Novel Sensors for Future Transportation Means
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: closed (20 September 2023) | Viewed by 717
Special Issue Editors
Interests: functional safety; edge computing; human physiological parameters analysis
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent systems; robotics; control systems; sensors and multi-sensor fusion; wireless sensor networks; intelligent communications; intelligent transportation; machine learning; computational neuroscience
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Sensors are widely adopted on vehicles of every kind.
The significance of these elements has increased considerably in the last few years, and this trend is set to continue.
For example, it is usual for the automotive industry to measure classical physical quantities such as position, speed and rpm, acceleration, pressure, force and torque, as well as insert, flowmeters, temperature, gas, and concentration sensors in vehicles. Other trends of the last decade are feature radars (long-range or near-range), imaging sensors to provide coverage of vehicle surroundings and passenger compartments, close-range ultrasound, and LiDARs.
The information obtained from these sensors can be used for varied purposes, including reductions in emissions (lambda probe) and improvements in drivability or comfort (semi- / active suspensions thanks to acceleration or displacement information) for the implementation of advanced driving assistance systems (imaging sensors for lane assist, radar for adaptive cruise control) or autonomous driving/flying.
Interest is now also focused on adopting this type of sensor to measure biomedical parameters (for example, considering Regulation (EU) 2019/2144, the driver or pilot's drowsiness), the health status of the vehicle body, especially when composite materials are adopted, or other safety reasons (for example, in collective transport, the correct wearing of face masks).
In all the transportation means, these newer measurement systems require cheap, precise, and accurate sensors and complex software to determine the readout and take opportune actions.
Various techniques are adopted to design (data fusion) and implement (machine learning) the approach. Moreover, due to the massive quantity of data collected by the imaging and radar sensors, it is possible to estimate the same physical quantity from different sources indirectly, thus improving the reliability (fault-tolerance), or, oppositely, it is possible to merge the information to create virtual sensors. Another possibility, opened by 5G, vehicle-to-vehicle, and vehicle-to-infrastructure communication capabilities, is to share information between different vehicles, improving the overall situational awareness increasing safety, providing diagnostic information on the vehicle itself, and reducing traveling time and energy consumption.
This possibility of communication with the external world benefits autonomous vehicles, such as robotaxis or uncrewed aerial vehicles, as well as the possibility to receive and visualize data remotely also by computer graphics or augmented reality.
This Special Issue aims to invite contributors to present their novel achievements in measurement and instruments for transportation means.
The topics of interest include, but are not limited to:
- Instrument fault detection and isolation (IFDI);
- Data fusion algorithms;
- Artificial intelligence for instrumentation and measurement;
- Sensors with auto-diagnosis capabilities;
- Reliable measurement systems;
- Fault-tolerant sensor networks;
- Distributed measurement systems;
- Vehicular structural health measurement system;
- Smart sensors;
- Wireless sensor networks;
- Data visualization.
Dr. Jacopo Sini
Prof. Dr. Simon X. Yang
Guest Editors
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