Learning vehicle trajectory uncertainty

Klein, Itzik

doi:10.1016/j.engappai.2023.106101

Cited by 7 publications

(1 citation statement)

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“…Recently, with the development of data collection devices and automatic extraction algorithms, an increasing number of scholars have employed high-precision trajectory data for the study of LC behaviors [38][39][40]. For example, ref.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Spatiotemporal Characteristics of Lane-Changing at the Freeway Weaving Area from Trajectory Data

Ouyang,

Yang

2024

Sustainability

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Intensive lane-changing (LC) events are one of the great causes that make freeway weaving areas become bottlenecks. This study proposes an approach using vehicle trajectory data to investigate the spatiotemporal distributions of the number of LC events, void occupancies, and throughput variations at the freeway weaving area. Firstly, all LC events are extracted from the cleaned dataset and classified into four types according to the LC vehicles’ origin–destination lanes and LC directions. Secondly, the time and space void occupancies are calculated using the kinematic theory. Thirdly, the throughput variations are identified with the oblique N-curve method. Finally, the spatial and temporal distributions of the LC events, void occupancies, and throughput variations are plotted to analyze their characteristics and relationships. The spatial distributions of different types of LC events indicate that most LC events occur at the surrounding area of the on-ramp entrance. Spatial distributions of time void occupancies show that the time void in the original lanes is quite small while that in the target lanes is much larger. Furthermore, the time void occupancies amplify downstream when considering vehicles traveling on the road. By comparing the temporal distributions of LC events, void occupancies, and throughput variations, there is a lag effect between the large value occurrences of space void occupancy and throughput reduction and that of the LC events, which can conclude a causal relationship between LC events and the occurrences of the space void occupancies and throughput reductions.

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Section: Introductionmentioning

confidence: 99%