| A comprehensive analysis of the urban transit operation and accident data showed that traditional technical countermeasures have not addressed vital human-factors issues, such as, operator workload and suitability of operator task. It was also found that positive technological changes in vehicle systems achieved in recent times, which should have caused reduction in man-machine interface problems, have not yielded significant results.;The need for giving more attention to important transit systems operator-related use-factors has been addressed in this study. One particular interest regards the way operators are assigned to routes, and vice versa. A review of available literature shows that: (a) operators need more cognitive skills today than before, (b) operators with deficient cognitive skills are often assigned to computerized and sophisticated equipment, with little or no change in their basic cognitive abilities, (c) that the existence of ability-task mismatches inhibits expected performance improvements from more modern and better technology being used by the industry.;These important issues of functional task allocation in urban mass transit and a possible fuzzy knowledge-based ergonomics engineering solution is discussed and addressed. First, the essential operator and route risk factors, with their relative importance weights, are identified using advanced statistical procedures. Then a model is developed that uses these weights and the methodologies of Fuzzy Set Theory to capture and predict both operator and route accident risk potentials. A second model is developed that classifies these weights into risk categories and provides basis for their use in assigning operators to routes. The Reversed Hierarchical Order (RHO) technique, as an assignment tool is explored, demonstrated, and applied. Then, the possibilities for implementation and validation of the effectiveness of these models are discussed with illustrations. |
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