Comprehensive evaluation of driver gaze pattern using fuzzy rules for driver training

The over representation of novice drivers in crashes is alarming. Research indicates that one in five drivers’ crashes within their first year of driving. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the drive. This paper presents a system that evaluates the data stream acquired from multiple in-vehicle sensors (acquired from Driver Vehicle Environment-DVE) using fuzzy rules and classifies the driving manoeuvres (i.e. overtake, lane change and turn) as low risk or high risk. The fuzzy rules use parameters such as following distance, frequency of mirror checks, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvre to assess risk. The fuzzy rules to estimate risk are designed after analysing the selected driving manoeuvres performed by driver trainers. This paper focuses mainly on the difference in gaze pattern for experienced and novice drivers during the selected manoeuvres. Using this system, trainers of novice drivers would be able to empirically evaluate and give feedback to the novice drivers regarding their driving behaviour.

An assessment system for evaluation of driving competencies

Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

How consistent are drivers in their driving? A driver training perspective

The value and effectiveness of driver training as a means of improving driver behaviour and road safety continues to fuel research and societal debates. Knowledge about what are the characteristics of safe driving that need to be learnt is extensive. Research has shown that young drivers are over represented in crash statistics. The encouraging fact is that novice drivers have shown improvement in road scanning pattern after training. This paper presents a driver behaviour study conducted on a closed circuit track. A group of experienced and novice drivers performed repeated multiple manoeuvres (i.e. turn, overtake and lane change) under identical conditions Variables related to the driver, vehicle and environment were recorded in a research vehicle equipped with multiple in-vehicle sensors such as GPS accelerometers, vision processing, eye tracker and laser scanner. Each group exhibited consistently a set of driving pattern characterising a particular group. Behaviour such as the indicator usage before lane change, following distance while performing a manoeuvre were among the consistent observed behaviour differentiating novice from experienced drivers. This paper will highlight the results of our study and emphasize the need for effective driver training programs focusing on young and novice drivers.

A behavioral comparison between motorcyclists and a matched group of non-motorcycling car drivers: factors influencing accident risk

Motorcyclists and a matched group of non-motorcycling car drivers were assessed on behavioral measures known to relate to accident involvement. Using a range of laboratory measures, we found that motorcyclists chose faster speeds than the car drivers, overtook more, and pulled into smaller gaps in traffic, though they did not travel any closer to the vehicle in front. The speed and following distance findings were replicated by two further studies involving unobtrusive roadside observation. We suggest that the increased risk-taking behavior of motorcyclists was only likely to account for a small proportion of the difference in accident risk between motorcyclists and car drivers. A second group of motorcyclists was asked to complete the simulator tests as if driving a car. They did not differ from the non-motorcycling car drivers on the risk-taking measures but were better at hazard perception. There were also no differences for sensation seeking, mild social deviance, and attitudes to riding/driving, indicating that the risk-taking tendencies of motorcyclists did not transfer beyond motorcycling, while their hazard perception skill did. (C) 2002 Elsevier Science Ltd. All rights reserved.

Insights on the HLA-G Evolutionary History Provided by a Nearby Alu Insertion

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Evaluation of the Intelligent Cruise Control System. Volume I: study results.

National Highway Traffic Safety Administration, Washington, D.C.

Driving performance after an extended period of travel in an automated highway system.

Federal Highway Administration, Office of Safety and Traffic Operations, Washington, D.C.

Marijuana, alcohol and actual driving performance.

National Highway Traffic Safety Administration, Washington, D.C.

Visibility and spacing of lane control signals for freeway traffic management.

Texas Department of Transportation, Austin

Fundamental studies in automatic vehicle control. Interim report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Fundamental studies in automatic vehicle control. Final report.

Federal Highway Administration, Office of Research, Washington, D.C.

Assessment of IVHS countermeasures for collision avoidance: rear-end crashes.

Mode of access: Internet.

Autonomic, biometric and oculomotor correlates of myopia in young adults

The principal work reported in this thesis is the examination of autonomic profile of ciliary muscle innervation as a risk factor in myopia development. Deficiency in sympathetic inhibitory control of accommodation has been proposed as a contributory factor in the development of late onset myopia (LOM). Complementary measurements of ocular biometry, oculomotor function and dynamic accommodation response were carried out on the same subject cohort, thus allowing cross-correlation of these factors with. autonomic profile. Subjects were undergraduate and postgraduate students of Aston University. A 2.5 year longitudinal study of refractive error progression in 40 subjects revealed the onset of LOM in 10, initially emmetropic, young adult subjects (age range 18-24 years) undertaking substantial amounts of near work. A controlled, double blind experimental protocol was conducted concurrently to measure post-task open-loop accommodative regression following distance (0 D) or near (3 D above baseline tonic accommodation) closed-loop tasks of short (10 second) or long (3 minute) duration. Closed-loop tasks consisted of observation of a high contrast Maltese cross target; open-loop conditions were imposed by observation of a 0.2 c/deg Difference of Gaussian target. Accommodation responses were recorded continuously at 42 Hz using a modified Shin-Nippon SRW-5000 open-view infra-red optometer. Blockade of the sympathetic branch of accommodative control was achieved by topical instillation of the non-selective b-adrenoceptor antagonist timolol maleate. Betaxolol hydrochloride (non-selective b1-adrenoceptor antagonist) and normal saline were employed as control agents. Retarded open-loop accommodative regression under b2 blockade following the 3 minute near task indicated the presence of sympathetic facility. Sympathetic inhibitory facility in accommodation control was found in similar proportions between LOM and stable emmetropic subjects. A cross-sectional study (N=60) of autonomic profile showed that sympathetic innervation of ciliary muscle is present in similar proportions between emmetropes, early-, and late-onset myopes. Sympathetic facility was identified in 27% of emmetropes, 21% of EOMs and 29% of LOMs.

Axial elongation following prolonged near work in myopes and emmetropes

Background/aims: To investigate the influence of a period of sustained near work upon axial length in groups of emmetropes and myopes. Methods: Forty young adult subjects (20 myopes and 20 emmetropes) were recruited for the study. Myopes were further classified as either early onset (EOM), late onset (LOM), stable (SM) or progressing (PM) subgroups. Axial length was measured with the IOLMaster instrument before, immediately after and then again 10 minutes after a continuous 30 minute near task of 5 D accommodation demand. Measures of distance objective refraction were also collected. Results: Significant changes in axial length were observed immediately following the near task. EOM axial length elongated on average by 0.027 ± 0.021 mm, LOM by 0.014 ± 0.020 mm, EMM by 0.010 ± 0.015 mm, PM by 0.031 ± 0.022 mm, and SM by 0.014 ± 0.018 mm. At the conclusion of the 10 minute regression period, axial length measures were not significantly different from baseline values. Conclusion: Axial elongation was observed following a prolonged near task. Both EOM and PM groups showed increases in axial length that were significantly greater than emmetropes

Aerial object following using visual fuzzy servoing

This article presents a visual servoing system to follow a 3D moving object by a Micro Unmanned Aerial Vehicle (MUAV). The presented control strategy is based only on the visual information given by an adaptive tracking method based on the colour information. A visual fuzzy system has been developed for servoing the camera situated on a rotary wing MAUV, that also considers its own dynamics. This system is focused on continuously following of an aerial moving target object, maintaining it with a fixed safe distance and centred on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigation