Driving Behaviour Modelling and Analysis

In VANET clustering, the cluster construction is dependent on the stable node list that combines the node within the coverage zone of the subject node. Higher size of stable nodes implies bigger clusters and more stable ones. On the other side, lower size of stable nodes implies small and sparse clustering performance. The size of the stable node list is related to various parameters within the traffic model. In the literature, few of the research work have concentrated on the relation between the traffic model parameters and the size of stable node list of a subject node. In this article, we aim at exploring the interrelation between various parameters and variables in the traffic model of VANET network in the highway and its impact on the coverage node list and stable node list. Furthermore, we aim at characterizing this relation to predict the cluster size and lifetime based on the provided parameters.

Driving style analysis and road anomaly detection have a remarkable impact on road safety. They directly influence road accidents and have been a vital area of research in order to address road safety problems. In this paper, a system called D&RSense have been proposed that uses GPS and accelerometer of smartphones to categorize driving style of drivers, assess the road quality as well as to give real-time warnings to drivers in order to make driving safer. D&RSense does the categorization through detection of driving events like acceleration and braking and road anomalies like bumps and potholes by using the popular machine learning technique, Support Vector Machine (SVM) and gives real-time warning and instructions to drivers using a locally running Fast Dynamic Time Warping (FastDTW) algorithm. Extensive experiments have been conducted to evaluate the effectiveness of the proposed system.

Learning to drive can be a daunting experience.  Getting a licence is a rite of passage,  freedom, and coming of age, glorified for decades in cinema movies .

However, the reality of learning to drive can be difficult – the price of obtaining a driving licence can be a burden for many with driving lessons being a significant cost factor. With EDT being compulsory from April 2011, learner drivers must take 12 one-hour compulsory driving lessons with an ADI.

However, it’s not only the cost that causes concern for learners – issues such as the length of time the learning to drive process takes, can be arduous for many learners (minimum of 6 months). Safety issues pose a critical consideration for our learner drivers - 158 people lost their lives on Irish roads in 2017 . On average 13 learner drivers lose their lives on Irish roads annually (RSA) .

Learner drivers obtain a learner’s permit to allow them practice driving while supervised, however, there is a protracted history of generally unregulated driving with relatively low enforcement rates for unaccompanied learner drivers in Ireland (CAS 2009).

The most significant challenge facing this dissertation was consideration of how to interpret, reflect and translate findings into recommendations. As all recommendations require change to existing systems/processes, it is reasonable to consider findings in light of their implications for change management. The recommendations are as much to do with modifying driving culture as with fundamental process change. Unless culture changes alongside process change, it is unlikely that the recommendations cited can be successfully implemented.

Driving provides a terrific sense of freedom, but it’s also potentially the most dangerous action we do daily. Learning to drive isn’t just about passing a test – it’s about learning skills from experience and continually improving and advancing the quality of those skills.

With research revealing low road safety campaign efficacy and links between reckless driving behaviors and crash frequency, further investigation into the foundations and composition of driver education and training is required. Through two studies, the current research aimed to develop a measure that utilized the principles of Kelly’s (1955) personal construct theory to a) elicit constructs, or construals, specific to selected elements of reckless driving behaviors, b) pilot a method in which the elicited constructs could be measured by asking participants to choose those they deemed most important, c) group participants based on their constructs, and d) assess between-group differences in self-reported reckless driving behavior. Results suggest that drivers can be categorized based on the constructs they use, and that rates of self-reported past engagement in reckless driving behavior, and willingness to do so in the future, vary systematically between these construal-based driver categories. Continuing research is required to develop and test applications of these findings.

Two-hundred young and old, experienced and inexperienced tricycle drivers of Antipolo City were surveyed to indentify each groups driving behavior and find out what common driving behavior they possess. The groups were divided amongst their years of driving experience and their age (1 to 5 years Inexperienced, 6 and above Experienced, 18 to 35 Young, 36 and above Old). With the use of the taxonomy of driving behavior by Leon James, the researchers formulated a 36-item situational based questionnaire and translated it to the local language of the Philippines. After conducting the survey, the researchers found the significances of each result then related it to the Driving Psychology of James and Nahl. Using the taxonomy of driving behavior, the researchers have specifically focused on the levels of driver competence to relate the results of the study to the related literatures. The results from Keskinen et al. (1998) supported the theories for old and young drivers respectively. Researchers then found out that neither age nor experience affects driving behavior of each tricycle driver. Implications of the study can contribute to the further development of driving psychology and its taxonomy. The researchers highly recommend seminars to help improve the driving behavior of the tricycle drivers.

Drivers' hazardous physical and mental states (e.g., distraction, fatigue, stress, and high workload) have a major effect on driving performance and strongly contribute to 25-50% of all traffic accidents. They are caused by numerous factors, such as cell phone use or lack of sleep. However, while significant research has been done on detecting hazardous states, most studies have not tried to identify the causes of the hazardous states. Such information would be very useful, as it would allow intelligent vehicles to better respond to a detected hazardous state. Thus, this study examined whether the cause of a driver's hazardous state can be automatically identified using a combination of driver characteristics, vehicle kinematics, and physiological measures. Twenty-one healthy participants took part in four 45-min sessions of simulated driving, of which they were mildly sleep-deprived for two sessions. Within each session, there were eight different scenarios with different weather (sunny or snowy), traffic density and cell phone usage (with or without cell phone). During each scenario, four physiological (respiration, electrocardiogram, skin conductance, and body temperature) and eight vehicle kinematics measures were monitored. Additionally, three self-reported driver characteristics were obtained: personality, stress level, and mood. Three feature sets were formed based on driver characteristics, vehicle kinematics, and physiological signals. All possible combinations of the three feature sets were used to classify sleep deprivation (drowsy vs. alert), traffic density (low vs. high), cell phone use, and weather conditions (foggy/snowy vs. sunny) with highest accuracies of 98.8%, 91.4%, 82.3%, and 71.5%, respectively. Vehicle kinematics were most useful for classification of weather and traffic density while physiology and driver characteristics were useful for classification of sleep deprivation and cell phone use. Furthermore, a second classification scheme was tested that also incorporates information about whether or not other causes of hazardous states are present, though this did not result in higher classification accuracy. In the future, these classifiers could be used to identify both the presence and cause of a driver's hazardous state, which could serve as the basis for more intelligent intervention systems.

This paper is about analyzing the efficiency of drivers using an android based smartphone. Smartphones have built-in sensors for instance: accelerometer, gyroscope etc. Utilizing these sensors will provide day-end analysis to track the driving behaviour and provide feedback to the drivers if there is any inappropriate or reckless action taken while driving. To summarize this, we propose to build an active and accurate monitoring system that gives the response to the driving behaviours of a driver.

In this research, we estimate the influence of different bicycle infrastructure on the severity of motorist-cyclist conflicts via an interconnected simulator study. Our focus is a specific conflict type: motorist is turning at an intersection and the cyclist is going straight, crossing the intersection based on previous evaluations from literature. Additionally, we reason on previously-conducted bicycle simulator studies and adapt specific methodological components of investigation area depiction in VR and scenario definition. In the end, we present four scenarios of a case study based on a signalized intersection in Ingolstadt, Germany, where we inspect motorist-cyclist conflicts in an interconnected simulator environment. After every simulator run both test subjects will be teleported to specific starting positions.

Der Mensch hat sich Werkzeuge, Haustiere, die Technik, insbesondere die Informatik und das Deep Learning (DL) in Virtuellen Intelligenten Assistenten (VIA) zu eigen gemacht. Nun sind digitale technische Assistenzsysteme, die die Zukunft in Kultur, Wirtschaft und Politik vorhersagen, gefragt. Die bisher gesammelten Erfahrungen mit Deep Learning (DL) sollen auf ein Modell eines Virtuellen Intelligenten Assistenten (VIA) für die Gesellschaftswissenschaft, Kultur und der Volkswirtschaft abgebildet werden. Das Modell des Deep Learning (DL) basiert auf einem Künstlichen Neuronalen Netzwerk (KNN), das künstliche Knoten (vereinfachte Nervenzellen) und künstliche Neuronen (vereinfachte Synapsen) enthält. Die Besonderheit ist, dass die künstlichen Knoten (vereinfachten Nervenzellen) in mehreren versteckten Ebenen (Hidden Layers) mit autonomen Filterprozessen angeordnet sind. Für autonome Filter in den künstlichen Knoten (vereinfachten Nervenzellen) werden Regeln benötigt, die statisch d.h. zeitinvariant sind. Dafür werden die Logien des Thomasevangeliums vorgeschlagen. Es sieht so aus, dass das Thomasevangelium Erkenntnisse und Erfahrungen aus 80 Tausend Jahren Menschheitsgeschichte in 114 Logien zusammenfasst. Sie sind in den Gliederungspunkten 1 bis 114 dargestellt. Letztlich entscheidet das Gewicht der Wechselwirkung, dass durch künstliche Neuronen (vereinfachte Synapsen) im Modell repräsentiert wird, wie eine eingegebene Aussage am Ausgang des Künstlichen Neuronalen Netzwerkes (KNN) zu verstehen ist. Die Grenzen zwischen Maschine, Individuum und Gesellschaft lösen sich im Chaotischen immer weiter auf. Es wäre schön, wenn das Weltwissen, so wie es die Fa. Cyrorp sammelt, modellierbar ist. Anstelle eines Modells des Weltwissens schlägt Eva Soyah die Sammlung der Logien in den Gliederungspunkten 1 bis  114 und Zeitlosen Wahrheiten ab Gliederungspunkt 115 vor.

The frequency and severity of computer-based attacks such as viruses and worms, logic bombs, trojan horses, computer fraud, and plagiarism of software code have all become of increasing concern to many of those involved with information systems. Part of the difficulty experienced in collecting evidence regarding the attack or theft in such situations has been the definition and collection of

Using a closed-circuit driving track environment, we investigated the influence of using a hands-free
mobile (or cell) phone on various biomechanical and perceptual factors that underlie the control of driving.
Results showed that in three tasks representative of everyday driving conditions, the perceptual control of
action was compromised when compared to a control condition where no mobile phone conversation was
present. While conversing, critical control actions related to braking were postponed on approach to a corner.
During controlled braking, as when approaching a stationary car at a traffic light, the degree of braking
was reduced and braking style was altered in a non-optimal manner. During an obstacle avoidance task,
car dynamics were affected as a result of the conversation. Interpretation of the results is motivated by the
ecological approach to perception–action and the theory of affordances. It is concluded that a driver
s sensitivity
to prospective information about upcoming events and the associated perception and awareness of
what the road environment affords may both significantly be degraded when simultaneously using a handsfree
mobile phone. Implications for intervention and policy are discussed.

The present study examined age-related differences in car following performance when contrast of the driving scene was reduced by simulated fog. Older (mean age of 72.6) and younger (mean age of 21.1) drivers were presented with a car following scenario in a simulator in which a lead vehicle (LV) varied speed according to a sum of three sine wave functions. Drivers were shown an initial following distance of 18m and were asked to maintain headway distance by controlling speed to match changes in LV speed. Five simulated fog conditions were examined ranging from a no fog condition (contrast of 0.55) to a high fog condition (contrast of 0.03). Average LV speed varied across trials (40, 60, or 80 km/h). The results indicated age-related declines in car following performance for both headway distance and RMS (root mean square) error in matching speed. The greatest decline occurred at moderate speeds under the highest fog density condition, with older drivers maintaining a headway distance that was 21% closer than younger drivers. At higher speeds older drivers maintained a greater headway distance than younger drivers. These results suggest that older drivers may be at greater risk for a collision under high fog density and moderate speeds.

Autonomous vehicles (AVs) at varying market penetration rates will change traffic flow and highway performance. At AV market penetration rates of between 0 percent and 100 percent, human-driven vehicles (HVs) will be interacting with AVs. However, little is known about how HVs interact with AVs. Using the Oregon State University Driving Simulator, this study measured HV headways when drivers followed an AV and integrated those data into a multi-agent simulation to quantify new highway travel time and flow predictions at varying AV market penetration levels. This study also collected galvanic skin response data to quantify drivers’ levels of stress when presented with a hard-braking AV and HV. The driving simulator experiment was successfully completed by 36 participants. The results of this study showed that drivers’ levels of stress were 70 percent higher in hard braking scenarios involving HVs versus AVs. Additionally, drivers over the age of 34.5 were found to give AVs 2 percent more headway than HVs, while younger drivers gave AVs 18 percent less headway than HVs. Thirty-six scenarios were tested in the multi-agent simulation using results from the driving simulator. Given the driving simulator results, average travel times were found to increase at most by 2.3 percent, while flow was found to decrease at most by 1.3 percent.

