Layout Optimization of Campus Bike-Sharing Parking Spots

Guo, Tangyi; Yang, Jie; Liu, He; Tang, Kun

doi:10.1155/2020/8894119

Cited by 8 publications

(9 citation statements)

References 18 publications

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“…In addition, we conducted statistics on the distribution of personal attributes in the survey results. Similar to the proportion of BS users in China [ 24 ], the frequency of BS trips was above 50% for both college students and office workers, with college students using BS slightly more frequently than office workers. Undergraduates used BS more frequently than postgraduates, who had regular weekly classes and commuted more frequently between different academic buildings compared to postgraduates.…”

Section: Resultsmentioning

confidence: 77%

“…From the perspective of BS user groups, it have mainly concentrated on college students and office workers in China [ 23 ]. For one thing, the BS increase the interest of college students, with the advantages of easy cycling, low costs and low carbons [ 24 ]. Furthermore, it could reduce the travel pressure on campus as an alternative means [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

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A Comparison in Travel Characteristics of Bike-Sharing between College Students and Office Workers Based on Theory of Planned Behavior

Duan

Wang

et al. 2023

Behavioral Sciences

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As an important component of bike-sharing (BS) users, the travel behavior of college students and office workers is important to the promotion of BS within Chinese cities. To explore the influencing factors for the behavioral intentions of BS, this paper makes a different analysis between the two groups. Based on the theory of planned behavior, and using environmental awareness as an extended variable, a BS travel intention model was developed. A total of 676 valid questionnaires were collected and analyzed from college students and office workers in Zhengzhou. The results indicate that attitude, subjective norms, perceived behavior control, and environmental awareness have a positive impact on the behavioral intentions of BS. However, the influence degree of each variable is different between the two groups. Perceived behavior control, including travel time, travel cost, and cycling difficulty, has the greatest impact on BS behavioral intention for college students. Meanwhile, subjective norms, including policy and media publicity, has the most significant impact on BS behavioral intention for office workers. The impact of environmental awareness on college students’ use of BS is higher than that of office workers. We also found that undergraduates use BS more frequently than postgraduates. The findings provide the clear influence factors on behavioral intentions of BS between college students and office workers, that can help policy optimization in terms of bike-sharing systems, giving some suggestion for an approach devoted to deepen the individual-context interactions

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Section: Resultsmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

A Comparison in Travel Characteristics of Bike-Sharing between College Students and Office Workers Based on Theory of Planned Behavior

Duan

Wang

et al. 2023

Behavioral Sciences

View full text Add to dashboard Cite

show abstract

“…In addition, for decentralized cities, it is also necessary to establish a walking and non motorized slow traffic system to form a slow traffic network connecting various centers, so as to provide convenience for residents' travel, so as to reduce the traffic problems in the core area of the city. In the lemma 2, the estimation model is defined [17][18][19][20][21].…”

Section: Fig 2 the Traffic Network Modelmentioning

confidence: 99%

Intelligent Shared Bicycle Transportation Planning System Under the Concept of Green Transportation and Smart Cities

2023

International Journal of Science and Engineering Applications

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Intelligent shared bicycle transportation planning system under the concept of the green transportation and smart cities is studied in this paper. The main part of the system we designed is based on the GIS, including the indexing, retrieval, positioning, spatial topology analysis of highway data, etc. The data needs to be accessed through Web GIS during operation to ensure the normal operation of the website. Our simulation study assumes that there is a certain connection between land use and transportation. Under the assumption that other influencing factors remain unchanged. Predict changes in transportation and travel by changing one or more land use variables. Furthermore, the concept of green transportation and smart cities are then combined to enhance the model. The designed framework is simulated under the complex environment.

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“…eir optimization model selected placements that maximized user coverage for a given level of investment. Guo et al [28] used a branch and bound optimization algorithm to address the bike-stowage problem for a university campus [28]. eir optimization model solved an impedance minimization problem by considering all pairwise combinations of candidate locations and demand points.…”

Section: Level Of Traffic Stressmentioning

confidence: 99%

Micromobility Station Placement Optimization for a Rural Setting

Askarzadeh

Bridgelall

2021

Journal of Advanced Transportation

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Micromobility is an evolving form of transportation modality that uses small human- or electric-powered vehicles to move people short distances. Planners expected that bike sharing, the first form of micromobility, would reduce traffic congestion, cut travel cost, reduce pollution, enable connectivity with other modes of transport, and promote public health. However, micromobility options also brought new challenges such as the difficulty of placement decisions to encourage adoption and to minimize conflict with other transport modes. Sound deployment decisions depend on the unique environmental characteristics and demographics of a location. Most studies analyzed deployments in high-density urban areas. This research determines the best locations for 5 new bike-sharing stations in Fargo, North Dakota, a small urban area in the rural United States. The workflow combines a geographic information system (GIS), level of traffic stress (LTS) ratings, and location-allocation optimization models. The spatial analysis considered 18 candidate station locations and eliminated those that fell within the 700-meter isochrone walking distance of the 11 existing stations. This case study demonstrates a scalable workflow that planners can repeat to achieve sustainable micromobility deployments by considering the land use, population density, activity points, and characteristics of the available pathways in their unique setting.

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Layout Optimization of Campus Bike-Sharing Parking Spots

Cited by 8 publications

References 18 publications

A Comparison in Travel Characteristics of Bike-Sharing between College Students and Office Workers Based on Theory of Planned Behavior

A Comparison in Travel Characteristics of Bike-Sharing between College Students and Office Workers Based on Theory of Planned Behavior

Intelligent Shared Bicycle Transportation Planning System Under the Concept of Green Transportation and Smart Cities

Micromobility Station Placement Optimization for a Rural Setting

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