Abstract

TRB 2014 - Transportation Research Board 93rd Annual Meeting, WASHINGTON D.C, ETATS-UNIS, 12-/01/2014 - 16/01/2014; An empirical analysis is conducted on lane changing behavior using a trajectory data set collected at a weaving section in Grenoble (France). A detailed literature review shows that strong empirical understanding of the weaving mechanisms is still lacking. The goal is to investigate the lane changing behavior at a microscopic level. Data collection distinguished lane changes from the main road and those towards the main road. Descriptive empirical analysis examines the positions of the lane changes and the corresponding accepted gaps. Results show that under heavy congested traffic conditions the weaving vehicles tend to change lane as soon as possible after the start of the weaving section. When the traffic conditions are fluid, the weaving vehicles coming from the main road tend to change lane earlier than the weaving vehicles coming from the auxiliary lane. Moreover, weaving vehicles coming from the auxiliary lane accept smaller gaps and headways than the weaving vehicles coming from the main road. Our findings are questioning some results of previous works using micro-simulation to study weaving sections. As the weaving vehicles change lane at the beginning of the studied weaving section, our findings ask whether the length of the weaving section is a key variable to estimate its capacity. Our findings raise also some questions about the relevance of the gap acceptance theory to model lane changes at weaving sections. But further research are needed to asses these hypothesis.

Abstract

The 21st IEEE International Conference on Intelligent Transportation Systems, Maui - Hawaï, Etats-Unis, 04-/11/2018 - 07/11/2018; The continuous increase in air traffic is pressuring airport operators to augment their capacity while still complying with safety regulations. To achieve this goal, operators need a thorough knowledge of how the airport surface is put to use (i.e., how aircraft are routed) under various conditions. We propose an approach to characterizing traffic in an airport from radar-collected aircraft ground trajectories. The approach does not require prior knowledge of the airport's topology (since it reconstructs it from the available data) and uses network constrained trajectory clustering to produce groups of similar trajectories that represent frequently traveled routes in the airport. Our main findings from experimental results on real data from the Paris-Charles-de-Gaulle airport (France) indicate that the retrieved routes are highly linked to exploitation constraints (maneuver undertaken by the aircraft, runway, and configuration) and that the approach can help uncover the existence of less traveled alternative routes that can be useful for rerouting purposes.