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Journal articles on the topic 'Driver behaviour models'

Author: Grafiati

Published: 6 September 2023

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1

Li, Yi, Yuren Chen, and Fan Wang. "The Impact of Traffic Environmental Vision Pressure on Driver Behaviour." Journal of Advanced Transportation 2018 (June 5, 2018): 1–12. http://dx.doi.org/10.1155/2018/4941605.

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Car-following (CF) and lane-changing (LC) behaviours are basic components in driving process. Previous models described them as physical processes with vehicle dynamics and physical criteria. However, drivers’ decisions are greatly influenced by their subjective vision information of various traffic environment elements. To solve this problem, we propose a new concept of traffic environmental vision pressure to explain these two behaviours. The pressure source consists of two parts: nearby vehicles and infrastructures. Pressure models were built to quantify the impact of traffic and roadside i

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Chodur, Janusz, and Radosław Bąk. "Study of driver behaviour at turbo-roundabouts." Archives of Transport 38, no. 2 (2016): 17–28. http://dx.doi.org/10.5604/08669546.1218790.

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The article presents the results of preliminary research into the behaviour of drivers at turbo-roundabouts. The subject of the research included the frequency of driver behaviour against the traffic rules, and the speed at which vehicles drive through turbo-roundabouts. One of the crucial problems which was analysed was the influence of different kinds of traffic lane division on the behaviour of drivers. The analysis results affirm that the raised lane dividers can visibly improve the propensity of drivers to stay within the designated traffic corridor. However, it does not eliminate the phe

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McGordon, A., J. E. W. Poxon, C. Cheng, R. P. Jones, and P. A. Jennings. "Development of a driver model to study the effects of real-world driver behaviour on the fuel consumption." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 225, no. 11 (2011): 1518–30. http://dx.doi.org/10.1177/0954407011409116.

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The real-world fuel economy of vehicles is becoming increasingly important to manufacturers and customers. One of the major influences in this is driver behaviour, but it is difficult to study in a controlled and repeatable manner. An assessment of driver models for studying real-world driver behaviour has been carried out. It has been found that none of the currently existing driver models has sufficient fidelity for studying the effects of real-world driver behaviour on the fuel economy of the individual vehicle. A decision-making process has been proposed which allows a driver model with a

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Manjunath, Abhijna. "Prediction of Crash Risk based on Driving Behaviour." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 453–56. http://dx.doi.org/10.22214/ijraset.2022.45252.

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Abstract: The major interest which is increasing for many kinds of applications includes human driver’s characterisation. There are different promising approaches in order to characterise the drivers by means of control theoretic driver models. The driver state is monitored by applying features of driver model from survey till real road distraction experiment. The dataset for the experiment consists of driving behavior with visuomotor and even few secondary tasks like auditory and even driving reference. The individual estimation of model parameters uses data of driving of nearly eleven driver

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Babojelić, Karlo, and Luka Novacko. "Modelling of Driver and Pedestrian Behaviour – A Historical Review." Promet - Traffic&Transportation 32, no. 5 (2020): 727–45. http://dx.doi.org/10.7307/ptt.v32i5.3524.

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Driver and pedestrian behaviour significantly affect the safety and the flow of traffic at the microscopic and macroscopic levels. The driver behaviour models describe the driver decisions made in different traffic flow conditions. Modelling the pedestrian behaviour plays an essential role in the analysis of pedestrian flows in the areas such as public transit terminals, pedestrian zones, evacuations, etc. Driver behaviour models, integrated into simulation tools, can be divided into car-following models and lane-changing models. The simulation tools are used to replicate traffic flows and inf

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Rothkrantz, Leon, Madalina Toma, and Mirela Popa. "AN INTELLIGENT CO-DRIVER SURVEILLANCE SYSTEM." Acta Polytechnica CTU Proceedings 12 (December 15, 2017): 83. http://dx.doi.org/10.14311/app.2017.12.0083.

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In recent years many car manufacturers developed digital co-drivers , which are able to monitor the driving behaviour of a car. Sensors in the car measure if a car passes speed limits, leaves its lane, or violates other traffic rules. A new generation of co-drivers is based on sensors in the car which are able to monitor the driver behaviour. Driving a car is a sequence of actions. In case a driver doesn’t show one of the actions the co-driver generates a warning signal. Experiments in the car simulator TORC were performed to extract the actions of a car driver. These actions were used to deve

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Yannes, Craig D., and Nicholas E. Lownes. "Driver behaviour considerations in calibrating microsimulation models for capacity." International Journal of Society Systems Science 2, no. 1 (2010): 84. http://dx.doi.org/10.1504/ijsss.2010.031468.

