Volume XLII-4/W18
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 875–878, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-875-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 875–878, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-875-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Oct 2019

19 Oct 2019

A NOVEL APPROACH TO OPTIMIZE THE RIDESHARING PROBLEM USING GENETIC ALGORITHM

S. Rangriz1, M. Davoodi2, and J. Saberian3 S. Rangriz et al.
  • 1Department of Surveying Engineering, Technical and Engineering Faculty, Islamic AZAD University South Tehran Branch, Iran
  • 2Faculty of Geodesy and Geomatics, K. N. Toosi University of Technology, Iran
  • 3Technical and Engineering Faculty, Islamic AZAD University South Tehran Branch, Iran

Keywords: Ridesharing, Urban Traffic Management, Route Finding, Genetic Algorithm, Dijkstra

Abstract. The enormous increase in the number of vehicles in the cities makes plenty of problems including air pollution, noise pollution, and traffic jam. Overcoming these annoying issues needs a significant plan in urban management such as using modern techniques in public transportation systems. Sharing either cars or taxies is one of the most interesting ways that has been used in some countries recently. In this phenomenon, 2 or 3 people use other’s car or taxi. In this article, an innovative approach to share taxies is proposed, and it uses a Genetic Algorithm to determine the placement of travelers in taxies. Therefore, some taxis will be switched off, and this helps to decrease urban traffic jam in cities. The results present that the proposed model turns off 69.8 % of taxies, and also 27.8 % of them carry more than one passenger; hence, this confirms the performance of the proposed model.