Energy-Efficient Cooperative Adaptive Cruise Control Strategy using V2I

Cooperative longitudinal motion control can greatly contribute to safety, mobility, and sustainability issues in today’s transportation systems. This article deals with the development of cooperative adaptive cruise control (CACC) under uncertainty using a model predictive control strategy. Specifically, uncertainties arising in the system are presented as disturbances acting in the system and measurement equations in a state-space formulation. We aim to design a predictive controller under a common goal (cooperative control) such that the equilibrium from initial condition of vehicles will remain stable under disturbances. The state estimation problem is handled by a Kalman filter and the optimal control problem is formulated by the quadratic programming method under both state and input constraints considering traffic safety, efficiency, as well as driving comfort. In the sequel, adopting the CACC system in four-vehicle platoon scenarios are tested via MATLAB/Simulink for cooperative vehicle platooning control under different disturbance realizations. Moreover, the computational effectiveness of the proposed control strategy is verified with respect to different platoon sizes for possible real-time deployment in next-generation cooperative vehicles.

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Cooperative Adaptive Cruise Control Strategy Optimization for Electric Vehicles Based on SA-PSO With Model Predictive Control

IEEE Access ◽

10.1109/access.2020.3043370 ◽

2020 ◽

pp. 1-1

Author(s):

Hao Ma ◽

Liang Chu ◽

Jianhua Guo ◽

Jiawei Wang ◽

Chong Guo

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Electric Vehicles ◽

Control Strategy ◽

Adaptive Cruise Control ◽

Cruise Control ◽

Cooperative Adaptive Cruise Control

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A Safety Reinforced Cooperative Adaptive Cruise Control Strategy Accounting for Dynamic Vehicle-to-Vehicle Communication Failure

Sensors ◽

10.3390/s21186158 ◽

2021 ◽

Vol 21 (18) ◽

pp. 6158

Author(s):

Yi Liu ◽

Wei Wang

Keyword(s):

Wireless Communication ◽

Control Strategy ◽

Adaptive Cruise Control ◽

Smooth Transition ◽

Cruise Control ◽

Communication Failure ◽

Advanced Technique ◽

Vehicle To Vehicle ◽

Cooperative Adaptive Cruise Control ◽

Vehicle Platoon

Cooperative Adaptive Cruise Control (CACC) is an advanced technique for organizing and managing a vehicle platoon, which employs the Vehicle-to-Vehicle/Vehicle-to-Infrastructure (V2V/V2I, or V2X) wireless communication to minimize the inter-vehicle distance while guaranteeing string-stability. Consequently, the conventional CACC system relies heavily on the quality of communications, which means that the regular CACC platoon is sensitive to the communication failure. Therefore, in this paper, a Safety Reinforced Cooperative Adaptive Cruise Control (SR-CACC) strategy is proposed to resist unexpected communication failure. Different from the regular CACC system, the safety enhanced platoon control system is embedded with a dual-branch control strategy. When a fatal wireless communication failure is detected and confirmed, the SR-CACC system will automatically activate the alternative sensor-based adaptive cruise control strategy. Moreover, to make the transforming process smooth, a linear smooth transition algorithm is added to the SR-CACC system. Then, to verify the performance of the proposed SR-CACC system, we conducted a simulation experiment with a heterogonous platoon constructed with eight vehicles. The experiments results reveal that, under the extremely poor communication environment, the proposed SR-CACC strategy can significantly improve the safety performance of the organized vehicle platoon.

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Smart Driving System for Improving Traffic Flow

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse/v7i7/0174 ◽

2017 ◽

Vol 7 (7) ◽

pp. 236

Author(s):

Rajesh Kumar Gupta ◽

L. N. Padhy ◽

Sanjay Kumar Padhi

Keyword(s):

Traffic Flow ◽

Traffic Congestion ◽

Urban Areas ◽

Adaptive Cruise Control ◽

Human Perception ◽

Cruise Control ◽

Driving System ◽

V2v Communication ◽

Traffic Conditions ◽

Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay. For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

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