A Visualization Based Analysis to Assist Rebalancing Issues Related to Last Mile Problem for Bike Sharing Programs in China: A Big-Data Case Study on Mobike

2019 ◽  
pp. 145-153
Author(s):  
Ercument Gorgul ◽  
Chaoran Chen
Keyword(s):  
Big Data ◽  
Last Mile ◽  
Bike Sharing ◽  
Last Mile Problem

scholarly journals Sharing and Riding: How the Dockless Bike Sharing Scheme in China Shapes the City

Urban Science ◽  
2018 ◽  
Vol 2 (3) ◽  
pp. 68 ◽  
Author(s):  
Yiyun Sun
Keyword(s):  
Sharing Economy ◽  
Market Demand ◽  
Negative Consequences ◽  
Negative Effects ◽  
The Public ◽  
Sharing Scheme ◽  
Last Mile ◽  
Bike Sharing ◽  
Future Direction

Over the last three years, the dockless bike sharing scheme has become prevalent in the context of the boom in the sharing economy, the wide use of mobile online payment, the increasing environmental awareness and the inherent market demand. This research takes Beijing as a case study, investigates the users’ characteristics, their behaviour change, and perceptions of dockless bike sharing scheme by the quantitative survey, and then analyzes the reasons behind it and how it has changed the residents’ life in Beijing. This new kind of dockless shared bikes, with great advantages of accessibility, flexibility, efficiency and affordability, helps to solve the ‘last mile’ problem, reduce the travel time, and seems to be very environmentally-friendly and sustainable. However, with the help of interview and document analysis, this research finds that the shared bikes are not the effective alternative for the frequent car-users. Nevertheless, it also has numerous negative consequences such as ‘zombie’ bikes blocking the sidewalks and vandalism to the bikes. The public is also worried about their quality and safety, especially the issues of ‘right of way’. How to coordinate and solve these problems is not only related to the future direction of the dockless bike sharing scheme but also to the vital interests of the general public. Therefore, it is important to emphasize that governments, enterprises, and the public participate in multi-party cooperation and build synergic governance networks to carry forward the advantages and avoid the negative effects of the new bike sharing system.

scholarly journals Operating Characteristics of Dockless Bike-Sharing Systems near Metro Stations: Case Study in Nanjing City, China

2019 ◽  
Vol 11 (8) ◽  
pp. 2256 ◽  
Author(s):  
Yuan Li ◽  
Zhenjun Zhu ◽  
Xiucheng Guo
Keyword(s):  
Activity Patterns ◽  
Land Development ◽  
Operating Characteristics ◽  
Railway Stations ◽  
Trip Chain ◽  
Spatial Distribution Characteristics ◽  
Last Mile ◽  
Bike Sharing ◽  
Nanjing City

With the growth of dockless bike-sharing (DLBS) systems, the first-and-last mile connection to public transport, such as metro and light railway stations, could be improved. DLBS systems complete the trip chain by connecting metro stations with points of interest and enhance the sustainability of urban transportation. Therefore, it is necessary to understand the trans-shipment characteristics of DLBS systems for metro stations. In this study, we collected data from the Mobike DLBS system in Nanjing City, China and applied K-means clustering to analyse the activity patterns of DLBS systems near local metro stations. Metro stations were categorised into five types on workdays and three types on weekends. An analysis of the relationships between activity patterns and spatial distribution characteristics demonstrated that the distribution of clusters possesses a strong connection with the surrounding environment. Low land development rates and a sparse distribution of metro stations cause a large range of influences. This research has direct implications for understanding the operating state of DLBS systems near metro stations and promoting the proper management of DLBS systems.

scholarly journals Evaluation methods of dynamic flexible transportation systems

2021 ◽  
Author(s):  
Shadi Djavadian
Keyword(s):  
Real Data ◽  
User Equilibrium ◽  
Adjustment Process ◽  
Social Optimum ◽  
Agent Based ◽  
Digital World ◽  
Transport Services ◽  
Last Mile ◽  
Last Mile Problem

With advances in mobile technologies, social networks and global positioning (GPS) in the digital world, alternative mobility systems (taxis, carpool, demand-responsive services, peer-to-peer ridesharing, carsharing) have garnered interest from both public and private sectors as potential solutions to address last mile problem in public transit. Although there are number of models to optimize flexible or dynamic transit operations there has not been any methodology to evaluate equilibrium demand and effect on social welfare for these systems in an integrated supply-demand context. This study lays the groundwork for studying the equilibrium of these systems, and proposes an agent-based adjustment process to evaluate the properties of a stable sate as an agent-based stochastic user equilibrium (SUE). Four sets of experiments are conducted: (1) illustration with a simple 2-link network, (2) evaluation of a dynamic dial-a-ride policy, and (3 &4) illustration using real data from Oakville, Ontario & Manhattan, NY. The experiments demonstrate that the proposed model with multiple sample populations can generate an invariant distribution of demand and welfare effects and it can effectively be used to measure the effect of changes in flexible transport services operation policies on ridership. Moreover, this study also explores flexible transport services as two-sided markets, and extends the proposed agent-based day-to-day adjustment process to include day-to-day adjustment of the service operator(s) as a two-sided market. Additional computational experiments and a case study are conducted. Findings confirm the existence of thresholds from which network externalities cause two-sided and one-sided market equilibria to diverge. The Ramsey pricing criterion is used for social optimum to show that perfectly matched states from the proposed day-to-day process are equivalent to a social optimum. A case study using real data from Oakville, Ontario, as a first/last mile problem example demonstrates the sensitivity of the two-sided day-to-day model to operating policies.

scholarly journals Evaluation methods of dynamic flexible transportation systems

2021 ◽  
Author(s):  
Shadi Djavadian
Keyword(s):  
Real Data ◽  
User Equilibrium ◽  
Adjustment Process ◽  
Social Optimum ◽  
Agent Based ◽  
Digital World ◽  
Transport Services ◽  
Last Mile ◽  
Last Mile Problem

With advances in mobile technologies, social networks and global positioning (GPS) in the digital world, alternative mobility systems (taxis, carpool, demand-responsive services, peer-to-peer ridesharing, carsharing) have garnered interest from both public and private sectors as potential solutions to address last mile problem in public transit. Although there are number of models to optimize flexible or dynamic transit operations there has not been any methodology to evaluate equilibrium demand and effect on social welfare for these systems in an integrated supply-demand context. This study lays the groundwork for studying the equilibrium of these systems, and proposes an agent-based adjustment process to evaluate the properties of a stable sate as an agent-based stochastic user equilibrium (SUE). Four sets of experiments are conducted: (1) illustration with a simple 2-link network, (2) evaluation of a dynamic dial-a-ride policy, and (3 &4) illustration using real data from Oakville, Ontario & Manhattan, NY. The experiments demonstrate that the proposed model with multiple sample populations can generate an invariant distribution of demand and welfare effects and it can effectively be used to measure the effect of changes in flexible transport services operation policies on ridership. Moreover, this study also explores flexible transport services as two-sided markets, and extends the proposed agent-based day-to-day adjustment process to include day-to-day adjustment of the service operator(s) as a two-sided market. Additional computational experiments and a case study are conducted. Findings confirm the existence of thresholds from which network externalities cause two-sided and one-sided market equilibria to diverge. The Ramsey pricing criterion is used for social optimum to show that perfectly matched states from the proposed day-to-day process are equivalent to a social optimum. A case study using real data from Oakville, Ontario, as a first/last mile problem example demonstrates the sensitivity of the two-sided day-to-day model to operating policies.

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