A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Understanding the Social Gifts of Drinking Rituals: An Alternative Framework for PSA Developers

Binge drinking behavior has been described as the most significant health hazard on college campuses today. Using definitions of ritual behavior drawn from the literature, the authors conducted focus groups, depth interviews, and participant observations to explore the ritualized nature of alcohol beverage consumption among college students at two large universities. The themes that emerged provide an understanding of the rituals associated with college student drinking. With the drinking-as-ritual interpretation as a theoretical framework, the authors discuss how developers of public service announcements (PSAs) could capture and contextualize drinking rituals and thus make PSAs more relevant to the target audience. They provide examples of PSAs that could be tested

Discretionary Behavior and Racial Bias in Issuing Traffic Tickets: Theory and Evidence

Recently, police departments, legislators, media, and the public at large in the U.S. have increasingly been concerned about racial disparities in officers' issuing traffic tickets. Ascertaining the extent to which an observed disparity reflects racial bias is the crucial issue. First, we use a theoretical model which borrows features from the recent literature regarding racial bias in vehicle searches. In our model, motorists, picking the speed to travel at, take into account the probability of getting ticketed and the speed that the officer will cite, while officers maximize a benefit function generically increasing in the speed of ticketed drivers; this benefit function, however, is general enough to allow officers to give certain drivers a break by citing them at a lower speed than they were traveling. Empirically, we exploit the existence of a massive accumulation of speeding tickets at 10 m.p.h. over the speed limit to elicit officers' discretionary behavior and leniency. Surprisingly,about 30% of all ticketed drivers were cited for driving exactly at this particular speed. Using our novel measure of officers' leniency, we find that especially white and male officers are heavily engaged in discretionary behavior. We also find officers' discretion is racially biased; minority officers are less lenient to minority drivers. This is interesting in comparison with Antonovics and Knight (forthcoming) who, using the same data set, found evidence on own-race preferences in vehicle searches.Discretionary behavior, strict behavior, leniency, racial bias, drivers' speeding decision, officers' ticketing and citation decision.

Final Report of the Kentucky State Module: Adult Basic Education Recruitment Research Program

The final report of the Kentucky State Module on the Adult Basic Education Recruitment Research Program submitted by Elwood Cornett in June of 1971

An Evaluation of the Utilization of Psychological Knowledge Concerning Potential Roadside Distractors

See this work in the Center for Transportation Research Library catalog: https://library.ctr.utexas.edu/Presto/catalogid=5775This report presents the findings of a project designed: (1) to evaluate the effect of nighttime distractors on accidents at signalized intersections, and (2) to facilitate the implementation at the local level of traffic safety standards. The findings of Part I, based on a study of nighttime accidents occurring at 30 metropolitan intersections, offer tentative data that both the color and the proximity of lights may be important in determining their distractibility with respect to the traffic signal. Part II describes the procedures followed by the project team to disseminate psychological knowledge concerning environmental distractors in the traffic environment to appropriate local agencies and includes an evaluation of the utilization of this information by these agencies.Texas Office of Traffic SafetyCenter for Transportation ResearchSee this work in the Center for Transportation Research Library catalog

Driver Response to Simulated Intersections: An Analysis of Workload-Related Variables

A roadway intersection driving simulation was created to investigate driver information processing at intersections. Research participants were provided a visual simulation of approaching intersections using a video display with a 120 degree visual field. Six groups, each containing 12 subjects, were formed according to age and gender, with age ranging from 18 to 74 years. All participants viewed 14 separate intersections, which varied according to types of traffic control signs and signals. Individual workload was assessed in three categories of response: performance, subjective, and physiological. A MANOVA was performed on six dependent variables in the 3 (age) by 2 (gender) design. Results indicate significant main effects for both age and gender. The three significant dependent variables were pedal response errors, speed of response, and heart rate reactivity to each intersection. The responses suggest greater workloads for older drivers and female drivers. In addition to age and gender, a number of driver information processing characteristics were measured. Stepwise regressions indicated that performance decrements to the simulated driving situations could best be predicted by subjects\u27 scores for field dependency, visual acuity, and depth perception. However, age alone, accounted for more variance in performance than any single information processing variable

