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Intelligent Control Strategies for Vehicle Departure in Urban Complex Parking Lots of the Jinding Area in Shanghai, China.
- Source :
- Applied Sciences (2076-3417); Sep2022, Vol. 12 Issue 17, p8781, 11p
- Publication Year :
- 2022
-
Abstract
- Featured Application: This study introduces ramp control into parking management and proposes intelligent control strategies for vehicle departure in urban complex parking lots. Specifically, in these strategies, the frequency of gate lever lift is optimized using timing control and inductive control. The proposed intelligent control strategies are applied in the Jinding area in Shanghai, China, with large underground parking lots. Compared to non-controlled situations, the driving efficiency of the ground-level traffic is improved. The entrances and exits of underground parking lots of large complexes are the key nodes for the conversion between ground-level dynamic traffic and underground static traffic. Since congestion is caused by a large number of vehicles leaving parking lots at peak hours, the departure control strategy can effectively manage vehicle departure and reduce the congestion of ground-level traffic. In this study, we introduce cooperative control in ramp control into parking lot exit management. The frequency of parking lot exit gate lever lift is used as the control and optimization variable. To ensure the efficiency of regional traffic, we designed timing and inductive control strategies to control the speed of departing vehicles. In an experimental model, we took Shanghai Jinding super-large underground parking lot as an example. The changes in the external road network were simulated when different strategies were implemented on the Simulation of Urban Mobility (SUMO) simulation platform. The experimental results show that the proposed control strategies can significantly ease the congestion of the regional road network, improve the average speed of dynamic traffic, and reduce the queue length at intersections. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 12
- Issue :
- 17
- Database :
- Complementary Index
- Journal :
- Applied Sciences (2076-3417)
- Publication Type :
- Academic Journal
- Accession number :
- 159005825
- Full Text :
- https://doi.org/10.3390/app12178781