A node optimization model based on the spatiotemporal characteristics of the road network for urban traffic mobile crowd sensing

2021 ◽  
pp. 100383
Author(s):  
Haiyang Yu ◽  
Jing Fang ◽  
Shuai Liu ◽  
Yilong Ren ◽  
Jian Lu
Keyword(s):  
Optimization Model ◽  
Road Network ◽  
Urban Traffic ◽  
Mobile Crowd Sensing ◽  
The Road ◽  
Model Based ◽  
Spatiotemporal Characteristics ◽  
Crowd Sensing ◽  
Mobile Crowd

scholarly journals Service node selection optimization for mobile crowd sensing in a road network environment

2020 ◽  
Vol 22 ◽  
pp. 100203
Author(s):  
Haiyang Yu ◽  
Chenyang Liu ◽  
Yilong Ren ◽  
Nan Ji ◽  
Can Yang
Keyword(s):  
Road Network ◽  
Network Environment ◽  
Mobile Crowd Sensing ◽  
Node Selection ◽  
Crowd Sensing ◽  
Mobile Crowd

scholarly journals Optimization Model for the Supply Volume of Bike-Sharing: Case Study in Nanjing, China

Information ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 182
Author(s):  
Jiajie Yu ◽  
Yanjie Ji ◽  
Chenyu Yi ◽  
Chenchen Kuai ◽  
Dmitry Ivanovich Samal
Keyword(s):  
Optimization Model ◽  
Road Network ◽  
Optimal Solution ◽  
Traffic Analysis ◽  
Urban Traffic ◽  
Mixed Integer ◽  
The Road ◽  
Bike Sharing ◽  
Flow Conservation ◽  
Parking Facilities

In order to solve the oversupply and repositioning problems of bike-sharing, this paper proposes an optimization model to obtain a reasonable supply volume scheme for bike-sharing and infrastructure configuration planning. The optimization model is constrained by the demand for bike-sharing, urban traffic carrying capacity (road network and parking facilities carrying capacities), and the flow conservation of shared bikes in each traffic analysis zone. The model was formulated through mixed-integer programming with the aim of minimizing the total costs for users and bike-sharing enterprises (including the travel cost of users, production and maintenance costs of shared bikes, and repositioning costs). CPLEX was used to obtain the optimal solution for the model. Then, the optimization model was applied to 183 traffic analysis zones in Nanjing, China. The results showed that not only were user demands met, but the load ratios of the road network and parking facilities with respect to bike-sharing in each traffic zone were all decreased to lower than 1.0 after the optimization, which established the rationality and effectiveness of the optimization results.

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