State Machine and Downhill Simplex Approach for Vision-Based Nighttime Vehicle Detection

Choi, Kyoung-Ho; Kim, Dohyun; Kim, Kwang-Sup; Kwon, Jang-Woo; S, Lee; Chen, Ken; Park, Jong‐Hyun

doi:10.4218/etrij.14.0113.0509

Cited by 9 publications

(2 citation statements)

References 27 publications

(29 reference statements)

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“…In most cases, a driver's visual and cognitive driving-workload can be improved through clever human factor engineering combined with an HUD and obstacle detection technologies [9]. In particular, to deal with obstacles, new approaches for vehicle tracking and nighttime vehicle detection were proposed to improve the stability and robustness [10], [11]. In addition, a two-step pedestrian detection was used to reduce the computation time of the algorithm, and an iterative particle repropagation method was proposed to enhance its tracking accuracy [12].…”

Section: Effects Of a Head-up Display On Driver Behaviorsmentioning

confidence: 99%

The Effects of Augmented-Reality Head-Up Display System Usage on Drivers? Risk Perception and Psychological Change

Hwang¹,

Park²,

Kim³

2016

ETRI J

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This study was conducted to examine the usage effects of an augmented reality head‐up display (AR‐HUD) system on the risk perception and psychological changes of drivers. To do so, we conducted an experiment to collect the driver response times for vehicles and pedestrians as their risk perception behavior, and used a driving behavior determinants questionnaire consisting of Problem Evading, Benefits/Sensation Seeking, Anti‐Personal Anxiety, Anti‐Personal Angry, and Aggression factors for collecting the psychological characteristics of the drivers. Thirty drivers were randomly assigned into an in‐vehicle AR‐HUD using group and a control group. As a result, the Anti‐Personal Anxiety and Anti‐Personal Angry factors were negatively correlated with the response time for the control group. In contrast, these results were not shown for the in‐vehicle AR‐HUD system using group. These results indicate that the in‐vehicle AR‐HUD system may partially induce a relaxation of tension or stress for drivers with a high level of interpersonal anxiety. Therefore, the in‐vehicle AR‐HUD system might contribute to not only the visual safety driving behaviors of drivers, but also to their psychological driving safety with specific characteristics.

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Section: Effects Of a Head-up Display On Driver Behaviorsmentioning

confidence: 99%

The Effects of Augmented-Reality Head-Up Display System Usage on Drivers? Risk Perception and Psychological Change

Hwang¹,

Park²,

Kim³

2016

ETRI J

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“…In order to solve this problem, several preceding studies have been attempted to automate the traffic volume survey [2][3][4][5][6]. There have been many attempts to measure vehicle traffic using sensors [7] or image processing methods [4,[8][9][10]. However, there is a risk of damage or loss when using the sensors installed for a long time, and it is difficult to distinguish between vehicle types when using the image processing method.…”

Section: Introductionmentioning

confidence: 99%

Method for Obtaining Better Traffic Survey Data

et al. 2021

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Road traffic surveys determine the number and type of vehicles passing by a specific point over a certain period of time. The manual estimation of the number and type of vehicles from images captured by a camera is the most commonly used method. However, this method has the disadvantage of requiring high amounts of manpower and cost. Recently, methods of automating traffic volume surveys using sensors or deep learning have been widely attempted, but there is the disadvantage that a person must finally manually verify the data in order to ensure that they are reliable. In order to address these shortcomings, we propose a method for efficiently conducting road traffic volume surveys and obtaining highly reliable data. The proposed method detects vehicles on the road from CCTV (Closed-circuit television) images and classifies vehicle types using deep learning or a similar method. After that, it automatically informs the user of candidates with a high probability of error and provides a method for efficient verification. The performance of the proposed method was tested using a data set collected by an actual road traffic survey company. As a result, we proved that our method shows better accuracy than the previous method. The proposed method can reduce the labor and cost in road traffic volume surveys, and increase the reliability of the data due to more accurate results.

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Performance of vehicle speed estimation using wireless sensor networks: a region-based approach

Kim

Choi

et al. 2014

J Supercomput

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State Machine and Downhill Simplex Approach for Vision-Based Nighttime Vehicle Detection

Cited by 9 publications

References 27 publications

The Effects of Augmented-Reality Head-Up Display System Usage on Drivers? Risk Perception and Psychological Change

The Effects of Augmented-Reality Head-Up Display System Usage on Drivers? Risk Perception and Psychological Change

Method for Obtaining Better Traffic Survey Data

Performance of vehicle speed estimation using wireless sensor networks: a region-based approach

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