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Author:

Zhang, Z. (Zhang, Z..) | Weng, J. (Weng, J..) | Wang, L. (Wang, L..) | Sui, L. (Sui, L..)

Indexed by:

Scopus

Abstract:

Passenger volume of lasting large scale activities have the features of gathering, dispersing and large scale within a short time and a small range. Lasting large scale activities are defined as the large activities or events held for days, they have long duration, wide range of influence, and obvious passenger volume fluctuation, the passenger volume scale and time-space distribution is affected by weather, environment, holiday trip mode and other factors. It is important to reveal influencing factors and the influencing mechanism for the transportation operation and organize for lasting large scale activities. This study based on the passenger volume of the 9th China International Garden Expo, collected vehicle load coefficient through field car-following investigation. After observing the passenger volume by automated method, the study gained passenger volume data in a period of four months. Based on the collected data, the paper analyzes the characteristics of trip mode and passenger arrival and departure, as well as the influencing factors of passenger volume scale. This analysis shows that visit cost, weather and holidays are the main factors which are influencing the passenger volume scale. People tend to take care about their cost during visit and prefer to travel in good weather or holiday. Compared with the working day, weekend and holiday passenger volume highest average growth is over 200%, passenger volume growth is 30% on average. However, on rainy days, high temperature and other abnormal weather conditions, the passenger volume will decrease 20%-50%. The self-promotion activities held has not been obvious influenced on the passenger flow. The analysis of the influencing factors and time-space distribution characteristics of passenger volume of lasting large scale activities, will contribute to the study of traffic impact model of special activities, and provide effective data to support to make valid traffic organization and management measures during lasting large scale activities. © 2015 IEEE.

Keyword:

passenger forecast; passenger volume distribution; special activities; traffic management

Author Community:

  • [ 1 ] [Zhang, Z.]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing, China
  • [ 2 ] [Weng, J.]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing, China
  • [ 3 ] [Wang, L.]Beijing Transportation Information Center, Beijing, China
  • [ 4 ] [Sui, L.]Beijing Transportation Information Center, Beijing, China

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Source :

ICTIS 2015 - 3rd International Conference on Transportation Information and Safety, Proceedings

Year: 2015

Page: 414-418

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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