Decision-making for automated vehicles at intersections adapting human-like behavior
P De Beaucorps, T Streubel… - 2017 IEEE Intelligent …, 2017 - ieeexplore.ieee.org
Learning from human driver's strategies for solving complex and potentially dangerous
situations including interaction with other road users has the potential to improve decision …
situations including interaction with other road users has the potential to improve decision …
Classification of drivers manoeuvre for road intersection crossing with synthethic and real data
When approaching a road intersection, drivers consider several factors and choose amongst
different likely manoeuvres. For an autonomous agent, it is fundamental to understand what …
different likely manoeuvres. For an autonomous agent, it is fundamental to understand what …
Incentive mechanism for vehicular crowdsensing with budget constrains
In this paper, we present an incentive mechanism for vehicular crowdsensing (VCS) based
on a recurrent reverse auction. The proposed approach encourages participant's vehicles to …
on a recurrent reverse auction. The proposed approach encourages participant's vehicles to …
An Association-Rules Learning Approach to Unsupervised Classification of Street Networks
Street networks (SN) are intricate connections of roads and intersections; there is an
enormous amount of available, open source street network (SN) data, such as the worldwide …
enormous amount of available, open source street network (SN) data, such as the worldwide …