Computer-based support for the evaluation of ship handling exercise results

One of the most important parts of the simulator exercise is the evaluation of the students’ results by the instructor both during and after the training session. This should be performed in two ways: first, during the exercise run to ensure that the training objective can be achieved and second after exercise completion in order to give the students an indication of their performance during the simulation run. For these purposes software tools have been created and implemented at the Maritime Simulation Centre in Warnemünde: the “Surveillance Tool”, allows for a monitoring during the run and the “Evaluation Tool” will enable a detailed evaluation by the instructor after the run. It allows for in-depth search within the replay data and at the same time facilitates the calculation of the final score for the student’s performance based on measurement factors as penalties for exceeding quality limits. Within this paper a brief overview of the principles of these methods is high-lighted and selected examples of applications are described.     

e-Navigation and situation-dependent manoeuvring assistance to enhance maritime emergency response

Safe ship handling in every situation and under all prevailing circumstances of ship status and the environment is a core element contributing to the safety of the maritime transportation system. Especially in case of emergencies, there is a need for quick, accurate and reliable information to manoeuvre a ship safely. This paper focusses on investigations into enhanced response to maritime emergencies by means of onboard manoeuvring support. The research and discussions are done exemplarily for person overboard (PoB) accidents. PoB is a typical situation for application of manoeuvring assistance and decision support, e.g. in order to return quickly to the position of the accident. Based on the analysis of selected accident case studies and existing solutions representing the technical state-of-the-art, shortcomings will be identified and discussed, and a potential approach for advanced manoeuvring support in the context of e-Navigation-based requirements will be introduced and discussed.     

Scrutinizing individuals’ leisure-shopping travel decisions to appraise activity-based models of travel demand

Activity-based models for modeling individuals’ travel demand have come to a new era in addressing individuals’ and households’ travel behavior on a disaggregate level. Quantitative data are mainly used in this domain to enable a realistic representation of individual choices and a true assessment of the impact of different Travel Demand Management measures. However, qualitative approaches in data collection are believed to be able to capture aspects of individuals’ travel behavior that cannot be obtained using quantitative studies, such as detailed decision making process information. Therefore, qualitative methods may deepen the insight into human’s travel behavior from an agent-based perspective. This paper reports on the application of a qualitative semi-structured interview method, namely the Causal Network Elicitation Technique (CNET), for eliciting individuals’ thoughts regarding fun-shopping related travel decisions, i.e. timing, shopping location and transport mode choices. The CNET protocol encourages participants to think aloud about their considerations when making decisions. These different elicited aspects are linked with causal relationships and thus, individuals’ mental representations of the task at hand are recorded. This protocol is tested in the city centre of Hasselt in Belgium, using 26 young adults as respondents. Response data are used to apply the Association Rules, a fairly common technique in machine learning. Results highlight different interrelated contexts, instruments and values considered when planning a trip. These findings can give feedback to current AB models to raise their behavioral realism and to improve modeling accuracy.