Robust Function and Sensor Design Considering Sensor Measurement Errors Applied to Automatic Emergency Braking

Stockle, Christoph; Utschick, Wolfgang; Herrmann, Stephan; Dirndorfer, Tobias

doi:10.1109/ivs.2019.8814142

Cited by 8 publications

(1 citation statement)

References 7 publications

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“…The technological equipment of vehicles is continuously advancing to make the driving experience safer and more pleasant. Radar and front camera can track the car ahead for adaptive cruise control 1 and automatic emergency braking, 2 ultrasonic sensors can recognize the parking spot for automatic parking assist, 3 services exploiting positioning systems such as global positioning system (GPS) and Galileo give directions and suggest alternate routes during navigation, 4 and so forth. A driver directly enjoys the benefits of the data collected and processed by his or her vehicle, but more advantages, both for the driver and the whole community, can be obtained by sharing the collected information among the vehicles.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy control system for energy‐efficient wireless devices in the Internet of vehicles

et al. 2021

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Embedded systems are common in the Internet of Things domain: their integration in vehicles and mobile devices is being fostered in the Internet of vehicles (IoV). IoV has direct applications on intelligent transportation systems and smart cities. Besides basic requirements, such as ease of installation, cost-effectiveness, scalability, and flexibility, IOV applications need to guarantee energyefficient and good-quality communication. In fact, IoV implementations are commonly based on wireless nodes, which rely on a limited energy source; therefore, an efficient communication among the nodes is desirable to prolong the lifetime of the devices. In particular, the alternation of active and sleep states and the regulation of the transmission power represent two common approaches to save energy. Based on this strategy, an effective fuzzy control system is presented in the paper to manage power consumption and quality of services of IoV applications. Two fuzzy controllers increase the battery life while keeping a good throughput to workload ratio. This technique has been simulated with two leading technologies in IoV: IEEE 802.11b/g/n and IEEE 802.11p. Experimental results show a network lifetime improvement ranging from 30% to 40%, according to the adopted medium access control protocol.

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