Wydziale Systemów Nawigacyjnych DLR wykazały, że informacje przekazywane za pośrednictwem AIS mogą zawierać wiele danych niepełnych, a system nie ma żadnego mechanizmu zapewniającego przesyłanie informacji o wiarygodności tych danych. Dlatego w artykule zaprezentowano obliczenia punktu największego zbliżenia (CPA) oraz czasu do tego punktu (TCPA) na podstawie danych z AIS od różnych statków, by porównać prognozy z faktycznymi manewrami, a następnie ocenić użyteczność danych AIS w obecnej postaci dla szacowania sytuacji kolizyjnych w warunkach rzeczywistych.
The standard for interfacing marine electronic devices (NMEA – National Marine Electronics Association), does not provide unambiguous information regarding the reliability of data and its timing. In this paper, time delays in navigational data are investigated. For this purpose AIS and navigational data collected offshore and onshore are used. The investigations are concentrated on lags among various NMEA sentences recorded in a relational database during the survey voyage. The analysis is based on standard elements of descriptive statistics.
Since its introduction the Automatic Identification System (AIS) has played an important part in improving safety at sea, making bridge watchkeeping duties more comfortable and enhancing vessel traffic management ashore. However the analysis of a AIS data set describing the vessel traffic of the Baltic Sea came to conclusion, that specific parameters with relevance to navigation seemed to be defective or implausible. Essentially, it concerned the true heading (THDG) and the rate of turn (ROT) parameters. With the paper we are trying to clarify, which parameters of the AIS position report and to what extent, are affected. The detailed data analysis gives answers on how reliable the AIS data in different traffic areas is.
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