Children's School Travel Mode Choice Considering Customized Travel

Journal of Transportation Systems Engineering and Information Technology ›› 2020, Vol. 20 ›› Issue (1): 111-116.

• Systems Engineering Theory and Methods • Previous Articles Next Articles

Children's School Travel Mode Choice Considering Customized Travel

HAO Jing-jing^{1, 2a, 2b}, ZHANG Ling^{1, 2a, 2b}, WU Xiao-long³, YANG Xiao-quan⁴, LIU Lan¹

1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China; 2a. Yunnan Engineering Research Center of Modern Logistics, 2b.Yunnan Integrated Transport Development and Regional Logistics Management Think Tank, Kunming University of Science and Technology, Kunming 650500, China; 3. Kunming Qianmo Traffic Engineering Consulting Co. LTD, Kunming 650028, China; 4. Road Network Monitoring and Emergency Command Center, Yunnan Provincial Transportation Department, Kunming 650100, China

Received:2019-09-17 Revised:2019-11-20 Online:2020-02-25 Published:2020-03-02

考虑定制出行的儿童通学方式选择行为研究

郝京京^{1, 2a, 2b}，张玲^{1, 2a, 2b} ，吴小龙³，杨晓泉⁴，刘澜^*1

1. 西南交通大学交通运输与物流学院，成都 610031；2. 昆明理工大学a. 云南省现代物流工程研究中心， b. 综合交通发展与区域物流管理智库，昆明 650500；3. 昆明阡陌交通工程咨询有限公司，昆明 650028； 4. 云南省交通运输厅路网监测与应急指挥中心，昆明 650100

作者简介:郝京京(1990-)，男，河北石家庄人，博士生.
基金资助:
国家自然科学基金/ National Natural Science Foundation of China(61873216)；国家重点研发计划项目/National Key Research and Development Program of China (2017YFB1200702).

Abstract

Abstract:

To obtain the family's mode choice behavior mechanism for children's school travel considering the introduction of the customized travel mode, the variables influencing children's school travel decision was selected systematically first, and the hybrid choice model (HCM) for children's school travel choice was then proposed based on the combination of structural equation model (SEM) and discrete choice model. A verification analysis was conducted by using Zhaotong, Yunnan province as a case area. The results show that: Compared with traditional modes of discrete choice model and SEM, the HCM model shows a higher fitting degree and is more suitable for the analysis of mode choice behavior of children's school travel; Taking car travel mode as a reference, the behavior intention plays a more significant role in parents' choice of customized school is behavior intention, the popularity of customized travel mode mostly depends on families' acceptance and reliance on it; Time and cost are not the primary factors influencing parents' choice of customized travel mode.

Key words: traffic engineering, school travel mode choice, hybrid choice model, customized travel, children

摘要：

为系统获取考虑定制出行后儿童通学方式选择的行为模式，在系统选取影响儿童通学方式决策变量的基础上，集成结构方程模型和离散选择模型，提出儿童通学方式选择的混合选择模型(HCM)，以云南省昭通市为案例进行分析.结果表明：所构建的HCM模型相比结构方程模型和离散选择模型具有更高的拟合优度，更适用于儿童通学方式选择行为分析；与小汽车出行方式相比，行为意向对家长选择定制出行方式的影响更大，定制出行方式的普及更多取决于家庭的接受和依赖程度；时间和成本并非是家长选择定制出行方式的首要考虑因素.

关键词: 交通工程, 通学方式选择, 混合选择模型, 定制出行, 儿童

CLC Number:

U491.1

HAO Jing-jing, ZHANG Ling, WU Xiao-long, YANG Xiao-quan, LIU Lan. Children's School Travel Mode Choice Considering Customized Travel[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(1): 111-116.

郝京京，张玲，吴小龙，杨晓泉，刘澜. 考虑定制出行的儿童通学方式选择行为研究[J]. 交通运输系统工程与信息, 2020, 20(1): 111-116.

Add to citation manager EndNote|Ris|BibTeX

URL: http://www.tseit.org.cn/EN/abstract/abstract19983.shtml

http://www.tseit.org.cn/EN/Y2020/V20/I1/111

References

[1] MCDONALD N C, AALBORG A E. Why parents drive children to school: Implications for safe routes to school programs[J]. Journal of the American Planning Association, 2009, 75(3): 331-342.

[2] STEWART O, MOUDON A V, CLAYBROOKE C. Common ground: Eight factors that influence walking and biking to school[J]. Transport Policy, 2012, 24: 240- 248.

[3] NOLAND R B, PARK H, VON-HAGEN L A, et al. A mode choice analysis of school trips in New Jersey[J]. Journal of Transport Land Use, 2014, 7(2): 111-133.

[4] SMITH L, NORGATE S H, CHERRETT T, et al. Walking school buses as a form of active transportation for children: A review of the evidence[J]. Journal of School Health, 2015, 85(3): 197-210.

[5] PÉREZ-MARTÍN P, PEDRÓS G, MARTÍNEZJIMÉNEZ P, et al. Evaluation of a walking school bus service as an intervention for a modal shift at a primary school in Spain[J]. Transport Policy, 2018, 64: 1-9.

