Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems
Extensive usage of private vehicles has led to increased traffic congestion, carbon emissions, and usage of non-renewable resources. These concerns have led to the wide adoption of vehicle sharing (ex: bike sharing, car sharing) systems in many cities of the world. In vehicle-sharing systems, base s...
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Association for the Advancement of Artificial Intelligence (AAAI)
2015
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Online Access: | http://hdl.handle.net/1721.1/100439 https://orcid.org/0000-0002-8585-6566 |
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author | Ghosh, Supriyo Varakantham, Pradeep Adulyasak, Yossiri Jaillet, Patrick |
author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Ghosh, Supriyo Varakantham, Pradeep Adulyasak, Yossiri Jaillet, Patrick |
author_sort | Ghosh, Supriyo |
collection | MIT |
description | Extensive usage of private vehicles has led to increased traffic congestion, carbon emissions, and usage of non-renewable resources. These concerns have led to the wide adoption of vehicle sharing (ex: bike sharing, car sharing) systems in many cities of the world. In vehicle-sharing systems, base stations (ex: docking stations for bikes) are strategically placed throughout a city and each of the base stations contain a pre-determined number of vehicles at the beginning of each day. Due to the stochastic and individualistic movement of customers,there is typically either congestion (more than required)or starvation (fewer than required) of vehicles at certain base stations. As demonstrated in our experimental results, this happens often and can cause a significant loss in demand. We propose to dynamically redeploy idle vehicles using carriers so as to minimize lost de-mand or alternatively maximize revenue for the vehicle sharing company. To that end, we contribute an optimization formulation to jointly address the redeploy-ment (of vehicles) and routing (of carriers) problemsand provide two approaches that rely on decomposability and abstraction of problem domains to reduce the computation time significantly. Finally, we demonstrate the utility of our approaches on two real world data sets of bike-sharing companies. |
first_indexed | 2024-09-23T14:16:40Z |
format | Article |
id | mit-1721.1/100439 |
institution | Massachusetts Institute of Technology |
language | en_US |
last_indexed | 2024-09-23T14:16:40Z |
publishDate | 2015 |
publisher | Association for the Advancement of Artificial Intelligence (AAAI) |
record_format | dspace |
spelling | mit-1721.1/1004392022-10-01T20:20:15Z Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems Ghosh, Supriyo Varakantham, Pradeep Adulyasak, Yossiri Jaillet, Patrick Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Jaillet, Patrick Extensive usage of private vehicles has led to increased traffic congestion, carbon emissions, and usage of non-renewable resources. These concerns have led to the wide adoption of vehicle sharing (ex: bike sharing, car sharing) systems in many cities of the world. In vehicle-sharing systems, base stations (ex: docking stations for bikes) are strategically placed throughout a city and each of the base stations contain a pre-determined number of vehicles at the beginning of each day. Due to the stochastic and individualistic movement of customers,there is typically either congestion (more than required)or starvation (fewer than required) of vehicles at certain base stations. As demonstrated in our experimental results, this happens often and can cause a significant loss in demand. We propose to dynamically redeploy idle vehicles using carriers so as to minimize lost de-mand or alternatively maximize revenue for the vehicle sharing company. To that end, we contribute an optimization formulation to jointly address the redeploy-ment (of vehicles) and routing (of carriers) problemsand provide two approaches that rely on decomposability and abstraction of problem domains to reduce the computation time significantly. Finally, we demonstrate the utility of our approaches on two real world data sets of bike-sharing companies. Singapore. National Research Foundation (Singapore-MIT Alliance for Research and Technology Center. Future Urban Mobility Program) 2015-12-18T16:56:29Z 2015-12-18T16:56:29Z 2015-06 Article http://purl.org/eprint/type/ConferencePaper http://hdl.handle.net/1721.1/100439 Ghosh, Supriyo, Pradeep Varakantham, Yossiri Adulyasak, and Patrick Jaillet. "Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems." 25th International Conference on Automated Planning and Scheduling (June 2015). https://orcid.org/0000-0002-8585-6566 en_US http://www.aaai.org/ocs/index.php/ICAPS/ICAPS15/paper/view/10602 Proceedings of the 25th International Conference on Automated Planning and Scheduling Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Association for the Advancement of Artificial Intelligence (AAAI) MIT web domain |
spellingShingle | Ghosh, Supriyo Varakantham, Pradeep Adulyasak, Yossiri Jaillet, Patrick Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems |
title | Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems |
title_full | Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems |
title_fullStr | Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems |
title_full_unstemmed | Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems |
title_short | Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems |
title_sort | dynamic redeployment to counter congestion or starvation in vehicle sharing systems |
url | http://hdl.handle.net/1721.1/100439 https://orcid.org/0000-0002-8585-6566 |
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