Transportation Mode Selection Using Reinforcement Learning in Simulation of Urban Mobility

Transportation Mode Selection Using Reinforcement Learning in Simulation of Urban Mobility

Transportation mode selection is pivotal for navigating through cities plagued by heavy traffic congestion. This plays a crucial role in ensuring the efficient utilization of time and resources to achieve the desired objectives. Given the complex dynamics of urban mobility, strategically selecting a...

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Bibliographic Details
Main Authors:	Mehmet Bilge Han Taş, Kemal Özkan, İnci Sarıçiçek, Ahmet Yazici
Format:	Article
Language:	English
Published:	MDPI AG 2025-01-01
Series:	Applied Sciences
Subjects:	transportation mode selection reinforcement learning Gaussian distribution Poisson distribution simulation of urban mobility (SUMO)
Online Access:	https://www.mdpi.com/2076-3417/15/2/806
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