The paper applies the choice model incorporating attribute cut-offs proposed by . A non-compensatory choice model incorporating attribute cutoffs. Transportation Research: Part B 35 (10), 903-928] to evaluate shippers' preferences for freight service attributes. A stated preference experiment on a sample of Italian manufacturing firms shows that the marginal utilities of attributes are not constant over the whole range of values presented, and that significant improvements can be made by introducing non-linearities at points specified by individual respondents. It is found that the conventional model overestimates the importance of the attributes, though their relative ranking is maintained. The proposed choice model provides useful information on the difficulty of achieving a modal transfer of freight from road to truck-rail intermodal transport.

Research has shown the negative effects of emotions on driving performance and safety, whereas a small number of neuroimaging studies has been conducted to investigate a driver's brain activities while driving with emotions. This study aims to explore angry drivers' oxygen concentration level using functional Near Infrared Spectroscopy (fNIRS). To this end, ten participants drove with induced anger in a scenario where they encountered different hazards. Both cluster analysis and factor analysis showed that we can distinguish their anger state from the neutral state based on fNIRS data. Results are discussed with the application of real-time emotion mitigation system for drivers.

The paper applies the choice model incorporating attribute cut-offs proposed by . A non-compensatory choice model incorporating attribute cutoffs. Transportation Research: Part B 35 (10), 903-928] to evaluate shippers' preferences for freight service attributes. A stated preference experiment on a sample of Italian manufacturing firms shows that the marginal utilities of attributes are not constant over the whole range of values presented, and that significant improvements can be made by introducing non-linearities at points specified by individual respondents. It is found that the conventional model overestimates the importance of the attributes, though their relative ranking is maintained. The proposed choice model provides useful information on the difficulty of achieving a modal transfer of freight from road to truck-rail intermodal transport.

The paper applies the choice model incorporating attribute cut-offs proposed by [Swait, J.D., 2001. A non-compensatory choice model incorporating attribute cutoffs. Transportation Research: Part B 35 (10), 903–928] to evaluate shippers’ preferences for freight service attributes. A stated preference experiment on a sample of Italian manufacturing firms shows that the marginal utilities of attributes are not constant over the whole

In the last two decades, the percentage volume of carbon emissions has increased from 280 to more than 380 parts per million in the atmosphere, the problem is that it is still increasing daily in which it caused many environmental hazards that has been seen the last couple of years. The end of this century, It is expected that the uncontrolled amount of emissions emitted to the atmosphere will increase the surface temperature of plant earth by 3.4ºC. Worldwide, the percentage of carbon emissions in the atmosphere and its effect on air quality has been the main concern of scientist and researchers in the past decade. Egypt is one of the biggest emitters that surfer from atmospheric pollution, almost 24% of the atmosphere pollutants in Egypt is from the transportation sector due to the heavy use of fossil fuels. Reducing the roads carbon emissions through streets design and form is the main scope of this research. This research intends to control the amount of carbon emission released in air by vehicles through controlling vehicles speed and motion, which affected by the street design and form. The presented research analysis the relation between carbon emissions and streets condition and forms, through measuring the amount of CO 2 and CO emission produced in one of the Egyptian roads from different types of vehicles in road with three different conditions. El-Shuhada Street has been chosen to be the study area of this research. The researchers used Testo 315-3 to measure the Carbon emissions in the street and to identify the relation between CO 2 emission and street condition and form. The results revealed that straight route with vehicle speeds ranged between 80 to 100 kn/h produces less carbon emissions then straight Journal of Engg. Research Online First Article 2 routes with street bumps and vehicle speed ranged between 26 to 19 km/h. Moreover, curved routes emitted more emission than straight routes.

Software forensics is the use of authorship analysis techniques to analyse computer programs for a legal or official purpose. This generally consists of plagiarism detection and malicious code analysis. IDENTIFIED is a system that has been designed to assist with the extraction of count based metrics from source code, and with the development of models of authorship using statistical and machine learning approaches. Software forensic models can be used for identification, classification, characterisation, and intent analysis. One of the ...

