Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Jiqian Dong"'
Publikováno v:
Journal of Intelligent and Connected Vehicles, Vol 5, Iss 3, Pp 235-249 (2022)
Purpose – Perception has been identified as the main cause underlying most autonomous vehicle related accidents. As the key technology in perception, deep learning (DL) based computer vision models are generally considered to be black boxes due to
Externí odkaz:
https://doaj.org/article/cbd40296506c4ae2b3b12c20bc3603a2
Publikováno v:
Frontiers in Built Environment, Vol 6 (2020)
The evolution of scientific advances has often been characterized by the amalgamation of two or more technologies. With respect to vehicle connectivity and automation, recent literature suggests that these two emerging transportation technologies can
Externí odkaz:
https://doaj.org/article/c6a8adb88e45472b8163128762b14bd2
Publikováno v:
Computer-Aided Civil & Infrastructure Engineering; 3/15/2024, Vol. 39 Issue 6, p793-813, 21p
Publikováno v:
Computer-Aided Civil and Infrastructure Engineering. 36:838-857
A connected autonomous vehicle (CAV) network can be defined as a set of connected vehicles including CAVs that operate on a specific spatial scope that may be a road network, corridor, or ...
Large network multi-level control for CAV and Smart Infrastructure: AI-based Fog-Cloud collaboration
Publikováno v:
Center for Connected and Automated Transportation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d258bb90c8f3acb29824c2d3b7c02c26
https://docs.lib.purdue.edu/context/ccat/article/1000/viewcontent/Report__55___Large_network__compliant_report.pdf
https://docs.lib.purdue.edu/context/ccat/article/1000/viewcontent/Report__55___Large_network__compliant_report.pdf
Publikováno v:
Center for Connected and Automated Transportation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bcde35bbb38eba8cd94b1fc299386911
https://docs.lib.purdue.edu/context/ccat/article/1011/viewcontent/_41_AI_based_control__compliant_report.pdf
https://docs.lib.purdue.edu/context/ccat/article/1011/viewcontent/_41_AI_based_control__compliant_report.pdf
Autor:
Jiqian Dong, Sikai Chen, Yujie Li, Paul Young Joun Ha, Samuel Labi, Panagiotis Ch. Anastasopoulos, Runjia Du
Publikováno v:
ITSC
Autonomous vehicles (AVs) are expected to increase the safety of transportation systems because automation minimizes human error in driving tasks. It is likely that such benefits will be fully manifested only when AV market penetration reaches 100%.
Publikováno v:
ITSC
In the last decade, deep learning (DL) approaches have been used successfully in computer vision (CV) applications. However, DL-based CV models are generally considered to be black boxes due to their lack of interpretability. This black box behavior
Publikováno v:
ISC2
Dynamic rerouting framework can improve urban traffic management by mitigating urban traffic congestion. Emerging technologies such as fog-computing offers low-latency capabilities and facilitates the information exchange between the vehicles and inf
Dissertation/ Thesis
Autor:
Jiqian Dong (18505497)
Motion planning for Autonomous Vehicles (AVs) and Connected Autonomous Vehicles (CAVs) involves the crucial task of translating road environmental data obtained from sensors and connectivity devices into a sequence of executable vehicle actions. This