Vehicle control algorithms for cooperative driving with automated vehicles and intervehicle communications

By S. Kato, S. Tsugawa, K. Tokuda, T. Matsui, H. Fujii. IEEE transactions on intelligent transportation systems (Print), 2002

411 citations recorded by the source corpus.

Subfields: Automotive Engineering, Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/604b993e50d85d562f0c30c58357b492f972ad8f

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In Automotive Engineering

In Control and Systems Engineering

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Citations in the corpus

Enhancements of V2X communication in support of cooperative autonomous driving (2015, background): “More recently, several research activities [4], [5] and successful ﬁeld trials of V2X communication for safety and trafﬁc efﬁciency in the last years [6] have triggered manifold ongoing activities to bring V2X communication for autonomous driving closer to reality.”
Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review (2020, neutral): “Additionally, multiple studies consider connected Additionally, multiple studies consider adding connected vehicle technologies [9,10], such as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technologies, where essential information is shared to create an enhanced cooperative driving…”
Cooperative Driving at Blind Crossings Using Intervehicle Communication (2006, background): “Since then, the feasibility and benefits of cooperative driving have been further discussed and examined worldwide, i.e., in the California PATH project in the USA [4], [5], the Chauffeur project in the EU [6], and the Demo 2000 Cooperative Driving System in Japan [7].”
AMOEBA: Robust Location Privacy Scheme for VANET (2007, background): “The mobility of vehicles can be observed to have the following unique characteristics [24]: (1) The movement of vehicles is spatially restricted due to geographical constraints.”
A Survey of Deep Learning Applications to Autonomous Vehicle Control (2019, background): “Indeed, full-scale vehicle studies with multiple vehicles have typically been achieved through collaboration of government research projects with automotive manufacturers, such as Demo ’97 [192]–[194] or Demo 2000 [195].”
Control of Connected and Automated Vehicles: State of the Art and Future Challenges (2018, background): “Other demonstrations of cooperative driving took place in the Demo 2000 program in Japan in 2000 [21], in the Grand Cooperative Driving Challenge in 2011 and 2016 in the Netherlands [22, 23], the SARTRE program [24], and the Energy-ITS program started in 2008 in Japan [25].”
A Survey of the Connected Vehicle Landscape—Architectures, Enabling Technologies, Applications, and Development Areas (2017, background): “increase packing density, ease congestion, and improve traffic flow [130].”
Platooning With IVC-Enabled Autonomous Vehicles: Strategies to Mitigate Communication Delays, Improve Safety and Traffic Flow (2012, methodology): “Kato et al. [23] described the technologies of the cooperative driving with automated vehicles and IVCs in the Demo 2000 cooperative driving.”
A human-like game theory-based controller for automatic lane changing (2018, background): “In such a way, these vehicles can cooperate with each other to increase efficiency and safety (Kato et al., 2002).”
Platoon management with cooperative adaptive cruise control enabled by VANET (2015, neutral): “The CACC control logic which falls in the regulation and physical layer of each vehicle is also shown in Fig.”
Research Advances and Challenges of Autonomous and Connected Ground Vehicles (2019, methodology): “The PATH program [41], the Energy-ITS program [42], the Demo 2000 program [43], and the SARTRE program [46] tested platooning by using cooperative adaptive cruise control (CACC), which can improve trafﬁc throughput and safety.”
Lane-Change Fuzzy Control in Autonomous Vehicles for the Overtaking Maneuver (2008, background): “[22] presented an automatic driving system that manages longitudinal and lateral controls.”
Three Decades of Driver Assistance Systems: Review and Future Perspectives (2014, background): “Past and potential future evolution towards automated cooperative driving.”