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Arumugam, Subramanian, and R. Bhargavi. "Road Rage and Aggressive Driving Behaviour Detection in Usage-Based Insurance Using Machine Learning." International Journal of Software Innovation 11, no. 1 (2023): 1–29. http://dx.doi.org/10.4018/ijsi.319314.

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Driving behaviour is a critical issue in modern transportation systems due to the increasing concerns about the safety of drivers, passengers, and road users. Machine learning models are capable of learning driving patterns from sensor data and recognizing individuals by their driving behaviours. This paper presents a novel framework for aggressive driving detection and driver classification based on driving events identified from GPS data collected with smartphones and heart rate of the driver captured with a wearable device. The proposed system for road rage and aggressive driving detection

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Mirbeygi Moghaddam, Amirreza, Ali Ghaffari, and Alireza Khodayari. "Adaptive comfort-oriented vehicle lateral control with online controller adjustments according to driver behaviour and look-ahead dynamics." Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics 234, no. 2 (2019): 272–87. http://dx.doi.org/10.1177/1464419319895835.

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This paper presents a comfort-oriented adaptive fuzzy-model predictive control strategy to control the lateral motion of a vehicle with the steering angle as the input while preventing sudden changes and unwanted motions. This is reached by utilizing three main contributions: an adaptive fuzzy model based on look-ahead dynamics, limiting the controller to the acceptable range of states to the driver and introducing an adjustment factor to the controller's cost function. Using adaptive-fuzzy models to describe the vehicle lateral dynamics and driver behaviour for the purpose of the control-orie

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Bevrani, Kaveh, Edward Chung, and Pauline Teo. "The Space-Based Car-Following Model: Development and Application for Managed Motorway System Safety Evaluation." Future Transportation 1, no. 3 (2021): 443–65. http://dx.doi.org/10.3390/futuretransp1030024.

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Traffic safety studies need more than what the current micro-simulation models can provide, as they presume that all drivers exhibit safe behaviors. Therefore, existing micro-simulation models are inadequate to evaluate the safety impacts of managed motorway systems such as Variable Speed Limits. All microscopic traffic simulation packages include a core car-following model. This paper highlights the limitations of the existing car-following models to emulate driver behaviour for safety study purposes. It also compares the capabilities of the mainstream car-following models, modelling driver b

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Jurecki, Rafał S., and Tomasz L. Stańczyk. "Modelling Driver’s Behaviour While Avoiding Obstacles." Applied Sciences 13, no. 1 (2023): 616. http://dx.doi.org/10.3390/app13010616.

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This article presents a short description of mathematical driver models. In the literature, there are no models that are generally considered fully satisfactory for use in analysing drivers’ behaviour in emergencies. This paper presents a concept of model, which includes two sub-models related to the driver’s defensive manoeuvres—avoiding the obstacle and braking. This article describes a model used for a simple road situation—a single obstacle (pedestrian) appearing on the road in front of the vehicle. In the model, the method of artificial potential fields was used, but it was enriched with

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Olstam, Johan, Viktor Bernhardsson, Charisma Choudhury, Gerdien Klunder, Isabel Wilmink, and Martijn van Noort. "Modelling Eco-Driving Support System for Microscopic Traffic Simulation." Journal of Advanced Transportation 2019 (December 25, 2019): 1–16. http://dx.doi.org/10.1155/2019/2162568.

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Microscopic traffic simulation is an ideal tool for investigating the network level impacts of eco-driving in different networks and traffic conditions, under varying penetration rates and driver compliance rates. The reliability of the traffic simulation results however rely on the accurate representation of the simulation of the driver support system and the response of the driver to the eco-driving advice, as well as on a realistic modelling and calibration of the driver’s behaviour. The state-of-the-art microscopic traffic simulation models however exclude detailed modelling of the driver

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Ali, Faryal, Zawar Hussain Khan, Fayaz Ahmad Khan, Khurram Shehzad Khattak, and Thomas Aaron Gulliver. "A New Driver Model Based on Driver Response." Applied Sciences 12, no. 11 (2022): 5390. http://dx.doi.org/10.3390/app12115390.

