Perceived importance of inclusive street dimensions: a public questionnaire survey from a vision(ing) perspective

Transportation - The increasingly prevalent concept of inclusiveness in the public discourse is gaining a foothold in the paradigm shift of street design from a predominance of vehicular traffic...     

Conceptual framework for Comparing University baccalaureate programmes in shipping management

For a long time, a maritime education meant the education of a mariner where technical knowledge of seafaring was taught. However, shipping has evolved into a global and sophisticated business where two kinds of managers are required: one that deals with the operation of the vessel and the other that deals with the shore-side business. The education landscape for shipping has also evolved with time. A mariner’s education has evolved from apprenticeship on a ship to a professional certificate from maritime academies. The shore-side business is traditionally staffed by master mariners that made the career transition from sea to shore but the current staffing trend is to employ graduates schooled in business and/or management. It has been long recognised that shore-side business personnel should ideally be also knowledgeable in vessel operations. Under this scenario, several maritime degree programmes have cropped up around the world to bridge the knowledge gap of shore-side business personnel. This paper provides an overview of the evolution of maritime education and selected maritime degree programmes around the world and proposes a conceptual framework for comparing the programmes. The conceptual framework serves as a guide for evaluating maritime education and an aid to curriculum design where choices of courses need to be made to fit into a 3-year or 4-year study programme.     

Traffic performance of shared lanes at signalized intersections based on cellular automata modeling

Shared lanes at signalized intersections are designed for use by vehicles of different movement directions. Shared lane usage increases the flexibility of assigning lane grouping to accommodate variable traffic volume by direction. However, a shared lane is not always beneficial as it can at time result in blockage that leads to both capacity and safety constraints. This paper establishes a cellular automata model to simulate traffic movements at signalized intersections with shared lanes. Several simulation experiments are carried out both for a single shared lane and for an approach with a shared lane. Simulation of a single shared lane used by straight‐through and right‐turn (as similar to left‐turn in the USA) vehicles suggests that the largest travel delay occurs when traffic volumes (vehicles/lane) of the two movement streams along the shared lane are at about the same level. For a trial lane‐group with a shared lane, when traffic volumes of the two movement streams are quite different, the shared lane usage is not efficient in terms of reduction in traffic delay. The simulation results are able to produce the threshold traffic volume to arrange a shared lane along an approach. Copyright © 2013 John Wiley & Sons, Ltd.     

ANFIS model for assessing near-miss risk during tanker shipping voyages

Adaptive neuro-fuzzy inference system (ANFIS) was applied to predict the risk of near-miss incidents during tanker shipping voyages. Firstly, near-miss incidents recorded by a global tanker shipping management company were analysed. Four variables—type of operation, vessel’s location, on-board position, and harm potential were selected to train and predict the risk levels of near-miss incidents. The selected variables were found to be correlated with the observed frequency at three risk levels, namely low, medium and high. Gravity factor (GF) was calculated using the frequency of the categories in each variable and their associated risk levels. The calculated GF values and the risk levels of near-miss incidents were used as input values in the ANFIS model. Triangular, Trapezoidal and Gaussian membership functions were used. Subsequently, fuzzy logical theory and artificial neural networks were applied to train the data. Causal factors in terms of direct contributory factors, indirect contributory factors and root contributory factors to the near-miss incidents were analysed. Risk control measures were also proposed to improve safety during tanker shipping.