[6] 玛依拉·艾则孜, 林强, 姚志刚, 等. 基于家庭结构差异的学生出行方式选择行为[J]. 长安大学学报(自然科学版), 2017, 37(6): 113- 120. [MAYILA A, LIN Q, YAO Z G, et al. Behavior of students' travel mode choice based on family structure differences[J]. Journal of Chang'an University (Natural Science Edition), 2017, 37 (6): 113-120.]

[7] 马书红, 韩亚慧, 姚志刚, 等. 基于父母出行特性的学生出行方式选择研究[J]. 交通运输系统工程与信息, 2016, 16(2): 225-231. [MA S H, HAN Y H, YAO Z G, et al. Students' travel mode choice based on parents' travel mode[J]. Journal of Transportation Systems Engineering and Information Technology, 2016, 16(2): 225-231.]

[8] 景鹏, 王静, 查奇芬, 等. 影响学校出行方式选择的心理因素研究综述[J]. 中国公路学报, 2017, 30(2): 108- 119. [JIN P, WANG J, ZHA Q F, et al. Influence of psychological factors on school travel mode choice: A systematic review[J]. China Journal of Highway and Transport, 2017, 30(2): 108-119.]

[9] JUNG J, HAN H, OH M. Travelers' switching behavior in the airline industry from the perspective of the pushpull- mooring framework[J]. Tourism Management, 2017, 59: 139-153.

[10] CHOI A S, RITCHIE B W, FIELDING K S. A mediation model of air travelers' voluntary climate action[J]. Journal of Travel Research, 2016, 55(6): 709-723.

[11] ZWERTS E, ALLAERT G, JANSSENS D, et al. How children view their travel behaviour: A case study from Flanders (Belgium)[J]. Journal of Transport Geography, 2010, 18(6): 702-710.

[12] BEN-AKIVA M, WALKER J L, BERNARDINO A T, et al. Integration of choice and latent variable models, in: Hani S. Mahmassani (Ed.): In perpetual motion: Travel behavior research opportunities and application challenges[M]. Amsterdam: Elsevier, 2002.

[1]	LIN Jian-xin, LIU Bo , ZHAO Xia , ZHANG Lei. Intelligent Construction Method of Vehicle Condition Based on Hybrid Constrained Autoencoder [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2): 109-116.
[2]	JI Xiao-feng , GENG Zhao-shi. Bivariate Traffic Conflict Extreme Value Model of Truck Collision Prediction on Two-lane Mountain Highway [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2): 230-238.
[3]	ZHANG Jian-bo , SUN Jian-ping , XU Chun-ling , GUO Jing-xia, WEN Hui-min , SONG Guo-hua. Driver Characteristics Clustering Under Impact of Varying Traffic Operation Conditions [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2): 330-336.
[4]	MA Jing-feng, REN Gang , LI Hao-jie, CAO Qi, DU Jian-wei. Analysis on Contributing Factors Influencing Severity of E-Bicycle and Motor Vehicle Crashes [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2): 337-348.
[5]	ZONG Fang , WANG Meng, HE Zheng-bing. A Molecular Dynamics-based Car-following Model for Connected and Automated Vehicles Considering Impact of Multiple Vehicles [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 37-48.
[6]	MA Xiao-long , YU Qiang , LIU Jian-bei . A Calculation Method of Vehicle Collision Probability Based on Roadside Millimeter Wave Radar [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 57-66.
[7]	LIAO Peng, TANG Tie-qiao. Optimization Strategy of Lane-changing Trajectory Based on Vehicle Powertrain and Steering System [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 98-105.
[8]	LIU Yong-hong, LUO Xia , HU Jian-peng. Dynamic Allocation Method for Shared Berth Considering Immediate and Reservation Demands [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 171-181.
[9]	YUAN Zhen-zhou, GUO Man-ze, PENG Yong-xin, YANG Yang. Risk Recognition of Older Pedestrian Traffic Crashes Based on XGB-Apriori Algorithm [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 195-208.
[10]	XUE Shu-qi , LIU Yu-han, CHEN Qing-hua. Analysis of Children Behavior in Unidirectional Collective Movement [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 209-216.
[11]	ZHANG Yu-ting , CHEN Bo-you , ZHANG Shuang-yan, YAN Xue-dong , LI Xiao-meng. Recognition Model of Distracted Drivers When Approaching Signalized Intersections [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 217-224.
[12]	SONG Lang , WANG Jian , YANG Bin-yu , AN Shi. Innovative Design of Transportation Organization for Left-turn Non-motor Vehicles at Continuous Flow Intersection [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 225-233.
[13]	BAI Jing-rong , TANG Bo-ming, SUN Zong-yuan , BI Hui-yun , XIANG Tian-jun. On Driving Load of Super-long Tunnel Adjacent to Interchanges [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 301-310.
[14]	GUO Yan-ru , LUO Zhi-xiong , WANG Jia-chuan , HE Fang. Data-driven Planning and Design for Bike Sharing Parking Spots [J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(6): 9-16.
[15]	LI Jun-xian , SHEN Zhou-biao , TONG Wen-cong , WU Zhi-zhou. Impact of Large Vehicles on Urban Roads with Varying Headway Distributions [J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(6): 55-62.

Children's School Travel Mode Choice Considering Customized Travel

考虑定制出行的儿童通学方式选择行为研究

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics