Quantification of human operator skill in a driving simulator for applications in human adaptive mechatronics

Nowadays, the Human Machine System (HMS) is considered to be a proven technology, and now plays an important role in various human activities. However, this system requires that only a human has an in-depth understanding of the machine operation, and is thus a one-way relationship. Therefore, researchers have recently developed Human Adaptive Mechatronics (HAM) to overcome this problem and balance the roles of the human and machine in any HMS. HAM is different compared to ordinary HMS in terms of its ability to adapt to changes in its surroundings and the changing skill level of humans. Nonetheless, the main problem with HAM is in quantifying the human skill level in machine manipulation as part of human recognition. Therefore, this thesis deals with a proposed formula to quantify and classify the skill of the human operator in driving a car as an example application between humans and machines. The formula is evaluated using the logical conditions and the definition of skill in HAM in terms of time and error. The skill indices are classified into five levels: Very Highly Skilled, Highly Skilled, Medium Skilled, Low Skilled and Very Low Skilled. Driving was selected because it is considered to be a complex mechanical task that involves skill, a human and a machine. However, as the safety of the human subjects when performing the required tasks in various situations must be considered, a driving simulator was used. The simulator was designed using Microsoft Visual Studio, controlled using a USB steering wheel and pedals, as was able to record the human ii path and include the desired effects on the road. Thus, two experiments involving the driving simulator were performed; 20 human subjects with a varying numbers of years experience in driving and gaming were used in the experiments. In the first experiment, the subjects were asked to drive in Expected and Guided Conditions (EGC). Five guided tracks were used to show the variety of driving skill: straight, circular, elliptical, square and triangular. The results of this experiment indicate that the tracking error is inversely proportional to the elapsed time. In second experiment, the subjects experienced Sudden Transitory Conditions (STC). Two types of unexpected situations in driving were used: tyre puncture and slippery surface. This experiment demonstrated that the tracking error is not directly proportional to the elapsed time. Both experiments also included the correlation between experience and skill. For the first time, a new skill index formula is proposed based on the logical conditions and the definition of skill in HAM

Initial study toward a methodical approach for the engineering of driver assistance technology

Bayerische Motoren Werke, Palo Alto, Calif.http://deepblue.lib.umich.edu/bitstream/2027.42/1283/2/92176.0001.001.pd

Conceptualising automated driving shared control hazard causes

The motivation for this research was the realisation that the introduction of greater vehicle automation would not only change the task of driving but would also potentially change how vehicles are developed and safety is assured. Undertaking a practice-based workshop identified many Automated Driving (AD) safety assurance challenges having different levels of human-machine control. These challenges include an increase in the size and complexity of AD safety analyses, a need to re-examine the notion of controllability in the context of shared control, and the need to conceptualise the vehicle as a system of systems. To begin addressing these challenges and to answer the research question “how can the safety of AD be assured under different levels of shared control?” this research has created three products: a vehicle model and behavioural competency taxonomy that allows AD shared control to be conceptualised, a concrete hazard analysis method for analysing AD shared control hazard causes, and a safety case argument pattern for that. A series of case studies evaluate the research products described above. These cases have used contemporary AD vehicle features, having varying levels of automation. The evaluation of driver assistance, partial and conditional automation cases have been completed by the author. Complementing these is the analysis of a highly automated vehicle system, which has been undertaken with the engineering team from Oxbotica. Considered together these case studies establish the research products as a proof-of-concept hazard analysis method for AD shared control. Further evaluation work is needed to test the viability of the method as an engineering tool for use by automotive practitioners working in a product development environment

Classification and reduction of pilot error

Human error is a primary or contributing factor in about two-thirds of commercial aviation accidents worldwide. With the ultimate goal of reducing pilot error accidents, this contract effort is aimed at understanding the factors underlying error events and reducing the probability of certain types of errors by modifying underlying factors such as flight deck design and procedures. A review of the literature relevant to error classification was conducted. Classification includes categorizing types of errors, the information processing mechanisms and factors underlying them, and identifying factor-mechanism-error relationships. The classification scheme developed by Jens Rasmussen was adopted because it provided a comprehensive yet basic error classification shell or structure that could easily accommodate addition of details on domain-specific factors. For these purposes, factors specific to the aviation environment were incorporated. Hypotheses concerning the relationship of a small number of underlying factors, information processing mechanisms, and error types types identified in the classification scheme were formulated. ASRS data were reviewed and a simulation experiment was performed to evaluate and quantify the hypotheses