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In this paper, a new microscopic traffic model based on forward and rearward driver response is proposed. Driver response is characterized using the distance and time headways. Existing models such as the Intelligent Driver (ID) model characterize traffic flow based on a constant acceleration exponent. This exponent reflects uniform driver behaviour during different conditions which is unrealistic. Driver response is slow with a large distance headway and quick with a short time headway. Conversely, it is quick with a small distance headway and slow with a long time headway. Thus, a new micros

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Vamshi, B., Challa Sri Nikitha, Gangula Sreya, G. Sai Sindhuja, and Hasan Nazneen. "Detection of Distracted Driver Using Convolutional Neural Network." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (2023): 3642–51. http://dx.doi.org/10.22214/ijraset.2023.54176.

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Abstract: Abnormal driving behaviour detection helps to ensure safety of driver and passenger. Recent studies have concluded that talking on phone while driving distracts driver attention upto 20%, which leads to accidents. Deep learning models can be used to find these distracted actions. In this system the abnormal behaviour of the driver like reaching behind, hair and makeup, drinking, texting etc. are detected through deep learning. Densely connected Convolutional Neural Networks, Residual Networks are used for detection. AWGRD model, the most sophisticated model of ResNet, is formedby sup

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Li, S. H., and J. Y. Ren. "Driver Steering Control and Full Vehicle Dynamics Study Based on a Nonlinear Three-Directional Coupled Heavy-Duty Vehicle Model." Mathematical Problems in Engineering 2014 (2014): 1–16. http://dx.doi.org/10.1155/2014/352374.

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Under complicated driving situations, such as cornering brake, lane change, or barrier avoidance, the vertical, lateral, and longitudinal dynamics of a vehicle are coupled and interacted obviously. This work aims to propose the suitable vehicle and driver models for researching full vehicle dynamics in complicated conditions. A nonlinear three-directional coupled lumped parameters (TCLP) model of a heavy-duty vehicle considering the nonlinearity of suspension damping and tire stiffness is built firstly. Then a modified preview driver model with nonlinear time delay is proposed and connected to

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Banks, Victoria A., and Neville A. Stanton. "Contrasting models of driver behaviour in emergencies using retrospective verbalisations and network analysis." Ergonomics 58, no. 8 (2015): 1337–46. http://dx.doi.org/10.1080/00140139.2015.1005175.

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Rebitschek, Felix G., Gerd Gigerenzer, Ariane Keitel, Sarah Sommer, Christian Groß, and Gert G. Wagner. "Acceptance of criteria for health and driver scoring in the general public in Germany." PLOS ONE 16, no. 4 (2021): e0250224. http://dx.doi.org/10.1371/journal.pone.0250224.

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Numerous health insurers offer bonus programmes that score customers’ health behaviour, and car insurers offer telematics tariffs that score driving behaviour. In many countries, however, only a minority of customers participate in these programmes. In a population-representative survey of private households in Germany (N = 2,215), we study the acceptance of the criteria (features) on which the scoring programmes are based: the features for driver scoring (speed, texting while driving, time of driving, area of driving, accelerating and braking behaviour, respectively) and for health scoring (w

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Savolainen, Reijo. "Information need as trigger and driver of information seeking: a conceptual analysis." Aslib Journal of Information Management 69, no. 1 (2017): 2–21. http://dx.doi.org/10.1108/ajim-08-2016-0139.

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Purpose The purpose of this paper is to elaborate the picture of the motivators for information behaviour by examining the nature of information need as a trigger and driver of information seeking. Design/methodology/approach A conceptual analysis was made by focussing on the ways in which researchers have conceptualised information need in models for human information behaviour (HIB). The study draws on conceptual analysis of 26 key studies focussing on the above topic. Findings Researchers have employed two main approaches to conceptualise information needs in the HIB models. First, informat

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Markkula, G., O. Benderius, and M. Wahde. "Comparing and validating models of driver steering behaviour in collision avoidance and vehicle stabilisation." Vehicle System Dynamics 52, no. 12 (2014): 1658–80. http://dx.doi.org/10.1080/00423114.2014.954589.

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Hoseini, Seyyed Mohammad Sadat. "Comparison of Microscopic Drivers' Probabilistic Lane-changing Models With Real Traffic Microscopic Data." PROMET - Traffic&Transportation 23, no. 4 (2012): 241–51. http://dx.doi.org/10.7307/ptt.v23i4.127.

