Platooning of Car-like Vehicles in Urban Environments: Longitudinal Control Considering Actuator Dynamics, Time Delays, and Limited Communication Capabilities

International audienceThis paper proposes a longitudinal control framework for platooning in an urban environment. The targetted application is to redistribute vehicles involved in car-sharing systems, where only the leader vehicle is human-driven. We propose a platoon model and control law considering actuator dynamics. This control relies on a hybrid Information Flow Topology (IFT), where the leader broadcasts its state but each follower only measures the position of its predecessor. A consensusbased control law incorporates the effect of the network/sensor time delay and the variable velocity of the leader. Conditions for the platoon internal and string stability are given. Experiments demonstrate the efficiency of the framework in simulation and real experiments with three commercial cars

Theoretical Development and Numerical Validation of an Asymmetric Linear Bilateral Control Model For an Automated Truck Platoon

In this study, the author theoretically develops and numerically validates an asymmetric linear bilateral control model (LBCM) for an automated truck platoon, in which the motion information (i.e., position and speed) from the immediate leading truck and the immediate following truck are weighted differently. The novelty of the asymmetric LBCM is that using this model, all the follower trucks in a platoon can adjust their acceleration and deceleration to closely follow a constant desired time headway at all times to improve platoon operational efficiency while maintaining local and string stability. The author theoretically proves the local stability of the asymmetric LBCM using the condition for asymptotic stability of a linear time-invariant system and derives the condition for string stability using a space headway error attenuation approach. Then, the author evaluates the efficacy of the asymmetric LBCM by simulating a closely coupled cooperative adaptive cruise control (CACC) platoon of fully automated trucks in various non-linear acceleration and deceleration states. To evaluate the platoon operational efficiency of the asymmetric LBCM, the author compares the performance of the asymmetric LBCM to a baseline model, i.e., the symmetric LBCM, for three different time headway settings, i.e., 0.6 sec, 0.8 sec, and 1.1 sec. Analyses indicate that the asymmetric LBCM yields lower sum of squared time headway error and sum of squared speed error compared to the baseline model considered in this study. These findings demonstrate the potential of the asymmetric LBCM in improving platoon operational efficiency and stability of an automated truck platoon

Improved information flow topology for vehicle convoy control

A vehicle convoy is a string of inter-connected vehicles moving together for mutual support, minimizing traffic congestion, facilitating people safety, ensuring string stability and maximizing ride comfort. There exists a trade-off among the convoy's performance indices, which is inherent in any existing vehicle convoy. The use of unrealistic information flow topology (IFT) in vehicle convoy control, generally affects the overall performance of the convoy, due to the undesired changes in dynamic parameters (relative position, speed, acceleration and jerk) experienced by the following vehicle. This thesis proposes an improved information flow topology for vehicle convoy control. The improved topology is of the two-vehicle look-ahead and rear-vehicle control that aimed to cut-off the trade-off with a more robust control structure, which can handle constraints, wider range of control regions and provide acceptable performance simultaneously. The proposed improved topology has been designed in three sections. The first section explores the single vehicle's dynamic equations describing the derived internal and external disturbances modeled together as a unit. In the second section, the vehicle model is then integrated into the control strategy of the improved topology in order to improve the performance of the convoy to two look-ahead and rear. The changes in parameters of the improved convoy topology are compared through simulation with the most widely used conventional convoy topologies of one-vehicle look-ahead and that of the most human-driver like (the two-vehicle look-ahead) convoy topology. The results showed that the proposed convoy control topology has an improved performance with an increase in the intervehicular spacing by 19.45% and 18.20% reduction in acceleration by 20.28% and 15.17% reduction in jerk by 25.09% and 6.25% as against the one-look-ahead and twolook- ahead respectively. Finally, a model predictive control (MPC) system was designed and combined with the improved convoy topology to strictly control the following vehicle. The MPC serves the purpose of handling constraints, providing smoother and satisfactory responses and providing ride comfort with no trade-off in terms of performance or stability. The performance of the proposed MPC based improved convoy topology was then investigated via simulation and the results were compared with the previously improved convoy topology without MPC. The improved convoy topology with MPC provides safer inter-vehicular spacing by 13.86% refined the steady speed to maneuvering speed, provided reduction in acceleration by 32.11% and a huge achievement was recorded in reduction in jerk by 55.12% as against that without MPC. This shows that the MPC based improved convoy control topology gave enough spacing for any uncertain application of brake by the two look-ahead or further acceleration from the rear-vehicle. Similarly, manoeuvering speed was seen to ensure safety ahead and rear, ride comfort was achieved due to the low acceleration and jerk of the following vehicle. The controlling vehicle responded to changes, hence good handling was achieved

