TY - JOUR
T1 - Adjustment of the Number of Ride-Sharing Vehicles by Introducing the pre-declaration on the expected time period of use
AU - Ota, Masato
AU - Sakurai, Yuko
AU - Okadome, Takeshi
AU - Noda, Itsuki
N1 - Publisher Copyright:
© 2021, Japanese Society for Artificial Intelligence. All rights reserved.
PY - 2021
Y1 - 2021
N2 - In this paper, we introduce a user ’s pre-declaration for her demand in order to improve a on-demand ridesharing operation plan by decreasing the number of vehicles. While a reservation requires a user to declare a precise riding time, we allow users to report a certain time period in advance. We evaluate the effectiveness of pre-declaration by computational simulations. In more detail, we evaluate the number of vehicles based on users’ pre-declarations to satisfy the threshold condition for average pick-up time by running computational simulations. However, A detailed simulation requires huge computation time. To solve this problem, we propose a method to determine the number of vehicles to run a simulation by applying Bayesian optimization. In the proposed method, the acquisition function is used to search for the number of vehicles whose average pickup time is around a threshold value. The experimental results show that the proposed method works well in reducing the number of vehicles.
AB - In this paper, we introduce a user ’s pre-declaration for her demand in order to improve a on-demand ridesharing operation plan by decreasing the number of vehicles. While a reservation requires a user to declare a precise riding time, we allow users to report a certain time period in advance. We evaluate the effectiveness of pre-declaration by computational simulations. In more detail, we evaluate the number of vehicles based on users’ pre-declarations to satisfy the threshold condition for average pick-up time by running computational simulations. However, A detailed simulation requires huge computation time. To solve this problem, we propose a method to determine the number of vehicles to run a simulation by applying Bayesian optimization. In the proposed method, the acquisition function is used to search for the number of vehicles whose average pickup time is around a threshold value. The experimental results show that the proposed method works well in reducing the number of vehicles.
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U2 - 10.1527/TJSAI.36-6_AG21-K
DO - 10.1527/TJSAI.36-6_AG21-K
M3 - Article
AN - SCOPUS:85123458291
VL - 36
JO - Transactions of the Japanese Society for Artificial Intelligence
JF - Transactions of the Japanese Society for Artificial Intelligence
SN - 1346-0714
IS - 6
M1 - AG21-K_1-9
ER -