Human Detection Capacity of Vehicle Front Sonar Sensors in Light and Small Passenger Cars and Minivan.

Sonar sensor systems have been developed to prevent collisions between vehicles and surrounding objects by employing ultrasonic sensors mounted at the front of the vehicle. These systems warn drivers when nearby obstacles are detected. However, relatively few studies have examined the capacity of sonar to detect humans. This study aims to clarify the human detection capacity of front sonar sensors installed in two light passenger cars (LPC-I and LPC-II), one small passenger car (SPC), and one minivan (MNV). The LPC-I, SPC, and MNV were equipped with center and corner sensors, whereas the LPC-II had only corner sensors. Three volunteers-a child, an adult female, and an adult male-participated in the study. Human detectability was assessed using the "maximum detection distance ratio," defined as the ratio of the maximum detection distance for a volunteer to that for a standard pipe. The results showed that both the center and corner sensors consistently detected front- and side-facing human volunteers. For front-facing human volunteers, the maximum detection distance ratios relative to the pipe were 99-101% (child), 93-101% (adult female), and 98-101% (adult male) for the center sonar sensor, and 99-102%, 94-102%, and 96-100% for the corner sensor. For side-facing human volunteers, the corresponding ratios were 97-100%, 92-97%, and 94-99% for the center sensor, and 95-99%, 91-98%, and 93-98% for the corner sensor. These detection ratios were closely aligned with those of the pipe. These findings suggest that front sonar sensors can effectively detect humans prior to vehicle motion initiation, indicating their potential to reduce low-speed vehicle collisions with nearby pedestrians.

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Publication Details

Journal
PubMed
Published
2026-02-01
DOI
https://doi.org/10.4271/2025-22-0009
Primary Topic
Gait Recognition and Analysis
Type
article
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article

Human Detection Capacity of Vehicle Front Sonar Sensors in Light and Small Passenger Cars and Minivan.

Shoko Oikawa, Yasuhiro Matsui
PubMed
Gait Recognition and Analysis
article

Human Detection Capacity of Vehicle Front Sonar Sensors in Light and Small Passenger Cars and Minivan.

Shoko Oikawa, Yasuhiro Matsui
article en

Abstract

Sonar sensor systems have been developed to prevent collisions between vehicles and surrounding objects by employing ultrasonic sensors mounted at the front of the vehicle. These systems warn drivers when nearby obstacles are detected. However, relatively few studies have examined the capacity of sonar to detect humans. This study aims to clarify the human detection capacity of front sonar sensors installed in two light passenger cars (LPC-I and LPC-II), one small passenger car (SPC), and one minivan (MNV). The LPC-I, SPC, and MNV were equipped with center and corner sensors, whereas the LPC-II had only corner sensors. Three volunteers-a child, an adult female, and an adult male-participated in the study. Human detectability was assessed using the "maximum detection distance ratio," defined as the ratio of the maximum detection distance for a volunteer to that for a standard pipe. The results showed that both the center and corner sensors consistently detected front- and side-facing human volunteers. For front-facing human volunteers, the maximum detection distance ratios relative to the pipe were 99-101% (child), 93-101% (adult female), and 98-101% (adult male) for the center sonar sensor, and 99-102%, 94-102%, and 96-100% for the corner sensor. For side-facing human volunteers, the corresponding ratios were 97-100%, 92-97%, and 94-99% for the center sensor, and 95-99%, 91-98%, and 93-98% for the corner sensor. These detection ratios were closely aligned with those of the pipe. These findings suggest that front sonar sensors can effectively detect humans prior to vehicle motion initiation, indicating their potential to reduce low-speed vehicle collisions with nearby pedestrians.

PubMedVol. 69(2)
National Traffic Safety and Environment Laboratory (JP), Tokyo Metropolitan University (JP)
Life below water
Openalex Percentile: Top 69%
Gait Recognition and Analysis
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