Redundancy Mitigation Mechanism for Collective Perception in Connected and Autonomous Vehicles
Future Internet, 2023 Due to poor local range of the perception and object recognition mechanisms used by autonomous vehicles, incorrect decisions can be made, which can jeopardize a fully autonomous operation.
Wellington Lobato +4 more
doaj +1 more source
Robust Autonomous Intersection Control Approach for Connected Autonomous Vehicles [PDF]
IEEE Access, 2020 Traffic light-free intersection control is envisioned to alleviate congestion and manage vehicles intelligently. With the help of vehicle-to-infrastructure (V2I) communication and edge computing (EC), vehicles are instructed to cross the intersection with high vehicle safety and traffic efficiency without traffic lights.
Yuheng Zhang +4 more
openaire +3 more sources
Impact of dedicated lanes for connected and autonomous vehicle on traffic flow throughput [PDF]
, 2018 This paper presents an application of a recently proposed methodology for modeling connected and autonomous vehicles (CAVs) in heterogeneous traffic flow, to investigate the impact of setting dedicated lanes for CAVs on traffic flow throughput.
Yamamoto, Toshiyuki, Ye, Lanhang
core +1 more source
Ambivalence in Stakeholders’ Views on Connected and Autonomous Vehicles
, 2020 Connected and autonomous vehicles (CAVs) are often discussed as a solution to pressing issues of the current transport systems, including congestion, safety, social inclusion and ecological sustainability. Scientifically, there isagreement that CAVs may solve, but can also aggravate these issues, depending on the specific CAV solution.
Celina Kacperski +2 more
openaire +5 more sources
, 2020 The future of traffic management will be based on “connected” and “autonomous” vehicles. With connected vehicles it is possible to gather real-time information.
Demetrio Festa +4 more
core +1 more source
Vulnerable Road Users and Connected Autonomous Vehicles Interaction: A Survey
Sensors, 2022 There is a group of users within the vehicular traffic ecosystem known as Vulnerable Road Users (VRUs). VRUs include pedestrians, cyclists, motorcyclists, among others.
Angélica Reyes-Muñoz +1 more
doaj +1 more source
Potential impact of autonomous vehicles in mixed traffic from simulation using real traffic flow [PDF]
, 2023 This work focuses on the potential impacts of the autonomous vehicles in a mixed traffic condition represented in traffic simulator Simulation of Urban MObility (SUMO) with real traffic flow.
Boyraz Baykas, Pinar +8 more
core +1 more source
Divergent Selection Task Offloading Strategy for Connected Vehicles Based on Incentive Mechanism
, 2023 With the improvements in the intelligent level of connected vehicles (CVs), travelers can enjoy services such as self-driving, self-parking and audiovisual entertainment inside the vehicle, which place extremely high demands on the computing power of ...
Yan Guo +4 more
core +1 more source
Symbolic Imitation Learning: From Black-Box to Explainable Driving Policies
Applied SciencesCurrent imitation learning approaches, predominantly based on deep neural networks (DNNs), offer efficient mechanisms for learning driving policies from real-world datasets.
Iman Sharifi +2 more
doaj +1 more source
Benefits of V2V Communication for Autonomous and Connected Vehicles [PDF]
IEEE Transactions on Intelligent Transportation Systems, 2019 In this paper, we investigate the benefits of Vehicle-to-Vehicle (V2V) communication for autonomous vehicles and provide results on how V2V information helps reduce employable time headway in the presence of parasitic lags. For a string of vehicles adopting a Constant Time Headway Policy (CTHP) and availing the on-board information of predecessor's ...
Swaroop Darbha +2 more
openaire +3 more sources