Two experiments addressed the relation between postural stability, perceptual sensitivity, and stability of driving performance. A vehicle was fitted with differential GPS for measuring position and speed, position sensors for measuring brake and accelerator depression, force transducers for measuring door, console and footrest bracing forces, and an accelerometer for measuring the 3D accelerations of the vehicle. In Experiment 1, we investigated whether the initiation of deceleration and the control of braking might be due to sensitivity to the perceptual variable tau, which specifies time-to-contact (TTC), and in particular, whether its first derivative, tau-dot, is used to maintain a constant deceleration profile. Using both untrained experienced drivers (EDs) and trained driving instructors from the Holden Performance Driving Centre (HPDC), results confirmed that, regardless of skill level, tau-dot was maintained at a value close to 0.5 and, as predicted by Lee [Perception 5 (1976) 437], braking was initiated when TTC % 5 s. In Experiment 2, we wished to quantify the purported differences in driving behaviour between EDs and HPDC instructors during a variety of everyday manoeuvres. Results indicated that instructors utilised a different cornering trajectory, a different emergency braking strategy, and were able to perform a high-speed swerve and recovery task more effectively than the EDs. In general, the instructors applied greater bracing forces using the door and console compared with EDs. The instructors also applied greater footrest forces during emergency braking than did the EDs. The greater use of bracing by instructor drivers to resist g-forces represents a strategy of active stabilisation that enhances both postural stability, as well as overall stability and consistency of driving performance. Results are discussed with regard to the dynamics of perceptual-motor coordination, and how increased stability might improve sensitivity to relevant perceptual information. We conclude that driver-training programmes that focus on increasing driver stability (as a pre-requisite for increased control) show great promise as a means to improving oneÕs attention during driving, and hence have the potential to dramatically improve road safety in general.

Previous research (Andersen & Kim, 2001) has shown that a linear trajectory collision event (i.e., a collision between a moving object and an observer) is specified by objects that expand and maintain a constant bearing (the object location remains constant in the visual field). In the present study, we examined the optical information for detecting a collision event when the trajectory was of constant curvature. Under these conditions, a collision event is specified by expansion of an object and a constant rate-of-bearing change. Three experiments were conducted in which trajectory curvature and display duration were varied while time to contact, speed, and initial image position of the collision objects were maintained. The results indicated that collision detection performance decreased with an increase in trajectory curvature and decreased with a decrease in display duration, especially for highly curved trajectories. In Experiment 3, we found that the presentation of a constant rate-of-bearing change in noncollision stimuli resulted in an increase in the false alarm rate. These results demonstrate that observers can detect collision events on curved trajectories and that observers utilize bearing change information.

This paper investigates the aspects of regional digital convergence, i.e. the capability of the use of Information and Communication Technologies (ICTs) among all people living in the peripheral areas of a country, in relation to the ICT applications into the transport sector, known as Intelligent Transport Systems (ITS). It also examines the interdependent relationships between the digital and physical accessibility. Firstly, the ICT infrastructures and their access via the households and enterprises set the conditions for the use of ITS. On the other hand, the expansion of transport networks and decentralization of transport flows can contribute to the widespread adoption of ITS and ICTs in general, and the higher specialization and diversification of digital services. These interactions are analyzed in Greece, through investigating the spatial allocation of public expenditure, at a regional level, for the Information Society and the transport sector, during 2000-2009. The finding...

In the last two decades, the percentage volume of carbon emissions has increased from 280 to more than 380 parts per million in the atmosphere, the problem is that it is still increasing daily in which it caused many environmental hazard that has been seen the last couple of years. The end of this century, It is expected that the uncontrolled amount of emissions emitted to the atmosphere will increase the surface temperature of plant earth by 3.4ºC. Worldwide, the percentage of carbon emissions in the atmosphere and its effect on air quality has been the main concern of scientist and researchers in the past decade. Egypt, is one of the biggest emitters that surfer from atmospheric pollution, almost 24% of the atmosphere pollutants in Egypt is from the transportation sector due to the heavy use of fossil fuels. Reducing the roads carbon emissions through streets design and form is the main scope of this research. This research intend to control the amount of carbon emission released ...

