Detection of road traffic participants using cost-effective arrayed ultrasonic sensors in low-speed traffic situations
Artikel i vetenskaplig tidskrift, 2019

Effective detection of traffic participants is crucial for driver assistance systems. Traffic safety data reveal that the majority of preventable pedestrian fatalities occurred at night. The lack of light at night may cause dysfunction of sensors like cameras. This paper proposes an alternative approach to detect traffic participants using cost-effective arrayed ultrasonic sensors. Candidate features were extracted from the collected episodes of pedestrians, cyclists, and vehicles. A conditional likelihood maximization method based on mutual information was employed to select an optimized subset of features from the candidates. The belonging probability to each group along with time was determined based on the accumulated object type attributes outputted from a support vector machine classifier at each time step. Results showed an overall detection accuracy of 86%, with correct detection rate of pedestrians, cyclists and vehicles around 85.7%, 76.7% and 93.1%, respectively. The time needed for detection was about 0.8 s which could be further shortened when the distance between objects and sensors was shorter. The effectiveness of arrayed ultrasonic sensors on objects detection would provide all-around-the-clock assistance in low-speed situations for driving safety.

Driver assistance systems

Ultrasonic sensor

Driving safety

Object detection

Författare

Guofa Li

Shenzhen University

Shengbo Li

State Key Lab of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University

Ruobing Zou

State Key Lab of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University

Yuan Liao

Chalmers, Rymd-, geo- och miljövetenskap, Fysisk resursteori, Fysisk resursteori 2

Bo Cheng

State Key Lab of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University

Mechanical Systems and Signal Processing

0888-3270 (ISSN) 1096-1216 (eISSN)

Vol. 132 1 535-545

Styrkeområden

Transport

Ämneskategorier

Signalbehandling

DOI

10.1016/j.ymssp.2019.07.009

Mer information

Senast uppdaterat

2019-09-26