Microphone Array for Speaker Localization and Identification in Shared Autonomous Vehicles

Marques, Ivo; Sousa, João Duarte; Sá, Bruno; Costa, Diogo; Sousa, Pedro; Pereira, Samuel; Santos, Afonso; Lima, C. S.; Hammerschmidt, Niklas; Pinto, Sandro; Gomes, Tiago

doi:10.3390/electronics11050766

Cited by 10 publications

(10 citation statements)

References 48 publications

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“…The actions can range from simple notifications to the driver, to direct control over the vehicle's systems like braking or speed limitation. The action layer essentially allows the vehicle to respond appropriately to its environment [10].…”

Section: Action Layermentioning

confidence: 99%

“…Both densely populated urban regions and rural areas with less infrastructure have high traffic volumes on the road network due to the diverse and rapidly growing population. The challenges are exacerbated by poor road conditions, irregular traffic patterns, and a range of road users, such as pedestrians, cyclists [10], and users of other forms of transportation. These several elements come together to provide a convoluted traffic environment that is prone to collisions, particularly on singlecarriageway and interurban lines [3].…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Confluence of Technology and Driving: An Examination of Advanced Driver Assistance Systems

Editor,

Maharajpet,

2024

IJER

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This paper architecture analysis highlights the key components of the ADAS design, including the sensors, perception layer, decision-making layer, and action layer. It explains the flow of data through the system and how sensor fusion contributes to the creation of a comprehensive image of the car's surroundings. It goes on to cover further ADAS features and their advantages, such as automated braking, adaptive cruise control, traffic sign recognition, and blind-spot detection. The hopeful future of ADAS technology is highlighted in the article's conclusion, along with how it might change driving habits, boost traffic safety, and enhance driving in general. It draws attention to the critical issues that require more study and development in order to solve them and open the door for ADAS to be widely used in a variety of traffic situations, particularly in India.

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Section: Action Layermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exploring the Confluence of Technology and Driving: An Examination of Advanced Driver Assistance Systems

Editor,

Maharajpet,

2024

IJER

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“…Marques et al [6] presented how with the current technological transformation in the automotive industry, autonomous vehicles are getting closer to the Society of Automotive Engineers (SAE) automation level 5. This level corresponds to the full vehicle automation, where the driving system autonomously monitors and navigates the environment.…”

Section: Short Presentation Of the Papersmentioning

confidence: 99%

Autonomous Vehicles Technological Trends

Iclodean

Varga

Pfister³

2023

Electronics

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“…Driving users of AVs communicate with VCSs to perform a variety of hand-free functions. Some functions include navigation (setting a destination, changing routes, and searching for points of interest); climate control (temperature change, fan speed, and airflow); media and entertainment (operating infotainment systems such as changing the volume, skipping tracks, or switching between radio stations; communication (phone calls or sending and receiving emails); vehicle settings (headlight and windshield wiper controls); vehicle status (vehicle's current speed, fuel level, door and window locks and other status information); and emergency assistance (calling for help or requesting roadside assistance have been successfully incorporated into AVs using VCSs) [11]. Several researchers have also implemented vehicle control functions using voice commands through a VCS.…”

Section: Introductionmentioning

confidence: 99%

“…Several researchers have also implemented vehicle control functions using voice commands through a VCS. Several researchers have also implemented vehicle control functions, including turn signals, gear selection, engine control lane changes, or taking an exit due to divergence using voice commands through VCSs [11]. The VCS plays a critical role in the safety of driving users in situations where the AV has lost control due to malfunctioning or faults in the hardware of the installed computer, sensors, and other associated modules.…”

Section: Introductionmentioning

confidence: 99%

Improving Autonomous Vehicle Controls and Quality Using Natural Language Processing-Based Input Recognition Model

Anjum

Shahab

2023

Sustainability

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In contemporary development, autonomous vehicles (AVs) have emerged as a potential solution for sustainable and smart transportation to fulfill the increasing mobility demands whilst alleviating the negative impacts on society, the economy, and the environment. AVs completely depend on a machine to perform driving tasks. Therefore, their quality and safety are critical concerns for driving users. AVs use advanced driver assistance systems (ADASs) that heavily rely on sensors and camera data. These data are processed to execute vehicle control functions for autonomous driving. Furthermore, AVs have a voice communication system (VCS) to interact with driving users to accomplish different hand-free functions. Some functions such as navigation, climate control, media and entertainment, communication, vehicle settings, vehicle status, and emergency assistance have been successfully incorporated into AVs using VCSs. Several researchers have also implemented vehicle control functions using voice commands through VCSs. If a situation occurs when AV has lost control due to malfunctioning or fault in the installed computer, sensors and other associated modules, driving users can control the AV using voice notes to perform some driving tasks such as changing speeds, lanes, breaking, and directing the car to reach a safe condition. Furthermore, driving users need manual control over AV to perform these tasks in some situations, like lane changing or taking an exit due to divergence. These tasks can also be performed with the help of voice commands using VCSs. Therefore, finding the exact voice note used to instruct different actuators in risk situations is crucial. As a result, VCSs can greatly improve safety in critical situations where manual intervention is necessary. AVs’ functions and quality can be significantly increased by integrating a VCS with an ADAS and developing an interactive ADAS. Now, the driver functions are controlled by voice features. Therefore, natural language processing is utilized to extract the features to determine the user’s requirements. The extracted features control the vehicle functions and support driving activities. The existing techniques consume high computation while predicting the user command and causing a reduction in the AVs’ functions. This research issue is overcome by applying the variation continuous input recognition model. The proposed approach utilizes the linear training process that resolves the listening and time-constrained problems and uncertain response issues. The proposed model categorizes the inputs into non-trainable and trainable data, according to the data readiness and listening span. Then, the non-distinguishable data were validated by dividing it into the linear inputs used to improve the response in the AVs. Thus, effectively utilizing training parameters and the data decomposition process minimizes the uncertainty and increases the response rate. The proposed model has significantly improved the exact prediction of users’ voice notes and computation efficiency. This improvement enhances the VCS quality and reliability used to perform hand-free and vehicle control functions. The reliability of these functions ultimately improves the safety of AVs’ driving users and other road users.

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Microphone Array for Speaker Localization and Identification in Shared Autonomous Vehicles

Cited by 10 publications

References 48 publications

Exploring the Confluence of Technology and Driving: An Examination of Advanced Driver Assistance Systems

Exploring the Confluence of Technology and Driving: An Examination of Advanced Driver Assistance Systems

Autonomous Vehicles Technological Trends

Improving Autonomous Vehicle Controls and Quality Using Natural Language Processing-Based Input Recognition Model

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