Indiana University-Purdue University Indianapolis (IUPUI) / Autonomous vehicles currently dominate the automobile field for their impact on humanity and society. Connected and Automated Vehicles (CAV’s) are vehicles that use different communication technologies to communicate with other vehicles, infrastructure, the cloud, etc. With the information received from the sensors present, the vehicles analyze and take necessary steps for smooth, collision-free driving. This the sis talks about the cruise control system along with the intersection collision avoidance system based on Petri net models. It consists of two internal controllers for velocity and distance control, respectively, and three external ones for collision avoidance. Fault-tolerant redundant controllers are designed to keep these three controllers in check. The model is built using a PN toolbox and tested for various scenarios. The model is also validated, and its distinct properties are analyzed.

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Trust in automatic controllers may have an impact on awareness of system limitations and ultimately use of these systems. The purpose of this research is to determine the effects and likelihood of too much trust (overtrust) in drivers that use adaptive cruise control (ACC), a type of automatic controller that maintains vehicle speed and headway time. To add to the existing literature, this study aimed to define a significant relationship among trust, use, and awareness of ACC limitations. A post mailed or electronic-based survey was distributed to potential ACC users with 118 responses used for the main analysis. The survey responses provided demographic information, illustrated levels of trust, awareness of ACC limitations, and system use. A hierarchical cluster analysis of the data related to trust in ACC produced four clusters: overtrust, cautious, neutral, and distrust. Binary and multinomial logistic regression models then predicted the likelihood for overtrust (cluster membership). Participants in the overtrust cluster displayed the lowest level of awareness regarding ACC limitations and the highest levels of misuse. Users were more likely to overtrust ACC if they were male, misused the system, lacked limitation awareness, and indicated a willingness to opt for ACC in their next vehicle. Overtrust in ACC was shown to lead to misuse and cloud awareness of the systems' limitations. Trust seemed to be formed in the initial interactions with ACC therefore a priori trust levels of potential users should be sought before appropriate guidance is given or demonstrated through test use.

In driving, multiple variables in automated systems such as adaptive cruise control (ACC) and active steering, and in the environment dynamically change and interact. This complexity makes it difficult for operators to track the activities and responses of automation. The inability of operators to monitor and understand automation's behavior contributes to inappropriate reliance, i.e. when an operator uses automation that performs poorly or fails to use automation that is superior to manual control. The decision to use or not use automation is one of the most important an operator can make, particularly in time-critical or emergency situations, therefore it is essential that an operator is calibrated in their automation use. An operator's decision to rely on automation depends on trust. System feedback provided to the operator is one means to calibrate trust in automation in that the type of feedback may differentially affect trust. The goal of this research is to help operators manage imperfect automation in real-time and to promote calibrated trust and reliance. A continuous information display that provides information on system behavior relative to its operating context is one means to promote such calibration. Three specific aims are pursued to test the central hypothesis of this dissertation that continuous feedback on the state and behavior of the automation informs operators of the evolving relationship between system performance and operating limits, therefore promoting accurate mental models and calibrated trust. The first aim applies a quantitative model to define the effect of understanding on driver-ACC interaction failures and to predict driver response to feedback. The second aim presents a systematic approach to define the feedback needed to support appropriate reliance in a demanding multi-task domain such as driving. The third aim assesses the costs and benefits of presenting drivers with continuous visual and auditory feedback. Together these aims indicate that continuous feedback on automation's behavior is a viable means to promote calibrated trust and reliance. The contribution of this dissertation is in providing purpose, process, and performance information to operators through a continuous, concurrent information display that indicates how the given situation interacts with the characteristics of the automation to affect its capability.