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The difficulties of microscopic-level simulation models to accurately reproduce real traffic phenomena stem not only from the complexity of calibration and validation operations, but also from the structural inadequacies of the sub-models themselves. Both of these drawbacks originate from the scant information available on real phenomena because of the difficulty in gathering accurate field data. This paper studies the traffic behaviour of individual drivers utilizing vehicle trajectory data extracted from digital images collected from freeways in Iran. These data are used to evaluate the four

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Hart, Edward, Adam Stock, George Elderfield, et al. "Impacts of wind field characteristics and non-steady deterministic wind events on time-varying main-bearing loads." Wind Energy Science 7, no. 3 (2022): 1209–26. http://dx.doi.org/10.5194/wes-7-1209-2022.

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Abstract. This work considers the characteristics and drivers of the loads experienced by wind turbine main bearings. Simplified load response models of two different hub and main-bearing configurations are presented, representative of both inverting direct-drive and four-point-mounted geared drivetrains. The influences of deterministic wind field characteristics, such as wind speed, shear, yaw offset, and veer, on the bearing load patterns are then investigated for similarity scaled 5, 7.5, and 10 MW reference wind turbine models. Main-bearing load response in cases of deterministic gusts and

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Brow, Gerald R. "Traffic conflicts for road user safety studies." Canadian Journal of Civil Engineering 21, no. 1 (1994): 1–15. http://dx.doi.org/10.1139/l94-001.

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In this paper we advocate an approach to road safety studies in which traffic conflicts are used as indicators of roadway hazard. The critical traffic process event used to define conflict severity is the time to collision, modified by an observer's evaluation of the risk of collision. Field studies were done to assess the validity, reliability, and practicality of traffic conflicts. Experiments were conducted to test the threshold value of time to collision, and to examine a visual perception theory of crash avoidance behaviour. The experiments demonstrate that a time to collision threshold v

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ŽURA, Marijan. "Roundabout Capacity Estimation Model Considering Driver Behaviour on the Exiting and Entry Flows." Promet - Traffic&Transportation 34, no. 3 (2022): 397–405. http://dx.doi.org/10.7307/ptt.v34i3.3973.

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Roundabout capacity estimation has been the subject of several types of research in recent decades. Most of the analyses are based on the empirical or analytical models (e.g. gap acceptance theory) considering various kinds of conflicting flows, namely entry, circulating, and exit-ing flow. The drivers on the exiting flow either obey the traffic rule (use the right-turn indicator) or disobey the traffic rule (do not use the right-turn indicator). Accord-ing to the reviewed literature, the impact of these driv-ers on the roundabout capacity has not been studied to a greater extent. Therefore, t

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Othman, Walaa, Alexey Kashevnik, Ammar Ali, and Nikolay Shilov. "DriverMVT: In-Cabin Dataset for Driver Monitoring including Video and Vehicle Telemetry Information." Data 7, no. 5 (2022): 62. http://dx.doi.org/10.3390/data7050062.

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Developing a driver monitoring system that can assess the driver’s state is a prerequisite and a key to improving the road safety. With the success of deep learning, such systems can achieve a high accuracy if corresponding high-quality datasets are available. In this paper, we introduce DriverMVT (Driver Monitoring dataset with Videos and Telemetry). The dataset contains information about the driver head pose, heart rate, and driver behaviour inside the cabin like drowsiness and unfastened belt. This dataset can be used to train and evaluate deep learning models to estimate the driver’s healt

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Hassein, Udai, Maksym Diachuk, and Said Easa. "Evaluation of dynamic passing gap acceptance on two-lane highways using field data." Canadian Journal of Civil Engineering 44, no. 11 (2017): 871–80. http://dx.doi.org/10.1139/cjce-2016-0572.

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Gap availability is an important element of safe passing on two-lane highways. Time gaps are used to determine passing behaviour based on human factors. In this paper, the decision whether to accept or reject an available passing gap is modelled using logistic regression technique that included driver characteristics (age and experience) and the gap size. Field studies were conducted to collect experimental data regarding passing driver behaviour. The data were collected using dual camera Car DVRs and a GPS data logger device that records the instantaneous speed and position of the three vehic

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Al-Jameel, Hamid Athab. "DEVELOPING A NEW HYBRID SAFETY CAR-FOLLOWING MODEL." Kufa Journal of Engineering 5, no. 2 (2014): 47–60. http://dx.doi.org/10.30572/2018/kje/521327.

