DHPA: Dynamic Human Preference Analytics Framework: A Case Study on Taxi Drivers’ Learning Curve Analysis

Menghai Pan; Weixiao Huang; Yanhua Li; Xun Zhou; Zhenming Liu; Rui Song; Hui Lu; Zhihong Tian; Jun Luo

doi:10.1145/3360312

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DHPA: Dynamic Human Preference Analytics Framework: A Case Study on Taxi Drivers’ Learning Curve Analysis

Journal article

Open access

Peer reviewed

DHPA: Dynamic Human Preference Analytics Framework: A Case Study on Taxi Drivers’ Learning Curve Analysis

Menghai Pan, Weixiao Huang, Yanhua Li, Xun Zhou, Zhenming Liu, Rui Song, Hui Lu, Zhihong Tian and Jun Luo

ACM transactions on intelligent systems and technology, Vol.11(1), pp.1-19

02/11/2020

DOI: 10.1145/3360312

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Abstract

Many real-world human behaviors can be modeled and characterized as sequential decision-making processes, such as a taxi driver’s choices of working regions and times. Each driver possesses unique preferences on the sequential choices over time and improves the driver’s working efficiency. Understanding the dynamics of such preferences helps accelerate the learning process of taxi drivers. Prior works on taxi operation management mostly focus on finding optimal driving strategies or routes, lacking in-depth analysis on what the drivers learned during the process and how they affect the performance of the driver. In this work, we make the first attempt to establish Dynamic Human Preference Analytics. We inversely learn the taxi drivers’ preferences from data and characterize the dynamics of such preferences over time. We extract two types of features (i.e., profile features and habit features) to model the decision space of drivers. Then through inverse reinforcement learning, we learn the preferences of drivers with respect to these features. The results illustrate that self-improving drivers tend to keep adjusting their preferences to habit features to increase their earning efficiency while keeping the preferences to profile features invariant. However, experienced drivers have stable preferences over time. The exploring drivers tend to randomly adjust the preferences over time.

Details

Title: Subtitle: DHPA: Dynamic Human Preference Analytics Framework: A Case Study on Taxi Drivers’ Learning Curve Analysis
Creators: Menghai Pan - Worcester Polytechnic Institute
Weixiao Huang - Worcester Polytechnic Institute
Yanhua Li - Worcester Polytechnic Institute
Xun Zhou - University of Iowa
Zhenming Liu - College of William 8 Mary
Rui Song - North Carolina State University
Hui Lu - Guangzhou University
Zhihong Tian - Guangzhou University
Jun Luo - Lenovo Group Limited
Resource Type: Journal article
Publication Details: ACM transactions on intelligent systems and technology, Vol.11(1), pp.1-19
DOI: 10.1145/3360312
ISSN: 2157-6904
eISSN: 2157-6912
Grant note: name: DiDi Chuxing Inc.; DOI: 10.13039/100000001, name: NSF, award: CNS-1657350, CMMI-1831140, IIS-1566386, IIS-1755769 and DMS-1555244
Language: English
Date published: 02/11/2020
Academic Unit: Business Analytics
Record Identifier: 9984066339102771

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