The author's concept of the distance and tracking control problem for autonomous vehicles relates to the cooperative behaviour of two successive vehicles travelling in the same environment. This behaviour requires one vehicle, designated the leader to move autonomously around it's environment with other vehicles, designated followers maintaining a coincident travel path and desired longitudinal distance with respect to the leader. Distance and tracking control is beneficial in numerous applications including guiding autonomous vehicles in Intelligent Transport Systems (ITS) which increases traffic safety and the capacity of pre-existing road infrastructure. Service robotics may also benefit from the cost savings and flexibility offered by distance and tracking control which enables a number of robots to cooperate together in order to achieve a task beyond the capabilities ofjust one robot. Using a distance and tracking control scheme an intelligent leader robot may guide a number of less intelligent (and therefore less costly and less complex) followers to a work-site to perform a task. The author's approach to the distance and tracking control problem consisted of two separate solutions - an initial solution used as a starting point and learning experience and a second, more robust, fuzzy control-based solution. This thesis briefly describes the initial solution, but places a greater emphasis on the second solution. The reason for this is that the fuzzy control-based solution offers significant improvement on the initial solution and was developed based on conclusions drawn from the initial solution. Most implementations of distance and tracking control, sometimes referred to as Intelligent Cruise Control (ICC) or platooning, are limited to longitudinal distance control only. The leader tracking control is performed either implicitly by a separate lane-following control system or by human drivers. The fuzzy control-based solution offered in this thesis performs both distance and tracking control of an autonomous follower vehicle with respect to a leader vehicle in front of it. It represents a simple and cost effective solution to the requirements of autonomous vehicles operating in ITS schemes - particularly close formation platooning. The follower tracks a laser signal emitted by the leader and monitors the distance to the follower at the same time using ultrasonic ranging techniques. The follower uses the data obtained from these measuring techniques as inputs to a fuzzy controller algorithm to adjust its distance and alignment with respect to the leader. Other systems employed on road vehicles utilise video-based leader tracking, or a range of lane-following methods such as magnetometer or video-based methods. Typically these methods are disadvantaged by substantial unit and/or infrastructure costs associated with their deployment. The limitations associated with the solutions presented in this thesis arise in curved trajectories at larger longitudinal distance separations between vehicles. The effects of these limitations on road vehicles has yet to be fully quantified, however it is thought that these effects would not disadvantage its use in close formation platooning. The fuzzy control-based distance and tracking control solution features two inputs, which are the distance and alignment of the follower with respect to the leader. The fuzzy controller asserts two outputs, which are left and right wheel velocities to control the speed and trajectory of a differential drive vehicle. Each of the input and output fuzzy membership functions has seven terms based around lambda, Z-type and S-type functions. The fuzzy rule base consists of 49 rules and the fuzzy inference stage is based on the MAX/MIN method. A Centre of Maximum (CoM) def'uzzification method is used to provide the two crisp valued outputs to the vehicle motion control. The methods chosen for the fuzzy control of distance and tracking for autonomous vehicles were selected based on a compromise between their computational complexity and performance characteristics. This compromise was necessary in order to implement the chosen controller structure on pre-existing hardware test beds based on an 8-bit microcontrollers with limited memory and processing resources. Overall the fuzzy control-based solution presented in this thesis effectively solves the distance and tracking control problem. The solution was applied to differential drive hardware test-beds and was tested to verify performance. The solution was thoroughly tested in both the simulation environment and on hardware test-beds. Several issues are identified in this thesis regarding the application of the solution to other platforms and road vehicle use. The solution will be shown to be directly portable to service robotics applications and, with minor modifications, applicable to road vehicle close-formation platooning.

In this research, an autonomous vehicle function management methodology is studied. In accordance with the traffic situation, the decision making level chooses the optimal function that guarantees safety and minimizes fuel consumption while the control level is implemented via neuromorphic strategy based on the brain limbic system. To realize the decision making strategy, the Analytic Hierarchy Process (AHP) is used by considering driving safety, driving speed, and fuel efficiency as the objectives. According to the traffic situation and predefined driving mode, Lane Change Maneuver (LCM) and Adaptive Cruise Control (ACC) are chosen as the alternative functions in the AHP framework. The adaptive AHP is utilized to cope with dynamically changing traffic environment. The proposed adaptive AHP algorithm provides an optimal relative importance matrix that is essential to make decisions under a varying traffic situation and driving modes. The simulation results show that proposed autonomous vehicle function management structure produces optimal decisions that satisfy the driving preference. The stability of BLS based control is also investigated via Cell-to-Cell Mapping. In this research, autonomous vehicle functions such as Lane change maneuver and Adaptive cruise control are developed by means of BLS based control. The simulation results considered various traffic situations that an autonomous vehicle can encounter. To demonstrate the suggested control method Cell-to-Cell Mapping is utilized. Subsequently, the autonomous vehicle function management strategy is developed by Applying AHP and an adaptive AHP strategy is developed to cope with various traffic situations and driving modes. The suggested method is verified numerical simulations.

