Akademik Veri Yönetim Sistemi
2nd International Conference on Optimization and Data Science in Industrial Engineering, ODSIE 2024, Virtual, Online, 7 - 08 Kasım 2024, cilt.2482 CCIS, ss.197-216, (Tam Metin Bildiri)
In recent years, the use of personal mobility devices, particularly electric scooters, has become increasingly popular, especially for short-distance travel commonly referred to as the “last mile.” This growing trend has led to complex interactions between scooter riders and pedestrians, as pedestrians often exhibit unpredictable behavior, such as remaining stationary or walking at varying speeds, which increases the risk of collisions with fast-moving scooters. These interactions can lead to disturbances in pedestrian flow, irritation, or even accidents, particularly in environments lacking effective regulation or infrastructure. This study presents an advanced prediction model for pedestrian movement and the dynamics between pedestrians and electric scooters. The model is an enhanced version of the Social Force Model, incorporating the distinct movement characteristics of electric scooters, such as high speed and rapid acceleration, especially on curved roads. Simulation results showed that in low-density pedestrian environments, personal mobility devices can overtake pedestrians without significant disruptions, whereas in high-density areas, scooters and Segways face challenges overtaking pedestrians due to congestion. This study also highlights that pedestrian density plays a crucial role in the movement dynamics of electric scooters, with congestion reducing their ability to navigate efficiently. The results provide valuable insights into pedestrian safety risks, such as collisions and congestion, and offer a deeper understanding of mobility dynamics in urban environments. The findings emphasize the need for improved infrastructure and regulation to ensure safe and efficient coexistence of pedestrians and personal mobility devices.