activity
20202026
most citedRoadway Design Matters: Variation in Bicyclists' Psycho-Physiological Responses in Different Urban Roadway Designs

48 citations · 117 across the 22 of their papers we have counts for

collaborators

23 papers

cs.CV2026

UAV-Based Infrastructure Inspections: A Literature Review and Proposed Framework for AEC+FM

Amir Farzin Nikkhah, Dong Chen, Bradford Campbell +2

Unmanned Aerial Vehicles (UAVs) are transforming infrastructure inspections in the Architecture, Engineering, Construction, and Facility Management (AEC+FM) domain. By synthesizing…

cs.CV2025★ 1 cited

Real-Time Roadway Obstacle Detection for Electric Scooters Using Deep Learning and Multi-Sensor Fusion

Zeyang Zheng, Arman Hosseini, Dong Chen +2

The increasing adoption of electric scooters (e-scooters) in urban areas has coincided with a rise in traffic accidents and injuries, largely due to their small wheels, lack of sus…

eess.SP2025★ 1 cited

Detecting Plant VOC Traces Using Indoor Air Quality Sensors

Seyed Hamidreza Nabaei, Ryan Lenfant, Viswajith Govinda Rajan +4

In the era of growing interest in healthy buildings and smart homes, the importance of sustainable, health conscious indoor environments is paramount. Smart tools, especially VOC s…

cs.CV2025★ 1 cited

Multimodal Data Integration for Sustainable Indoor Gardening: Tracking Anyplant with Time Series Foundation Model

Seyed Hamidreza Nabaei, Zeyang Zheng, Dong Chen +1

Indoor gardening within sustainable buildings offers a transformative solution to urban food security and environmental sustainability. By 2030, urban farming, including Controlled…

cs.HC2025★ 1 cited

Adoption of AI-Assisted E-Scooters: The Role of Perceived Trust, Safety, and Demographic Drivers

Amit Kumar, Arman Hosseini, Arghavan Azarbayjani +2

E-scooters have become a more dominant mode of transport in recent years. However, the rise in their usage has been accompanied by an increase in injuries, affecting the trust and…

cs.CY2024

Impact of Road Infrastructure and Traffic Scenarios on E-scooterists' Riding and Gaze Behavior

Dong Chen, Arman Hosseini, Arik Smith +5

The growing adoption of e-scooters has raised significant safety concerns, particularly due to a surge in injuries and fatalities. This study explores the relationship between road…

cs.CV2024★ 2 cited

Performance Evaluation of Real-Time Object Detection for Electric Scooters

Dong Chen, Arman Hosseini, Arik Smith +4

Electric scooters (e-scooters) have rapidly emerged as a popular mode of transportation in urban areas, yet they pose significant safety challenges. In the United States, the rise…

cs.CV2024★ 2 cited

WcDT: World-centric Diffusion Transformer for Traffic Scene Generation

Chen Yang, Yangfan He, Aaron Xuxiang Tian +5

In this paper, we introduce a novel approach for autonomous driving trajectory generation by harnessing the complementary strengths of diffusion probabilistic models (a.k.a., diffu…

cs.HC2023★ 1 cited

Unveiling the Impact of Cognitive Distraction on Cyclists Psycho-behavioral Responses in an Immersive Virtual Environment

Xiang Guo, Arash Tavakoli, T. Donna Chen +1

The National Highway Traffic Safety Administration reported that the number of bicyclist fatalities has increased by more than 35% since 2010. One of the main reasons associated wi…

eess.SP2023

Building Performance Simulations Can Inform IoT Privacy Leaks in Buildings

Alan Wang, Bradford Campbell, Arsalan Heydarian

As IoT devices become cheaper, smaller, and more ubiquitously deployed, they can reveal more information than their intended design and threaten user privacy. Indoor Environmental…

cs.CR2023★ 5 cited

Exploring Smart Commercial Building Occupants' Perceptions and Notification Preferences of Internet of Things Data Collection in the United States

Tu Le, Alan Wang, Yaxing Yao +4

Data collection through the Internet of Things (IoT) devices, or smart devices, in commercial buildings enables possibilities for increased convenience and energy efficiency. Howev…

cs.HC2022★ 23 cited

Occupant Privacy Perception, Awareness, and Preferences in Smart Office Environments

