This page has only limited features, please log in for full access.

Unclaimed
Liangpeng Gao
Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Dongnandaxue Road 2, Nanjing 211189, China

Basic Info

Basic Info is private.

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 04 July 2019 in Sustainability
Reads 0
Downloads 0

Since the long dwell time and chaotic crowds make metro trips inefficient and dissatisfying, the importance of optimizing alighting and boarding processes has become more prominent. This paper focuses on the adjustment of passenger organizing modes. Using field data from the metro station in Nanjing, China, a micro-simulation model of alighting and boarding processes based on an improved social force paradigm was built to simulate the movement of passengers under different passenger organizing modes. Unit flow rate, delay, and social force work (SFW) jointly reflect the efficiency and, especially, the physical energy consumption of passengers under each mode. It was found that when passengers alighted and boarded by different doors, efficiency reached its optimal level which was 76.92% higher than the status quo of Nanjing, and the physical energy consumption was reduced by 16.30%. Both the findings and the model can provide support for passenger organizing in metro stations, and the concept of SFW can be applied to other scenes simulated by the social force model, such as evacuations of large-scale activities, to evaluate the physical energy consumption of people.

ACS Style

Jiajie Yu; Yanjie Ji; Liangpeng Gao; Qi Gao. Optimization of Metro Passenger Organizing of Alighting and Boarding Processes: Simulated Evidence from the Metro Station in Nanjing, China. Sustainability 2019, 11, 3682 .

AMA Style

Jiajie Yu, Yanjie Ji, Liangpeng Gao, Qi Gao. Optimization of Metro Passenger Organizing of Alighting and Boarding Processes: Simulated Evidence from the Metro Station in Nanjing, China. Sustainability. 2019; 11 (13):3682.

Chicago/Turabian Style

Jiajie Yu; Yanjie Ji; Liangpeng Gao; Qi Gao. 2019. "Optimization of Metro Passenger Organizing of Alighting and Boarding Processes: Simulated Evidence from the Metro Station in Nanjing, China." Sustainability 11, no. 13: 3682.

Journal article
Published: 09 December 2018 in Sustainability
Reads 0
Downloads 0

Long-distance school commuting is a key aspect of students’ choice of car travel. For cities lacking school buses, the metro and car are the main travel modes used by students who have a long travel distance between home and school. Therefore, encouraging students to commute using the metro can effectively reduce household car use caused by long-distance commuting to school. This paper explores metro ridership at the station level for trips to school and return trips to home in Nanjing, China by using smart card data. In particular, a global Poisson regression model and geographically weighted Poisson regression (GWPR) models were used to examine the effects of the built environment on students’ metro ridership. The results indicate that the GWPR models provide superior performance for both trips to school and return trips to home. Spatial variations exist in the relationship between the built environment and students’ metro ridership across metro stations. Built environments around metro stations, including commercial-oriented land use; the density of roads, parking lots, and bus stations; the number of docks at bikeshare stations; and the shortest distance between bike stations and metro stations have different impacts on students’ metro ridership. The results have important implications for proposing relevant policies to guide students who are being driven to school to travel by metro instead.

ACS Style

Yang Liu; Yanjie Ji; Zhuangbin Shi; Liangpeng Gao. The Influence of the Built Environment on School Children’s Metro Ridership: An Exploration Using Geographically Weighted Poisson Regression Models. Sustainability 2018, 10, 4684 .

AMA Style

Yang Liu, Yanjie Ji, Zhuangbin Shi, Liangpeng Gao. The Influence of the Built Environment on School Children’s Metro Ridership: An Exploration Using Geographically Weighted Poisson Regression Models. Sustainability. 2018; 10 (12):4684.

Chicago/Turabian Style

Yang Liu; Yanjie Ji; Zhuangbin Shi; Liangpeng Gao. 2018. "The Influence of the Built Environment on School Children’s Metro Ridership: An Exploration Using Geographically Weighted Poisson Regression Models." Sustainability 10, no. 12: 4684.