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For more than five decades, car-following models have been developed based on different theoretical backgrounds and conditions. The importance of these models belongs to their representation of longitudinal movement for any simulation model. Therefore, the accuracy of the car-following model is still the core of strength of any simulation model. For the purpose of this study, a hybrid car-following model has been developed to represent “go and stop” conditions. These conditions mostly occur in a weaving section. This model has been developed as a corner stone for a microscopic simulation model

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Nirmale, Sangram Krishna, and Abdul Rawoof Pinjari. "Discrete choice models with multiplicative stochasticity in choice environment variables: Application to accommodating perception errors in driver behaviour models." Transportation Research Part B: Methodological 170 (April 2023): 169–93. http://dx.doi.org/10.1016/j.trb.2023.02.014.

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Bhamjee, Muaaz, Simon H. Connell, and André Leon Nel. "The Modification of the Dynamic Behaviour of the Cyclonic Flow in a Hydrocyclone under Surging Conditions." Mathematical and Computational Applications 27, no. 6 (2022): 88. http://dx.doi.org/10.3390/mca27060088.

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The aim in this study was to determine how surging modifies the dynamic behaviour of the cyclonic flow in a hydrocyclone using computational fluid and granular dynamics models. The Volume-of-Fluid model was used to model the air-core formation. Fluid–particle, particle–particle, and particle–wall interactions were modelled using an unsteady two-way coupled Discrete Element Method. Turbulence was modelled using both the Reynold’s Stress Model and the Large Eddy Simulation. The model predictions indicate that the phenomenon of surging modifies the dynamics of the cyclonic flow in hydrocyclones a

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Errampalli, Madhu, Masashi Okushima, and Takamasa Akiyama. "Fuzzy Logic Based Lane Change Model for Microscopic Traffic Flow Simulation." Journal of Advanced Computational Intelligence and Intelligent Informatics 12, no. 2 (2008): 172–81. http://dx.doi.org/10.20965/jaciii.2008.p0172.

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Lane changing phenomenon is vital in representing individual vehicle behaviour in microscopic traffic simulation, yet many lane change models do not consider the uncertainties and perceptions in human behaviour that are involved in modelling lane changing. In the present study, fuzzy reasoning in lane changing model is introduced to reflect these uncertainties and perceptions to represent lane changing behaviour more realistically. The comparison of simulated results with observed data indicated that fuzzy reasoning represents driver behaviour more realistically than standard modelling. The ef

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Orecchini, Fabio, Adriano Santiangeli, Fabrizio Zuccari, Adriano Alessandrini, Fabio Cignini, and Fernando Ortenzi. "Real Drive Truth Test of the Toyota Yaris Hybrid 2020 and Energy Analysis Comparison with the 2017 Model." Energies 14, no. 23 (2021): 8032. http://dx.doi.org/10.3390/en14238032.

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This paper presents the performance analysis of a latest-generation hybrid vehicle (Toyota Yaris 2020) with a testing campaign in real road conditions and a comparison with the previous model (Toyota Yaris 2017). The study was conducted by applying the Real Drive Truth Test protocol, developed by the research group, validated and spread to other full hybrid vehicles: Toyota Prius IV (2016) and Toyota Yaris 2017 (2017). In the case of the 2020 tests, the co-presence on board—deemed unsafe in the usual ways given the ongoing pandemic—was achieved through precise and sophisticated remote control.

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Shankar, Reddy Shiva, Pilli Neelima, Voosala Priyadarshini, and Swaroop Ravi Chigurupati. "An approach to classify distraction driver detection system by using mining techniques." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 3 (2022): 1670. http://dx.doi.org/10.11591/ijeecs.v27.i3.pp1670-1680.

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According to the motor vehicle safety division, over the past 5-10 years, usage of motor vehicles has rapidly increased, in that specifical usage of cars has grown tremendously. The major contribution of this paper is a systematic evaluation of the scholarly literature on driver distraction detection techniques. Our driver distraction detection framework offers a systematic overview of evaluated methodologies for detecting driver attention. So, we need to develop a model that classifies each driver's behaviour and determines its corresponding class name. To overcome this dispute, we have attai

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St John, Freya A. V., Gareth Edwards-Jones, and Julia P. G. Jones. "Conservation and human behaviour: lessons from social psychology." Wildlife Research 37, no. 8 (2010): 658. http://dx.doi.org/10.1071/wr10032.

