Impact of a truck as an obstacle on vehicle-to-vehicle communications in rural and highway scenarios

This paper presents economic and reconfigurable RF based wireless communication at 2.4 GHz between two vehicles. It implements digital VLSI using two Spartan 3E FPGAs, where one vehicle receives the information of another vehicle and shares its own information to another vehicle. The information includes vehicle’s speed, location, heading and its operation, such as braking status and turning status. It implements autonomous vehicle technology. In this work, FPGA is used as central signal processing unit which is interfaced with two microcontrollers (ATmega328P). Microcontroller-1 is interfaced with compass module, GPS module, DF Player mini and nRF24L01 module. This microcontroller determines the relative position and the relative heading as seen from one vehicle to another. Microcontroller-2 is used to measure the speed of vehicle digitally. The resulting data from these microcontrollers are transmitted separately and serially through UART interface to FPGA. At FPGA, different signal processing such as speed comparison, turn comparison, distance range measurement and vehicle operation processing, are carried out to generate the voice announcement command, warning signals, event signals, and such outputs are utilized to warn drivers about potential accidents and prevent crashes before event happens.

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Vehicle-to-Vehicle Connectivity and Communication Framework for Vehicular Ad-Hoc Networks

2014 Eighth International Conference on Complex, Intelligent and Software Intensive Systems ◽

10.1109/cisis.2014.7 ◽

2014 ◽

Cited By ~ 20

Author(s):

Danda B. Rawat ◽

Bhed B. Bista ◽

Gongjun Yan ◽

Stephan Olariu

Keyword(s):

Ad Hoc Networks ◽

Vehicular Ad Hoc Networks ◽

Ad Hoc ◽

Communication Framework ◽

Vehicle To Vehicle ◽

Hoc Networks

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Analysis of Non-Stationarity for 5.9 GHz Channel in Multiple Vehicle-to-Vehicle Scenarios

Sensors ◽

10.3390/s21113626 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3626

Author(s):

Fang Li ◽

Wei Chen ◽

Yishui Shui

Keyword(s):

Transmission Rate ◽

Radio Channel ◽

Vertical Direction ◽

Statistical Characteristics ◽

Small Scale ◽

Delay Spread ◽

Important Indicator ◽

Power Delay Profile ◽

Channel Characteristics ◽

Vehicle To Vehicle

The vehicle-to-vehicle (V2V) radio channel is non-stationary due to the rapid movement of vehicles. However, the stationarity of the V2V channels is an important indicator of the V2V channel characteristics. Therefore, we analyzed the non-stationarity of V2V radio channels using the local region of stationarity (LRS). We selected seven scenarios, including three directions of travel, i.e., in the same, vertical, and opposite directions, and different speeds and environments in a similar driving direction. The power delay profile (PDP) and LRS were estimated from the measured channel impulse responses. The results show that the most important influences on the stationary times are the direction and the speed of the vehicles. The average stationary times for driving in the same direction range from 0.3207 to 1.9419 s, the average stationary times for driving in the vertical direction are 0.0359–0.1348 s, and those for driving in the opposite direction are 0.0041–0.0103 s. These results are meaningful for the analysis of the statistical characteristics of the V2V channel, such as the delay spread and Doppler spread. Small-scale fading based on the stationary times affects the quality of signals transmitted in the V2V channel, including the information transmission rate and the information error code rate.

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State Estimation for Cooperative Lateral Vehicle Following Using Vehicle-to-Vehicle Communication

Electronics ◽

10.3390/electronics10060651 ◽

2021 ◽

Vol 10 (6) ◽

pp. 651

Author(s):

Wouter Schinkel ◽

Tom van der Sande ◽

Henk Nijmeijer

Keyword(s):

State Estimation ◽

Cooperative Control ◽

The State ◽

State Estimator ◽

Estimation Process ◽

Vehicle Communication ◽

Vehicle To Vehicle ◽

Control Schemes ◽

Input Signals ◽

Vehicle To Vehicle Communication

A cooperative state estimation framework for automated vehicle applications is presented and demonstrated via simulations, the estimation framework is used to estimate the state of a lead and following vehicle simultaneously. Recent developments in the field of cooperative driving require novel techniques to ensure accurate and stable vehicle following behavior. Control schemes for the cooperative control of longitudinal and lateral vehicle dynamics generally require vehicle state information about the lead vehicle, which in some cases cannot be accurately measured. Including vehicle-to-vehicle communication in the state estimation process can provide the required input signals for the practical implementation of cooperative control schemes. This study is focused on demonstrating the benefits of using vehicle-to-vehicle communication in the state estimation of a lead and following vehicle via simulations. The state estimator, which uses a cascaded Kalman filtering process, takes the operating frequencies of different sensors into account in the estimation process. Simulation results of three different driving scenarios demonstrate the benefits of using vehicle-to-vehicle communication as well as the attenuation of measurement noise. Furthermore, in contrast to relying on low frequency measurement data for the input signals of cooperative control schemes, the state estimator provides a state estimate at every sample.

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Collaborative Autonomous Driving—A Survey of Solution Approaches and Future Challenges

Sensors ◽

10.3390/s21113783 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3783

Author(s):

Sumbal Malik ◽

Manzoor Ahmed Khan ◽

Hesham El-Sayed

Keyword(s):

Autonomous Vehicles ◽

Communication Technologies ◽

Autonomous Driving ◽

Use Cases ◽

Cooperative Driving ◽

Vehicle To Vehicle ◽

Future Challenges ◽

Vehicle To Infrastructure ◽

High Level ◽

Intersection Management

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.

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Index Coded PSK Modulation in Vehicle to Vehicle Communication

IEEE Transactions on Vehicular Technology ◽

10.1109/tvt.2021.3073788 ◽

2021 ◽

pp. 1-1

Author(s):

Jesy Pachat ◽

Nujoom Sageer Karat ◽

Anjana Ambika Mahesh ◽

Deepthi P P ◽

Sundar Rajan

Keyword(s):

Vehicle Communication ◽

Vehicle To Vehicle ◽

Vehicle To Vehicle Communication

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

Electronics ◽

10.3390/electronics10101221 ◽

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.

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Investigating and Modeling of Cooperative Vehicle-to-Vehicle Safety Stopping Distance

Future Internet ◽

10.3390/fi13030068 ◽

2021 ◽

Vol 13 (3) ◽

pp. 68

Author(s):

Steven Knowles Flanagan ◽

Zuoyin Tang ◽

Jianhua He ◽

Irfan Yusoff

Keyword(s):

High Reliability ◽

Base Station ◽

Ieee 802.11P ◽

Packet Losses ◽

The Road ◽

V2v Communication ◽

Stopping Distance ◽

Vehicle To Vehicle ◽

V2v Communications ◽

On The Road

Dedicated Short-Range Communication (DSRC) or IEEE 802.11p/OCB (Out of the Context of a Base-station) is widely considered to be a primary technology for Vehicle-to-Vehicle (V2V) communication, and it is aimed toward increasing the safety of users on the road by sharing information between one another. The requirements of DSRC are to maintain real-time communication with low latency and high reliability. In this paper, we investigate how communication can be used to improve stopping distance performance based on fieldwork results. In addition, we assess the impacts of reduced reliability, in terms of distance independent, distance dependent and density-based consecutive packet losses. A model is developed based on empirical measurements results depending on distance, data rate, and traveling speed. With this model, it is shown that cooperative V2V communications can effectively reduce reaction time and increase safety stop distance, and highlight the importance of high reliability. The obtained results can be further used for the design of cooperative V2V-based driving and safety applications.

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