Velocity and shape from tightly-coupled LiDAR and camera

Daraei, Mohammad Hossein; Vu, Alexander; Manduchi, Roberto

doi:10.1109/ivs.2017.7995699

Cited by 20 publications

(7 citation statements)

References 35 publications

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“…You et al [43] combined the vehicle sensor information to carry out research on environmental information collection and analysis, trajectory generation, collision detection and conflict processing during the lane change processes. Daraei et al [44] proposed that laser scanners can help to reduce the reliability and accuracy of computer vision detection and positioning. Data fusion based on laser scanner and computer vision can improve the accuracy of obstacle detection and positioning.…”

Section: Research On Traffic Conflict Based On Multi-sensor Fusionmentioning

confidence: 99%

A Review of Research on Traffic Conflicts Based on Intelligent Vehicles

Huang

et al. 2020

IEEE Access

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The traffic situation at an urban intersection is complicated, due to the numerous internal conflicts and all kinds of traffic accidents. With the objective of improving road safety, the automotive industry is moving toward intelligent vehicles. The major challenges are accurately perceiving the road traffic environment, detecting the potential traffic conflicts, and proposing the alternative driving strategies. This paper summarizes the existing researches on traffic conflicts from the perspective of intelligent vehicles. The intelligent vehicles can perceive the surrounding environment, extract road condition information, and detect obstacles for avoiding collisions or mitigating accidents. It expounds that the perception technology of intelligent vehicles can be divided into three main categories, namely, the perception technology, the communication technology, and the fusion of perception-communication technology. At the same time, the existing technical problems are analyzed. Finally, future development trends in this field are discussed. INDEX TERMS Intelligent vehicles, traffic conflicts, V2X communications, environment perception. I. INTRODUCTION

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Section: Research On Traffic Conflict Based On Multi-sensor Fusionmentioning

confidence: 99%

A Review of Research on Traffic Conflicts Based on Intelligent Vehicles

Huang

et al. 2020

IEEE Access

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“…The perception of intelligent vehicles faces a few main challenges, such as perception in poor weather and lighting conditions, or in complex urban environments, and limited perception ranges. Techniques such as sensor fusion can be used to compensate for shortcomings of individual sensors, by exploiting sensing data from different sensors [55], [56], [57]. However, this will significantly increase the onboard computation.…”

Section: Slammentioning

confidence: 99%

Mobile Edge Intelligence and Computing for the Internet of Vehicles

2020

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The Internet of Vehicles (IoV) is an emerging paradigm, driven by recent advancements in vehicular communications and networking. Advances in research can now provide reliable communication links between vehicles, via vehicle-to-vehicle communications, and between vehicles and roadside infrastructures, via vehicle-to-infrastructure communications. Meanwhile, the capability and intelligence of vehicles are being rapidly enhanced, and this will have the potential of supporting a plethora of new exciting applications, which will integrate fully autonomous vehicles, the Internet of Things (IoT), and the environment. These trends will bring about an era of intelligent IoV, which will heavily depend upon communications, computing, and data analytics technologies. To store and process the massive amount of data generated by intelligent IoV, onboard processing and Cloud computing will not be sufficient, due to resource/power constraints and communication overhead/latency, respectively. By deploying storage and computing resources at the wireless network edge, e.g., radio access points, the edge information system (EIS), including edge caching, edge computing, and edge AI, will play a key role in the future intelligent IoV. Such system will provide not only low-latency content delivery and computation services, but also localized data acquisition, aggregation and processing. This article surveys the latest development in EIS for intelligent IoV. Key design issues, methodologies and hardware platforms are introduced. In particular, typical use cases for intelligent vehicles are illustrated, including edge-assisted perception, mapping, and localization. In addition, various open research problems are identified.

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“…Özelikle siber saldırılar ve Vandalizm gibi önemli problemler henüz çözüme tam olarak ulaştırılabilmiş değildir. Bu bağlamda, tam otonom (seviye 5) araçların trafiğe çıkması ve kabul görmesi uzun yıllar alabilir [22]. Bu çerçevede otonom araçların (OA) trafiğe tam olarak penetre etmesi sürecinde belki 50 yıllık bir karma trafik ara döneminden söz etmek mümkün görünmektedir.…”

Section: Sonuçunclassified

Otonom Araçların Teknolojik Gelişim Süreci ve Trafik Seyir Özelliklerinin İncelenmesi

Karaşahin

Kızıltaş

2021

Düzce Üniversitesi Bilim Ve Teknoloji Dergisi

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Otonom araçlar gelecek ulaştırması ve kentinin en önemli unsurlarından bir tanesini teşkil etmektedir. İçinde bulunduğumuz yüzyılda kentleşme, sürdürülebilirlik ve dijitalleşme en temel unsurlar olacaktır. Bunun merkezinde ise otonom araçlar etkin ve belirleyici bir konuma sahiptir. Otonom araçların trafikte ağırlığı arttıkça ulaştırma ve kentleşme de yeniden şekillenecektir. Bu çalışma kapsamında, öncelikle otonom araç özelliklerinin kent ve ulaşımla ilişkisi ortaya konulmuştur. Ardından ise otonom araçların gelişim süreci detaylı olarak ele alınmıştır. Akabinde otonom araçlarda güvenlik ve emniyet konusu değerlendirilmiş bu olup sonrasında otonom araç teknolojileri çok yönlü olarak paylaşılmıştır. Son olarak da bu kapsamda sonuçlar verilmiştir.

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Velocity and shape from tightly-coupled LiDAR and camera

Cited by 20 publications

References 35 publications

A Review of Research on Traffic Conflicts Based on Intelligent Vehicles

A Review of Research on Traffic Conflicts Based on Intelligent Vehicles

Mobile Edge Intelligence and Computing for the Internet of Vehicles

Otonom Araçların Teknolojik Gelişim Süreci ve Trafik Seyir Özelliklerinin İncelenmesi

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