Driving can provide independent and efficient mobility. However, according to the driving license directive (91/439/EEC) are persons with locomotor impairments are only allowed drive if their disabilities can be compensated. Compensation can be realised by vehicle adaptations. The directive provides meagre guidance on how vehicles should be adapted or how to verify that the compensatory requirements are fulfilled. This is a gap in the current process for licensing drivers with physical disabilities. Furthermore, the Swedish process from driver assessment to driver licensing and adaptation approval is complex, fragmented, and suffer from lack of communication between involved authorities. The objective of this thesis was to contribute to the development of a method to evaluate vehicle adaptations for driver with physical disabilities. The focus was on the evaluation of adaptations for steering, accelerating and braking. Three driving simulator experiments and one manoeuvre test with adapted vehicles were conducted. A group of drivers with tetraplegia driving with hand controls were compared to able-bodied drivers in the first experiment. Even if the drivers with tetraplegia had a longer brake reaction time they performed comparable to the able-bodied drivers. However, they spent more effort and were more tired in order to perform as well as the able-bodied drivers. It was concluded that the adaptation was not sufficient. An Adaptive Cruise Controller (ACC) was tested in the second experiment in order to find out if it could alleviate the load on drivers using hand controls. It was found that the ACC decreased the workload on the drivers. However, ACC systems need to be adjustable and better integrated. The results from the first two experiments were used to provide some guidelines for ACCsystems to be used by drivers with disabilities. The third experiment was preceded by a manoeuvre test with joystick controlled cars. The test revealed some problems, which were attributed to time lags, control interference, and lack of feedback. Four joystick designs were tested with a group of drivers with tetraplegia in the third experiment. It was concluded that time lags should be made similar to what is found in standard cars. Lateral and longitudinal control should be separated. Active feedback can improve vehicle control but should be individually adjusted. The experiments revealed that drivers with the same diagnose can be functionally very diverse. Thus, an adaptation evaluation should be made individually. Furthermore, the evaluation should include a manoeuvre test. Finally, it was concluded that the evaluation approach applied in the experiments was relevant but needs to be further developed.

This thesis considers the cooperation and coordination of multi vehicle systems cohesively in order to keep the formation geometry and provide the string stability. We first present the modeling of aerial and road vehicles representing different motion characteristics suitable for cooperative operations. Then, a set of three dimensional cohesive motion coordination and formation control schemes for teams of autonomous vehicles is proposed. The two main components of these schemes are i) platform free high level online trajectory generation algorithms and ii) individual trajectory tracking controllers. High level algorithms generate the desired trajectories for three dimensional leader-follower structured tight formations, and then distributed controllers provide the individual control of each agent for tracking the desired trajectories. The generic goal of the control scheme is to move the agents while maintaining the formation geometry. We propose a distributed control scheme to solve this problem utilizing the notions of graph rigidity and persistence as well as techniques of virtual target tracking and smooth switching. The distributed control scheme is developed by modeling the agent kinematics as a single-velocity integrator; nevertheless, extension to the cases with simplified kinematic and dynamic models of fixed-wing autonomous aerial vehicles and quadrotors is discussed. The cohesive cooperation in three dimensions is so beneficial for surveillance and reconnaissance activities with optimal geometries, operation security in military activities, more viable with autonomous flying, and future aeronautics aspects, such as fractionated spacecraft and tethered formation flying. We then focus on motion control task modeling for three dimensional agent kinematics and considering parametric uncertainties originated from inertial measurement noise. We design an adaptive controller to perform the three dimensional motion control task, paying attention to the parametric uncertainties, and employing a recently developed immersion and invariance based scheme. Next, the cooperative driving of road vehicles in a platoon and string stability concepts in one-dimensional traffic are discussed. Collaborative driving of commercial vehicles has significant advantages while platooning on highways, including increased road-capacity and reduced traffic congestion in daily traffic. Several companies in the automotive sector have started implementing driver assistance systems and adaptive cruise control (ACC) support, which enables implementation of high level cooperative algorithms with additional softwares and simple electronic modifications. In this context, the cooperative adaptive cruise control approach are discussed for specific urban and highway platooning missions. In addition, we provide details of vehicle parameters, mathematical models of control structures, and experimental tests for the validation of our models. Moreover, the impact of vehicle to vehicle communication in the existence of static road-side units are given. Finally, we propose a set of stability guaranteed controllers for highway platooning missions. Formal problem definition of highway platooning considering constant and velocity dependent spacing strategies, and formal string stability analysis are included. Additionally, we provide the design of novel intervehicle distance based priority coefficient of feed-forward filter for robust platooning. In conclusion, the importance of increasing level of autonomy of single agents and platoon topology is discussed in performing cohesive coordination and collaborative driving missions and in mitigating sensory errors. Simulation and experimental results demonstrate the performance of our cohesive motion and string stable controllers, in addition we discuss application in formation control of autonomous multi-agent systems.

