scholarly journals Cluster Analysis of Stations Based on Weight SimRank in Sharing Bicycle

CONVERTER ◽  
2021 ◽  
pp. 09-18
Author(s):  
Bo Guan, Et al.
Keyword(s):  
Small World ◽  
Urban Traffic ◽  
Site Location ◽  
World Region ◽  
Root Cause ◽  
Large Numbers ◽  
Similarity Algorithm ◽  
Bike Sharing ◽  
Destination Station ◽  
Subway Stations

With the increasing popularity of shared bikes, the indiscriminate parking of bicycles in cities has increasingly become a difficulty in urban management. The tidal phenomenon of large numbers of urban residents during rush hour is the root cause of the indiscriminate parking of bicycles in many subway stations and commercial areas. Optimizing the scheduling strategy of shared bikes is one of the effective solutions to solve the problem of random parking and reduce the scheduling cost. The cycle is a short - distance vehicle, and its circulation law is in line with the characteristics of the small world of urban traffic. That is, most of the bikes flow within the small world region, while only a small part of the bikes flow between the small world regions. With the massive accumulation of bike-sharing borrow and return data, the method of clustering the borrow and return stations and dividing regions according to the clustering results has attracted the attention of industry experts and researchers. it is effectively to apply in intelligent scheduling related industries. Although there have been some studies on the station clustering in the current literature, because these studies are basically based on the fixed features of the site (site location, pile number, etc.), the results cannot find an effective small world region of bicycles. In order to find out the effective small world region of bicycles, we introduced the idea of SimRank (that is, the similarity of a station is due to the similarity of its bicycle source station and destination station), and assigned weights to association relationships (the number of times of borrowing and returning) to define the similarity algorithm w-SimRank of stations. Then, the station clustering was done in line with skyline thinking. Finally, in order to verify the effectiveness of the algorithm, we implemented the station clustering based on SimRank algorithm, and compared the clustering effect with the W-SimRank algorithm proposed in this paper to verify the effectiveness of the W-SimRank algorithm, and analyzed the influence of the key parameters of the algorithm on the algorithm. And then

scholarly journals Green transportation system to promote sustainable lifestyle in Chulalongkorn University

2018 ◽  
Vol 48 ◽  
pp. 07001 ◽  
Author(s):  
Jirarat Pinthong ◽  
Korb Limsuwan ◽  
Boonchai Stitmannaithum
Keyword(s):  
Traffic Congestion ◽  
Engineering Students ◽  
Good Health ◽  
Transportation System ◽  
Bus Routing ◽  
Bike Sharing ◽  
Parking Garages ◽  
Subway Stations ◽  
Bus Service ◽  
The University

Chulalongkorn University (CU) is located at the heart of Bangkok, which is one of the most traffic congested cities in the world. It is very crucial for the university to develop a green and clean transportation system that is good for both the CU community and the whole society. To reduce on-campus traffic, the university provides four parking buildings on the edge of four corners of the campus to serve visitors, students, faculties and staffs who travel by private cars. While providing added convenience, these parking garages reduce traffic congestion on campus and, thus, pollutions from harmful emissions and traffic noises. To promote eco-friendly transportation in the campus, the university provides “CU Shuttle Bus” - an electric shuttle bus service that cover not only campus area, but also reach out to public sky train and subway stations around the campus. The CU Shuttle Bus’s mobile application, developed by engineering students, helps improve user experience by showing all useful information including campus map, bus routing, and real-time locations of all buses. To encourage walking and cycling within the campus and to promote good health and fitness, the university has been constructing covered walkways and bike lanes throughout the campus. In addition, “CU Bike” - a bike sharing program, was first introduced in 2014 and has quickly grown in popularity among CU students since. A new “CU Toyota Hamo”, an electric vehicle rental program, is another great option of green transportations for those who cannot ride a bicycle and for older people of the aging society. All these projects help promote the development of innovations and practices that are both sustainable and protective of the environment of Chulalongkorn University, as well as the surrounding community, the country and planet as a whole.

scholarly journals Data Analysis of Pile-free bike-sharing from Market Status to Operation Management Mode

2021 ◽  
Vol 251 ◽  
pp. 01052
Author(s):  
Jingyu Liang ◽  
Yiqing Zhu ◽  
Peixue Lin
Keyword(s):  
Data Analysis ◽  
Active Role ◽  
Urban Traffic ◽  
Management Mode ◽  
Future Research ◽  
Bike Sharing ◽  
Market Status ◽  
Subject Areas ◽  
The Individual ◽  
Operation And Management

