Searched for: author%3A%22Farah%2C+H.%22
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Dong, Y. (author), Lu, Xingmin (author), Li, Ruohan (author), Song, Wei (author), van Arem, B. (author), Farah, H. (author)
The burgeoning navigation services using digital maps provide great convenience to drivers. However, there are sometimes anomalies in the lane rendering map images, which might mislead human drivers and result in unsafe driving. To accurately and effectively detect the anomalies, this paper transforms lane rendering image anomaly detection into...
poster 2024
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Razmi Rad, S. (author), Farah, H. (author), Taale, Henk (author), van Arem, B. (author), Hoogendoorn, S.P. (author)
Dedicated Lanes (DLs) have been proposed as a potential alternative for the deployment of Connected and Automated Vehicles (CAVs) to facilitate platooning and increase motorway capacity. However, the impact of the presence and utilization policy of such a lane on drivers’ preference to use automation and their behaviour has not yet been...
journal article 2024
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Dong, Y. (author), Patil, Sandeep (author), Farah, H. (author), Hellendoorn, J. (author)
Lane detection serves as a fundamental task for automated vehicles and Advanced Driver Assistance Systems. However, current lane detection methods can not deliver the versatility of accurate, robust, and realtime compatible lane detection in real-world scenarios especially under challenging driving scenes. Available vision-based methods in the...
poster 2023
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Dong, Y. (author), Li, Ruohan (author), Farah, H. (author)
Lane detection is crucial for vehicle localization which makes it the foundation for automated driving and many intelligent and advanced driving assistant systems. Available vision-based lane detection methods do not make full use of the valuable features and aggregate contextual information, especially <br/>the interrelationships between lane...
poster 2023
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Raju, Narayana (author), van Beinum, Aries (author), Farah, H. (author)
Traffic microsimulation is a commonly used tool in traffic engineering. Given its flexibility and cost-efficiency, it is increasingly used for evaluating traffic safety. In real life traffic, unsafety is in many cases due to human error in driving behaviour. In traffic microsimulations however, driving behaviour is highly dependent on the...
poster 2023
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Sevenster, A.L.A. (author), Farah, H. (author), Abbink, D.A. (author), Zgonnikov, A. (author)
Overtaking on two-lane roads can lead to increased collision risks due to drivers' errors in evaluating whether or not to accept the gap to the vehicle in the opposite lane. Understanding these gap acceptance decisions can help mitigate the risks associated with overtaking. Previous research on overtaking has focused on the factors...
journal article 2023
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Oskina, M.I. (author), Farah, H. (author), Morsink, Peter (author), Happee, R. (author), van Arem, B. (author)
The operation of automated vehicles (AVs) on shared roads requires attention concerning their interactions with vulnerable road users (VRUs), such as cyclists. This study investigates the safety of cyclists when they interact with an AV and compares it with their interaction with a conventional vehicle. Overall, 29 cyclists participated in a...
journal article 2023
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Zhang, Lanxin (author), Dong, Y. (author), Farah, H. (author), Zgonnikov, A. (author), van Arem, B. (author)
Detecting abnormal driving behavior is critical for road traffic safety and the evaluation of drivers' behavior. With the advancement of machine learning (ML) algorithms and the accumulation of naturalistic driving data, many ML models have been adopted for abnormal driving behavior detection. Most existing ML-based detectors rely on (fully)...
poster 2023
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Wang, Y. (author), Farah, H. (author), Yu, Rongjie (author), Qiu, Shuhan (author), van Arem, B. (author)
Autonomous vehicles (AVs) are being introduced to the traffic system with the promise of improving current traffic status. However, the empirical data also indicate contrary effects with estimated higher crash rate and change of crash patterns. Therefore, it is necessary to investigate the driving behavior of AVs and human-driven vehicles ...
