Journal of Jilin University(Engineering and Technology Edition) ›› 2026, Vol. 56 ›› Issue (8): 2095-2105.doi: 10.13229/j.cnki.jdxbgxb.20250050

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Impact of built environment on residents′ car dependence in different periods

Yi-lin SUN1,2(),Yu-kun CAI1,Fang-yuan JIA1,Yang SHU2   

  1. 1.Polytechnic Institute,Zhejiang University,Hangzhou 310015,China
    2.College of Civil Engineering and Architecture,Zhejiang University,Hangzhou 310058,China
  • Received:2025-01-14 Online:2026-08-01 Published:2026-09-02

Abstract:

To explore the differences in the impact of built environment on residents' car dependence in different periods,a light gradient boosting machine(LightGBM)model was constructed based on the residents' travel survey data of Hangzhou in 2010 and 2023. Nonlinear analysis was carried out using partial dependence plots and shapley additive explanations.The results show that the LightGBM model accurately captured the nonlinear relationship between built environment and residents' car dependence.The built environment has a significant impact on residents' car dependence,and there are significant differences in different periods.Compared with 2010,the impact of built environment on residents' car dependence in 2023 has significantly weakened.The influence of population and road density shows a threshold effect.When the population density of the residential area exceeds 20 000 people/km2 or the road density exceeds 0.04 km/buffer zone,the proportion of car travel among young people increases instead.This indicates that it is necessary to accurately grasp the impact of threshold effect to avoid the waste of construction resources and the negative effects brought by over-construction.

Key words: engineering of communicaiton and transportation system, built environment, car dependence, light gradient boosting machine, threshold effect

CLC Number: 

  • U491

Fig.1

Study area of Hangzhou"

Table 1

Descriptive of built environment"

属性指标变量描述2010年2023年
均值/占比标准差均值/占比标准差
小汽车依赖变量小汽车保有量家庭小汽车保有数量0.2490.431 90.2300.183 3
小汽车出行占比一日出行中小汽车出行的占比0.1670.362 30.2050.388 7
建成环境变量人口密度单位面积内的居住人口数14 10810 382.811 4417 957.18
土地利用混合度熵指数0.7400.2340.8240.066 2
道路密度单位面积内的道路里程数0.010 50.007 520.022 40.007 13
商圈易达性距离最近商圈的距离0.3964.150.2740.642
公交邻近度居住地附近的公交地铁站点数5.5433.904.464.08
社会经济变量性别0:女性51.2%(50%)0.499 948.5%(51%)0.499 9
1:男性48.8%(50%)51.5%(49%)
年龄1:20~35岁27.5%(32%)14.9926.9%(24%)14.21
2:35~60岁50.4%(47%)46.3%(45%)
3:60岁以上22.1%(21%)26.8%(31%)
家庭收入1:收入小于1 0003%1.229<0.1%1.337
2:收入为1 000~3 00045.6%0
3:收入为3 000~5 00028.2%0.2%
4:收入为5 000~7 00012.7%4.1%
5:收入为7 000~10 0006.2%5.5%
6:收入为10 000~12 0002.7%14.7%
7:收入为12 000~15 0000.8%24.9%
8:收入为15 000~20 0000.9%34.9%
9:收入为20 000~25 000<0.1%13.4%
10:收入为25 000~30 00002.0%
11:收入为30 000以上00.2%
学历1:小学及以下14.2%0.647 412.0%0.673 2
2:中学55.7%45.0%
3:大专、本科及以上30.1%43.0%

Fig.2

Histogram algorithm"

Fig.3

Splitting tactics of decision tree"

Fig.4

Machine model effect comparison chart"

Table 2

Feature importance"

变量小汽车保有量/%小汽车出行占比/%
2010年2023年2010年2023年
社会经济属性家庭收入28.8937.1316.196.52
年龄18.5222.2931.7641.46
学历11.4824.3912.495.4
性别10.370.9220.734.08
建成环境属性人口密度16.052.549.383.22
商圈易达性5.913.174.331.49
道路密度6.214.024.263.66
公交邻近度1.413.440.41.71
土地利用混合度1.172.10.492.47

Fig.5

Nonlinear effects of various variables on car ownership"

Fig.6

Non-linear effects of various variables on car share"

Fig.7

Interaction effects on car ownership"

Fig.8

Interaction effects on proportion of car trips"

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