Travel Behavior Analysis Using 2016 Qingdao’s Household Traffic Surveys and Baidu Electric Map API Data
المؤلفون المشاركون
Wang, Wei
Gao, Ge
Wang, Zhen
Liu, Xinmin
Zhang, Junyou
Li, Qing
المصدر
Journal of Advanced Transportation
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-18، 18ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-03-11
دولة النشر
مصر
عدد الصفحات
18
التخصصات الرئيسية
الملخص EN
Household traffic surveys are widely used in travel behavior analysis, especially in travel time and distance analysis.
Unfortunately, any one kind of household traffic surveys has its own problems.
Even all household traffic survey data is accurate, it is difficult to get the trip routes information.
To our delight, electric map API (e.g., Google Maps, Apple Maps, Baidu Maps, and Auto Navi Maps) could provide the trip route and time information, which remedies the traditional traffic survey’s defect.
Thus, we can take advantage of the two kinds of data and integrate them into travel behavior analysis.
In order to test the validity of the Baidu electric map API data, a field study on 300 taxi OD pairs is carried out.
According to statistical analysis, the average matching rate of total OD pairs is 90.74%, which reflects high accuracy of electric map API data.
Based on the fused data of household traffic survey and electric map API, travel behavior on trip time and distance is analyzed.
Results show that most purposes’ trip distances distributions are concentrated, which are no more than 10 kilometers.
It is worth noting that students have the shortest travel distance and company business’s travel distance distribution is dispersed, which has the longest travel distance.
Compared to travel distance, the standard deviations of all purposes’ travel time are greater than the travel distance.
Car users have longer travel distance than bus travelers, and their average travel distance is 8.58km.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Gao, Ge& Wang, Zhen& Liu, Xinmin& Li, Qing& Wang, Wei& Zhang, Junyou. 2019. Travel Behavior Analysis Using 2016 Qingdao’s Household Traffic Surveys and Baidu Electric Map API Data. Journal of Advanced Transportation،Vol. 2019, no. 2019, pp.1-18.
https://search.emarefa.net/detail/BIM-1170027
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Gao, Ge…[et al.]. Travel Behavior Analysis Using 2016 Qingdao’s Household Traffic Surveys and Baidu Electric Map API Data. Journal of Advanced Transportation No. 2019 (2019), pp.1-18.
https://search.emarefa.net/detail/BIM-1170027
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Gao, Ge& Wang, Zhen& Liu, Xinmin& Li, Qing& Wang, Wei& Zhang, Junyou. Travel Behavior Analysis Using 2016 Qingdao’s Household Traffic Surveys and Baidu Electric Map API Data. Journal of Advanced Transportation. 2019. Vol. 2019, no. 2019, pp.1-18.
https://search.emarefa.net/detail/BIM-1170027
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1170027
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر