This research investigates the physiological stress of e-scooter riders using virtual reality to simulate dynamic traffic conditions on a shared bike lane in Vienna. Over two months, data from 24 participants using a custom e-scooter simulator and biometric sensors were analyzed through mixed-effects modeling. The findings indicate that increased traffic volumes and complex infrastructure configurations elevate riders’ physiological stress, as evidenced by higher skin conductance levels. This elevation affected operational performance, reflected by reduced speeds under high-stress conditions. Additionally, the results identified a cumulative effect of increased traffic volume, demonstrating that even minor fluctuations can lead to substantial changes in riders’ physiological stress. These insights into factors shaping e-scooter riders’ physiological responses provide evidence for analyzing accidents and risky behaviors from a psychophysiological perspective and may guide the development of interventions to enhance e-scooter comfort, safety and integration in shared road spaces.