scholarly journals Design and Numerical Implementation of V2X Control Architecture for Autonomous Driving Vehicles

Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1696
Author(s):  
Piyush Dhawankar ◽  
Prashant Agrawal ◽  
Bilal Abderezzak ◽  
Omprakash Kaiwartya ◽  
Krishna Busawon ◽  
...  

This paper is concerned with designing and numerically implementing a V2X (Vehicle-to-Vehicle and Vehicle-to-Infrastructure) control system architecture for a platoon of autonomous vehicles. The V2X control architecture integrates the well-known Intelligent Driver Model (IDM) for a platoon of Autonomous Driving Vehicles (ADVs) with Vehicle-to-Infrastructure (V2I) Communication. The main aim is to address practical implementation issues of such a system as well as the safety and security concerns for traffic environments. To this end, we first investigated a channel estimation model for V2I communication. We employed the IEEE 802.11p vehicular standard and calculated path loss, Packet Error Rate (PER), Signal-to-Noise Ratio (SNR), and throughput between transmitter and receiver end. Next, we carried out several case studies to evaluate the performance of the proposed control system with respect to its response to: (i) the communication infrastructure; (ii) its sensitivity to an emergency, inter-vehicular gap, and significant perturbation; and (iii) its performance under the loss of communication and changing driving environment. Simulation results show the effectiveness of the proposed control model. The model is collision-free for an infinite length of platoon string on a single lane road-driving environment. It also shows that it can work during a lack of communication, where the platoon vehicles can make their decision with the help of their own sensors. V2X Enabled Intelligent Driver Model (VX-IDM) performance is assessed and compared with the state-of-the-art models considering standard parameter settings and metrics.

Author(s):  
Lung En Jan ◽  
Junfeng Zhao ◽  
Shunsuke Aoki ◽  
Anand Bhat ◽  
Chen-Fang Chang ◽  
...  

Abstract Connected and automated vehicles (CAVs) have real-time knowledge of the immediate driving environment, actions to be taken in the near future and information from the cloud. This knowledge, referred to as preview information, enables CAVs to drive safely, but can also be used to minimize fuel consumption. Such fuel-efficient transportation has the potential to reduce aggregate fuel consumption by billions of gallons of gas every year in the U.S. alone. In this paper, we propose a planning framework for use in CAVs with the goal of generating fuel-efficient vehicle trajectories. By utilizing on-board sensor data and vehicle-to-infrastructure (V2I) communications, we leverage the computational power of CAVs to generate eco-friendly vehicle trajectories. The planner uses an eco-driver model and a predictive cost-based search to determine the optimal speed profile for use by a CAV. To evaluate the performance of the planner, we introduce a co-simulation environment consisting of a CAV simulator, Matlab/Simulink and a CAV software platform called the InfoRich Eco-Autonomous Driving (iREAD) system. The planner is evaluated in various urban traffic scenarios based on real-world road network models provided by the National Renewable Energy Laboratory (NREL). Simulations show an average savings of 14.5% in fuel consumption with a corresponding increase of 2% in travel time using our method.


2021 ◽  
Vol 10 (3) ◽  
pp. 42
Author(s):  
Mohammed Al-Nuaimi ◽  
Sapto Wibowo ◽  
Hongyang Qu ◽  
Jonathan Aitken ◽  
Sandor Veres

The evolution of driving technology has recently progressed from active safety features and ADAS systems to fully sensor-guided autonomous driving. Bringing such a vehicle to market requires not only simulation and testing but formal verification to account for all possible traffic scenarios. A new verification approach, which combines the use of two well-known model checkers: model checker for multi-agent systems (MCMAS) and probabilistic model checker (PRISM), is presented for this purpose. The overall structure of our autonomous vehicle (AV) system consists of: (1) A perception system of sensors that feeds data into (2) a rational agent (RA) based on a belief–desire–intention (BDI) architecture, which uses a model of the environment and is connected to the RA for verification of decision-making, and (3) a feedback control systems for following a self-planned path. MCMAS is used to check the consistency and stability of the BDI agent logic during design-time. PRISM is used to provide the RA with the probability of success while it decides to take action during run-time operation. This allows the RA to select movements of the highest probability of success from several generated alternatives. This framework has been tested on a new AV software platform built using the robot operating system (ROS) and virtual reality (VR) Gazebo Simulator. It also includes a parking lot scenario to test the feasibility of this approach in a realistic environment. A practical implementation of the AV system was also carried out on the experimental testbed.


Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3783
Author(s):  
Sumbal Malik ◽  
Manzoor Ahmed Khan ◽  
Hesham El-Sayed

Sooner than expected, roads will be populated with a plethora of connected and autonomous vehicles serving diverse mobility needs. Rather than being stand-alone, vehicles will be required to cooperate and coordinate with each other, referred to as cooperative driving executing the mobility tasks properly. Cooperative driving leverages Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication technologies aiming to carry out cooperative functionalities: (i) cooperative sensing and (ii) cooperative maneuvering. To better equip the readers with background knowledge on the topic, we firstly provide the detailed taxonomy section describing the underlying concepts and various aspects of cooperation in cooperative driving. In this survey, we review the current solution approaches in cooperation for autonomous vehicles, based on various cooperative driving applications, i.e., smart car parking, lane change and merge, intersection management, and platooning. The role and functionality of such cooperation become more crucial in platooning use-cases, which is why we also focus on providing more details of platooning use-cases and focus on one of the challenges, electing a leader in high-level platooning. Following, we highlight a crucial range of research gaps and open challenges that need to be addressed before cooperative autonomous vehicles hit the roads. We believe that this survey will assist the researchers in better understanding vehicular cooperation, its various scenarios, solution approaches, and challenges.


Author(s):  
Shihuan Li ◽  
Lei Wang

For L4 and above autonomous driving levels, the automatic control system has been redundantly designed, and a new steering control method based on brake has been proposed; a new dual-track model has been established through multiple driving tests. The axle part of the model was improved, the accuracy of the transfer function of the model was verified again through acceleration-slide tests; a controller based on interference measurement was designed on the basis of the model, and the relationships between the controller parameters was discussed. Through the linearization of the controller, the robustness of uncertain automobile parameters is discussed; the control scheme is tested and verified through group driving test, and the results prove that the accuracy and precision of the controller meet the requirements, the robustness stability is good. Moreover, the predicted value of the model fits well with the actual observation value, the proposal of this method provides a new idea for avoiding car out of control.


Author(s):  
Alireza Nemati ◽  
Manish Kumar

In this paper, a nonlinear control of a tilting rotor quadcopter is presented. The overall control architecture is divided into two sub-controllers. The first controller is based on the feedback linearization control derived from the dynamic model of the tilting quadcopter. This controls the pitch, roll, and yaw motions required for movement along an arbitrary trajectory in space. The second controller is based on two PD controllers which are used to control the tilting of the quadcopter independently along the pitch and the yaw directions respectively. The overall control enables the quadcopter to combine tilting and movement along a desired trajectory simultaneously. Simulation studies are presented based on the developed nonlinear dynamic model of the tilting rotor quadcopter to demonstrate the validity and effectiveness of the overall control system for an arbitrary trajectory tracking.


Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 538
Author(s):  
Nicoleta Cristina Gaitan ◽  
Ioan Ungurean

The development of the smart building concept and building automation field is based on the exponential evolution of monitoring and control technologies. Residents of the smart building must interact with the monitoring and control system. A widely used method is specific applications executed on smartphones, tablets, and PCs with Bluetooth connection to the building control system. At this time, smartphones are increasingly used in everyday life for payments, reading newspapers, monitoring activity, and interacting with smart homes. The devices used to build the control system are interconnected through a specific network, one of the most widespread being the Building Automation and Control Network (BACnet) network. Here, we propose the use of the BACnet Application Layer over Bluetooth. We present a proposal of a concept and a practical implementation that can be used to test and validate the operation of the BACnet Application Layer over Bluetooth.


2018 ◽  
Author(s):  
Miroslaw Kondratiuk ◽  
Leszek Ambroziak ◽  
Ewa Pawluszewicz ◽  
Justyna Janczak

2021 ◽  
Author(s):  
James Gaston

The work area of a team of small robots is limited by their inability to traverse a very common obstacle: stairs. We present a complete integrated control architecture and communication strategy for a system of reconfigurable robots that can climb stairs. A modular robot design is presented which allows the robots to dynamically reconfigure to traverse certain obstacles. This thesis investigates the implementation of a system of autonomous robots which can cooperatively reconfigure themselves to collectively travers obstacle such as stairs. We present a complete behaviorand communication system which facilitates this autonomous reconfiguration. The layered behavior-based control system is fault-tolerant and extends the capabilities of a control architecture known as ALLIANCE. Behavior classes are introduced as mechanism for managing ordering dependencies and monitoring a robot's progress through a particular task. The communication system compliments the behavioral control and iimplementsinherent robot failure detection without the need for a base station or external monitor. The behavior and communication systems are validated by implementing them ona mobile robot platform synthesized specifically for this research. Experimental trials showed that the implementation of the behavior control systems was successful. The control system provided robust, fault-tolerant performance even when robots failed to perform docking tasks while recongifuring. Once the robots reconfigure to form a chain, a different control scheme based on gait control tables coordinates the individual movements of the robots. Several successful stair climbing trials were accomplished. Improvements to the mechanical design are proposed.


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