Zobrazeno 1 - 10
of 5 267
pro vyhledávání: '"Driving Behavior"'
Autor:
Thodoris Garefalakis, Eva Michelaraki, Stella Roussou, Christos Katrakazas, Tom Brijs, George Yannis
Publikováno v:
European Transport Research Review, Vol 16, Iss 1, Pp 1-13 (2024)
Abstract Road safety is a subject of significant concern and substantially affects individuals across the globe. Thus, real-time, and post-trip interventions have gained significant importance in the past few years. This study aimed to analyze differ
Externí odkaz:
https://doaj.org/article/2aa45d841fb940108b0fa9b2d8ae2bd8
Autor:
Radmila Magusic
Publikováno v:
Discover Civil Engineering, Vol 1, Iss 1, Pp 1-29 (2024)
Abstract Road safety is worldwide researched field where crashes play a causal role and injuries are counted as outcomes. Approaches and techniques are diverse, but with same goal—contribute to safer road environment for everyone included. Drivers
Externí odkaz:
https://doaj.org/article/b5b6aad38c9d48c4aa321b075312b680
Publikováno v:
Proceedings on Engineering Sciences, Vol 6, Iss 3, Pp 1349-1360 (2024)
Traffic Simulating and Evaluating Traffic Patterns at heterogeneous traffic Situations in the Indian Context is extremely increasing. Many researchers from all over the world are trying to explore driving behavior and simulate traffic flow conditions
Externí odkaz:
https://doaj.org/article/2afea95117bd4c46b48f7adb7db8e5d4
Autor:
Stella Roussou, Eva Michelaraki, Christos Katrakazas, Amir Pooyan Afghari, Christelle Al Haddad, Md Rakibul Alam, Constantinos Antoniou, Eleonora Papadimitriou, Tom Brijs, George Yannis
Publikováno v:
European Transport Research Review, Vol 16, Iss 1, Pp 1-13 (2024)
Abstract The i-DREAMS project focuses on establishing a framework known as the ‘Safety Tolerance Zone (STZ)’ to ensure drivers operate within safe boundaries. This study compares Long-Short-Term-Memory Networks and shallow Neural Networks to asse
Externí odkaz:
https://doaj.org/article/69b1b5004a5742908e65a1d3b5782965
Publikováno v:
In Transportation Research Part F: Psychology and Behaviour February 2025 109:439-457
Autor:
Efe Savran, Fatih Karpat
Publikováno v:
Ain Shams Engineering Journal, Vol 15, Iss 12, Pp 103060- (2024)
In this study, the generation of synthetic driving data that can reflect real behavior well using the Copula model was investigated. To see the difference in behavior patterns in the generated synthetic driving data, a feature correlation comparison
Externí odkaz:
https://doaj.org/article/f8d6ad8915114380a9fd941582bb397f
Publikováno v:
IEEE Access, Vol 12, Pp 56344-56355 (2024)
Driving behavior primitives play a crucial role in semantic explanation of driving behaviors. Although much work has been done on exacting driving behavior primitives from naturalistic driving data, few studies was published on primitive classificati
Externí odkaz:
https://doaj.org/article/fe631be0f8ac40febbaabdc916c4e6c2
Publikováno v:
International Journal of Transportation Science and Technology, Vol 14, Iss , Pp 219-236 (2024)
The aim of this paper is to understand the factors that influence unsafe driving practices by examining published studies that utilized the theory of planned behavior (TPB) to predict driving behavior. To this end, 42 studies published up to the end
Externí odkaz:
https://doaj.org/article/eacb88cd975740ba8676cf2e6bafbd24
Akademický článek
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Autor:
Byung hyun KIM, Kakeru TAKAHASHI, Hiroshi YOSHITAKE, Tomoya MURAKI, Yoshiro EGAMI, Motoki SHINO
Publikováno v:
Mechanical Engineering Journal, Vol 11, Iss 5, Pp 24-00151-24-00151 (2024)
To reduce unsafe driving among older drivers, clarifying the process and factors leading to such behaviors is essential. In this study, we proposed a method to express the process and factors leading to unsafe driving using Bayesian networks. In the
Externí odkaz:
https://doaj.org/article/ea12af5fd84b4a4f85af67434ecbb571