Tag: Research Area: Safety of Transportation Systems

Work Zone Safety: Virtual reality-based traffic co-simulation platform for workforce training and pedestrian behavior analysis

Molly

Building off of the research team’s previous work on a smartwatch alarm application and worker attention monitoring system, this project will expand the scope to a) understand workers’ behaviors to modalities of alarms in real physical work environments, and b) improve the VR based traffic co-simulation platform to co-simulate workers position in SUMO in real time as obstacles to be recognized and calibrate the vehicle trajectories in SUMO through larger work zone/traffic vehicle trajectory datasets.

Finite Element Analyses and Crash Testing of NYSDOT Bridge Railing and Barrier (MASH 2016)

MollyLeave a Comment on Finite Element Analyses and Crash Testing of NYSDOT Bridge Railing and Barrier (MASH 2016)

The AASHTO-FHWA Joint Agreement for the Implementation of MASH 2016 requires that any roadside safety hardware (guide rail, bridge rail, transitions, attenuators, etc.) to be installed on the National Highway System must be MASH-compliant. Transitions were not previously required to be crash tested, so the NYSDOT designs needs to be.

Calibration/Development of Safety Performance Functions for New Jersey

Elena ChungLeave a Comment on Calibration/Development of Safety Performance Functions for New Jersey

Safety Performance Functions (SPFs) in the Highway Safety Manual (HSM) were developed using historic crash data collected in different states. Because local state or geographic conditions vary, to make the SPFs better accommodate the local data, two strategies are usually undertaken: the first strategy is to calibrate SPFs provided in HSM so that the contents of HSM can be fully leveraged and the second strategy is to develop location-specific SPFs regardless of the predictive modeling framework in the HSM.

Development of Mountable Sensors to Improve Bicyclist Safety

Elena Chung

These new sensors are focused on obtaining data about the bicyclist’s behavior, which will complement the current data and contribute to new findings. An iOS platform is also being developed to track the devices and visualize real-time data collected with them. More units are expected to be implemented into the device in the near future for crowdsourcing.