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Profil bibliographique

Haneen Farah

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

184Publications signalées
3863Citations signalées
2Affiliations récentes

Les institutions déclarées

Les domaines associés

Traffic and Road SafetyTraffic control and managementHuman-Automation Interaction and SafetyAutonomous Vehicle Technology and SafetyTransportation Planning and Optimization

Les publications récentes

Accès ouvert 2026 article OpenAlex

Road safety capacity in Africa: benchmarking professional education through a Safe System lense

Aslak Fyhri, Anteneh Afework Mekonnen, Haneen Farah, Tor‐Olav Nævestad et autres

Africa faces a growing road safety crisis, with the highest global traffic fatality rates and a 17% increase in deaths between 2010 and 2021, in contrast to declining trends globally. Structural and institutional challenges, including weak crash data systems, limited use of …

no, nl, ro, se, Ghana, Tanzanie, Zambie (code pays fourni par la source)

0 citations Traffic Safety Research
Accès ouvert 2026 article OpenAlex

Interaction of road, traffic and environment in the operational design domain of lane support systems: hybrid factorial–observational design and causal analysis

Omid Ghaderi, Giuseppina Pappalardo, Alessandro Di Graziano, Giovanni Andrea Dimauro et autres

The Operational Design Domain (ODD) defines the conditions under which automated driving and driver-assistance systems are expected to operate. This study evaluates the ODD of a camera-based Lane Support System (LSS) using direct Mobileye 6.0 lane-detection quality outputs. A large-scale hybrid factorial–observational …

it, cn, nl (code pays fourni par la source)

0 citations Accident Analysis & Prevention
Accès ouvert 2026 article OpenAlex

Perception and response of cyclists interacting with autonomous electric vehicles - a virtual reality study

Yixin Sun, Haneen Farah, Yan Feng

Autonomous electric vehicles (AEVs) will increasingly characterize future motorized traffic in urban areas. These vehicles are often silent and can be driverless. Therefore, understanding the interactions between these vehicles and vulnerable road users (VRUs) is crucial for traffic safety. This study explores …

1 citation Transportation Research Part F Traffic Psychology and Behaviour
2026 conference-paper OpenAlex

Understanding Cycling Safety Perceptions:Response Scale Heterogeneity and Urban Street Design

D.T.L.; id_orcid 0009-0007-1711-4855 Andreoli, S.; id_orcid 0000-0001-8044-8654 Rasouli, R.P.; id_orcid 0000-0003-4847-9770 van Dongen, Haneen Farah

This presentation examines how cyclists perceive safety in different urban street environments and how these perceptions are shaped by infrastructure, traffic conditions, situational context, and individual response patterns. Using an image-based survey and a two-stage modelling approach, the study shows that perceived …

kr, nl (code pays fourni par la source)

0 citations TU/e Research Portal
Accès ouvert 2026 article OpenAlex

Safe System maturity and Safe System readiness in three European and three African countries: A comparison of an emerging versus a mature context

Tor‐Olav Nævestad, Enoch F. Sam, Haneen Farah, Daniel Mwamba et autres

The study provides a comparison of Safe System maturity and Safe System readiness in three European countries (Norway, Sweden, the Netherlands) and three African countries (Ghana, Tanzania, Zambia), based on document studies and focus group discussions (n = 73 interviewees and n …

no, Ghana, nl, Zambie, Tanzanie, se (code pays fourni par la source)

0 citations Transportation Research Interdisciplinary Perspectives
2026 article OpenAlex

Cyclists and Automated Vehicles' Interactions: Literature Review, Conceptual Framework, and Future Directions

Jinyang Zhao, Serge Paul Hoogendoorn, Haneen Farah

Future traffic will include automated vehicles (AVs) that will interact with other road users, including cyclists. These interactions need to be safe for AVs to be accepted by society. To accomplish this, the interaction process needs to be studied from both the …

nl (code pays fourni par la source)

0 citations IEEE Transactions on Intelligent Transportation Systems
Accès ouvert 2026 article OpenAlex

Calibration of car-following models of human driven vehicles interacting with automated vehicles in mixed traffic: a driving simulator experiment

Nagarjun Reddy, SP Hoogendoorn, Haneen Farah

The deployment of automated vehicles (AVs) on public roads remains limited due to concerns about their interaction with human-driven vehicles (HDVs) in mixed traffic. While previous studies suggest that AVs influence HDV behaviour, the nature of this influence is still not well …

nl (code pays fourni par la source)

0 citations Transportmetrica A Transport Science
Accès ouvert 2026 article OpenAlex

Riding the circle: Cyclists' perceived safety and comfort in urban roundabouts

Ian Trout, Maria Salomons, Amir Pooyan Afghari, Haneen Farah

Perceived safety and comfort influence cycling mode choice and behaviour. While roundabouts are associated with a decreased severity of motor vehicle crashes, recent crash data in the Netherlands suggests that this is not the case for bicycle crashes, with 12% of all …

ie, nl (code pays fourni par la source)

2 citations Transportation Research Part F Traffic Psychology and Behaviour
Accès ouvert 2026 preprint OpenAlex

Efficient Sequential Neural Network with Spatial-Temporal Attention and Linear LSTM for Robust Lane Detection Using Multi-Frame Images

Sandeep Patil, Yongqi Dong, Haneen Farah, J. Hellendoorn

Lane detection is a crucial perception task for all levels of automated vehicles (AVs) and Advanced Driver Assistance Systems, particularly in mixed-traffic environments where AVs must interact with human-driven vehicles (HDVs) and challenging traffic scenarios. Current methods lack versatility in delivering accurate, …

0 citations arXiv (Cornell University)
Accès ouvert 2026 preprint OpenAlex

Efficient Sequential Neural Network with Spatial-Temporal Attention and Linear LSTM for Robust Lane Detection Using Multi-Frame Images

Sandeep Patil, Yongqi Dong, Haneen Farah, J. Hellendoorn

Lane detection is a crucial perception task for all levels of automated vehicles (AVs) and Advanced Driver Assistance Systems, particularly in mixed-traffic environments where AVs must interact with human-driven vehicles (HDVs) and challenging traffic scenarios. Current methods lack versatility in delivering accurate, …

de, nl (code pays fourni par la source)

0 citations arXiv (Cornell University)

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