چکیده:
In this paper, car sharing is introduced as a new method for traffic optimization. Car sharing system is a new subject, which is studied in several recent researches. This method finds the
best pathway between drivers and passengers by employing controled optimization techniques. The optimized path results in less traffic jam, more people using a vehicle, and
finally cheaper and cleaner transportaion for everyone. Car sharing’s main target is to reduce
single-seating vehicles as much as possible. That being said, this method tries to oprimize the pathways to find the closest and the most number of passengers for each driver. Eventhough this method is proven very useful worldwide, there has been limited numbers of researchers in Iran studying its reuirement and employment methods inside the country. So, here, car sharing method is discussed by utilizing optimization algorithm within cloud services such as Bing Map. This paper demonstrates how to use such a cloud service to solve car sharing problems. By using this optimizd system, drivers will provide transportation for more numbers of passengers with much shorter trips.
خلاصه ماشینی:
"Keyword:Optimization;Traffic; Make smart; Car sharing, Autonomous * Corresponding author: Hossein Jafari Peer review under responsibility of UCT Journal of Research in Science, Engineering and Technology INTRODUCTION Private vehicle occupation rates (the number of trips per journey trip) are relatively down; average car holders in Europe vary from 1.
Active usage of empty vehicle seats by carpooling may show an important chance to raise occupancy rates, and could substantially raise the utility of urban transportation systems, potentially cutting roadway congestion, fuel consumption, and air pollution [4] with the grow in traffic congestion, the ability to monitor the state of the urban route network, by a variety of means, has become serious.
Use genetic and SMA* algorithms to obtain gasoline in medium seats (3 - 6 modes) 3- RESULTS It is possible to find the most optimal route for each driver and also the largest by number of passengers with the minimum of distance using the methods outlined in sections 2-3 and 2-4.
Each driver collects the maximum number of passengers on the route according to the starting point and destination; as a result, the total traveled distance decreases as well as it leads to reduce the amount of carbon dioxide released into the air and also gas consumption.
In this research, an interchange model has been proposed in which the patterns have been moving throughout the urban area and have presented a genetic algorithm and SMA* to determine the optimal route of travel and users allocation practice.
"Optimizing the carpool service problem with genetic algorithm in service-based computing.
"A genetic-algorithm-based approach to solve carpool service problems in cloud computing."