63 citations · 69 across the 8 of their papers we have counts for
9 papers
Ordered-logit pedestrian stress model for traffic flow with automated vehicles
Kimia Kamal, Bilal Farooq, Mahwish Mudassar +1
An ordered-logit model is developed to study the effects of Automated Vehicles (AVs) in the traffic mix on the average stress level of a pedestrian when crossing an urban street at…
Analysis of pedestrian stress level using GSR sensor in virtual immersive reality
Mahwish Mudassar, Arash Kalatian, Bilal Farooq
Level of emotional arousal of one's body changes in response to external stimuli in an environment. Given the risks involved while crossing streets, particularly at unsignalized mi…
Multi-task Recurrent Neural Networks to Simultaneously Infer Mode and Purpose in GPS Trajectories
Ali Yazdizadeh, Arash Kalatian, Zachary Patterson +1
Multi-task learning is assumed as a powerful inference method, specifically, where there is a considerable correlation between multiple tasks, predicting them in an unique framewor…
A context-aware pedestrian trajectory prediction framework for automated vehicles
Arash Kalatian, Bilal Farooq
With the unprecedented shift towards automated urban environments in recent years, a new paradigm is required to study pedestrian behaviour. Studying pedestrian behaviour in futuri…
Decoding pedestrian and automated vehicle interactions using immersive virtual reality and interpretable deep learning
Arash Kalatian, Bilal Farooq
To ensure pedestrian friendly streets in the era of automated vehicles, reassessment of current policies, practices, design, rules and regulations of urban areas is of importance.…
DeepWait: Pedestrian Wait Time Estimation in Mixed Traffic Conditions Using Deep Survival Analysis
Arash Kalatian, Bilal Farooq
Pedestrian's road crossing behaviour is one of the important aspects of urban dynamics that will be affected by the introduction of autonomous vehicles. In this study we introduce…
Analysis of distracted pedestrians' waiting time: Head-Mounted Immersive Virtual Reality application
Arash Kalatian, Anae Sobhani, Bilal Farooq
This paper analyzes the distracted pedestrians' waiting time before crossing the road in three conditions: 1) not distracted, 2) distracted with a smartphone and 3) distracted with…
A semi-supervised deep residual network for mode detection in Wi-Fi signals
Arash Kalatian, Bilal Farooq
Due to their ubiquitous and pervasive nature, Wi-Fi networks have the potential to collect large-scale, low-cost, and disaggregate data on multimodal transportation. In this study,…
Mobility Mode Detection Using WiFi Signals
Arash Kalatian, Bilal Farooq
We utilize Wi-Fi communications from smartphones to predict their mobility mode, i.e. walking, biking and driving. Wi-Fi sensors were deployed at four strategic locations in a clos…