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巡游出租车运力规模动态调整回归树模型
引用本文:叶骐铭,叶晓飞,李敏,郑彭军,谢金. 巡游出租车运力规模动态调整回归树模型[J]. 宁波大学学报(理工版), 2020, 33(4): 89-96
作者姓名:叶骐铭  叶晓飞  李敏  郑彭军  谢金
作者单位:1.宁波大学 海运学院, 浙江 宁波 315832; 2.宁波市港口贸易合作与发展协同创新中心, 浙江 宁波 315832; 3.国家道路交通管理工程技术研究中心 宁波大学分中心, 浙江 宁波 315832; 4.现代城市交通技术江苏高校协同创新中心, 江苏 南京 210096
基金项目:浙江省自然科学基金;国家自然科学基金;国家重点研发计划;交通运输科技项目
摘    要:针对巡游出租车运力规模调整指标体系的匮乏, 以宁波市出租车信息管理系统运营数据为基础, 梳理了巡游车运力规模调整的主要影响因素, 综合考虑各项运营指标, 构建了巡游车运力规模调整阈值回归树模型, 并采用方差分析的卡方自动交叉诊断器算法对模型进行标定. 最后, 耦合了万人拥有量、出租车在公交出行结构分担率、巡游车与网约车业务分担比以及乘客平均等候时间等指标在供需状态中的表征作用和重要性排序关系, 提出了巡游出租车运力规模动态调整机制及关键指标的阈值标准, 为城市巡游出租车运力规模调整提供理论依据和决策支持.

关 键 词:交通工程  运力规模  回归树  巡游出租车  阈值分析

Regression tree model for dynamic adjustment of the scale of cruising taxicab capacity
YE Qiming1,YE Xiaofei1,' target="_blank" rel="external">2,LI Min1,ZHENG Pengjun1,3,' target="_blank" rel="external">4,XIE Jin1. Regression tree model for dynamic adjustment of the scale of cruising taxicab capacity[J]. Journal of Ningbo University(Natural Science and Engineering Edition), 2020, 33(4): 89-96
Authors:YE Qiming1,YE Xiaofei1,' target="  _blank"   rel="  external"  >2,LI Min1,ZHENG Pengjun1,3,' target="  _blank"   rel="  external"  >4,XIE Jin1
Affiliation:1.Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China; 2.Ningbo Port Trade Cooperation and Development Collaborative Innovation Center, Ningbo 315832, China; 3.Ningbo University Sub-center, National Traffic Management Engineering & Technology Research Center, Ningbo 315832, China; 4.Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, Nanjing 210096, China
Abstract:In view of the lack of indicator system for the scale adjustment of the cruising taxicab capacity, this paper collects the operation datasets of taxicab from the Taxi Information Management System in Ningbo and analyzes the influential factors on cruising taxicab capacity. The regression tree model for the dynamic adjustment of the scale of cruising taxicab capacity is then established by considering the various operational indicators of the cruise taxicab. Next, the chi-squared automatic interaction detector is applied to calibrate the model. Finally, the dynamic adjustment mechanism of the scale of cruising taxicab capacity and the thresholds of the key indicators are proposed by coupling the representation functions on the balance of taxi supply and demand with the ordering relationship of importance of other indicators, which consist of the taxi ownership per person, the sharing ratio of taxi in public transport trip structure, the sharing ratio between cruising taxi and ride-hailing taxi, and the average waiting time of passengers, to provide theoretical basis and decision-making support for the scale adjustment of urban cruise taxi capacity.
Keywords:traffic engineering  the scale of capacity  regression tree  cruising taxicab  threshold analysis
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