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Despite increased effort from non-governmental organisations, academics and governments over recent decades, several threats continue to cause species declines and even extinctions. Resource use by a growing human population is a significant driver of biodiversity loss, so conservation scientists need to be interested in the factors that motivate human behaviour. Economic models have been applied to human decision making for many years; however, humans are not financially rational beings and other characteristics of the decision maker (including attitude) and the pressure that people perceive

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Lapiedra, Oriol, Daniel Sol, Salvador Carranza, and Jeremy M. Beaulieu. "Behavioural changes and the adaptive diversification of pigeons and doves." Proceedings of the Royal Society B: Biological Sciences 280, no. 1755 (2013): 20122893. http://dx.doi.org/10.1098/rspb.2012.2893.

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What factors determine the extent of evolutionary diversification remains a major question in evolutionary biology. Behavioural changes have long been suggested to be a major driver of phenotypic diversification by exposing animals to new selective pressures. Nevertheless, the role of behaviour in evolution remains controversial because behavioural changes can also retard evolutionary change by hiding genetic variation from selection. In the present study, we apply recently implemented Ornstein–Uhlenbeck evolutionary models to show that behavioural changes led to associated evolutionary respon

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Lyu, Aihong. "Driver Distracted Behavior Detection Using a Light Weight Model based on the W-MSA." Journal of Physics: Conference Series 2560, no. 1 (2023): 012046. http://dx.doi.org/10.1088/1742-6596/2560/1/012046.

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Abstract The percentage of traffic accidents caused by driver factors is about 90% in the world. Despite the great development of autonomous driving, it is still not completely self-driving. So, it is still not possible to avoid traffic accidents caused by drivers. Computer vision technology has made great progress with deep learning development. That makes it possible to detect the driver’s behaviour using a camera. To reduce the detection price, this paper presents a light weight model to detect the driver’s behavior based on the W-MSA. This model consists of 2 encoder modules and a classifi

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Vaa, Truls. "From Gibson and Crooks to Damasio: The role of psychology in the development of driver behaviour models." Transportation Research Part F: Traffic Psychology and Behaviour 25 (July 2014): 112–19. http://dx.doi.org/10.1016/j.trf.2014.02.004.

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Russo, Francesca, Salvatore Antonio Biancardo, and Mariarosaria Busiello. "OPERATING SPEED AS A KEY FACTOR IN STUDYING THE DRIVER BEHAVIOUR IN A RURAL CONTEXT." TRANSPORT 31, no. 2 (2016): 260–70. http://dx.doi.org/10.3846/16484142.2016.1193054.

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The research aims to explore the effects of geometric road features on driver speed behaviour in order to identify unsafe road segments where high reductions in speed between successive road elements occur. The sample involves two-lane rural roads on flat terrain (vertical grade less than 5%) in Southern Italy, totalling 184 km without spiral transition curves between the tangent segments and circular elements. The testing was carried out on 567 study sites, of which 248 are on circular curves and 319 on tangents. Speed data collection was carried out in environmental and traffic conditions us

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Rudisill, Toni Marie, Motao Zhu, and Haitao Chu. "Association between cellphone use while driving legislation and self-reported behaviour among adult drivers in USA: a cross-sectional study." BMJ Open 9, no. 2 (2019): e023456. http://dx.doi.org/10.1136/bmjopen-2018-023456.

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ObjectivesCellphone use behaviours can vary demographically in the USA. This study examined whether legislation restricting cellphone use while driving was associated with lower self-reported hand-held cellphone conversations or texting behaviours among adult drivers of different ages (19–24, 25–39, 40–59,≥60 years), sex, race/ethnicity (white non-Hispanic, black non-Hispanic, Hispanic, Other) or rurality (urban, rural).DesignCross-sectional study.SettingUSA.ParticipantsIndividuals ≥19 years of age who indicated they were a current driver and participated in the 2011–2014 Traffic Safety Cultur

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RADOVIĆ, Dunja, Mithun MOHAN, and Vuk BOGDANOVIĆ. "Comparative Analysis of Critical Headway Estimation at Urban Single-Lane Roundabouts." Promet - Traffic&Transportation 34, no. 2 (2022): 323–35. http://dx.doi.org/10.7307/ptt.v34i2.3902.

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According to models commonly used in practice, the capacity of roundabouts largely depends on the value of critical headway. The value of critical headway depends on the characteristics of vehicles, driving conditions, and geometric characteristics of intersections, but also on driver behaviour. Driver behaviour is the result of many factors that depend on the influence of the local environment, driver habits, mentality, etc. Accordingly, to calculate the capacity of roundabouts within the op-erational and planning analyses of roundabouts more accurately, it is necessary to use data that corre

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Poor Arab Moghadam, M., and P. Pahlavani. "MOVING OBJECTS TRAJECTOTY PREDICTION BASED ON ARTIFICIAL NEURAL NETWORK APPROXIMATOR BY CONSIDERING INSTANTANEOUS REACTION TIME, CASE STUDY: CAR FOLLOWING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (December 11, 2015): 577–82. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-577-2015.

