Classification of driver-assistance systems according to their impact on road safety and traffic efficiency

The aim was to examine driver-assistance systems that seem to have a considerable potential for road safety and traffic efficiency improvement, and to propose an impact-oriented classification of these systems. A broad overview of a series of driver-assistance systems under development or in some cases already available is presented and it identifies the basic characteristics of each system and its expected impact on traffic efficiency and road safety. The latter is assessed on the basis of appropriate evaluation criteria. Expert judgement and literature evidence available are used in this context. This impact approach, in contrast with the usually adopted user or system-oriented approaches, allows for more appropriate identification of the priorities in the field of future research, development and promotion of driver-assistance systems. The proposed classification allocates the driver-assistance systems in four different categories on the basis of whether traffic efficiency and safety impact are high or low. This categorization reveals that 40% of the systems considered are expected to have a high safety and low traffic-efficiency impact, while only 15% is expected to have both impacts high.     

Testing the SERVQUAL scale in the passenger port industry: a confirmatory study

A key question is whether the service quality instruments developed for other services’ industries may be used to gauge service quality perceptions in shipping. Grounded on similar studies that test the most widely used American service quality instrument, SERVQUAL, in the commercial shipping sector, this study examines its applicability in the passenger shipping realm. Based on a survey of 436 passengers in Piraeus port, SERVQUAL's five main dimensions have been checked regarding their fit with the use of Confirmatory Factor Analysis. Results support that this is a valid instrument for measuring service quality in passenger shipping besides certain considerations regarding its dimensionality. A more parsimonious two-factor model seems more applicable and should therefore be also considered. Finally, it is evident from the study that passengers place more importance to the physical than the interactive elements of service to form their overall satisfaction.     

Revisiting the application of simultaneous perturbation stochastic approximation towards signal timing optimization

Simultaneous Perturbation Stochastic Approximation (SPSA) has gained favor as an efficient optimization method for calibrating computationally intensive, “black box” traffic flow simulations. Few recent studies have investigated the efficiency of SPSA for traffic signal timing optimization. It is important for this to be investigated, because significant room for improvement exists in the area of signal optimization. Some signal timing methods and products perform optimization very quickly, but deliver mediocre solutions. Other methods and products deliver high-quality solutions, but at a very slow rate. When using commercialized desktop signal timing products, engineers are often forced to choose between speed and solution quality. Real-time adaptive control products, which must optimize timings within seconds on a cycle-by-cycle basis, have limited time to reach a high-quality solution. The existing literature indicates that SPSA provides the potential for upgrading both off-line and on-line solutions alike, by delivering high-quality solutions within seconds. This article describes an extensive set of optimization tests involving SPSA and genetic algorithms (GAs). The final results suggest that GA was slightly more efficient than SPSA. Moreover, the results suggest today's signal timing solutions could be improved significantly by incorporating GA, SPSA, and “playbooks” of preoptimized starting points. However, it may take another 5–10 years before our computers become fast enough to simultaneously optimize coordination settings (i.e., cycle length, phasing sequence, and offsets) at numerous intersections, using the most powerful heuristic methods, at speeds that are compatible with real-time adaptive solutions.