Engineering Commons^™

Enhancing Pedestrian-Autonomous Vehicle Safety In Low Visibility Scenarios: A Comprehensive Simulation Method, Zizheng Yan, Yang Liu, Hong Yang

Modeling, Simulation and Visualization Student Capstone Conference

Self-driving cars raise safety concerns, particularly regarding pedestrian interactions. Current research lacks a systematic understanding of these interactions in diverse scenarios. Autonomous Vehicle (AV) performance can vary due to perception accuracy, algorithm reliability, and environmental dynamics. This study examines AV-pedestrian safety issues, focusing on low visibility conditions, using a co-simulation framework combining virtual reality and an autonomous driving simulator. 40 experiments were conducted, extracting surrogate safety measures (SSMs) from AV and pedestrian trajectories. The results indicate that low visibility can impair AV performance, increasing conflict risks for pedestrians. AV algorithms may require further enhancements and validations for consistent safety performance …

The Effects Of External Motivation And Real-Time Automated Feedback On Speeding Behavior In A Naturalistic Setting, Ian J. Reagan, James P. Bliss, Ron Van Houten, Bryan W. Hilton

Psychology Faculty Publications

Objective: In this field experiment, the authors tested an alerting system and a monetary incentive system with the objective of reducing speeding more than 5 mph faster than the posted speed limit.

Background: Speeding is a factor in a significant number of traffic fatalities. The systems tested in this project have been evaluated outside but not within the United States. These studies indicated that similar systems led to reductions in speeding.

Method: For this study, eight vehicles were instrumented such that vehicle speed and speed limits were linked in real time. A total of 50 participants drove assigned vehicles for …