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Car following models as well-known moving objects trajectory problems have been used for more than half a century in all traffic simulation software for describing driving behaviour in traffic flows. However, previous empirical studies and modeling about car following behavior had some important limitations. One of the main and clear defects of the introduced models was the very large number of parameters that made their calibration very time-consuming and costly. Also, any change in these parameters, even slight ones, severely disrupted the output. In this study, an artificial neural network

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Fei, Rong, Shasha Li, Xinhong Hei, Qingzheng Xu, Fang Liu, and Bo Hu. "The Driver Time Memory Car-Following Model Simulating in Apollo Platform with GRU and Real Road Traffic Data." Mathematical Problems in Engineering 2020 (March 17, 2020): 1–18. http://dx.doi.org/10.1155/2020/4726763.

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Car following is the most common phenomenon in single-lane traffic. The accuracy of acceleration prediction can be effectively improved by the driver’s memory in car-following behaviour. In addition, the Apollo autonomous driving platform launched by Baidu Inc. provides fast test vehicle following vehicle models. Therefore, this paper proposes a car-following model (CFDT) with driver time memory based on real-world traffic data. The CFDT model is firstly constructed by embedded gantry control unit storage capacity (GRU assisted) network. Secondly, the NGSIM dataset will be used to obtain the t

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Comolli, Francesco, Massimiliano Gobbi, and Gianpiero Mastinu. "Study on the Driver/Steering Wheel Interaction in Emergency Situations." Applied Sciences 10, no. 20 (2020): 7055. http://dx.doi.org/10.3390/app10207055.

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Advanced driver assistance systems (ADAS) are becoming increasingly prevalent. The tuning of these systems would benefit from a deep knowledge of human behaviour, especially during emergency manoeuvres; however, this does not appear to commonly be the case. We introduced an instrumented steering wheel (ISW) to measure three components of force and three components of the moment applied by each hand, separately. Using the ISW, we studied the kick plate manoeuvre. The kick plate manoeuvre is an emergency manoeuvre to recover a lateral disturbance inducing a spin. The drivers performed the manoeu

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Othman, Walaa, Batol Hamoud, Alexey Kashevnik, Nikolay Shilov, and Ammar Ali. "A Machine Learning-Based Correlation Analysis between Driver Behaviour and Vital Signs: Approach and Case Study." Sensors 23, no. 17 (2023): 7387. http://dx.doi.org/10.3390/s23177387.

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Driving behaviour analysis has drawn much attention in recent years due to the dramatic increase in the number of traffic accidents and casualties, and based on many studies, there is a relationship between the driving environment or behaviour and the driver’s state. To the best of our knowledge, these studies mostly investigate relationships between one vital sign and the driving circumstances either inside or outside the cabin. Hence, our paper provides an analysis of the correlation between the driver state (vital signs, eye state, and head pose) and both the vehicle maneuver actions (cause

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Suchoy, Lior, Saskia Goes, Benjamin Maunder, Fanny Garel, and Rhodri Davies. "Effects of basal drag on subduction dynamics from 2D numerical models." Solid Earth 12, no. 1 (2021): 79–93. http://dx.doi.org/10.5194/se-12-79-2021.

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Abstract. Subducting slabs are an important driver of plate motions, yet the relative importance of different forces in governing subduction motions and styles remains incompletely understood. Basal drag has been proposed to be a minor contributor to subduction forcing because of the lack of correlation between plate size and velocity in observed and reconstructed plate motions. Furthermore, in single subduction system models, low basal drag leads to subduction behaviour most consistent with the observation that trench migration velocities are generally low compared to convergence velocities.

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Lim, Clark, Tarek Sayed, and Francis Navin. "A driver visual attention model. Part 1. Conceptual framework." Canadian Journal of Civil Engineering 31, no. 3 (2004): 463–72. http://dx.doi.org/10.1139/l04-020.

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This paper describes a driver visual attention model that gathers information based on a selective process so that events such as distractions can be modelled. This model contains visual information gathering capabilities and visual attention mechanisms based on subjective and objective factors. As the research focused on applicability, the model's framework was designed to be integrated as a component processor within a microscopic computer traffic simulation. The model determines visual attention using two mechanisms: internal and external focusing. The internal focusing mechanism is a proac

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Hassan, Yasser, and Tarek Sayed. "Effect of driver and road characteristics on required preview sight distance." Canadian Journal of Civil Engineering 29, no. 2 (2002): 276–88. http://dx.doi.org/10.1139/l02-002.

