Personalization of Itineraries search using Ontology and Rules to Avoid
  Congestion in Urban Areas
  There is a relatively small amount of research covering urban freight
movements. Most research dealing with the subject of urban mobility focuses on
passenger vehicles, not commercial vehicles hauling freight. However, in many
ways, urban freight transport contributes to congestion, air pollution, noise,
accident and more fuel consumption which raises logistic costs, and hence the
price of products. The main focus of this paper is to propose a new solution
for congestion in order to improve the distribution process of goods in urban
areas and optimize transportation cost, time of delivery, fuel consumption, and
environmental impact, while guaranteeing the safety of goods and passengers. A
novel technique for personalization in itinerary search based on city logistics
ontology and rules is proposed to overcome this problem. The integration of
personalization plays a key role in capturing or inferring the needs of each
stakeholder (user), and then satisfying these needs in a given context. The
proposed approach is implemented to an itinerary search problem for freight
transportation in urban areas to demonstrate its ability in facilitating
intelligent decision support by retrieving the best itinerary that satisfies
the most users preferences (stakeholders).
