A faulty sensor may lead to degraded system performance, unstable system, or even a fatal accident. On the other hand, the increasing need for safety and reliability has motivated the development of fault-tolerant control (FTC) techniques. This paper proposes a robust fault-tolerant gain-scheduled noisy output-feedback controller (GSNOF) that guarantees system stability and performance in the presence of sensor aging under control input constraints, where the sensor performance degradation due to aging is modeled by its measurement noisy covariance. The closed-loop system stability and performance, in terms of numerical complexity, computation time, and ℋ 2 performance, are studied. The proposed controller is compared in simulations with the published results, which shows that the proposed controller is capable of guaranteeing the stability, performance with reduced numerical complexity and computation load under gradual sensor performance degradation, and it is feasible for real-time control.

This paper presents a socially acceptable collision avoidance system for an automated vehicle based on the elastic band method. Both stationary and moving Vulnerable Road Users (VRUs: pedestrians or bicyclists) are considered in the proposed system. A collision free path is first determined and then Model Predictive Control (MPC) based vehicle front wheel steering is applied to track this collision free path. For the purposes of benchmarking and comparison, the results of a conventional PID steering controller are also presented. The designed system is tested with simulations on a path chosen from the west campus of the Ohio State University, whose waypoints are extracted automatically from OpenStreetMap (OSM). Simulation results show that the MPC based steering control system successfully achieves the required collision avoidance and path following and has comparable or better performance when compared with the conventional PID solution.

Functional safety of hybrid electric and electric vehicles has attracted a great deal of attention among automobile industries worldwide. Torque security is one of the main hazards that should be considered for functional safety of electrified vehicles. Over the past decades, a significant number of accidents have been reported to be caused by unintended acceleration that results from torque security problems. This paper investigates the factors related to torque security problems in electric vehicles using the Failure Modes and Effect Analysis (FMEA) approach. The fault scenarios that can potentially result in loss of torque security in electrified vehicles are evaluated in a simulation study.

Dynamics of a pickup truck undergoing a rear tire blowout are analyzed as a system controlled by a human driver. Analysis is based on a large nonlinear vehicle dynamics model combined with a human driver model. The main reason why some tire blowouts result in accidents is identified. Insight is generated in experiments with human drivers in a driving simulator that runs the same vehicle model as the one used for analysis. A driver assist system for controlling tire blowouts is developed and validated in real time in the driving simulator.

Overhead cranes are widely used in industries all over the world. It is not easy to move crane payloads without oscillation, increasing the likelihood of obstacle collisions and other accidents. Even experienced crane operators make mistakes that cause loss of money and time. Some reasons for these incidents are limitations of the operator’s field of view, depth perception, knowledge of the workspace, and the dynamic environment of the workspace. One possible solution to these problems could be aiding the operator with a dynamic map of the workspace that shows the current position of obstacles. The probable areas of finding obstacles based on the previous positions of obstacles could also be shown. This paper describes a simple method of generating such a map of the crane workspace using machine vision.

Best practices in product design require engineers to perform preliminary hazard analyses on the most promising conceptual designs, as well as a more rigorous hazard analysis when the details of the product are being finalized. When the product is a complex dynamic system that interacts directly with a human, the engineers must consider the wide range of possible motions and forces that the device could create. Such an analysis goes beyond a simple thought exercise and requires detailed knowledge about the system dynamics and operating environment. This paper presents such an analysis of an inverted-pendulum human transporter. The list of hazards is constructed by using fundamental knowledge of the dynamics and the mechanical design obtained through simulation and experimentation. However, the dynamics are so complex that the list is augmented with hazards that are revealed by searching through accident videos posted on the Internet. The severity of each hazard is estimated using an energy-based measurement of the hazard onset conditions. While this case study is interesting, it also provides a systematic approach to hazard analysis that can be applied to other complex and dangerous dynamic systems.

This paper presents a multi-objective safety system that is capable of avoiding unintended collisions with stationary and moving road obstacles, vehicle control loss as well as unintended roadway departures. The safety system intervenes only when there is an imminent safety risk while full control is left to the driver otherwise. The problems of assessing wether an intervention is required as well as controlling the vehicle motion in case an intervention is needed are jointly formulated as a single optimization problem, that is repeatedly solved in receding horizon. The novelty of the formulation lies in the ability of simultaneously avoiding moving obstacles while assessing the necessity thereof. The versatility of the proposed formulation is demonstrated through simulations showing its ability of avoiding a wide range of accident scenarios.

Racecar drivers are skilled at tracking a path, avoiding accidents, and controlling their vehicles at the limits of handling. Better understanding of how a skilled driver selects and drives a racing line, could potentially lead to a new technique for obstacle avoidance. To investigate this, the characteristics of a racecar driver’s line must be captured mathematically. This paper describes an algorithm for fitting a path to the GPS data of a driver’s racing line. A family of path primitives composed of straights, clothoids, and constant radius arcs are used to describe the racing line. The fitted paths provide a method for analyzing racing lines and the different techniques used by skilled drivers to navigate the track.

Loss of control accidents result in thousands of fatalities in the United States each year. Production stability control systems are highly effective in preventing these accidents, despite their reliance on a hand-tuned response to data from a small set of sensors. However, improvements in sensing offer opportunities to determine stabilizing actions in a more systematic manner. This paper presents an approach that utilizes the yaw-sideslip phase plane to choose boundaries that eliminate unstable and undesirable driving regimes. These boundaries may be varied to obtain desirable performance and driver acceptance and form the basis for a driver assistance system that augments the driver input to maintain the vehicle within the bounds of a safe handling envelope. Experimental results from a model predictive controller used to enforce the envelope boundaries on a steer-by-wire vehicle are presented to demonstrate the viability of this framework for implementing stability boundaries.

The potential for UAVs to benefit the civilian consumer is driving the demand for the integration of these vehicles into the national airspace. With UAV accidents occurring at a significantly higher rate than commercial airlines, the urgent issue becomes designing systems and protocols that can prevent UAV accidents, better train UAV operators and augment pilot performance. This paper presents three directions of research stemming from the goal of a UAV piloting and training system. Research direction one is the development of a research platform to assess UAV pilot skills and recreate the sensation of shared fate for UAV pilots. The second research direction looks at utilizing flight simulation packages to create virtual tools for training UAV pilots. The third direction covers the investigation of UAV’s in near earth environments as future applications will place UAVs in these areas.