Understanding drivers' route choice behaviours in the urban network with machine learning models
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DOI: 10.1049/iet-its.2018.5190
Abstract: Drivers' route choice model is essential in transportation software such as navigation, fleet management, and simulation, where the random utility models (RUM) have dominated for years. The authors investigate here whether machine learning (ML) models… read more here.
Keywords: machine learning; network; learning models; drivers route ... See more keywords
En-Route Battery Management and a Mixed Network Equilibrium Problem Based on Electric Vehicle Drivers’ En-Route Recharging Behaviors
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DOI: 10.3390/en13164061
Abstract: With the rapidly increasing number of electric vehicle users, in many urbans transport networks, there are mixed traffic flows (i.e., electric vehicles and gasoline vehicles). However, limited by driving ranges and long battery recharging, the… read more here.
Keywords: vehicle; drivers route; equilibrium; electric vehicle ... See more keywords