Smartphone-based Pedestrian Localization Algorithm using Phone Camera and Location Coded Targets

Yang-lin, Zhou; Li, Guangyun; Wang, Li; Li, Shuaixin; Zong, Wenpeng

doi:10.1109/upinlbs.2018.8559868

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…Pedestrian-vehicle interaction is a topic that has been under study for the past years in the context of intelligent vehicle environments. As a result, many surveys have been published on pedestrian detection within vehicle environments, using different sensors, cameras, and artificial intelligence algorithms [12][13][14][15][16].…”

Section: State Of the Artmentioning

confidence: 99%

Assistive Self-Driving Car Networks to Provide Safe Road Ecosystems for Disabled Road Users

Guerrero-Ibañez,

Contreras-Castillo,

Amezcua-Valdovinos

et al. 2023

Machines

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Disabled pedestrians are among the most vulnerable groups in road traffic. Using technology to assist this vulnerable group could be instrumental in reducing the mobility challenges they face daily. On the one hand, the automotive industry is focusing its efforts on car automation. On the other hand, in recent years, assistive technology has been promoted as a tool for consolidating the functional independence of people with disabilities. However, the success of these technologies depends on how well they help self-driving cars interact with disabled pedestrians. This paper proposes an architecture to facilitate interaction between disabled pedestrians and self-driving cars based on deep learning and 802.11p wireless technology. Through the application of assistive technology, we can locate the pedestrian with a disability within the road traffic ecosystem, and we define a set of functionalities for the identification of hand gestures of people with disabilities. These functions enable pedestrians with disabilities to express their intentions, improving their confidence and safety level in tasks within the road ecosystem, such as crossing the street.

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