Traffic flow and emissions improvement via Vehicle‐to‐vehicle and vehicle‐to‐infrastructure communication for an intelligent intersection

2021 ◽  
Author(s):  
Hosna Namazi ◽  
Amir Taghavipour
Keyword(s):  
Traffic Flow ◽  
Vehicle To Vehicle ◽  
Vehicle To Infrastructure ◽  
Vehicle To Infrastructure Communication

scholarly journals Traffic Flow Management of Autonomous Vehicles Using Platooning and Collision Avoidance Strategies

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1221
Author(s):  
Anum Mushtaq ◽  
Irfan ul Haq ◽  
Wajih un Nabi ◽  
Asifullah Khan ◽  
Omair Shafiq
Keyword(s):  
Traffic Flow ◽  
Collision Avoidance ◽  
Autonomous Vehicles ◽  
Flow Management ◽  
V2v Communication ◽  
Cooperative Strategies ◽  
Vehicle To Vehicle ◽  
Traffic Flow Management ◽  
Vehicle To Infrastructure ◽  
Formation And Evolution

Connected Autonomous Vehicles (AVs) promise innovative solutions for traffic flow management, especially for congestion mitigation. Vehicle-to-Vehicle (V2V) communication depends on wireless technology where vehicles can communicate with each other about obstacles and make cooperative strategies to avoid these obstacles. Vehicle-to-Infrastructure (V2I) also helps vehicles to make use of infrastructural components to navigate through different paths. This paper proposes an approach based on swarm intelligence for the formation and evolution of platoons to maintain traffic flow during congestion and collision avoidance practices using V2V and V2I communications. In this paper, we present a two level approach to improve traffic flow of AVs. At the first level, we reduce the congestion by forming platoons and study how platooning helps vehicles deal with congestion or obstacles in uncertain situations. We performed experiments based on different challenging scenarios during the platoon’s formation and evolution. At the second level, we incorporate a collision avoidance mechanism using V2V and V2I infrastructures. We used SUMO, Omnet++ with veins for simulations. The results show significant improvement in performance in maintaining traffic flow.

Social interactions in traffic: The effect of external factors

2018 ◽  
Vol 62 (1) ◽  
pp. 97-101 ◽  
Author(s):  
Tanja Stoll ◽  
Nadine-Rebecca Strelau ◽  
Martin Baumann
Keyword(s):  
Social Interactions ◽  
Cooperative Behavior ◽  
Lane Change ◽  
Lane Changing ◽  
Vehicle To Vehicle ◽  
Driving Task ◽  
Vehicle To Infrastructure ◽  
Underlying Mechanisms ◽  
Intention To Change ◽  
Vehicle To Infrastructure Communication

Social interactions were always part of the driving task, but the introduction of vehicle-to-vehicle and vehicle-to-infrastructure communication opens up new possibilities for cooperative interactive driving. It enables drivers to coordinate their maneuvers cooperatively with other involved traffic users. To ensure drivers’ acceptance of such automated systems it is necessary to understand the underlying mechanisms of human cooperation in traffic. In this experiment, we investigate potential influencing factors on the willingness to behave cooperatively in a lane change situation on a highway. In a video-based study, we manipulated the costs of cooperation, the situation’s criticality for the lane-changing vehicle and the way in which the intention to change the lane was indicated. Cooperative behavior is influenced by lower costs, a higher situation’s criticality and by signaling the intention to lane change. These results offer insights that may be used in the developing process of Human Machine Interfaces (HMI) for cooperatively interacting vehicles

scholarly journals Design and Implementation of V2V and V2I Communication Systems using ML based Li-Fi technology

2021 ◽  
Author(s):  
Manimegaai C T ◽  
kali muthu ◽  
sabitha gauni
Keyword(s):  
Machine Learning ◽  
Communication Systems ◽  
Machine Learning Techniques ◽  
Light Emitting ◽  
Design And Implementation ◽  
Vehicle To Vehicle ◽  
The People ◽  
Learning Techniques ◽  
Vehicle To Infrastructure ◽  
Vehicle To Infrastructure Communication

Abstract These days population are taking a risk in their drive and in no time dangers are happening, and loosing lives by doing tiny wrongs when on drive near restricted zones. To escape these accidents to make population risk free traffic department are introducing signboards. But then again with the ignorance of the people, dangers are happening again, so “Li-Fi technology” is being used here to decrease the count of accidents. The transmission takes place with the help of LEDs (Light Emitting Diodes).Text, audio and video can also be transmitted with the help of this li-fi. The transmission is done when the light turns on and off. When this is compared to Wi-Fi it has many advantages like this light is not harmful to human body. The Transmission takes place in the form of zeroes and ones. Therefore to avoid accidents we suggested an intelligent, adaptable, and efficient model that utilizes Machine Learning techniques. The proposed system helps in vehicle to vehicle and vehicle to Infrastructure communication systems.

