Agents in traffic and transportation: Exploring autonomy in logistics, management, simulation, and cooperative driving

摘要

The increasing demand for mobility in the 21st century challenges researchers from several fields to devise more efficient traffic and transportation systems designs, including control devices, techniques to optimize the existing network, and also information systems. More and more, interdisciplinary approaches are necessary. A successful experience has been the cross-fertilization between traffic, transportation, and artificial intelligence, which dates at least from the 1980s and 1990s when expert systems were built to help traffic experts control traffic lights. Also, information on how to combine parking and public transportation can be provided by intelligent systems, and transportation and logistics have also benefited from artificial intelligence techniques, especially those tied to optimization. However, given the increasing complexity of those systems, a product of the modern way of life and new means of transportation, more and more the individual choices must be better understood if the whole system is to become more efficient. Thus, it is not surprising that there is a growing debate aiming at modeling transportation systems at both the individual (micro) and the society (macro) level. This may raise technical problems, as transportation systems can contain thousands of autonomous, "intelligent" entities that need to be simulated and/or controlled. Therefore, traffic and transportation scenarios are extraordinarily appealing for (multi-)agent technology in particular.