Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (11): 2568-2573.doi: 10.13229/j.cnki.jdxbgxb20210530

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Residents' commuting time model under the nonlinear impact of urban built environment

Jing-xian WU1,2(),Hua-peng SHEN1,Yin HAN1(),Min YANG3   

  1. 1.Business School，University of Shanghai for Science and Technology，Shanghai 200093，China
    2.Key Laboratory of Earthquake Engineering and Engineering Vibration，Institute of Engineering Mechanics，China Earthquake Administration，Harbin 150080，China
    3.School of Transportation，Southeast University，Nanjing 210096，China
  • Received:2021-06-18 Online:2022-11-01 Published:2022-11-16
  • Contact: Yin HAN E-mail:wujingxiannn@163.com;hanyin2000@sina.com

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Abstract:

To investigate the nonlinear impact of built environment on residents' commuting time， a case study was conducted in Nanjing by using a Gradient Boosting Decision Tree. The model has considered the impact of socio-demographics， trip characteristics， and built environment at traffic analysis zone. The result shows that trip characteristics have the largest cumulative contribution on commuting time as high as 52%， followed by built environment factors（38.88%）. Significant nonlinear impacts of built environment have been presented. The nonlinear thresholds of land-use mix and residential ratio are identified. This study expects to provide supportive scientific references for urban future planning and design at the micro-level.

Key words: engineering of communications and transportation system, built environment, commuting time, nonlinear effects, gradient boosting decision tree

CLC Number: 

  • U491.1

Fig.1

Traffic analysis zones in central city of Nanjing"

Table 1

Sample data description （N=3200）"

属性变量变量定义均值标准差
个人家庭性别是否为男性：0-否（48.2%）；1-是（51.8%）0.5180.500
学历是否具有大专及以上学历：0-否（48.0%）；1-是（52.0%）0.5200.500
年龄

年龄：1-18~29岁（34.9%）；2-30~40岁（24.0%）；

3-40~50岁以上（25.8%）；4-50岁以上（15.3%）

2.2141.080
驾照是否拥有驾照：0-否（40.3%）；1-是（59.7%）0.5970.491
汽车拥有数家庭中小汽车拥有数量（辆）0.7900.590
学龄前儿童家庭中学龄前儿童个数（个）0.1240.332
家庭年收入家庭年收入是否高于10万元：0-否（43.0%）；1-是（57.0%）0.5700.494
通勤出行特征慢行出行是否使用慢行交通方式出行：0-否（44.6%）；1-是（55.4%）0.5540.497
公交出行是否使用公共交通出行：0-否（85.3%）；1-是（14.7%）0.1470.354
机动车出行是否使用私人机动车出行：0-否（70.1%）；1-是（29.9%）0.2990.458
出发时间是否高峰时期出行：0-否（47.0%）；1-是（53.0%）0.5300.499
通勤距离职住交通小区间直线距离（km）8.4207.620
通勤时间居民通勤所需时间（min）34.72019.950

建成环境

距市中心距离居住地交通小区距离市中心的距离（km）9.0597.394
公交站点密度居住地交通小区公交站台个数/交通小区面积（个/km2）20.06111.685
交叉口密度居住地交叉口个数/交通小区面积（个/km2）19.63731.801
混合度居住地交通小区用地混合熵0.6490.169
地铁站密度居住地交通小区地铁站个数/交通小区面积（个/km2）1.1971.979
住宅用地占比居住地交通小区住宅用地面积/交通小区面积0.3160.205
工作用地占比居住地交通小区商业、工业等用地面积/交通小区面积0.2970.181
路网密度居住地交通小区所有道路长度/交通小区面积（km/km2）12.3008.860

Table 2

Relative importance and ranking of explanatory variables"

属性变 量影响程度影响程度/%总计/%
建成环境属性路网密度36.6138.88
工作用地占比45.61
公交站点密度55.52
距市中心距离65.45
住宅用地占比75.22
混合度84.74
交叉口密度94.06
地铁站点密度141.67
通勤出行特征慢行出行221.1752.00
公交出行112.72
私人机动车131.92
通勤距离122.50
出发时间103.69
个人家庭属性性别161.389.12
学历191.03
年龄122.33
家庭小汽车拥有量151.64
家庭收入171.20
学龄前儿童数目200.37
驾照181.17
总计100

Fig.2

Nonlinear impact of land use mixture"

Fig.3

Nonlinear impact of intersection density"

Fig.4

Nonlinear impact of job density"

Fig.5

Nonlinear impact of house density"

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