中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

Journal of Chongqing Jiaotong University(Natural Science) ›› 2023, Vol. 42 ›› Issue (4): 124-130.DOI: 10.3969/j.issn.1674-0696.2023.04.16

• Transportation Infrastructure Engineering • Previous Articles    

Family Activities-Travel Decision Based on Genetic Algorithm

HE Baohong1, DUAN Yulin1, GUO Miao2   

  1. (1. Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, Yunnan, China; 2. College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China)
  • Received:2021-10-13 Revised:2023-03-09 Published:2023-06-12

基于遗传算法的家庭活动-出行决策研究

何保红1,段玉琳1,郭淼2   

  1. (1.昆明理工大学 交通工程学院,云南 昆明 650500;2.北京工业大学 城市交通学院,北京 100124)
  • 作者简介:何保红(1973—),女,云南昆明人,教授,博士。主要从事交通运输规划与管理方面的研究。E-mail: 94002267@qq.com
  • 基金资助:
    国家自然科学基金项目(51668029)

Abstract: In order to explore the familys daily activities-travel decision-making behavior, the time geography method was used to highlight the procedural expression of interactive decision-making between family joint activities and individual travel chains.Based on the optimization theory, family joint activities were regarded as the result of maximizing the effectiveness of activity arrangements and travel choices made by members through collaboration and cooperation under certain spatiotemporal constraints, and a family joint activity-travel decision-making model was established.The travel data of nuclear family was selected from the 2016 resident travel database of Kunming as the model validation data, and the genetic algorithm was used to solve the model.By setting different scenarios to reproduce the family activity-travel decision-making process, the model calculation results were compared with the actual travel chain of family members.The results show that 75.84% of the family travel chains in the normal scene are consistent with the actual travel chains, and the compliance rate of the extended scene is 83.64%, which verifies the rationality and applicability of the proposed model. For activities that are strongly constrained by time and space, when a family member is unable to complete the activity, the family will transmit it through dependency between members, and other members will assist in the form of alternative activities to achieve a balance of time and space constraints among family members.

Key words: traffic and transportation engineering; activity-travel decision; family joint activities; genetic algorithm

摘要: 为探究家庭日常活动-出行决策行为,基于时间地理学方法,突出家庭联合活动与个体出行链间互动决策的过程化表达,基于最优化理论,将家庭联合活动视为在一定时空条件约束下,成员通过彼此间协作配合做出效用最大化的活动安排和出行选择的结果,建立了家庭联合活动-出行决策模型;从昆明市2016年居民出行数据库中选取核心家庭出行数据作为模型验证数据,采用遗传算法对模型进行求解,通过设置不同场景再现家庭活动-出行决策过程,对模型计算结果与家庭成员实际出行链进行比较。结果表明:基础场景中有75.84%的家庭出行链与实际出行链相符,扩展场景符合率为83.64%,验证了所建模型的合理性和适用性;对于受时空制约较强的活动,当某一家庭成员无法完成该活动时,家庭会通过成员之间的依赖性进行传递,由其他成员以替代活动的形式进行协助,以实现家庭成员时空制约的平衡。

关键词: 交通运输工程;活动-出行决策;家庭联合活动;遗传算法

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