Liu, Zelin (Tongji University), Zeng, Mengyuan (Tongji University), Zhao, Hongduo (Tongji University), Xiao, An (Tongji University)

Field Study on the Lateral Distribution of Aircraft Based on Measured Data

Scheduled for presentation during the Invited Session "S20c-Foundation Model-Enabled Scene Understanding, Reasoning, and Decision-Making for Autonomous Driving and ITS" (TH-LA-T20), Thursday, November 20, 2025, 16:00−16:20, Surfers Paradise 2

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Abstract

This study conducted continuous monitoring of the lateral distribution of aircraft wheel-paths at a major hub airport in China using laser measurement technology. Through probability statistics and the Kolmogorov–Smirnov test, the distribution characteristics under different conditions were analyzed, focusing on aircraft type, operational period, speed, and pavement wetness. Results show that during takeoff and landing, the average lateral distance between the nosewheel and the runway centerline for five aircraft types was less than 0.43 m, with landing distributions closer to normality than takeoff. The standard deviation of wheel-paths was smaller during takeoff (0.91~1.13 m) than during landing (1.45~1.89 m). Aircraft alignment was better during daytime than nighttime, while nighttime takeoffs exhibited larger lateral dispersion. At speeds below 140 km/h, lateral deviations remained within 2 m, whereas at higher speeds they extended within 4 m. Wheel-paths were more concentrated under dry pavement conditions (standard deviation 0.74 m) and more dispersed under wet conditions (standard deviation 2.00 m). These findings emphasize the importance of continuous dynamic monitoring to optimize ACR-PCR parameters, enhance pavement design precision, and support dynamic load monitoring and runway structural health monitoring for smart airport development.