After you: Merging at Highway On-Ramps

2020 ◽  
Vol 64 (1) ◽  
pp. 1105-1109
Author(s):  
Tanja Stoll ◽  
Lucas Weihrauch ◽  
Martin Baumann
Keyword(s):  
Influencing Factors ◽  
The Other ◽  
Lane Change ◽  
Lane Changing ◽  
Vehicle To Vehicle ◽  
Human Machine Interfaces ◽  
Human Driver ◽  
Vehicle To Infrastructure ◽  
Intention To Change ◽  
Vehicle To Infrastructure Communication

Vehicle-to-vehicle and vehicle-to-infrastructure communication offer new possibilities for cooperatively interactive driving. It enables vehicles to carry out maneuvers cooperatively with other vehicles. However, these maneuvers have to be predictable and understandable to a human driver to prevent the driver from intervening with the automation. In a video-based study, we investigated potential influencing factors on the willingness to behave cooperatively in an on-ramp situation on a highway: the situation’s criticality for the lane-changing vehicle, the way the intention to change the lane was indicated and the scope of action. Moreover, we asked participants to rate their perceived criticality. Participants preferred to change lanes to the left or decelerate to let the other vehicle merge in front of them. If a lane change was not possible, participants rated the situation as more critical. These results are useful for the developing process of human-machine interfaces for cooperatively interacting vehicles.

scholarly journals Agent Based Resilient Transportation Infrastructure With Surrogate Adaptive Networks

2020 ◽  
Author(s):  
Andre A. Apostol ◽  
Cameron J. Turner
Keyword(s):  
Decision Making ◽  
Traffic Flow ◽  
Intelligent Agents ◽  
Autonomous Vehicle ◽  
Transportation Infrastructure ◽  
Adaptive Networks ◽  
Agent Based ◽  
Vehicle To Vehicle ◽  
Vehicle To Infrastructure ◽  
Vehicle Technology

Abstract Connected autonomous intelligent agents (AIA) can improve intersection performance and resilience for the transportation infrastructure. An agent is an autonomous decision maker whose decision making is determined internally but may be altered by interactions with the environment or with other agents. Implementing agent-based modeling techniques to advance communication for more appropriate decision making can benefit autonomous vehicle technology. This research examines vehicle to vehicle (V2V), vehicle to infrastructure (V2I), and infrastructure to infrastructure (I2I) communication strategies that use gathered data to ensure these agents make appropriate decisions under operational circumstances. These vehicles and signals are modeled to adapt to the common traffic flow of the intersection to ultimately find an traffic flow that will minimizes average vehicle transit time to improve intersection efficiency. By considering each light and vehicle as an agent and providing for communication between agents, additional decision-making data can be transmitted. Improving agent based I2I communication and decision making will provide performance benefits to traffic flow capacities.

scholarly journals Arduino-Based Solution for In-Car-Abandoned Infants' Detection Remotely Managed by Smartphone Application

2019 ◽  
Vol 15 (2) ◽  
Author(s):  
Paolo Visconti ◽  
Roberto De Fazio ◽  
Paolo Costantini ◽  
Simone Miccoli ◽  
Donato Cafagna
Keyword(s):  
Control System ◽  
Communication Systems ◽  
Smartphone Application ◽  
Mobile App ◽  
Research Groups ◽  
Software Applications ◽  
Vehicle To Vehicle ◽  
Safety And Reliability ◽  
Vehicle To Infrastructure ◽  
Vehicle To Infrastructure Communication

This manuscript deals with V2V/V2I (Vehicle-to-Vehicle and Vehicle-to-Infrastructure) communication systems developed for smart city applications, with the aim to provide new services and tools for making driving safer and improving the human lifestyle. The considered systems can be supported by suitable software applications for making the services more accessible. In this context, research groups and automotive companies are currently developing systems against children abandonment in unattended vehicles and are installing them on new car models. In this paper, an innovative Arduino-based control system against children abandonment in cars is described. It introduces new functionalities respect to systems reported in literature or already on the market, in order to improve safety and reliability. The proposed system integrates a mobile app, which gives the possibilities of receiving alert or status messages, along with images directly acquired from car cockpit. In addition, the app allows to remotely control several car functionalities, such as horn activation, windows lowering and doors locking/unlocking.

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