What kind of information do drivers need? An investigation of drivers' information requirements in Kuala Lumpur, Malaysia

Past research indicated that driver information requirements were varied (e. g. Spyridakis et al., 1991) and the motorists population cannot be consider homogeneous in terms of information requirements (e. g. Haselkorn et al., 1991). Some of the previous studies even suggestedth at before the so-called intelligent systemsg o into production, several unresolved issues concerning what kind of information drivers require need to be resolved. Thus, this thesis is interested in exploring several human factors issues concerning drivers; ' information requirements. First, the study is trying to provide at least a general picture of what kind of information is suitable to be presented to drivers in certain types of journey. Secondly, the thesis is interested in exploring the suitable timing and mode to present the required information to the target audiences. Besides the aforementioned human factors issues, this research also investigated how drivers plan their routes and find their way in unfamiliar destinations. The study is also interested in examining criteria used by drivers in choosing a route to their intended destination. Finally, this thesis aims to measure respondents' behavioral responses when they were given several traffic messages on congestion while commuting to and from work. The results also revealed that local drivers used more than one strategy for route planning and wayfinding in unfamiliar locations. Maps were the main strategy used by most of the respondents who participated in this study. Other strategies used by respondents were asking a passer-by, relying on memory and going without preparation. Apart from that, this study also demonstrated the difficulty in arriving at a general conclusion concerning the appropriate criteria that drivers would use in selecting a route for different trips. Local drivers would use a variety types of criteria in order to choose a route to a particular destination. However, the thesis identifies that drivers mainly employed three types of criteria in selecting a route to a particular destination. These criteria were safety, saving mileage and avoiding congested routes The final study (Study 3) was interested in extending the results of both studies I and 2 particularly the presentationo f congestionm essagesto its end users,i . e. motorists. An experiment was conducted to investigate drivers' response towards the presentation of traffic messagesa bout congestion.T he findings clearly supportedp revious work that found different types of information are likely to elicit different kind of responses from the drivers. In addition, local drivers also had ideas about the design of future traffic messages on congestion. For example, the need to have a quick solution when faced with the problem, e. g. offer alternate route; the need to have information on travel time if they decided to use the alternate route recommended by the systems; and some of the messages should be given as early as possible to serve as pre-trip advanced warning to drivers. The findings clearly demonstrated the preference for having more information rather than less

A multidisciplinary research approach for experimental applications in road-driver interaction analysis

This doctoral dissertation represents a cluster of the research activities conducted at the DICAM Department of the University of Bologna during a three years Ph.D. course. In relation to the broader research topic of “road safety”, the presented research focuses on the investigation of the interaction between the road and the drivers according to human factor principles and supported by the following strategies: 1) The multidisciplinary structure of the research team covering the following academic disciplines: Civil Engineering, Psychology, Neuroscience and Computer Science Engineering. 2) The development of several experimental real driving tests aimed to provide investigators with knowledge and insights on the relation between the driver and the surrounding road environment by focusing on the behaviour of drivers. 3) The use of innovative technologies for the experimental studies, capable to collect data of the vehicle and on the user: a GPS data recorder, for recording the kinematic parameters of the vehicle; an eye tracking device, for monitoring the drivers’ visual behaviour; a neural helmet, for the detection of drivers’ cerebral activity (electroencephalography, EEG). 4) The use of mathematical-computational methodologies (deep learning) for data analyses from experimental studies. The outcomes of this work consist of new knowledge on the casualties between drivers’ behaviour and road environment to be considered for infrastructure design. In particular, the ground-breaking results are represented by: - the reliability and effectiveness of the methodology based on human EEG signals to objectively measure driver’s mental workload with respect to different road factors; - the successful approach for extracting latent features from multidimensional driving behaviour data using a deep learning technique, obtaining driving colour maps which represent an immediate visualization with potential impacts on road safety

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