Vehicle platooning has been the subject of much research. Transfer function analysis of intervehicle distance errors is traditionally utilized to analyze the string stability of platoons. Consensus theory has been the subject of recent study of close-loop stability of platoons. This thesis extends the cooperative control approach to platoon behavior analysis to include the leader as an internal source of information for the communication graph of a platoon. A 1-Leader Type (1LT) graph is defined and an equation is proposed for the formation consensus values of leader and follower nodes in a platoon. Simulations are performed to support the proposed equations. A method is proposed to tune controller gains to achieve collision avoidance despite string instability.
This report is the third in a series of four human factors experiments to examine the effects of cooperative adaptive cruise control (CACC) on driver performance in a variety of situations. The experiment reported here was conducted in a driving simulator scenario in which the subject driver was embedded in a platoon of CACC-equipped vehicles. The experiment explored the interaction effect of the presence or absence of an auditory warning with the presence or absence of automated braking on drivers’ responses to a maximum deceleration crash avoidance event. The subject was in the fourth position in a five-car platoon. Dependent measures were crash avoidance (yes/no), manual brake reaction time (seconds), and adjusted time to collision (seconds). The results indicated that a crash avoidance safety benefit was achieved with full CACC (warning and automated braking) but not otherwise. Brake reaction times were longer when automated braking was present, but without the auditory alarm, about half the drivers took too long to react.
This study is the second in a series of four experiments exploring human factors issues associated with the introduction of cooperative adaptive cruise control (CACC). Specifically, this study explored drivers’ abilities to merge into a stream of continuously moving vehicles in a dedicated lane. Participants were asked to complete one of three different types of merges in the Federal Highway Administration Highway Driving Simulator: Merge with non-CACC vehicle into a left dedicated lane without CACC platooning and varying vehicle gaps. Merge with CACC vehicle into the middle of a CACC platoon or continuous stream of vehicles without speed assistance. Merge with CACC vehicle into a CACC platoon with longitudinal speed assistance. As measured by the National Aeronautics and Space Administration Task Load Index, drivers’ perceived workload was significantly less for both groups that drove with the CACC system engaged than for the group that was required to manually maintain speed the entire drive. Perhaps surprisingly, participant condition did not significantly affect physiological arousal as assessed by galvanic skin response (GSR). However, across all groups, GSR was significantly greater during the merges than during cruising/straight highway driving time periods. The participants who drove with the CACC system during the merges (as defined by the operation of the system) did not experience any collisions. Both groups that were required to manually adjust speed to merge into the platoon of vehicles experienced collisions in 24 (18 percent) of the merges, suggesting that some gaps may be too small for drivers to merge into at high speeds. An alternative explanation, supported by participant feedback, is that drivers expect others to act in a courteous manner and to create larger gaps for entrance onto a freeway—something that may not be possible in real-world CACC deployment.
This book focuses on the design of a multi-criteria automated vehicle longitudinal control system as an enhancement of the adaptive cruise control system. It analyses the effects of various parameters on the average traffic speed and the traction force of the vehicles in mixed traffic from a macroscopic point of view, and also demonstrates why research and development in speed control and predictive cruise control is important. The book also summarises the main steps of the system’s robust control design, from the modelling to its synthesis, and discusses both the theoretical background and the practical computation method of the control invariant sets. The book presents the analysis and verification of the system both in a simulation environment and under real-world conditions. By including the systematic design of the predictive cruise control using road and traffic information, it shows how optimization criteria can lead to multiobjective solutions, and the advanced optimization and control design methods required. The book focuses on a particular method by which the unfavourable effect of the traffic flow consideration can be reduced. It also includes simulation examples in which the speed design is performed, while the analysis is carried out in simulation and visualization environments. This book is a valuable reference for researchers and control engineers working on traffic control, vehicle control and control theory. It is also of interest to students and academics as it provides an overview of the strong interaction between the traffic flow and an individual vehicle cruising from both a microscopic and a macroscopic point of view.
In recent years, the control of Connected and Automated Vehicles (CAVs) has attracted strong attention for various automotive applications. One of the important features demanded of CAVs is collision avoidance, whether it is a stationary or a moving obstacle. Due to complex traffic conditions and various vehicle dynamics, the collision avoidance system should ensure that the vehicle can avoid collision with other vehicles or obstacles in longitudinal and lateral directions simultaneously. The longitudinal collision avoidance controller can avoid or mitigate vehicle collision accidents effectively via Forward Collision Warning (FCW), Brake Assist System (BAS), and Autonomous Emergency Braking (AEB), which has been commercially applied in many new vehicles launched by automobile enterprises. But in lateral motion direction, it is necessary to determine a flexible collision avoidance path in real time in case of detecting any obstacle. Then, a path-tracking algorithm is designed to assure that the vehicle will follow the predetermined path precisely, while guaranteeing certain comfort and vehicle stability over a wide range of velocities. In recent years, the rapid development of sensor, control, and communication technology has brought both possibilities and challenges to the improvement of vehicle collision avoidance capability, so collision avoidance system still needs to be further studied based on the emerging technologies. In this book, we provide a comprehensive overview of the current collision avoidance strategies for traditional vehicles and CAVs. First, the book introduces some emergency path planning methods that can be applied in global route design and local path generation situations which are the most common scenarios in driving. A comparison is made in the path-planning problem in both timing and performance between the conventional algorithms and emergency methods. In addition, this book introduces and designs an up-to-date path-planning method based on artificial potential field methods for collision avoidance, and verifies the effectiveness of this method in complex road environment. Next, in order to accurately track the predetermined path for collision avoidance, traditional control methods, humanlike control strategies, and intelligent approaches are discussed to solve the path-tracking problem and ensure the vehicle successfully avoids the collisions. In addition, this book designs and applies robust control to solve the path-tracking problem and verify its tracking effect in different scenarios. Finally, this book introduces the basic principles and test methods of AEB system for collision avoidance of a single vehicle. Meanwhile, by taking advantage of data sharing between vehicles based on V2X (vehicle-to-vehicle or vehicle-to-infrastructure) communication, pile-up accidents in longitudinal direction are effectively avoided through cooperative motion control of multiple vehicles.
Contains 63 papers covering 11 years of research on the progress and challenges in the design of Adaptive Cruise Control (ACC) systems and components. Subjects covered include: ACC sensors overview; Hybrid ACC systems; Interactive cruise control; Predictive safety systems; Brake actuation; ACC radar sensors; Vision sensors; and Miscellaneous ACC sensors.
Contains 51 papers covering eight years of research on object detection, collision warning, and collision avoidance. Topics covered include: Parking aids; Target tracking with cameras; Sensor combinations; Blind spot detection; Imager chips; Lane tracking; Lane and road departure warning; Sensor fusion; Intersection collision warning; Front- and rear-end crash avoidance; Automatic collision avoidance systems; Braking systems for collision avoidance; and Driver-vehicle interface requirements.
