Increasing Work Zone Safety: Worker behavioral analysis with integration of wearable sensors and virtual reality


According to the Federal Highway Administration (FHWA), work zone fatalities at road construction projects account for up to 3% of all workplace fatalities in a given year, and the primary causes are runovers/backovers, collisions, and caught in-between mobile equipment. One of the main proactive approaches adopted by construction companies to prevent these incidents is safety training courses, which are designed to help increase workers’ awareness of hazards around the job sites and take timely actions to avoid injuries. However, work zone safety knowledge from training courses is not enough to change the level of vigilance of workers, which is easily affected by factors such as fatigue or environmental distractions. With the development of wearable technologies, an increasing number of research studies have been exploring the feasibility of using wearable sensors to detect workers’ attention and vigilance towards job site hazards. However, merely measuring workers’ awareness of hazards is not sufficient. There is still a need to understand key parameters that impact worker and driver behaviors regarding received alarms/warnings/notifications and design notification systems that are calibrated for the optimal time, frequency, and modality to push information on potential hazards at work zones.

With the goal of reducing the number of injuries and fatalities, this project aims to understand the key parameters (e.g., work zone location characteristics, personal vigilance levels, types of construction work) that play roles in achieving responsive behaviors in workers. Key questions this research will address include in what conditions people ignore or respond to warnings, how notification systems can be calibrated for getting responsive actions from workers, and what modalities, frequencies, and timings of pushing notifications are most effective. Through wearable sensors and realistic representations of work zones in virtual reality, we plan to collect worker behavioral and physiological (heart rate) responses to warnings issued under various realistic scenarios and various warning mechanisms.

Research Objectives

This project’s objectives include:

  • Define the key factors that influence the reaction of workers and drivers in and around work zones to warning notifications received
  • Evaluate the effectiveness of wearable sensors and virtual reality in determining the key factors that influence the reactions of workers and drivers to notifications
  • Calibrate notification mechanisms using reinforcement learning

To achieve these objectives, the research methodology includes:

  • Development of a mobile application to be deployed on smart watches/wearable wristbands to collect integrated data on driver/worker choices and bodily states (heart rate, body temperature)
  • Design of virtual environments simulating highway work zone scenarios by changing work zone location characteristics and type of construction activities
  • Development of a reinforcement learning model that builds off of the collected data on simulated scenarios to minimize incidents

Related Media



Associate Professor, NYU

Semiha Ergan is the Principal Investigator on this project.

Yubin Shen

Research Associate, NYU

Yubin Shen is an Researcher on this project.


Affiliated Researcher, NYU

Abdullah Kurkcu is a Co-Principal Investigator on this project.

Abdullah Kurkcu

Researcher, NYU

Abdullah Kurkcu is a Researcher on this project.

Kaan Ozbay

Director, C2SMART Professor, NYU

Kaan Ozbay is a Co-Principal Investigator on this project.

Zhengbo Zou

Researcher, NYU

Zhengbo Zou is a Researcher on this project.

Suzana Duran Bernardes

Researcher, NYU

Suzana Duran Bernardes is a Researcher on this project.