Key features of one automated intelligent vehicle/highway system (IVHS) are outlined, it is shown how core driver decisions are improved, a basic IVHS control system architecture is proposed, and a design of some control subsystems is offered. Some experimental work is summarized. A system that promises a threefold increase in capacity is outlined, and a four-layer hierarchical control architecture that decomposes this problem into more manageable units is proposed. >

Smart cars on smart roads: problems of control

Safety critical systems involve the tight coupling between potentially conflicting control objectives and safety constraints. As a means of creating a formal framework for controlling systems of this form, and with a view toward automotive applications, this paper develops a methodology that allows safety conditions—expressed as control barrier functions —to be unified with performance objectives—expressed as control Lyapunov functions—in the context of real-time optimization-based controllers. Safety conditions are specified in terms of forward invariance of a set, and are verified via two novel generalizations of barrier functions; in each case, the existence of a barrier function satisfying Lyapunov-like conditions implies forward invariance of the set, and the relationship between these two classes of barrier functions is characterized. In addition, each of these formulations yields a notion of control barrier function (CBF), providing inequality constraints in the control input that, when satisfied, again imply forward invariance of the set. Through these constructions, CBFs can naturally be unified with control Lyapunov functions (CLFs) in the context of a quadratic program (QP); this allows for the achievement of control objectives (represented by CLFs) subject to conditions on the admissible states of the system (represented by CBFs). The mediation of safety and performance through a QP is demonstrated on adaptive cruise control and lane keeping, two automotive control problems that present both safety and performance considerations coupled with actuator bounds.

https://ieeexplore.ieee.org/ielaam/9/7993115/7782377-aam.pdf

Control Barrier Function Based Quadratic Programs for Safety Critical Systems

The design of a cooperative adaptive cruise-control (CACC) system and its practical validation are presented. Focusing on the feasibility of implementation, a decentralized controller design with a limited communication structure is proposed (in this case, a wireless communication link with the nearest preceding vehicle only). A necessary and sufficient frequency-domain condition for string stability is derived, taking into account heterogeneous traffic, i.e., vehicles with possibly different characteristics. For a velocity-dependent intervehicle spacing policy, it is shown that the wireless communication link enables driving at small intervehicle distances, whereas string stability is guaranteed. For a constant velocity-independent intervehicle spacing, string stability cannot be guaranteed. To validate the theoretical results, experiments are performed with two CACC-equipped vehicles. Implementation of the CACC system, the string-stability characteristics of the practical setup, and experimental results are discussed, indicating the advantages of the design over standard adaptive-cruise-control functionality.

String-Stable CACC Design and Experimental Validation: A Frequency-Domain Approach

This paper develops a control methodology that unifies control barrier functions and control Lyapunov functions through quadratic programs. The result is demonstrated on adaptive cruise control, which presents both safety and performance considerations, as well as actuator bounds. We begin by presenting a novel notion of a barrier function associated with a set, formulated in the context of Lyapunov-like conditions; the existence of a barrier function satisfying these conditions implies forward invariance of the set. This formulation naturally yields a notion of control barrier function (CBF), yielding inequality constraints in the control input that, when satisfied, again imply forward invariance of the set. Through these constructions, CBFs can naturally be unified with control Lyapunov functions (CLFs) in the context of a quadratic program (QP); this allows for the simultaneous achievement of control objectives (represented by CLFs) subject to conditions on the admissible states of the system (represented by CBFs). These formulations are illustrated in the context of adaptive cruise control, where the control objective of achieving a desired speed is balanced by the minimum following conditions on a lead car and force-based constraints on acceleration and braking.

/pdf/control-barrier-function-based-quadratic-programs-with-4f6pnxj8wm.pdf

Control barrier function based quadratic programs with application to adaptive cruise control

Nowadays, throughput has become a limiting factor in road transport. An effective means to increase the road throughput is to employ a small intervehicle time gap using automatic vehicle-following control systems. String stability, i.e., the disturbance attenuation along the vehicle string, is considered an essential requirement for the design of those systems. However, the formal notion of string stability is not unambiguous in literature, since both stability and performance interpretations exist. Therefore, a novel definition for string stability of nonlinear cascaded systems is proposed, using input-output properties. This definition is shown to result in well-known string stability conditions for linear cascaded systems. The theoretical results are experimentally validated using a platoon of six passenger vehicles equipped with cooperative adaptive cruise control.

/pdf/lp-string-stability-of-cascaded-systems-application-to-2qer765sh8.pdf

Lp String Stability of Cascaded Systems: Application to Vehicle Platooning

Vehicle following and its effects on traffic flow has been an active area of research. Human driving involves reaction times, delays, and human errors that affect traffic flow adversely. One way to eliminate human errors and delays in vehicle following is to replace the human driver with a computer control system and sensors. The purpose of this paper is to develop an autonomous intelligent cruise control (AICC) system for automatic vehicle following, examine its effect on traffic flow, and compare its performance with that of the human driver models. The AICC system developed is not cooperative; i.e., it does not exchange information with other vehicles and yet is not susceptible to oscillations and "slinky" effects. The elimination of the "slinky" effect is achieved by using a safety distance separation rule that is proportional to the vehicle velocity (constant time headway) and by designing the control system appropriately. The performance of the AICC system is found to be superior to that of the human driver models considered. It has a faster and better transient response that leads to a much smoother and faster traffic flow. Computer simulations are used to study the performance of the proposed AICC system and analyze vehicle following in a single lane, without passing, under manual and automatic control. In addition, several emergency situations that include emergency stopping and cut-in cases were simulated. The simulation results demonstrate the effectiveness of the AICC system and its potentially beneficial effects on traffic flow. >

C.C. Chien

Papers

Autonomous intelligent cruise control