Vehicle simulators are becoming more common in vehicle industries. Company earns lot of money on simulations instead of real tests. Real tests are necessary but not made so extensively as before. In this thesis the building of an vehice simulator will be described and a comparison between three different cruise controls. The three cruise controls are PI-regulator, a regulator who regulates after positions in the terrain and a MPC-regulator. The reason for choosing this three is to see the difference between simple regulation and more complex regulation with respect to fuel consumption, travel time and complexity. The vehicle simulator is made in Matlab/Simulink, Visual Studio and Open Scene Graph. The facilities needed for runnning the simulator is a relative good computer with a grapics card on at least 128 MB RAM plus a steering wheel and pedals for brake and gas to achieve best feeling. A keyboard can be used but it reduces almost all feeling. After several simulations a conclusion was made. The MPC-regulator was the regulator who consumed least fuel and travel time. The regulator who regulates after positions in the terrain was not too far away. It would be interesting to do more research about it. In fact it is only a PI-regulator who makes ``clever'' decisions when a hill with enough slope appears. With enough slope means a downhill where the vehicle can accelerate without the use of fuel and an uphill where the vehicle can not keep its speed with maximum use of fuel. A conclusion was stated that the friction and height profile influenced on settings for the PI-regulator and with some adjustments on this settings, fuel could be saved.

In recent decades, open, online learning environments have become progressively more popular and well-funded. An integral aspect of this open learning movement is the transition of a substantial amount of control of the learning process from designers and instructors to the users engaging with the environment. With heavy investments coming from both the public and private sectors, and an ever-growing market of online learners, it is crucial that we better understand how the provision of user control over the learning process affects the quality of that learning process. The purpose of this study was to investigate the effects of one aspect of open learning environments that has yet to be fully understood: user choice of learning sequence, or non-sequential user choice. Building on previous research with open educational resources (OERs) designed to help drivers learn about adaptive cruise control (ACC), an advanced car safety system, this research compared the learning process of subjects with (N = 42) and without (N = 42) control of the learning sequence. Specifically, this study sought to investigate two core issues: 1) the effect(s), positive or negative, that non-sequential user choice has on the development of mental models of ACC, as measured by a post-test assessment; and 2) the relationship among post-test performance, chosen order of resources, and time spent engaging with individual learning resources. To examine these issues, two primary analyses were completed. To address the effect of non-sequential user choice, subjects’ performance on scenario problems and a declarative knowledge post-test was compared using independent sample t-tests (α = .05). A multiple regression analysis was conducted to investigate the relationship among post-test performance, chosen order of resources, and time spent on each of three learning resources (α = .05). Subjects in the experimental (choice) condition scored significantly worse on the post-test assessment than subjects in the control (non-choice) condition (t[82] = -2.116, p < .05, d = -0.462). The regression analysis found a significant regression equation (F(4,37) = 3.930, p < .05) with an R2 of 0.298 (Adjusted R2 = 0.222). Surprisingly, however, only one of the resource time predictor variables was an individually significant predictor of post-test performance. Possible explanations for these findings are explored based on the available research literature. These explanations include the possibility of choice overload, poor decision-making by subjects, confusion due to a lack of instructional guidance, and the development of choice apathy. However, further research is necessary to determine why non-sequential user choice had a negative effect, as well as to expand research on non-sequential user choice to other contexts and content areas.