Kalman filter (KF) is a widely used estimation algorithm for many applications. However, in
many cases, it is not easy to estimate the exact state of the system due to many reasons …

Research on autonomous vehicles has made significant advances in recent years. To
operate an autonomous vehicle safely and effectively, precise localization is essential. This …

This paper proposes a method for mobile robot localization in a partially unknown indoor
environment. The method fuses two types of range measurements: the range from the robot …

Vehicle state estimation and path prediction, which usually involve Kalman filter and motion
model, are critical tasks for intelligent driving. In vehicle state estimation, the comparative …

This paper aims to analyze two major quantities related to the performances of IEEE 802.11
p-based vehicle ad hoc networks (VANETs): the mean number of simultaneous transmitters …

This paper proposes a generalized method for tracking of multiple objects from moving,
cooperative vehicles-bringing together an Unscented Kalman Filter for vehicle localization …

The precise localization system of autonomous vehicles is one of the important techniques
in the research of autonomous driving. In the case of outdoor localization, the Global …

Reducing the energy consumption of vehicles is one of the greatest challenges we are
facing in the mobility sector. A major step in this direction has been taken with the …

The unscented Kalman filter (UKF) has four implementations in the additive noise case,
according to whether the state is augmented with noise vectors and whether a new set of …

Vehicular Ad~ Hoc Networks (VANETs) allow vehicles to communicate with each other
using wireless means and thus connect them in a very dynamic wireless network. The …