Shared travel plays a more and more active role in the emergence of urban traffic, but there is no systematic and perfect combing and analysis on the study of bike-sharing without piles, especially on its operation and management mode. This paper will conduct a comprehensive data analysis on the research of bike-sharing without piles from the individual micro level and the enterprise government level, and explore the research focus and possible subject areas of future research.

scholarly journals Incorporation of the Driver’s Personality Profile in an Agent Model

2015 ◽  
Vol 27 (6) ◽  
pp. 505-514 ◽  
Author(s):  
Mian Muhammad Mubasher ◽  
Syed Waqar Ul Qounain Jaffry
Keyword(s):  
Traffic Flow ◽  
Serious Games ◽  
Urban Traffic ◽  
Driver Model ◽  
Big Five Personality ◽  
Personality Profile ◽  
Traffic Planning ◽  
Agent Model ◽  
Root Cause ◽  
Surrounding Environment

Urban traffic flow is a complex system. Behavior of an individual driver can have butterfly effect which can become root cause of an emergent phenomenon such as congestion or accident. Interaction of drivers with each other and the surrounding environment forms the dynamics of traffic flow. Hence global effects of traffic flow depend upon the behavior of each individual driver. Due to several applications of driver models in serious games, urban traffic planning and simulations, study of a realistic driver model is important. Hhence cognitive models of a driver agent are required. In order to address this challenge concepts from cognitive science and psychology are employed to design a computational model of driver cognition which is capable of incorporating law abidance and social norms using big five personality profile.

scholarly journals Heuristic Bike Optimization Algorithm to Improve Usage Efficiency of the Station-Free Bike Sharing System in Shenzhen, China

2019 ◽  
Vol 8 (5) ◽  
pp. 239 ◽  
Author(s):  
Zhihui Gu ◽  
Yong Zhu ◽  
Yan Zhang ◽  
Wanyu Zhou ◽  
Yu Chen
Keyword(s):  
Optimization Algorithm ◽  
Public Transportation ◽  
User Satisfaction ◽  
Small Scale ◽  
Supply And Distribution ◽  
Trip Chain ◽  
Large Numbers ◽  
Bike Sharing ◽  
New Type ◽  
Objective Basis

Station-free bike sharing systems (BSSs) are a new type of public bike system that has been widely deployed in China since 2017. However, rapid growth has vastly outpaced the immediate demand and overwhelmed many cities around the world. This paper proposes a heuristic bike optimization algorithm (HBOA) to determine the optimal supply and distribution of bikes considering the effect of bicycle cycling. In this approach, the different bike trips with separate bikes can be connected in space and time and converted into a continuous trip chain for a single bike. To improve this cycling efficiency, it is important to properly design the bicycle distribution. Taking Shenzhen as an example, we implement the algorithm with OD matrix data from Mobike and Ofo, the two large bike sharing companies which account for 80% of the shared bike market in Shenzhen, over two days. The HBOA results are as follows. 1) Only one-fifth of the bike supply is needed to meet the current usage demand if the bikes are used efficiently, which means a large number of shared bikes in Shenzhen remain in an idle state for long periods. 2) Although the cycling demand is high in many areas, it does not mean that large numbers of bikes are needed because the continuous inflow caused by the cycling effect of bikes will meet most of the demand by itself. 3) The areas with the highest demands for optimal bikes are residential, followed by industrial, public transportation, official and commercial areas, on both working and non-working days. This algorithm can be an objective basis for city related departments to manage station-free BSSs and be applied to design the layout of bikes in small-scale spatial units to help station-free BSSs operate efficiently and minimize the need to relocate the bikes without reducing the level of user satisfaction.

URBAN TRAFFIC CONGESTION SPREADING IN SMALL WORLD NETWORKS

2005 ◽  
Vol 19 (28) ◽  
pp. 4239-4246 ◽  
Author(s):  
HUIJUN SUN ◽  
JIANJUN WU
Keyword(s):  
Infection Rate ◽  
Traffic Congestion ◽  
Small World ◽  
Urban Traffic ◽  
Small World Network ◽  
Small World Networks ◽  
Seir Model

In this paper, two definitions about traffic congestion are proposed. We describe the traffic congestion spreading with the SEIR model of a complex small-world network. In addition, the relationships among the congestion factor, the number of average infection, the average recover rate and the infection rate are given by simulations in general traffic congestion conditions.

