scholarly journals Voice Controlled Wiper for Smart Helmets

2019 ◽  
Vol 8 (12) ◽  
pp. 2086-2089
Keyword(s):  
Autonomous Vehicles ◽  
Intelligent Transportation System ◽  
Low Cost ◽  
Road Accidents ◽  
Major Focus ◽  
Safe Driving ◽  
Integrated Devices ◽  
Great Ease ◽  
Unmanned Autonomous Vehicles ◽  
The Voice

Intelligent transportation system is one of the major focus in today’s era. Several sensor integrated devices and unmanned autonomous vehicles, not only enhance the comfort of drivers but also help in safe driving. Specifically, for motorcyclists, helmets embedded with sensors are lifesaving gadgets. Researchers have focused on developing low power low cost smart helmets to prevent road accidents. However, the existing smart helmets are not season friendly. This paper proposes an extension for smart helmets that can assist riders to ride the motorcycle with great ease during heavy rains. The hardware unit consists of wiper integrated to helmet which turns ON and OFF based on the voice commands issued by the motorcyclists.

Female Voice Agents in Fully Autonomous Vehicles Are Not Only More Likeable and Comfortable, But Also More Competent

2020 ◽  
Vol 64 (1) ◽  
pp. 1033-1037
Author(s):  
Jiayuan Dong ◽  
Emily Lawson ◽  
Jack Olsen ◽  
Myounghoon Jeon
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Driving ◽  
Preference Ranking ◽  
Uncanny Valley ◽  
Tracking Data ◽  
Effective Solution ◽  
User Perception ◽  
Future Studies ◽  
Underlying Mechanisms ◽  
The Voice

Driving agents can provide an effective solution to improve drivers’ trust in and to manage interactions with autonomous vehicles. Research has focused on voice-agents, while few have explored robot-agents or the comparison between the two. The present study tested two variables - voice gender and agent embodiment, using conversational scripts. Twenty participants experienced autonomous driving using the simulator for four agent conditions and filled out subjective questionnaires for their perception of each agent. Results showed that the participants perceived the voice only female agent as more likeable, more comfortable, and more competent than other conditions. Their final preference ranking also favored this agent over the others. Interestingly, eye-tracking data showed that embodied agents did not add more visual distractions than the voice only agents. The results are discussed with the traditional gender stereotype, uncanny valley, and participants’ gender. This study can contribute to the design of in-vehicle agents in the autonomous vehicles and future studies are planned to further identify the underlying mechanisms of user perception on different agents.

scholarly journals Event-triggering $${H}_{\infty }$$-based observer combined with NN for simultaneous estimation of vehicle sideslip and roll angles with network-induced delays

2021 ◽  
Vol 103 (3) ◽  
pp. 2733-2752
Author(s):  
Maria Jesus L. Boada ◽  
Beatriz L. Boada ◽  
Hui Zhang
Keyword(s):  
Autonomous Vehicles ◽  
Networked Control System ◽  
Observer Design ◽  
Simultaneous Estimation ◽  
Road Accidents ◽  
Sideslip Angle ◽  
Current Series ◽  
Event Triggering ◽  
Communication Scheme ◽  
Proper Design

AbstractNowadays, vehicles are being fitted with systems that improve their maneuverability, stability, and comfort in order to reduce the number of accidents. Improving these aspects is of particular interest thanks to the incorporation of autonomous vehicles onto the roads. The knowledge of vehicle sideslip and roll angles, which are among the main causes of road accidents, is necessary for a proper design of a lateral stability and roll-over controller system. The problem is that these two variables cannot be measured directly through sensors installed in current series production vehicles due to their high costs. For this reason, their estimation is fundamental. In addition, there is a time delay in the relaying of information between the different vehicle systems, such as, sensors, actuators and controllers, among others. This paper presents the design of an $${H}_{\infty }$$ H ∞ -based observer that simultaneously estimates both the sideslip angle and the roll angle of a vehicle for a networked control system, with networked transmission delay based on an event-triggered communication scheme combined with neural networks (NN). To deal with the vehicle nonlinearities, NN and linear-parameter-varying techniques are considered alongside uncertainties in parameters. Both simulation and experimental results are carried out to prove the performance of observer design.

scholarly journals An Intelligent Task Scheduling Mechanism for Autonomous Vehicles via Deep Learning

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1788
Author(s):  
Gomatheeshwari Balasekaran ◽  
Selvakumar Jayakumar ◽  
Rocío Pérez de Prado
Keyword(s):  
Execution Time ◽  
Autonomous Vehicles ◽  
Rapid Development ◽  
Single Layer ◽  
Battery Life ◽  
Learning Approaches ◽  
Task Management ◽  
Inference System ◽  
Safe Driving ◽  
Self Driving Cars

