Scipediacontent: Scipediacontent moved page Draft Content 763597485 to 238,295pi

2021-03-23T03:16:03Z

Scipediacontent moved page Draft Content 763597485 to 238,295pi

Scipediacontent: Created page with " == Abstract == With the improvement of people’s living standards, people’s demand of traveling by taxi is increasing, but the taxi service system is not perfect yet; tax..."

2021-03-23T03:14:08Z

Created page with " == Abstract == With the improvement of people’s living standards, people’s demand of traveling by taxi is increasing, but the taxi service system is not perfect yet; tax..."

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== Abstract ==

With the improvement of people’s living standards, people’s demand of traveling by taxi is increasing, but the taxi service system is not perfect yet; taxi drivers usually rely on their operational experience or cruise randomly to find passengers. Without macroguidance, the role of the taxi system cannot be fully utilized. Many scholars have studied taxi behaviors to find better operational strategies for drivers, but their researches rely on local optimization methods to improve the profit of drivers, which will lead to imbalance between supply and demand in the city. To solve this problem, we propose a Multiagent Reinforcement Learning- (MARL-) based taxi predispatching model through analyzing the running data of 13,000 taxis. Different from other methods of scheduling taxis based on the real-time location of orders, our model first predicts the demand for taxis in different regions in the next period and then dispatches taxis in advance to meet the future requirement; thus, the number of taxis needed and available in different regions can be balanced. Besides, in order to reduce computational complexity, we propose several methods to reduce the state space and action space of reinforcement learning. Finally, we compare our method with another taxi dispatching method, and the results show that the proposed method has a significant improvement in vehicle utilization rate and passenger demand satisfaction rate.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_763597485-beopen1425-4468-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1155/2020/8674512 http://dx.doi.org/10.1155/2020/8674512] under the license http://creativecommons.org/licenses/by/4.0/

* [https://doi.org/10.1155/2020/8674512 https://doi.org/10.1155/2020/8674512]

* [http://downloads.hindawi.com/journals/jat/2020/8674512.pdf http://downloads.hindawi.com/journals/jat/2020/8674512.pdf],
: [http://downloads.hindawi.com/journals/jat/2020/8674512.xml http://downloads.hindawi.com/journals/jat/2020/8674512.xml],
: [http://dx.doi.org/10.1155/2020/8674512 http://dx.doi.org/10.1155/2020/8674512] under the license cc-by

* [http://dx.doi.org/10.1155/2020/8674512 http://dx.doi.org/10.1155/2020/8674512],
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license http://creativecommons.org/licenses/by/4.0/

* [https://www.hindawi.com/journals/jat/2020/8674512 https://www.hindawi.com/journals/jat/2020/8674512],
: [http://downloads.hindawi.com/journals/jat/2020/8674512.pdf http://downloads.hindawi.com/journals/jat/2020/8674512.pdf],
: [https://academic.microsoft.com/#/detail/3007054387 https://academic.microsoft.com/#/detail/3007054387]

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Scipediacontent: Scipediacontent moved page Draft Content 763597485 to 238,295pi

Scipediacontent: Created page with " == Abstract == With the improvement of people’s living standards, people’s demand of traveling by taxi is increasing, but the taxi service system is not perfect yet; tax..."