"Under the aegis of Intelligent Transportation Systems (ITS), real-time information provision strategies are being proposed to manage traffic congestion, alleviate the effects of incidents, enhance response efficiency after disasters, and improve the multimodal/intermodal travel experience. Several simulation-based studies have been conducted in the past to analyze the evolution of the traffic network under real-time information provision to travelers†. Some of them assume specific driver behavior models and seek to understand the effect of real-time information on the unfolding network states. However, the various simulation studies are typically limited by the use of pre-specified behavior models and simple/small network topologies. Hence, there is an underlying disconnect with the real-world needs beyond the key issues related to restrictive behavioral assumptions. The proposed study seeks to address these issues by conducting experiments using a driving simulator with laboratory-based interactive experiments where the participants are provided real-time routing information on traffic conditions related to their origin-destination (O-D) trip. In this paper, we describe the survey design and methodology for the planned experiments that explicitly captures psychological factors rather than implicitly so as done in traditional models. Various variables and attributes have been identified for survey design and used in the questionnaire. The challenges associated with identification of variables, psychological factors and framing appropriate questions have been discussed. Two types of surveys are planned in this study: static and dynamic. The static survey comprises of socio-economic characteristics, travel behavior related tendencies, inherent behavioral tendencies, and attitude related characteristics. The dynamic survey is a recurring survey that captures the learning behavior of drivers based on information provision on a day-to-day basis. Hence, the study proposes to more explicitly understand the role of human behavior by incorporating appropriate elements in the experiment survey design rather than passively inferring it based on traffic measurements of the system evolution over time as is the case in simulation studies"

Software forensics is the use of authorship analysis techniques to analyse computer programs for a legal or official purpose. This generally consists of plagiarism detection and malicious code analysis. IDENTIFIED is a system that has been designed to assist with the extraction of count based metrics from source code, and with the development of models of authorship using statistical and machine learning approaches. Software forensic models can be used for identification, classification, characterisation, and intent analysis. One of the ...

This paper investigates the aspects of regional digital convergence, i.e. the capability of the use of Information and Communication Technologies (ICTs) among all people living in the peripheral areas of a country, in relation to the ICT applications into the transport sector, known as Intelligent Transport Systems (ITS). It also examines the interdependent relationships between the digital and physical accessibility. Firstly, the ICT infrastructures and their access via the households and enterprises set the conditions for the use of ITS. On the other hand, the expansion of transport networks and decentralization of transport flows can contribute to the widespread adoption of ITS and ICTs in general, and the higher specialization and diversification of digital services. These interactions are analyzed in Greece, through investigating the spatial allocation of public expenditure, at a regional level, for the Information Society and the transport sector, during 2000-2009. The finding...

Keselamatan berkendara ini kurang begitu diperhatikan oleh para pengguna jalan terutama pengguna sepeda motor. Hal ini terbukti pada rekapitulasi Polresta Malang pada tahun 2008 menunjukkan bahwa kecelakaan di jalan raya ini didominasi oleh sepeda motor yang mencapai 403 kasus kecelakaan atau mencapai 83,78 % dari total kasus kecelakaan. Konsep psikologi meyakini bahwa keselamatan berlalu lintas dipengaruhi oleh sikap mereka pada aturan lalu-lintas (Lieb & Wiseman, 2001), sehingga mengetahui sikap merupakan aspek pengendara penting dalam kajian psikologi lalu lintas. Salah satu yang membentuk sikap adalah pengaruh sosial yang terjadi dalam kelompok. Dengan menggunakan Theory of Reasoned Action (Fishben & Ajzen, 1980), dapat diprediksikan bahwa keyakinan pada norma kelompok dan keyakinan pada kontrol orang lain pada perilaku individu akan mempengaruhi sikap dan perilaku berkendara. Penelitian ini menggunakan mixed methode (kuantitatif dan kualitataif), dengan melibatkan 147 responden dengan rincian 45 anggota komunitas Vespa, 41 anggota komunitas Mio dan 61 anggota non komunitas. Hasil penelitian menunjukkan ada perbedaan sikap terhadap aturan lalu lintas dalam hal ini responsibility riding antara komunitas motor Vespa, komunitas motor Mio dan non komunitas. Penelusuran dengan wawancara dan observasi menunjukkan bahwa norma kelompok mempengaruhi perilaku anggotanya dalam berlalu lintas.