A Receding Horizon Switching Control Resilient to Communication Failures for Connected Vehicles

2017 ◽  
Author(s):  
Gianluca Savaia ◽  
Zoleikha Abdollahi Biron ◽  
Pierluigi Pisu
Keyword(s):  
Networked Control Systems ◽  
Switching Control ◽  
Connected Vehicles ◽  
Cruise Control ◽  
Control Logic ◽  
Receding Horizon ◽  
Transmission Delays ◽  
Cooperative Adaptive Cruise Control ◽  
Finite Set ◽  
Optimal Control Action

This paper focuses on networked control systems subject to network-induced constraints, namely transmission delays and packet dropping. The proposed framework is based on a switching control logic which selects the optimal control action in a finite set of strategies tailored to a specific scenario. The switching logic relies on a receding horizon optimization — which resembles model predictive control — and does not require any prior knowledge on the condition of the network. This strategy is tested on a platoon of connected vehicles engaged in cooperative adaptive cruise control which communicate over an imperfect DSRC network. The main objective consists in avoiding unsafe scenarios where the network is subject to the aforementioned failures; results show the proposed approach achieves the objective whereas a nominal controller would lead the platoon to crash.

Smooth-Switching Control-Based Cooperative Adaptive Cruise Control by Considering Dynamic Information Flow Topology

2020 ◽  
Vol 2674 (4) ◽  
pp. 444-458
Author(s):  
Anye Zhou ◽  
Siyuan Gong ◽  
Chaojie Wang ◽  
Srinivas Peeta
Keyword(s):  
Information Flow ◽  
Adaptive Cruise Control ◽  
Switching Control ◽  
Cruise Control ◽  
Flow Topology ◽  
Dynamic Information ◽  
String Stability ◽  
Kalman Predictor ◽  
Cooperative Adaptive Cruise Control ◽  
Smooth Switching

Vehicle-to-vehicle communications can be unreliable because of interference and information congestion, which leads to the dynamic information flow topology (IFT) in a platoon of connected and autonomous vehicles. Some existing studies adaptively switch the controller of cooperative adaptive cruise control (CACC) to optimize string stability when IFT varies. However, the difference of transient response between controllers can induce uncomfortable jerks at switching instances, significantly affecting riding comfort and jeopardizing vehicle powertrain. To improve riding comfort while maintaining string stability, the authors introduce a smooth-switching control-based CACC scheme with IFT optimization (CACC-SOIFT) by implementing a bi-layer optimization model and a Kalman predictor. The first optimization layer balances the probability of communication failure and control performance optimally, generating a robust IFT to reduce controller switching. The second optimization layer adjusts the controller parameters to minimize tracking error and the undesired jerk. Further, a Kalman predictor is applied to predict vehicle acceleration if communication failures occur. It is also used to estimate the states of preceding vehicles to suppress the measurement noise and the acceleration disturbance. The effectiveness of the proposed CACC-SOIFT is validated through numerical experiments based on NGSIM field data. Results indicate that the CACC-SOIFT framework can guarantee string stability and riding comfort in the environment of dynamic IFT.

Robust Cooperative Adaptive Cruise Control Design for Connected Vehicles

2015 ◽  
Author(s):  
Mark Trudgen ◽  
Javad Mohammadpour
Keyword(s):  
Traffic Congestion ◽  
Adaptive Cruise Control ◽  
Connected Vehicles ◽  
Cruise Control ◽  
String Stability ◽  
Reduction Techniques ◽  
Stability Robustness ◽  
Cooperative Adaptive Cruise Control ◽  
And Performance ◽  
Viable Approach

In this paper, we design and validate a robust H∞ controller for Cooperative Adaptive Cruise Control (CACC) in connected vehicles. CACC systems take advantage of onboard sensors and wireless technologies working together in order to achieve smaller inter-vehicle following distances, with the overall goal of increasing vehicle throughput on busy highways, and hence serving as a viable approach to reduce traffic congestion. A group of connected vehicles equipped with CACC technology must also ensure what is known as string stability. This requirement effectively dictates that disturbances should be attenuated as they propagate along the platoon of following vehicles. In order to guarantee string stability and to cope with the uncertainties seen in the vehicle model used for a model-based CACC, we propose to design and implement a robust H∞ controller. Loop shaping design methodology is used in this paper to achieve desired tracking characteristics in the presence of competing string stability, robustness and performance requirements. We then employ model reduction techniques to reduce the order of the controller and finally implement the reduced-order controller on a simulation model demonstrating the robust properties of the closed-loop system.

Smart Driving System for Improving Traffic Flow

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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