Beatrice Li, Arash Tavakoli, Arsalan Heydarian

Building management systems tout numerous benefits, such as energy efficiency and occupant comfort but rely on vast amounts of data from various sensors. Advancements in machine le…

cs.HC2022★ 1 cited

The Hitchiker's Guide to Successful Living Lab Operations

Alan Wang, Feng Yi Chang, Siavash Yousefi +3

Living labs have been established across different countries to evaluate how the interaction between humans and buildings can be optimized to improve comfort, health, and energy sa…

cs.HC2022★ 1 cited

Rethinking infrastructure design: Evaluating pedestrians and VRUs' psychophysiological and behavioral responses to different roadway designs

Xiang Guo, Austin Angulo, Arash Tavakoli +3

The integration of human-centric approaches has gained more attention recently due to more automated systems being introduced into our built environments (buildings, roads, vehicle…

cs.HC2022★ 1 cited

How are Drivers' Stress Levels and Emotions Associated with the Driving Context? A Naturalistic Study

Arash Tavakoli, Nathan Lai, Vahid Balali +1

Understanding and mitigating drivers' negative emotions, stress levels, and anxiety is of high importance for decreasing accident rates, and enhancing road safety. While detecting…

cs.HC2022

The Impact of Surrounding Road Objects and Conditions on Drivers Abrupt Heart Rate Changes

Arash Tavakoli, Arsalan Heydarian

Recent studies have pointed out the importance of mitigating drivers stress and negative emotions. These studies show that certain road objects such as big vehicles might be associ…

cs.LG2022★ 1 cited

Using Statistical Models to Detect Occupancy in Buildings through Monitoring VOC, CO, and other Environmental Factors

Mahsa Pahlavikhah Varnosfaderani, Arsalan Heydarian, Farrokh Jazizadeh

Dynamic models of occupancy patterns have shown to be effective in optimizing building-systems operations. Previous research has relied on CO sensors and vision-based technique…

cs.HC2022★ 1 cited

Driver State Modeling through Latent Variable State Space Framework in the Wild

Arash Tavakoli, Steven Boker, Arsalan Heydarian

Analyzing the impact of the environment on drivers' stress level and workload is of high importance for designing human-centered driver-vehicle interaction systems and to ultimatel…

cs.HC2022★ 48 cited

Roadway Design Matters: Variation in Bicyclists' Psycho-Physiological Responses in Different Urban Roadway Designs

Xiang Guo, Arash Tavakoli, Erin Robartes +3

As a healthier and more sustainable way of mobility, cycling has been advocated by literature and policy. However, current trends in bicyclist crash fatalities suggest deficiencies…

cs.HC2021★ 15 cited

ORCLSim: A System Architecture for Studying Bicyclist and Pedestrian Physiological Behavior Through Immersive Virtual Environments

Xiang Guo, Austin Angulo, Erin Robartes +2

Injuries and fatalities for vulnerable road users, especially bicyclists and pedestrians, are on the rise. To better inform design for vulnerable road users, we need to conduct mor…

cs.HC2021★ 1 cited

Multimodal Driver State Modeling through Unsupervised Learning

Arash Tavakoli, Arsalan Heydarian

Naturalistic driving data (NDD) can help understand drivers' reactions to each driving scenario and provide personalized context to driving behavior. However, NDD requires a high a…

cs.HC2021

Driver State and Behavior Detection Through Smart Wearables

Arash Tavakoli, Shashwat Kumar, Mehdi Boukhechba +1

Integrating driver, in-cabin, and outside environment's contextual cues into the vehicle's decision making is the centerpiece of semi-automated vehicle safety. Multiple systems hav…

cs.CY2020★ 11 cited

A Survey Study to Understand Industry Vision for Virtual and Augmented Reality Applications in Design and Construction

Mojtaba Noghabaei, Arsalan Heydarian, Vahid Balali +1

With advances in Building Information Modeling (BIM), Virtual Reality (VR) and Augmented Reality (AR) technologies have many potential applications in the Architecture, Engineering…