Open Access
ARTICLE
An Entropy-Based Model for Recommendation of Taxis’ Cruising Route
Yizhi Liu1, 2, Xuesong Wang1, 2, Jianxun Liu1, 2, *, Zhuhua Liao1, 2, Yijiang Zhao1, 2, Jianjun Wang1, 2
1 School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, China.
2 Key Laboratory of Knowledge Processing and Networked Manufacturing in Hunan Province, Xiangtan, 411201, China.
* Corresponding Author: Jianxun Liu. Email: .
Journal on Artificial Intelligence 2020, 2(3), 137-148. https://doi.org/10.32604/jai.2020.010620
Received 14 March 2020; Accepted 06 June 2020; Issue published 15 July 2020
Abstract
Cruising route recommendation based on trajectory mining can improve taxidrivers' income and reduce energy consumption. However, existing methods mostly
recommend pick-up points for taxis only. Moreover, their performance is not good
enough since there lacks a good evaluation model for the pick-up points. Therefore, we
propose an entropy-based model for recommendation of taxis' cruising route. Firstly, we
select more positional attributes from historical pick-up points in order to obtain accurate
spatial-temporal features. Secondly, the information entropy of spatial-temporal features
is integrated in the evaluation model. Then it is applied for getting the next pick-up points
and further recommending a series of successive points. These points are constructed a
cruising route for taxi-drivers. Experimental results show that our method is able to
obviously improve the recommendation accuracy of pick-up points, and help taxi-drivers
make profitable benefits more than before.
Keywords
Cite This Article
Y. Liu, X. Wang, J. Liu, Z. Liao, Y. Zhao
et al., "An entropy-based model for recommendation of taxis’ cruising route,"
Journal on Artificial Intelligence, vol. 2, no.3, pp. 137–148, 2020.