Vehicle trajectory clustering for traffic intersection surveillance

Choong, Mei Yeen; Angeline, Lorita; Chin, Renee Ka Yin; Yeo, Kiam Beng; Teo, Kenneth Tze Kin

doi:10.1109/icce-asia.2016.7804776

Cited by 14 publications

(4 citation statements)

References 4 publications

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“…Furthermore, the problem of trajectory maps was also approached, almost simultaneously, by other communities, that is, data mining (Chen et al, 2011(Chen et al, , 2012Gaffney and Smyth, 1999;Li et al, 2010;Nanni and Pedreschi, 2006;Pelekis et al, 2009Pelekis et al, , 2017Tang et al, 2019Tang et al, , 2020, intelligent transportation systems (Atev et al 2010;Choong et al 2016Choong et al , 2017Li et al, 2006;Portugal et al, 2020;Song et al, 2017;Wang et al, 2019Wang et al, , 2020Won et al, 2009), air traffic (Enriquez and Kurcz, 2012), and maritime traffic (Dutt et al, 2018;Kontopoulos et al, 2021;Liu et al, 2014a;Li et al, 2017). The detailed discussion regarding relevant publications coming from these fields is presented in Section 7.…”

Section: Trajectorymentioning

confidence: 99%

Survey of maps of dynamics for mobile robots

Kucner

Magnusson

Mghames

et al. 2023

The International Journal of Robotics Research

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Robotic mapping provides spatial information for autonomous agents. Depending on the tasks they seek to enable, the maps created range from simple 2D representations of the environment geometry to complex, multilayered semantic maps. This survey article is about maps of dynamics (MoDs), which store semantic information about typical motion patterns in a given environment. Some MoDs use trajectories as input, and some can be built from short, disconnected observations of motion. Robots can use MoDs, for example, for global motion planning, improved localization, or human motion prediction. Accounting for the increasing importance of maps of dynamics, we present a comprehensive survey that organizes the knowledge accumulated in the field and identifies promising directions for future work. Specifically, we introduce field-specific vocabulary, summarize existing work according to a novel taxonomy, and describe possible applications and open research problems. We conclude that the field is mature enough, and we expect that maps of dynamics will be increasingly used to improve robot performance in real-world use cases. At the same time, the field is still in a phase of rapid development where novel contributions could significantly impact this research area.

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Section: Trajectorymentioning

confidence: 99%

Survey of maps of dynamics for mobile robots

Kucner

Magnusson

Mghames

et al. 2023

The International Journal of Robotics Research

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“…To find these patterns, density-based approaches are used mainly for anomaly detection of trajectories [18], [19]. Therefore, clustering methods [20] or neuronal networks [21] are set up to group attributes and find unusual data. Besides these density-based methods, especially trajectory prediction methods combine various influences to determine the best possible trajectory based on complex cost functions including e.g.…”

Section: A Assessment Systems For Traffic Scenariosmentioning

confidence: 99%

An Automated Analysis Framework for Trajectory Datasets

Glasmacher¹,

Krajewski²,

Eckstein³

2022

Preprint

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“…For the past few decades, traffic congestion and safety have become a hot topic with different approaches being researched. Some researchers tried to monitor traffic condition using trajectory clustering method to find out the factors causing heavy traffic congestion [2][3][4], while some of them trying to optimise the traffic light signal for optimum time allocation to ensure smooth traffic flow [5][6][7]. Apart from that, there are also researches known as vehicular ad hoc network (VANET) being carried out in making vehicles more intelligent [8].…”

Section: Introductionmentioning

confidence: 99%

Sumo Enhancement for Vehicular Communication Development

Lim

Lee

Chin

et al. 2017

IJCT

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It is normal that every family is having at least one vehicle at their home as vehicles have become a daily needs for all of us. However, this also leads to the increased of road accidents where major causes are related to human errors which can be prevented. To tackle with this problem, vehicular ad hoc network (VANET) is introduced with the aim to make vehicles intelligent. In order to study the algorithm in VANET, a mobility simulator is needed for simulation purpose. In this case, SUMO is proved to be a good simulation tool in generating VANET environment while MATLAB is good for algorithm development. Yet, to develop a good simulation platform, modification on SUMO files are necessary. This paper discusses on the procedures in creating a lefthand traffic (LHT) simulation file that is suitable to be used in Malaysia. LHT simulation is not easy to achieve as modification on the road connection and traffic light files are required. This paper also showed the results of the simulation after SUMO files modification. Apart from that, this paper also showed the simulation of VANET environment using SUMO and MATLAB through a third party interfacing named TraCI4Matlab, which allows communication between MATLAB and SUMO simulator.

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Vehicle trajectory clustering for traffic intersection surveillance

Cited by 14 publications

References 4 publications

Survey of maps of dynamics for mobile robots

Survey of maps of dynamics for mobile robots

An Automated Analysis Framework for Trajectory Datasets

Sumo Enhancement for Vehicular Communication Development

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