Colouring vehicle threat and minimising threat avoidance trajectory cost for adaptive vehicle collision defence system in active safe driving

Chang, Ben-Jye; Yu, Bo-Han; Liang, Ying-Hsin

doi:10.1049/iet-its.2016.0181

Cited by 8 publications

(5 citation statements)

References 29 publications

(32 reference statements)

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“…Computer vision, also known as machine vision, is a science and technology that uses computers to simulate biological appearance and macroscopic visual functions. e main purpose of computer vision analysis is to use plane images to create or reconstruct real-world models, that is, to study how to use two-dimensional images to reconstruct the three-dimensional visual world and then identify the world [10]. e theoretical methods used in computer vision are mainly computer vision theory based on geometry, probability, 3D motion, and reconstruction calculations.…”

Section: Computer Vision Technologymentioning

confidence: 99%

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Key Technologies of Vehicle Active Safety System Based on Computer Vision

Qian

Wang

2022

Journal of Advanced Transportation

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Due to the increase in the number of urban vehicles and the irregular driving behavior of drivers, urban accidents frequently occur, causing serious casualties and economic losses. Active vehicle safety systems can monitor vehicle status and driver status online in real time. Computer vision technology simulates biological vision and can analyze, identify, detect, and track the data and information in the captured images. In terms of driving accident warning and vehicle status warning, the vehicle active safety system has the potential to enhance the driver’s ability to detect abnormal situations, prolong the processing time, and reduce the risk of safety accidents. In this paper, an active safety system is developed according to the existing vehicle electronic system framework, and the early warning decision is made by evaluating the relationship between the minimum early warning distance and the actual vehicle distance, speed, and other factors. In this paper, the kinematics model established by the vehicle active safety early warning system is designed. The results found that, within 400 ms of the driver’s judgment time, for the driver with the reaction time of 0.6 s and 0.9 s, the following distance of 20 m does not constitute a safety threat and no braking operation is required.

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Section: Computer Vision Technologymentioning

confidence: 99%

“…e response value in a certain direction α is defined as the sum of the transformation results of different scales w in this direction. To obtain the two scales uniformly, the average value of the results of different scales is taken, as shown in formula (10).…”

Section: Feature Extraction Of Lane Line Directionmentioning

confidence: 99%

Key Technologies of Vehicle Active Safety System Based on Computer Vision

Qian

Wang

2022

Journal of Advanced Transportation

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“…Path planning is an important element for underwater search, underwater SLAM (simultaneous positioning and mapping) and underwater target hunting. Path planning is one of the key contents of underwater vehicle research [1–4]. Many achievements have been made in the study of AUV path planning.…”

Section: Introductionmentioning

confidence: 99%

Path planning for autonomous underwater vehicle in time‐varying current

Cao

Sun

Chen

2019

IET Intelligent Transport Systems

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“…However, owing to the blind spot, insufficient response time, algorithm failure and other factors, the vehicle might encounter some dangerous scenarios, one typical situation is the rear end collision. To avoid or mitigate these dangerous scenarios, vehicle active safety is proposed [15]. For rear‐end collision avoidance, braking and steering are two potential emergency manoeuvres.…”

Section: Introductionmentioning

confidence: 99%