Platooning of Car-like Vehicles in Urban Environments: An Observer-based Approach Considering Actuator Dynamics and Time delays

International audienceIn this paper, a distributed observer-based approach is proposed to control the longitudinal motion of car-like vehicle platoon moving in an urban environment. To the best of our knowledge, this is the first work presenting an observer-based platoon controller that combines the advantages of high traffic capacity and a minimum number of communication links. To achieve a high traffic flow, a constant-spacing policy is used. However, for that policy, to make platoon string stable, the leader information must be broadcast to all the vehicles. Therefore, we propose a control law in which the predecessor position information is acquired by a sensor-based link while a communication-based link is used to obtain the leader information. Then, an observer is designed and integrated into the control law such that the velocity information of the predecessor can be estimated without the need to communicate with the preceding vehicle. For navigation in urban environments, we present a third order platoon model represented in the curvilinear coordinates. Conditions for asymptotic stability and string stability are given considering the vehicle actuator dynamics and the induced network/sensor time delay. Finally, we provide both simulation and real-time results to validate our approach feasibility and to corroborate our theoretical findings. Index Terms-platoon in urban environments, curvilinear coordinates , observer-based longitudinal control, limited communication , high traffic flow

Real-time Autonomous Cruise Control of Connected Plug-in Hybrid Electric Vehicles Under Uncertainty

Advances in embedded digital computing and communication networks have enabled the development of automated driving systems. Autonomous cruise control (ACC) and cooperative ACC (CACC) systems are two popular types of these technologies, which can be implemented to enhance safety, traffic flow, driving comfort and energy economy. This PhD thesis develops robust and adaptive controllers for plug-in hybrid electric vehicles (PHEVs), with the Toyota Plug-in Prius as the baseline vehicle, in order to enable them to perform safe and robust car-following and platooning with improved vehicle performance. Three controllers are designed here to achieve three main goals. The first goal of this thesis is the development of a real-time Ecological ACC (Eco-ACC) system for PHEVs, that is robust to uncertainties. A novel adaptive tube-based nonlinear model predictive control (AT-NMPC) approach to the design of Eco-ACC systems is proposed. Through utilizing two separate models to define the constrained optimal control problem, this method takes into account uncertainties, modeling errors and delayed data in the design of the controller and guaranties robust constraint handling for the assumed uncertainty bounds. {In addition, it adapts to changes in order to improve the control performance when possible.} Furthermore, a Newton/GMRES fast solver is employed to implement the designed AT-NMPC in real-time. The second goal is the development of a real-time Ecological CACC (Eco-CACC) system that can simultaneously satisfy the frequency-domain and time-domain platooning criteria. A novel distributed reference governor (RG) approach to the constraint handling of vehicle platoons equipped with CACC is presented. RG sits behind the controlled string stable system and keeps the output inside the defined constraints. Furthermore, to improve the platoon's energy economy, a controller is presented for the leader's control using NMPC method, assuming it is a PHEV. The third objective of this thesis is the control of heterogeneous platoons using an adaptive control approach. A direct model reference adaptive controller (MRAC) is designed that enforces a string stable behavior on the vehicle platoon despite different dynamical models of the platoon members and the external disturbances acting on the systems. The proposed method estimates the controller coefficients on-line to adapt to the disturbances such as wind, changing road grade and also to different vehicle dynamic behaviors. The main purpose of all three controllers is to maintain the driving safety of connected vehicles in car-following and platooning while being real-time implementable. In addition, when there is a possibility for performance enhancement without sacrificing safety, ecological improvement is also considered. For each designed controller, Model-in-the-Loop (MIL) simulations and Hardware-in-the-Loop (HIL) experiments are performed using high-fidelity vehicle models in order to validate controllers' performance and ensure their real-time implementation capability

電気自動車における信号機を考慮した航続距離延長自動運転に関する研究

University of Tokyo(東京大学