Abstract
This paper presents an innovative evaluation and comparison of several methods and techniques necessary to implement an indoor localization system based on audible sound. Experiments were conducted in a room with conditions very close to possible practical application demonstrating that time delay estimation using generalized cross-correlation phase transform provides the best estimate to the distance to fixed anchors, and highlight the benefits of a new localization method entitled circle shrinking based on an optimization methodology. Of the three optimization methods tested, Gauss-Newton proves to be the most adequate, and among the three medium access methods evaluated, code division multiple access acoustic transmission provided the best results. A localization system combining these components and using only off-the-shelf hardware reached an average accuracy of 1.3 cm in the central area of the test room with an excitation signal-to-noise ratio as low as 7.2 dB, an almost unperceivable noise like audio signal. These results represent an advance of the state-of-the-art in indoor localization systems, pointing towards the possibility of widespread practical implementation with everyday use components.

Abstract
The current vehicle stability control techniques relies on an accurate sensor information and a complete system definition, such information is not easily obtained and requires expensive sensor technology. In this work it is presented a fusion algorithm for estimating the vehicle handling dynamic states, using inertial measurements combined with Global Positioning System (GPS) information, based on the Extended Kalman Filter algorithm (EKF). The proposed method will be able to track the state of the variable vector that includes the yaw rate, lateral velocity and longitudinal velocity of the vehicle using the information of the available sensors combined with the non-linear model of the system. In order to validate the proposed sensor fusion algorithm a simulation with a high-fidelity CarSim model is carried out and its sensors are compared with Extended Kalman Filter state variables.

Abstract
This paper addresses the tracking problem of the state variables of a nonlinear planar dynamic model of an overactuated electric vehicle with four-wheel independent drive (4WID) topology. In order to track the state variables of the system it is proposed a new sliding mode controller based on a nonlinear planar model. The controller explores the overactuated system in order to redistribute the control effort to the remaining actuators when a fault occurs. Although the system has multiple solutions due to the access of the torque applied in each wheel independently, there could be particular fault events where the remaining healthy actuators may not be able to maintain the system stability. In those particular cases the inclusion of the steering control variable is an important advantage as it allows the controller to manipulate the control effort in any directions. The proposed controller is validated in various driving scenarios with different fault schemes. The simulations are carried out with a high-fidelity vehicular model provided by the simulation software Carsim in co-simulation with Matlab/Simulink.

Abstract
This paper presents a method that allows mobile devices to be globally self-localised in indoor localisation systems by transmitting to them data from position reference anchors. The objective is to establish a reliable one-way down-link communication through signals used in the localisation process in a typically strong fading and multipath channel environment. This is accomplished by using signal processing techniques, including coding and forward error correction, to transmit data using a specific transmission control protocol. Experimental results, using audio as the signal between anchors and the mobile device, demonstrate successful data transmission in realistic scenarios like a common noisy and reverberant room. Spread spectrum noise-like masked signals 49 dB below background noise were sufficient to attain correct data reception at four metres distance between a loudspeaker anchor and a mobile device's microphone.

Abstract
Modern electric vehicles are most often designed with actuator redundancy and in-wheel propulsion, a combination that appears particularly suitable for the design of motion controllers that can optimally blend multiple objectives, such as dynamic, safety and driver-oriented. This paper considers such a technological setting and concentrates on the design of a path-following algorithm with minimum-time features, with the aim of combining performance and energy-oriented optimization of the vehicle motion. Specifically, an approximate minimum-time trajectory is obtained by appropriate convexification of the resulting optimization problem. The effectiveness of the approach is assessed by means of simulation tests carried out on the CarSim vehicle simulation environment.

Abstract
This study presents a scheme to detect and isolate faults in over-actuated electric vehicles. Although this research work is still emerging, it already provides a view of the main challenges on the problem and discusses some possible approaches that can be useful to overcome the key difficulties. This paper intends to present a fault detection algorithm based on Unknown Input Observer (UIO). The residuals are built through the difference of signals between the measured outputs and the output estimations from the observer. The main idea is to detect fault in the electric motors and steering wheel actuator. The algorithm is presented and tested with some fault scenarios using the co-simulation tool between Simulink/MATLAB and the high-fidelity model from Carsim software.