Multi-mode surround view for ADAS vehicles

Baftiu, Irfan; Pajaziti, Arbnor; Cheok, Ka C.

doi:10.1109/iris.2016.8066089

Cited by 14 publications

(3 citation statements)

References 2 publications

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“…Surround-view (SV) systems have played an important role in scene reconstruction [27]. Using several camera sensors, a 360degree feld depth of feld of the vehicle's surrounding can be extracted by combining those 2D images into a 360degree 3D view [28,29].…”

Section: Scene Interpretation and Reconstruction In Autonomousmentioning

confidence: 99%

Driving in the Rain: A Survey toward Visibility Estimation through Windshields

Morden,

Caraffini,

Kypraios

et al. 2023

International Journal of Intelligent Systems

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Rain can significantly impair the driver’s sight and affect his performance when driving in wet conditions. Evaluation of driver visibility in harsh weather, such as rain, has garnered considerable research since the advent of autonomous vehicles and the emergence of intelligent transportation systems. In recent years, advances in computer vision and machine learning led to a significant number of new approaches to address this challenge. However, the literature is fragmented and should be reorganised and analysed to progress in this field. There is still no comprehensive survey article that summarises driver visibility methodologies, including classic and recent data-driven/model-driven approaches on the windshield in rainy conditions, and compares their generalisation performance fairly. Most ADAS and AD systems are based on object detection. Thus, rain visibility plays a key role in the efficiency of ADAS/AD functions used in semi- or fully autonomous driving. This study fills this gap by reviewing current state-of-the-art solutions in rain visibility estimation used to reconstruct the driver’s view for object detection-based autonomous driving. These solutions are classified as rain visibility estimation systems that work on (1) the perception components of the ADAS/AD function, (2) the control and other hardware components of the ADAS/AD function, and (3) the visualisation and other software components of the ADAS/AD function. Limitations and unsolved challenges are also highlighted for further research.

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Section: Scene Interpretation and Reconstruction In Autonomousmentioning

confidence: 99%

Driving in the Rain: A Survey toward Visibility Estimation through Windshields

Morden,

Caraffini,

Kypraios

et al. 2023

International Journal of Intelligent Systems

View full text Add to dashboard Cite

show abstract

“…However, the angle of observation is limited due to narrow view of the camera lens [69]. Therefore, multiple cameras have been adopted in AVs to monitor the surrounding environment [70,71]. A three-stage RGBD architecture using deep learning and convolutional neural networks was proposed by Ferraz et al for vehicle and pedestrian detection [72].…”

Section: Camerasmentioning

confidence: 99%

A Survey of Autonomous Vehicles: Enabling Communication Technologies and Challenges

Ahangar

Ahmed

Khan

et al. 2021

Sensors

201

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The Department of Transport in the United Kingdom recorded 25,080 motor vehicle fatalities in 2019. This situation stresses the need for an intelligent transport system (ITS) that improves road safety and security by avoiding human errors with the use of autonomous vehicles (AVs). Therefore, this survey discusses the current development of two main components of an ITS: (1) gathering of AVs surrounding data using sensors; and (2) enabling vehicular communication technologies. First, the paper discusses various sensors and their role in AVs. Then, various communication technologies for AVs to facilitate vehicle to everything (V2X) communication are discussed. Based on the transmission range, these technologies are grouped into three main categories: long-range, medium-range and short-range. The short-range group presents the development of Bluetooth, ZigBee and ultra-wide band communication for AVs. The medium-range examines the properties of dedicated short-range communications (DSRC). Finally, the long-range group presents the cellular-vehicle to everything (C-V2X) and 5G-new radio (5G-NR). An important characteristic which differentiates each category and its suitable application is latency. This research presents a comprehensive study of AV technologies and identifies the main advantages, disadvantages, and challenges.

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“…target tracking tasks, including lane detection, pedestrian and vehicle identification, and local path planning [14]. To surmount the narrow measurable angle range of cameras, generally, AD adopts multiple cameras to form omnidirectional monitoring on the surrounding environment in the practical application [16], [17]. MMW-Radar can measure the acquisition of objects' distance through pulse compression and speed through the Doppler shift, which has extensive application for obstacle detection [18], pedestrian recognition, and vehicle recognition [19], [20].…”

Section: Introductionmentioning

confidence: 99%

Multi-Sensor Fusion in Automated Driving: A Survey

2020

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With the significant development of practicability in deep learning and the ultra-highspeed information transmission rate of 5G communication technology will overcome the barrier of data transmission on the Internet of Vehicles, automated driving is becoming a pivotal technology affecting the future industry. Sensors are the key to the perception of the outside world in the automated driving system and whose cooperation performance directly determines the safety of automated driving vehicles. In this survey, we mainly discuss the different strategies of multi-sensor fusion in automated driving in recent years. The performance of conventional sensors and the necessity of multi-sensor fusion are analyzed, including radar, LiDAR, camera, ultrasonic, GPS, IMU, and V2X. According to the differences in the latest studies, we divide the fusion strategies into four categories and point out some shortcomings. Sensor fusion is mainly applied for multi-target tracking and environment reconstruction. We discuss the method of establishing a motion model and data association in multi-target tracking. At the end of the paper, we analyzed the deficiencies in the current studies and put forward some suggestions for further improvement in the future. Through this investigation, we hope to analyze the current situation of multi-sensor fusion in the automated driving process and provide more efficient and reliable fusion strategies.

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Multi-mode surround view for ADAS vehicles

Cited by 14 publications

References 2 publications

Driving in the Rain: A Survey toward Visibility Estimation through Windshields

Driving in the Rain: A Survey toward Visibility Estimation through Windshields

A Survey of Autonomous Vehicles: Enabling Communication Technologies and Challenges

Multi-Sensor Fusion in Automated Driving: A Survey

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