Modeling and Empirical Analysis of Tailgating Behavior of Drivers

This dissertation presents a microscopic study of tailgating behavior of drivers. There are very few studies focused on tailgating, although it is a serious issue for traffic safety. The reason for very few studies might be the fact that tailgating is a complex problem involving human behavior and kinematics of the vehicle and it is also equally challenging to collect naturalistic driving data relevant to tailgating. Because this approach is empirical, we developed a sophisticated data acquisition system using an instrumented vehicle to collect naturalistic driving data. Data were collected on freeways in Maryland during times of moderate traffic flow. The instrumented vehicle was driven in a naturalistic way that was benign to the surrounding traffic. Tailgating events were detected using the empirical data and a model of safe following distance. We tested and affirmed the hypothesis that tailgaters of short tailgating duration are more willing to follow at close following distances than those who tailgated for longer durations. We also tested and affirmed the hypothesis that following vehicle speeds are strongly influenced by lead vehicle speeds. We studied the causal relations between certain observable data from the lead vehicle and possible reactions in the following vehicle. We contributed new estimates of driver reaction times, focusing on a subset of the population deemed to be tailgating at the time. We also conducted a new calibration of the well-known GHR car-following model that is specific to tailgating situations. The data and method for collecting the data are contemporary and relevant to current modes of thinking in traffic flow theory. The results can contribute directly to models and parameter estimates in microscopic simulators. Many of the results would also be of use in the automotive industry, for the development of driver safety assistance systems and countermeasures. Finally, we think the results could be useful for driving instructors, to help students understand better this dangerous driving behavior. In the end, we hope that this study could help to improve traffic safety by reducing the number of crashes resulting from this behavior

Development of a workload estimator: The influence of surrounding traffic behaviour on driver workload and performance

The consumers’ increasing desire to be connected at all times and the advancement of integrated functionality within the vehicle, increases the risk that drivers could be faced with information overload while driving. Given the importance of human interaction with technology within the vehicle, automobile manufacturers are introducing workload manager systems within the vehicles to help prevent driver overload. However the ability of the system to decide in a timely manner requires anticipation of changes in workload, depending on the capacity of the driver and matching it with the demand expected from the driving task such as the dynamic traffic environment. In relation to the need to understand the influence of traffic demand on driver workload, the work here comprises the systematic manipulation of traffic complexity and exploration of workload measures to highlight which are sensitive to primary task demand manipulated. A within-subjects design was used in the studies explored in this thesis to allow comparison between different manipulated traffic conditions. In the first simulator test, the ability of various objective and subjective workload measures to tap into drivers’ momentary workload was examined. Following the identification of a subjective measure that was sensitive to the influence of lane changes performed by neighbouring vehicle on drivers’ momentary workload, the characteristics of the lane change were explored in the subsequent studies involving single and dual-task conditions. Overall, these studies suggested suppression of non-urgent communications by a workload manager during safety-critical conditions involving critical cut-ins would be advantageous to both younger and older drivers. This thesis offers a novel and valuable contribution to the design of a workload estimator so as to ensure that the driving demand is always within drivers’ capacity to avoid driver overload. Results of these studies have also highlighted the utility of vehicle-based sensor data in improving workload manager functionality

A systematic approach to cooperative driving systems based on optimal control allocation

This dissertation proposes a systematic approach to vehicle dynamic control, where interaction between the human driver and on-board automated driving systems is considered a fundamental part of the overall control design. The hierarchical control system is to address motion control in three regions. First is normal driving, where the vehicle stays within the linear region of the tyre. Second is limit driving, where the vehicle stays within the nonlinear region of the tyre. Third is over-limit driving, where the driver demands go beyond the tyre force limits. The third case is addressed by a proposed control moderator (CM). The aim is to consider all three cases within a consistent hierarchical chassis control framework. The upper-level of the hierarchical control structure relates to both optimal vehicle control under normal and limit driving, and saturating driver demands for over-limit driving, these corresponding to a fully autonomous controller and driver assistance controller respectively. Model Predictive Control (MPC) is used as the core control technique for path following under normal driving conditions, and a Moderated Particle Reference (MPR) control strategy is proposed for the road departure mitigation during limit and over-limit driving. The MPR model is validated to ensure predictable and stable operation near the friction limits, maintaining controllability for curvature and speed tracking, which effectively limits demands on the vehicle while preserving the control interaction of the driver. In the next level of the hierarchical control structure, a novel control allocation (CA) approach based on pseudo-inverse method is proposed, while a general linearly constrained quadratic programming (CQP) approach is considered as a benchmark. From extended simulation experiments, it is found that the proposed Pseudo-Inverse CA (PICA) method can achieve a close match to CQP performance in normal driving conditions. This applies for multiple control targets (including path tracking, energy-efficient, etc.) and PICA is found to achieve improved performance in limit and over-limit driving, again addressing multiple control targets (including road departure mitigation, energyefficient, etc.). Furthermore, the PICA method shows its inherent advantages of achieving the same control performance with much less computational cost and is guaranteed to provide a feasible control target for the actuators to track during the highly dynamic driving scenarios. In addition, it can effectively solve the constrained optimal control problem with additional mechanical and electronic actuator constraints. Thus, the proposed PICA method, which uses Control Re-Allocation (making multiple calls to the pseudo-inverse operator) can be considered a feasible and novel alternative approach to control allocation, with advantages over the standard CQP method. Finally, in the lower-level of the hierarchical control structure, the desired tyre control variables are obtained through an analytical inverse tyre model and a sliding mode controller (SMC) is employed for the actuators to track the control target. The proposed hierarchical control system is validated with both driving simulator studies and from testing a real vehicle, considering a wide range of driving scenarios, from low-speed path tracking to safety-critical vehicle dynamic control. It therefore opens up a systematic approach to extended vehicle control applications, from fully autonomous driving to driver assistance systems and control objects from passenger cars to vehicles with higher centre of gravity (CoG) like SUVs, trucks and etc. . .