With the rapid development of the Internet of Things (IoT) and artificial intelligence, autonomous vehicles have received much attention in recent years. Safe driving is one of the essential concerns of self-driving cars. The main problem in providing better safe driving requires an efficient inference system for real-time task management and autonomous control. Due to limited battery life and computing power, reducing execution time and resource consumption can be a daunting process. This paper addressed these challenges and developed an intelligent task management system for IoT-based autonomous vehicles. For each task processing, a supervised resource predictor is invoked for optimal hardware cluster selection. Tasks are executed based on the earliest hyper period first (EHF) scheduler to achieve optimal task error rate and schedule length performance. The single-layer feedforward neural network (SLFN) and lightweight learning approaches are designed to distribute each task to the appropriate processor based on their emergency and CPU utilization. We developed this intelligent task management module in python and experimentally tested it on multicore SoCs (Odroid Xu4 and NVIDIA Jetson embedded platforms).Connected Autonomous Vehicles (CAV) and Internet of Medical Things (IoMT) benchmarks are used for training and testing purposes. The proposed modules are validated by observing the task miss rate, resource utilization, and energy consumption metrics compared with state-of-art heuristics. SLFN-EHF task scheduler achieved better results in an average of 98% accuracy, and in an average of 20–27% reduced in execution time and 32–45% in task miss rate metric than conventional methods.

scholarly journals Collision Avoidance on Unmanned Aerial Vehicles Using Neural Network Pipelines and Flow Clustering Techniques

2021 ◽  
Vol 13 (13) ◽  
pp. 2643
Author(s):  
Dário Pedro ◽  
João P. Matos-Carvalho ◽  
José M. Fonseca ◽  
André Mora
Keyword(s):  
Collision Avoidance ◽  
Autonomous Vehicles ◽  
High Demand ◽  
Novel Approach ◽  
Vision Sensors ◽  
Learning Techniques ◽  
Stationary Objects ◽  
Computationally Intensive ◽  
Unmanned Autonomous Vehicles ◽  
Positive Results

Unmanned Autonomous Vehicles (UAV), while not a recent invention, have recently acquired a prominent position in many industries, and they are increasingly used not only by avid customers, but also in high-demand technical use-cases, and will have a significant societal effect in the coming years. However, the use of UAVs is fraught with significant safety threats, such as collisions with dynamic obstacles (other UAVs, birds, or randomly thrown objects). This research focuses on a safety problem that is often overlooked due to a lack of technology and solutions to address it: collisions with non-stationary objects. A novel approach is described that employs deep learning techniques to solve the computationally intensive problem of real-time collision avoidance with dynamic objects using off-the-shelf commercial vision sensors. The suggested approach’s viability was corroborated by multiple experiments, firstly in simulation, and afterward in a concrete real-world case, that consists of dodging a thrown ball. A novel video dataset was created and made available for this purpose, and transfer learning was also tested, with positive results.

CASA: An Alternative Smartphone-Based ADAS

2021 ◽  
pp. 1-41
Author(s):  
Manolo Dulva Hina ◽  
Hongyu Guan ◽  
Assia Soukane ◽  
Amar Ramdane-Cherif
Keyword(s):  
Low Cost ◽  
Electronic System ◽  
Time Data ◽  
Case Scenario ◽  
Safe Driving ◽  
The Road ◽  
Driving Assistance ◽  
Alternative Means ◽  
On The Road ◽  
Driving Assistance System

Advanced driving assistance system (ADAS) is an electronic system that helps the driver navigate roads safely. A typical ADAS, however, is suited to specific brands of vehicle and, due to proprietary restrictions, has non-extendable features. Project CASA is an alternative, low-cost generic ADAS. It is an app deployable on smartphone or tablet. The real-time data needed by the app to make sense of its environment are stored in the vehicle or on the cloud, and are accessible as web services. They are used to determine the current driving context, and, if needed, decide actions to prevent an accident or keep road navigation safe. Project CASA is an undertaking of a consortium of industrial and academic partners. A use case scenario is tested in the laboratory (virtual) and on the road (actual) to validate the appropriateness of CASA. It is a contribution to safe driving. CASA’s contribution also lies in its approach in the semantic modeling of the context of the environment, the vehicle and the driver, and on the modeling of rules for fusion of data and fission process yielding an action to be implemented. In addition, CASA proposes a secured means of transmitting data using light, via light fidelity (LiFi), itself an alternative means of wireless vehicle–smartphone communication.

