Solving the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP): A model to explore the impacts of self-driving vehicles on urban mobility

Solving the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP): A model to explore the impacts of self-driving vehicles on urban mobility

"In this paper we propose a new method to study how replacing privately owned conventional vehicles with automated ones affects traffic delays and parking demand in a city. The model solves what we designate as the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP), which dynamically assigns family trips in their automated vehicles in an urban road network from a user equilibrium perspective where, in equilibrium, households with similar trips should have similar transport costs.

Key findings

Because fully-automated vehicles are free to move without a human occupant they are able to relocate and park themselves to satisfy as many household trips as is cost efficient for that family.

The number of trips satisfied by the cars in each iteration does not converge to a stable value; it has an oscillatory behavior which can be explained by the integer nature of the routing problem.

Having free special parking lots on the outskirts of the city is not as attractive as having them in the center because of the extra kilometers, but if the value of travel time is lower we found that the same number of trips satisfied today with conventional vehicles can be served with AVs, but in this case with the added advantage of completely freeing the city center from parked cars.

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