Psychological Analysis of Degree of Safety in Traffic Environment Design

See this work in the Center for Transportation Research Library catalog: https://library.ctr.utexas.edu/Presto/catalogid=5773Recent on-site accident investigation studies have estimated that between 10 and 25 percent of automobile accidents involve distraction as a principal causative factor. This report presents the findings of a research project designed to study the relationship between visual dis tractors in the roadside environment, such as advertising signs, neon lights, and gaudy billboards, and traffic safety. This project has involved the definition, operationalization, and measurement of visual distractibility in the traffic environment, including an analysis of distractions attributable to private signs and lights in the Vicinity of public signs and signals and of distractions caused by an overload or improper placement of public signs.Texas Office of Traffic SafetyCenter for Transportation ResearchSee this work in the Center for Transportation Research Library catalog

In-Vehicle information systems-related multiple task performance and driver

Doutoramento em Motricidade Humana, Especialidade em ErgonomiaThe presence of new technologies inside vehicles is becoming more common. Due to this fact, the potential changes produced on the driving task and also on the road safety must be examined. With the intention of contributing to amplify this knowledge, the present research aimed to study the impact of multiple visual and auditory inputs from in-vehicle information systems on the driver behaviour. It was investigated the interaction with more than one invehicle system (a guidance system and a mobile phone device) and verified its consequences on the drivers’ activity. To accomplish this goal two experimental moments were planned: one conducted in a real context and another in a simulated environment. Results revealed that the interaction with two in-vehicle systems produced considerable changes on drivers’behaviour once subjects assumed more frequently unsafe actions like: inadequate indication of their actions; abrupt and unexpected adoption of determined behaviours; and also negligence of some road information from the environment. It was also verified that this situation produced more severe consequences to the driving task performance of elderly drivers. The management of all sources of information induced them to compromise their safety and be more frequently involved in dangerous situations.O surgimento das novas tecnologias embarcadas e a sua contínua evolução têm alterado o contexto rodoviário. Como consequência, a cada vez maior aceitação e utilização deste tipo de equipamentos tem sido motivo de estudo, uma vez que é essencial conhecer as potenciais alterações produzidas na tarefa de condução e na segurança rodoviária. Com o intuito de contribuir para ampliar o conhecimento relativo a este tema, a presente investigação pretendeu estudar o impacto que múltiplas mensagens visuais e auditivas provenientes de sistemas embarcados possam ter no comportamento do condutor. Foi investigada a interacção com mais que um sistema embarcado (sistema de navegação e telemóvel) e verificadas as consequências na actividade dos condutores. Para cumprir este objectivo, dois momentos experimentais foram desenvolvidos: um em ambiente real e outro em envolvimento simulado. Os resultados revelaram que a interacção com os dois sistemas embarcados produziram alterações consideráveis no comportamento dos condutores uma vez que estes adoptaram mais frequentemente actos inseguros como: indicação inadequada das suas acções; comportamentos bruscos e inesperados; bem como negligência de determinada informação proveniente do envolvimento rodoviário. Foi igualmente verificado que esta situação produziu consequências mais gravosas no desempenho dos condutores idosos. A gestão de todas as fontes de informação impeliu este grupo de condutores a comprometer a sua segurança e a estar mais frequentemente envolvidos em situações perigosas

Maine’s Winter Roads: Salt, Safety, Environment and Cost

This report summarizes key findings from a yearlong study of the issues and practices in winter maintenance of Maine’s roads