Impact of COVID-19 on Traffic Signal Systems: Survey of Agency Interventions and Observed Changes in Pedestrian Activity

Impacts of the COVID-19 Pandemic on Pedestrian Push-Button Utilization and Pedestrian Volume Model Accuracy in Utah

This work investigated the impacts of COVID-19 on pedestrian behavior, answering two research questions using pedestrian push-button data from Utah traffic signals: How did push-button utilization change during the early pandemic, owing to concerns over disease spread through high-touch surfaces? How did the accuracy of pedestrian volume estimation models (developed pre-COVID based on push-button traffic signal data) change during the early pandemic? To answer these questions, we first recorded videos, counted pedestrians, and collected push-button data from traffic signal controllers at 11 intersections in Utah in 2019 and 2020. We then compared changes in push-button presses per pedestrian (to measure utilization), as well as model prediction errors (to measure accuracy), between the two years. Our first hypothesis of decreased push-button utilization was partially supported. The changes in utilization at most (seven) signals were not statistically significant; yet, the aggregate results (using 10 of 11 signals) saw a decrease from 2.1 to 1.5 presses per person. Our second hypothesis of no degradation of model accuracy was supported. There was no statistically significant change in accuracy when aggregating across nine signals, and the models were actually more accurate in 2020 for the other two signals. Overall, we concluded that COVID-19 did not significantly deter people from using push-buttons at most signals in Utah, and that the pedestrian volume estimation methods developed in 2019 probably do not need to be recalibrated to work for COVID conditions. This information may be useful for public health actions, signal operations, and pedestrian planning.

A UWB/INS Trajectory Tracking System Application in a Cycling Safety Study

This paper focuses on the safety issue for cyclists and pedestrians at unsignalized intersections. The cycling speed needs to be calmed when approaching the intersection. This study proposes and deploys an integrated portable ultra-wideband/inertial navigation system (UWB/INS) to extract cycling trajectories for a cycling safety study. The system is based on open-source hardware and delivers an open-source code for an adaptive Kalman filter to enhance positioning precision for data quality assurance at an outdoor experimental site. The results demonstrate that the system can deliver reliable trajectories for low-mobility objects. To mitigate accident risk and severity, varied cycling speed calming measures are tested at an experimental site. Based on the trajectory data, the statistical features of cycling velocities are evaluated and compared. A new proposed geometric design is found to be most effective when compared with conventional traffic signs.