The Last Mile Matters: Impact of Dockless Bike Sharing on Subway Housing Price Premium

2020 ◽  
Author(s):  
Junhong Chu ◽  
Yige Duan ◽  
Xianling Yang ◽  
Li Wang
Keyword(s):  
Housing Price ◽  
Relative Increase ◽  
Price Premium ◽  
Urban Residents ◽  
Difference In Differences ◽  
Last Mile ◽  
Bike Sharing ◽  
Subway Stations ◽  
The Relationship ◽  
The City

Dockless bike sharing provides a convenient and affordable means of transport for urban residents. It solves the “last-mile problem” in public transport by reducing the travel cost between home and subway stations and thus increasing the attractiveness of distant apartments. This may affect the relationship between housing price and distance to subway and reduce the price premium enjoyed by proximate apartments. Using resale apartment data in 10 major cities in China, a difference-in-differences approach at the apartment level, and a two-step estimator at the city-month level, we find that the entry of bike sharing reduces the housing price premium by 29% per km away from a subway station. The effect is equivalent to a reduction of 1,893–2,127 CNY (282–317 USD) in commuting costs per household per annum over 30 years. The effect is driven by a relative increase in the listing price of, and in the demand for, apartments distant from vis-à-vis proximate to subway stations. This paper was accepted by Juanjuan Zhang, marketing.

scholarly journals A Natural Origin of Life

2018 ◽  
Author(s):  
Timothy R Stout ◽  
George Matzko
Keyword(s):  
Small Molecules ◽  
Law Of Large Numbers ◽  
Product Distribution ◽  
Single Step ◽  
Initial Composition ◽  
Normal Product ◽  
Root Cause ◽  
Murchison Meteorite ◽  
Large Numbers ◽  
Subsequent Step

Prebiotic processes naturally randomize their feedstock. This has resulted in the failure of every experimentally tested hypothetical step in abiogenesis beginning with the 1953 Miller-Urey Experiment and continuing to the present. Not a single step has been demonstrated which starts with appropriate supply chemicals, operates on the chemicals with a prebiotic process, and yields new chemicals that represent progress towards life and which can also be used in a subsequent step as produced. Instead, the products of thousands of experiments over more than six decades consistently exhibit either increased randomization over their initial composition or no change. We propose the following hypothesis of Abiogenetic Randomization as the root cause for most if not all of the failures: 1) prebiotic processes naturally form many different kinds of products; life requires a few very specific kinds. 2) The needs of abiogenesis spatially and temporally are not connected to and do not change the natural output of prebiotic processes. 3) Prebiotic processes naturally randomize feedstock. A lengthy passage of time only results in more complete randomization of the feedstock, not eventual provision of chemicals suitable for life. The Murchison meteorite provides a clear example of this. 4) At each hypothetical step of abiogenesis, the ratio of randomized to required products proves fatal for that step. 5. The statistical law of large numbers applies, causing incidental appearances of potentially useful products eventually to be overwhelmed by the overall, normal product distribution. 6) The principle of emergence magnifies the problems: the components used in the later steps of abiogenesis become so intertwined that single-step first appearance of the entire set is required. Small molecules are not the answer. Dynamic self-organization requires from the beginning large proteins for replication, metabolism and active transport. Many steps across the entire spectrum of abiogenesis are examined, showing how the hypothesis appears to predict the observed problems qualitatively. There is broad experimental support for the hypothesis at each observed step with no currently known exceptions.

Understanding structure of urban traffic network based on spatial-temporal correlation analysis

2017 ◽  
Vol 31 (22) ◽  
pp. 1750230 ◽  
Author(s):  
Yanfang Yang ◽  
Limin Jia ◽  
Yong Qin ◽  
Shixiu Han ◽  
Honghui Dong
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Structural Characteristics ◽  
Small World ◽  
Temporal Correlation ◽  
Urban Traffic ◽  
Utilization Rate ◽  
Traffic Network ◽  
Pagerank Algorithm ◽  
Urban Traffic Network

Understanding the structural characteristics of urban traffic network comprehensively can provide references for improving road utilization rate and alleviating traffic congestion. This paper focuses on the spatial-temporal correlations between different pairs of traffic series and proposes a complex network-based method of constructing the urban traffic network. In the network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding spatial-temporal correlation. Further, a modified PageRank algorithm, named the geographical weight-based PageRank algorithm (GWPA), is proposed to analyze the spatial distribution of important segments in the road network. Finally, experiments are conducted by using three kinds of traffic series collected from the urban road network in Beijing. Experimental results show that the urban traffic networks constructed by three traffic variables all indicate both small-world and scale-free characteristics. Compared with the results of PageRank algorithm, GWPA is proved to be valid in evaluating the importance of segments and identifying the important segments with small degree.

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