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Gotowe bibliografie tematyczne / Driver behaviour models

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Artykuły w czasopismach

Gotowa bibliografia na temat „Driver behaviour models”

Autor: Grafiati

Data publikacji: 6 września 2023

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Artykuły w czasopismach na temat "Driver behaviour models"

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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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