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Highway geometric design is a complex process that is closely related to human perception and behaviour. Among the human perception issues that can affect highway geometric design is the preview sight distance, which has been defined as the distance required to perceive a horizontal curve and react properly to it. Previous attempts to quantify preview sight distance included measurement on actual roads, physical modelling, and computer animation. This paper presents a computer animation experiment that was designed to examine the effects of geometric parameters and driver characteristics on pr

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Priya, V. Vijay, and M. Uma. "EEG based Drowsiness Prediction Using Machine Learning Approach." Webology 18, no. 2 (2021): 740–55. http://dx.doi.org/10.14704/web/v18i2/web18351.

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Drowsiness is the main cause of road accidents and it leads to severe physical injury, death, and significant economic losses. To monitor driver drowsiness various methods like Behaviour measures, Vehicle measures, Physiological measures and Hybrid measures have been used in previous research. This paper mainly focuses on physiological methods to predict the driver’s drowsiness. Several physiological methods are used to predict drowsiness. Among those methods, Electroencephalography is one of the non-invasive physiological methods to measure the brain activity of the subject. EEG brain signal

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Ellsworth, L. M., A. P. Dale, C. M. Litton, and T. Miura. "Improved fuel moisture prediction in non-native tropical Megathyrsus maximus grasslands using Moderate-Resolution Imaging Spectroradiometer (MODIS)-derived vegetation indices." International Journal of Wildland Fire 26, no. 5 (2017): 384. http://dx.doi.org/10.1071/wf16131.

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The synergistic impacts of non-native grass invasion and frequent human-derived wildfires threaten endangered species, native ecosystems and developed land throughout the tropics. Fire behaviour models assist in fire prevention and management, but current models do not accurately predict fire in tropical ecosystems. Specifically, current models poorly predict fuel moisture, a key driver of fire behaviour. To address this limitation, we developed empirical models to predict fuel moisture in non-native tropical grasslands dominated by Megathyrsus maximus in Hawaii from Terra Moderate-Resolution

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Stanton, Neville A., James W. Brown, Kirsten M. A. Revell, et al. "Modelling Automation–Human Driver Handovers Using Operator Event Sequence Diagrams." Future Transportation 1, no. 2 (2021): 351–69. http://dx.doi.org/10.3390/futuretransp1020020.

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This research aims to show the effectiveness of Operator Event Sequence Diagrams (OESDs) in the normative modelling of vehicle automation to human drivers’ handovers and validate the models with observations from a study in a driving simulator. The handover of control from automation to human operators has proved problematic, and in the most extreme circumstances catastrophic. This is currently a topic of much concern in the design of automated vehicles. OESDs were used to inform the design of the interaction, which was then tested in a driving simulator. This test provided, for the first time

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Li, Yi, and Yuren Chen. "A New Method Based on Field Strength for Road Infrastructure Risk Assessment." Journal of Advanced Transportation 2018 (September 25, 2018): 1–13. http://dx.doi.org/10.1155/2018/6379146.

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Because road infrastructures have significant impact on driving safety, their risk levels need to be evaluated dynamically according to drivers’ perception. To achieve this, this paper proposes two field strength models to quantify the impact of road infrastructures on drivers. First, road infrastructures are classified into two types (continuous and discrete). Then, two field strength models for these types are proposed. Continuous field strength model describes the impact of long-belt-shape infrastructure by differential and integral methods. Discrete field strength model describes the stati

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Harri, Ardian, Drini Imami, and Edvin Zhllima. "The effect of the COVID-19 pandemic on consumer savings and retail sales: Evidence from a postcommunist transition economy." Ekonomski anali 67, no. 233 (2022): 39–59. http://dx.doi.org/10.2298/eka2233039h.

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When coupled with strong external shocks such as COVID-19, the high levels of uncertainty that characterise fragile economies can have a strong impact on household consumption and saving behaviour. This paper analyses household consumption and saving behaviour in conjunction with COVID-19 in the context of a post-communist economy. Models and intervention analysis are used to identify the effect of catastrophic events such as the COVID-19 pandemic on two key macroeconomic measures for the Albanian economy. The findings show that the pandemic period caused a significant contraction of consumer

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