journal article 2023
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Farah, H. (author), Olstam, Johan (author), Zheng, Zuduo (author)
contribution to periodical 2023
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Zhang, Li (author), Dong, Y. (author), Farah, H. (author), van Arem, B. (author)
The gradual deployment of automated vehicles (AVs) results in mixed traffic where AVs will interact with human-driven vehicles (HDVs). Thus, social-aware motion planning and control while considering interactions with HDVs on the road is critical for AVs' deployment and safe driving under various maneuvers. Previous research mostly focuses on...
conference paper 2023
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Yuan, Henan (author), Li, Penghui (author), van Arem, B. (author), Kang, Liujiang (author), Farah, H. (author), Dong, Y. (author)
Traffic scenarios in roundabouts pose substantial complexity for automated driving. Manually mapping all possible scenarios into a state space is labor-intensive and challenging. Deep reinforcement learning (DRL) with its ability to learn from interacting with the environment emerges as a promising solution for training such automated driving...
conference paper 2023
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Zhang, Li (author), Dong, Y. (author), Farah, H. (author), van Arem, B. (author)
The gradual deployment of automated vehicles (AVs) results in mixed traffic where AVs will interact with human-driven vehicles (HDVs). Thus, social-aware motion planning and control while considering interactions with HDVs on the road is critical for AVs’ deployment and safe driving under various maneuvers. Previous research mostly focuses on...
poster 2023
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Mohammad, Samir H.A. (author), Farah, H. (author), Zgonnikov, A. (author)
Driving automation holds significant potential for enhancing traffic safety. However, effectively handling interactions with human drivers in mixed traffic remains a challenging task. Several models exist that attempt to capture human behavior in traffic interactions, often focusing on gap acceptance. However, it is not clear how models of an...
conference paper 2023
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Vos, J. (author), de Winter, J.C.F. (author), Farah, H. (author), Hagenzieker, Marjan (author)
Although much research is done on speed and gaze behaviour inside curves, there is little understanding of which cues drivers use to anticipate and slow down while approaching curves. Therefore, an on road experiment was conducted in which 31 participants drove through six freeway curves in their own car. During the experiment, look-ahead...
journal article 2023
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Afghari, A.P. (author), Vos, J. (author), Farah, H. (author), Papadimitriou, E. (author)
Driver anticipation plays a crucial role in crashes along horizontal curves. Anticipation is related to road predictability and can be influenced by roadway geometric design. Therefore, it is essential to understand which geometric design elements can influence anticipation and cause the road to be (un)predictable. This exercise, however, is not...
journal article 2023
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Papadimitriou, E. (author), Farah, H. (author), van de Kaa, G. (author), Santoni De Sio, F. (author), Hagenzieker, Marjan (author), van Gelder, P.H.A.J.M. (author)
Automated vehicles (AVs) aim to dramatically improve traffic safety by reducing or eliminating human error, which remains the leading cause of road crashes. However, commonly accepted standards for the ‘safe driving behaviour of machines’ are pending and urgently needed. Unless a common understanding of safety as a design value is achieved,...
journal article 2022
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Vos, J. (author), Farah, H. (author)
Road designers need to have insights where deceleration and acceleration are expected related to the position of the curve, and in in which amount so that drivers are able to safely decelerate and accelerate respectively into and out of a freeway curve. For this, empirical speed data is needed. Therefore, Floating Car Data in 153 curves in...
journal article 2022
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Dong, Y. (author), Patil, Sandeep (author), Farah, H. (author), van Arem, B. (author)
Reliable and accurate lane detection is of vital importance for the safe performance of Lane Keeping Assistance and Lane Departure Warning systems. However, under certain challenging peculiar circumstances (e.g., marking degradation, serious vehicle occlusion), it is quite difficult to get satisfactory performance in accurately detecting the...
poster 2022
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Wang, Y. (author), Yu, Rongjie (author), Qiu, Shuhan (author), SUN, J. (author), Farah, H. (author)
Highly automated vehicles (HAVs) have been introduced to the transportation system for the purpose of providing safer mobility. Considering the expected long co-existence period of HAVs and human-driven vehicles (HDVs), the safety operation of HAVs interacting with HDVs needs to be verified. To achieve this, HAVs' Operational Design Domain ...
journal article 2022
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