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Digital capability and organisational resilience as drivers of project performance: a structural equation modelling approach. [PDF]
Sci RepWang Z, Li D, Huo J.
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Modified Intelligent Driver Model for driver safety and traffic stability improvement
IFAC Postprint Volumes IPPV / International Federation of Automatic Control, 2013 The Intelligent Driver Model (IDM) is an Adaptive Cruise Control (ACC) model which is widely used for longitudinal vehicle motion modeling. The IDM presents important advantages against the other ACC models which are the availability and the intuitive of its parameters.
Tamás Peter
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Analysis of the Generalized Intelligent Driver Model (GIDM) for merging situations
2021 IEEE Intelligent Vehicles Symposium (IV), 2021In this paper, we propose and analyze a Generalized Intelligent Driver Model (GIDM) as an extension of the Intelligent Driver Model (IDM) for its applicability to model merging scenarios. For this purpose, we extend the original longitudinal car-following IDM with several terms: (1) for anticipatory acceleration capabilities, we include the most nearby
Karsten Kreutz, Julian Eggert
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Driver Behavior Model Based on Ontology for Intelligent Transportation Systems
2015 IEEE 8th International Conference on Service-Oriented Computing and Applications (SOCA), 2015Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element that affects road safety is driver behavior, because driver errors are usually the principal cause of traffic accidents.
Susel Fernández, Takayuki Itô
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An intelligent driver model with trajectory planning
2012 15th International IEEE Conference on Intelligent Transportation Systems, 2012This paper presents an overall concept and framework of a driver model with the intent to generate realistic traffic flow and motion while reflecting the nature of driving characteristics. The proposed driver model simulates a driver's driving on the road with proper trajectory planning mechanism that takes into account the surrounding environment ...
Sumin Zhang +4 more
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Integrating Human Panic Factor in Intelligent Driver Model
2020 3rd International Conference on Advancements in Computational Sciences (ICACS), 2020This study aims to explore the effects of human panic factor on drivers' driving behavior. Most of the car following models focus on idealistic situations aiming for perfection, traffic psychology, however, suggests that emotions do play a significant role in drivers' behavior which in result effect their driving and decision making.
Hifsa Tanveer +2 more
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Analysis of the Generalized Intelligent Driver Model (GIDM) for Uncontrolled Intersections
2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021This paper proposes a Generalized Intelligent Driver Model (GIDM) as an extension of the Intelligent Driver Model (IDM) and analyzes its applicability to model uncontrolled intersection scenarios. We extend the original longitudinal car-following IDM with several terms: (1) for anticipatory acceleration capabilities, we include the most nearby backward
Karsten Kreutz, Julian Eggert
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Driver intent inference at urban intersections using the intelligent driver model
2012 IEEE Intelligent Vehicles Symposium, 2012Predicting turn and stop maneuvers of potentially errant drivers is a basic requirement for advanced driver assistance systems for urban intersections. Previous work has shown that an early estimate of the driver's intent can be inferred by evaluating the vehicle's speed during the intersection approach. In the presence of a preceding vehicle, however,
Martin Liebner +3 more
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