Authors:
Kamel Aissat
1
and
Ammar Oulmara
2
Affiliations:
1
University of Lorraine - LORIA, France
;
2
University of Lorraine, France
Keyword(s):
Operations Research, Transport, Ridesharing, Shortest Path Problem, Geographical Maps.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Information Systems
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
OR in Transportation
;
Pattern Recognition
;
Routing
;
Software Engineering
;
Symbolic Systems
Abstract:
Ridesharing is a travel mode that provides several benefits and solutions, such as the reduction of travel cost, the reduction of the traffic congestion and the provision of travel options. In the classical ridesharing approach, the driver makes a detour to the rider’s origin in order to pick-up the rider, then drives him to his destination and finally the driver goes to his own destination. This implies that the driver endures the whole detour and may not accept such matching if the detour is too long. However, the matching could be accepted if the rider meets the driver at an intermediate location. In this paper, we present a general ridesharing approach in which a driver and a rider accept to meet each other at an intermediate pick-up location and to separate at an
intermediate drop-off location not necessarily their origins and destinations locations, respectively. Thus, for a given rider, we propose an exact and heuristic methods to determine the best driver and the best meeting
locations that minimize a total travel cost. Finally, we perform a numerical study using a real road network and a real dataset. Our experimental analysis shows that our heuristics provide efficient performance within short CPU times and improve participants cost-savings and matching rate compared to the classical ridesharing.
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