activity
20182026
most citedA Hybrid Spatial-temporal Deep Learning Architecture for Lane Detection

49 citations · 59 across the 11 of their papers we have counts for

collaborators

11 papers

cs.HC2026

Linking Behaviour and Perception to Evaluate Meaningful Human Control over Partially Automated Driving

Ashwin George, Lucas Elbert Suryana, Lorenzo Flipse +5

Partial driving automation creates a tension: drivers remain legally responsible while being less active in control. Meaningful human control (MHC), a normative framework that can…

cs.RO2026

Beyond Conservative Automated Driving in Multi-Agent Scenarios via Coupled Model Predictive Control and Deep Reinforcement Learning

Saeed Rahmani, Gözde Körpe, Zhenlin +4

Automated driving at unsignalized intersections is challenging due to complex multi-vehicle interactions and the need to balance safety and efficiency. Model Predictive Control (MP…

cs.AI2026

CARE Drive A Framework for Evaluating Reason-Responsiveness of Vision Language Models in Automated Driving

Lucas Elbert Suryana, Farah Bierenga, Sanne van Buuren +6

Foundation models, including vision language models, are increasingly used in automated driving to interpret scenes, recommend actions, and generate natural language explanations.…

eess.SY2025

A Framework for Ethical Decision-Making in Automated Vehicles through Human Reasons-based Supervision

Lucas Elbert Suryana, Saeed Rahmani, Simeon Craig Calvert +2

Ethical dilemmas are a common challenge in everyday driving, requiring human drivers to balance competing priorities such as safety, efficiency, and rule compliance. However, much…

cs.CY2025

Principles and Reasons Behind Automated Vehicle Decisions in Ethically Ambiguous Everyday Scenarios

Lucas Elbert Suryana, Simeon Calvert, Arkady Zgonnikov +1

Automated vehicles (AVs) increasingly encounter ethically ambiguous situations in everyday driving--scenarios involving conflicting human interests and lacking clearly optimal cour…

cs.RO2025★ 3 cited

Towards Developing Socially Compliant Automated Vehicles: Advances, Expert Insights, and A Conceptual Framework

Yongqi Dong, Bart van Arem, Haneen Farah

Automated Vehicles (AVs) hold promise for revolutionizing transportation by improving road safety, traffic efficiency, and overall mobility. Despite the steady advancement in high-…

cs.RO2024★ 5 cited

Automated Vehicles at Unsignalized Intersections: Safety and Efficiency Implications of Mixed Human and Automated Traffic

Saeed Rahmani, Zhenlin Xu, Simeon C. Calvert +1

The integration of automated vehicles (AVs) into transportation systems presents an unprecedented opportunity to enhance road safety and efficiency. However, understanding the inte…

cs.CV2021★ 49 cited

A Hybrid Spatial-temporal Deep Learning Architecture for Lane Detection

Yongqi Dong, Sandeep Patil, Bart van Arem +1

Accurate and reliable lane detection is vital for the safe performance of lane-keeping assistance and lane departure warning systems. However, under certain challenging circumstanc…

physics.soc-ph2021

Ride Acceptance Behaviour of Ride-sourcing Drivers

Peyman Ashkrof, Gonçalo Homem de Almeida Correia, Oded Cats +1

The performance of ride-sourcing services such as Uber and Lyft is determined by the collective choices of individual drivers who are not only chauffeurs but private fleet provider…

eess.SY2020★ 1 cited

Managing connected and automated vehicles with flexible routing at "lane-allocation-free'' intersections

Wanjing Ma, Ruochen Hao, Chunhui Yu +2

Trajectory planning and coordination for connected and automated vehicles (CAVs) have been studied at isolated ``signal-free'' intersections and in ``signal-free'' corridors under…

math.PR2018★ 1 cited

Generalized Multivariate Extreme Value Models for Explicit Route Choice Sets

Erik-Sander Smits, Adam J. Pel, Michiel C. J. Bliemer +1

This paper analyses a class of route choice models with closed-form probability expressions, namely, Generalized Multivariate Extreme Value (GMEV) models. A large group of these mo…