The Design, Building and Testing of a Trans-Atlantic Autonomous Sailboat

2015 ◽  
Author(s):  
Satchel B. Douglas ◽  
Nolan R. Conway ◽  
Matthew B. Weklar
Keyword(s):  
Open Source ◽  
Autonomous Vehicles ◽  
Low Cost ◽  
Design Decisions ◽  
Hull Form ◽  
Construction Methods ◽  
Autonomous Surface Vehicles ◽  
Marine Industry ◽  
Long Duration ◽  
Rotating Wing

The use of autonomous vehicles is growing in all industries. However, there are no open-source autonomous surface vehicles available in the marine industry. This paper details the design decisions made, construction methods used, and testing performed on a low-cost, open-source vessel. The vessel was designed to cross the Atlantic Ocean as a means of proving its ability to survive the harsh marine environment. A trimaran hull form and free rotating wing sail were used because the combination provided good righting characteristics, durability and low power consumption. The vessel has been shown to navigate autonomously. Total costs were less than $4000 dollars, excluding labor. Vessels of this type could be used for long duration missions recording data in the open ocean at extremely low cost.

scholarly journals Feedforward ins aiding: an investigation of maneuvers for in-flight alignment

2007 ◽  
Vol 18 (4) ◽  
pp. 459-470 ◽  
Author(s):  
Jacques Waldmann
Keyword(s):  
Autonomous Vehicles ◽  
Inertial Sensors ◽  
Low Cost ◽  
Measurement Unit ◽  
Model Mismatch ◽  
External Data ◽  
Rate Gyro ◽  
External Position ◽  
The Impact ◽  
Gyro Drift

Navigation in autonomous vehicles involves integrating measurements from on-board inertial sensors and external data collected by various sensors. In this paper, the computer-frame velocity error model is augmented with a random constant model of accelerometer bias and rate-gyro drift for use in a Kalman filter-based fusion of a low-cost rotating inertial navigation system (INS) with external position and velocity measurements. The impact of model mismatch and maneuvers on the estimation of misalignment and inertial measurement unit (IMU) error is investigated. Previously, the literature focused on analyzing the stripped observability matrix that results from applying piece-wise constant acceleration segments to a stabilized, gimbaled INS to determine the accuracy of misalignment, accelerometer bias, and rate-gyro drift estimation. However, its validation via covariance analysis neglected model mismatch. Here, a vertically undamped, three channel INS with a rotating IMU with respect to the host vehicle is simulated. Such IMU rotation does not require the accurate mechanism of a gimbaled INS (GINS) and obviates the need to maneuver away from the desired trajectory during in-flight alignment (IFA) with a strapdown IMU. In comparison with a stationary GINS at a known location, IMU rotation enhances estimation of accelerometer bias, and partially improves estimation of rate-gyro drift and misalignment. Finally, combining IMU rotation with distinct acceleration segments yields full observability, thus significantly enhancing estimation of rate-gyro drift and misalignment.

scholarly journals Miniaturized Broadband-Multiband Planar Monopole Antenna in Autonomous Vehicles Communication System Device

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2715
Author(s):  
Ming-An Chung ◽  
Chih-Wei Yang
Keyword(s):  
Communication System ◽  
Autonomous Vehicles ◽  
Low Cost ◽  
Antenna Design ◽  
Dual Band ◽  
Impedance Change ◽  
Antenna Structure ◽  
Low Profile ◽  
Performance Results ◽  
Wireless Standards

The article mainly presents that a simple antenna structure with only two branches can provide the characteristics of dual-band and wide bandwidths. The recommended antenna design is composed of a clockwise spiral shape, and the design has a gradual impedance change. Thus, this antenna is ideal for applications also recommended in these wireless standards, including 5G, B5G, 4G, V2X, ISM band of WLAN, Bluetooth, WiFI 6 band, WiMAX, and Sirius/XM Radio for in-vehicle infotainment systems. The proposed antenna with a dimension of 10 × 5 mm is simple and easy to make and has a lot of copy production. The operating frequency is covered with a dual-band from 2000 to 2742 MHz and from 4062 to beyond 8000 MHz and, it is also demonstrated that the measured performance results of return loss, radiation, and gain are in good agreement with simulations. The radiation efficiency can reach 91% and 93% at the lower and higher bands. Moreover, the antenna gain can achieve 2.7 and 6.75 dBi at the lower and higher bands, respectively. This antenna design has a low profile, low cost, and small size features that may be implemented in autonomous vehicles and mobile IoT communication system devices.

scholarly journals A Hands-Free Obstacle Detection and Avoidance System

2015 ◽  
Vol 5 (3) ◽  
pp. 801-804
Author(s):  
M. Abdul-Niby ◽  
M. Alameen ◽  
O. Irscheid ◽  
M. Baidoun ◽  
H. Mourtada
Keyword(s):  
Obstacle Avoidance ◽  
Visually Impaired ◽  
Low Cost ◽  
Cost Effective ◽  
Obstacle Detection ◽  
Text To Speech ◽  
Voice Signal ◽  
Visually Impaired People ◽  
Impaired People ◽  
The Voice

In this paper, we present a low cost hands-free detection and avoidance system designed to provide mobility assistance for visually impaired people. An ultrasonic sensor is attached to the jacket of the user and detects the obstacles in front. The information obtained is transferred to the user through audio messages and also by a vibration. The range of the detection is user-defined. A text-to-speech module is employed for the voice signal. The proposed obstacle avoidance device is cost effective, easy to use and easily upgraded.

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