Towards Multi-Modal Advance Journey Planner in a Co-Modal Framework

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2018 by IJCTT Journal
Volume-61 Number-2
Year of Publication : 2018
Authors : Dr.G.Anandharaj, K.Navaneethakrishnan
DOI :  10.14445/22312803/IJCTT-V61P115

MLA

MLA Style: Dr.G.Anandharaj, K.Navaneethakrishnan "Towards Multi-Modal Advance Journey Planner in a Co-Modal Framework" International Journal of Computer Trends and Technology 61.2 (2018):87-92.

APA Style:Dr.G.Anandharaj, K.Navaneethakrishnan (2018). Towards Multi-Modal Advance Journey Planner in a Co-Modal Framework International Journal of Computer Trends and Technology, 61(2),87-92

Abstract
Traveler information systems play a significant role in most travelers’ daily trips. These systems assist travelers in choosing the best routes to reach their destinations and possibly select suitable departure times and modes for their trips. we present an advanced traveler information system (ATIS) for public and private transportation, including vehicle sharing and pooling services. The ATIS uses an agent based architecture and multi-objective optimization to answer trip planning requests from multiple users in a co-modal setting, considering vehicle preferences and conflicting criteria. At each set of user’s requests, the transportation network is represented by a co-modal graph that allows decomposing the trip planning problem into smaller tasks: the shortest routes between the network nodes are determined and then combined to obtain possible itineraries. Using multi-objective optimization, the set of user vehicle-route combinations is determined according to the user’s preferences, and all possible route agents’ coalitions are ranked. The ATIS is tested for the real case study of the Lille metropolitan area (Nord Pas de Calais, France).

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Keywords
Advanced traveller information system, trip planning, public transport, private transport, co-modal transport, multi-agent systems, directed graphs, optimization