Congestion Control for Medical Emergency with Vehicle-to-Vehicle Communication Using IoT

Traffic is a huge trouble which takes place after an accident. Vehicles in the accident area get congested, moreover without knowing about the accident, vehicles coming from the other roads make the situation difficult for the ambulance to travel and reach the nearest hospital on time. So keeping those problems in mind, an approach that will be able to avoid series of collision and also can control traffic jam using vehicle to vehicle communication.

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LACCVoV: Linear Adaptive Congestion Control With Optimization of Data Dissemination Model in Vehicle-to-Vehicle Communication

IEEE Transactions on Intelligent Transportation Systems ◽

10.1109/tits.2020.3041518 ◽

2020 ◽

pp. 1-10

Author(s):

Arun Kumar Sangaiah ◽

Jaya Subalakshmi Ramamoorthi ◽

Joel J. P. C. Rodrigues ◽

Md. Abdur Rahman ◽

Ghulam Muhammad ◽

...

Keyword(s):

Congestion Control ◽

Data Dissemination ◽

Vehicle Communication ◽

Vehicle To Vehicle ◽

Vehicle To Vehicle Communication ◽

Adaptive Congestion Control

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Time Division Broadcasting Scheme for Congestion Control in Vehicle-to-Vehicle Communication

Computer Science and its Applications - Lecture Notes in Electrical Engineering ◽

10.1007/978-3-662-45402-2_35 ◽

2015 ◽

pp. 239-244

Author(s):

Sang-woo Chang ◽

Shengbin Cao ◽

Sang-sun Lee

Keyword(s):

Congestion Control ◽

Vehicle Communication ◽

Vehicle To Vehicle ◽

Vehicle To Vehicle Communication ◽

Time Division

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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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