Integration of vulnerable road users in cooperative ITS systems

Scholliers, Johan; Sambeek, Marcel van; Moerman, Kees

doi:10.1007/s12544-017-0230-3

Cited by 27 publications

(18 citation statements)

References 10 publications

(13 reference statements)

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“…The latter includes a wide range of road users such as pedestrians, cyclist and powered two wheelers. Recent research tackling VRU safety, such as [41,42], mainly focused on detecting the pedestrians and avoiding accidents using vehicular cloud computing as a branch of mobile cloud computing.…”

Section: Road Safetymentioning

confidence: 99%

The Role of 5G Technologies: Challenges in Smart Cities and Intelligent Transportation Systems

2020

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The new mobile technology, 5G, challenges the current scenario in communications by overcoming the flaws of currently working 4G. Such new technology offers to smart cities and intelligent transportation systems a new way to become fully integrated by allowing massive simultaneous connections and ubiquity of network, even under high mobility situations or dense populated areas. In this way, 5G will become a key enabler for real Internet of Things and its corresponding Internet of Vehicles. This discussion is aimed at providing, in a comprehensive manner, how 5G technology will impact on smart cities, intelligent transportation systems –including autonomous or semi-autonomous vehicles– and vehicular communications, its technical, economic and legal challenges, in the following years.

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Section: Road Safetymentioning

confidence: 99%

The Role of 5G Technologies: Challenges in Smart Cities and Intelligent Transportation Systems

2020

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“…More specifically, the service called "Vulnerable road user protection (pedestrians and cyclists)" is included in the list of Day 1.5 C-ITS Services [30]. The EU VRUITS project [31] proposes an interesting architecture for the integration of VRUs in Cooperative ITS systems.…”

Section: State Of the Artmentioning

confidence: 99%

Reducing Unnecessary Alerts in Pedestrian Protection Systems Based on P2V Communications

et al. 2019

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There are different proposals in the literature on how to protect pedestrians using warning systems to alert drivers of their presence. They can be based on onboard perception systems or wireless communications. The evaluation of these systems has been focused on testing their ability to detect pedestrians. A problem that has received much less attention is the possibility of generating too many alerts in the warning systems. In this paper, we propose and analyze four different algorithms to take the decision on generating alerts in a warning system that is based on direct wireless communications between vehicles and pedestrians. With the algorithms, we explore different strategies to reduce unnecessary alerts. The feasibility of the implementation of the algorithms was evaluated with a deployment using real equipment, and tests were carried out to verify their behavior in real scenarios. The ability of each algorithm to reduce unnecessary alerts was evaluated with realistic simulations in an urban scenario, using a traffic simulator with vehicular and pedestrian flows. The results show the importance of tackling the problem of driver overload in warning systems, and that it is not straightforward to predict the load of alerts generated by an algorithm in a large-scale deployment, in which there are multiple interactions between vehicles and pedestrians.

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“…However, there is no cooperation on the level of detected intentions between different traffic participants. In [12], the authors proposed a concept and listing of requirements for cooperative intelligent transportation systems including smart devices.…”

Section: A Intention Detection Of Vulnerable Road Usersmentioning

confidence: 99%

Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble

Bieshaar

Zernetsch

Hubert

et al. 2018

IEEE Trans. Intell. Veh.

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In future, vehicles and other traffic participants will be interconnected and equipped with various types of sensors, allowing for cooperation on different levels, such as situation prediction or intention detection. In this article we present a cooperative approach for starting movement detection of cyclists using a boosted stacking ensemble approach realizing featureand decision level cooperation. We introduce a novel method based on a 3D Convolutional Neural Network (CNN) to detect starting motions on image sequences by learning spatio-temporal features. The CNN is complemented by a smart device based starting movement detection originating from smart devices carried by the cyclist. Both model outputs are combined in a stacking ensemble approach using an extreme gradient boosting classifier resulting in a fast and yet robust cooperative starting movement detector. We evaluate our cooperative approach on real-world data originating from experiments with 49 test subjects consisting of 84 starting motions.M. Bieshaar, and B. Sick are with the Intelligent Embedded Systems Lab,

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Integration of vulnerable road users in cooperative ITS systems

Cited by 27 publications

References 10 publications

The Role of 5G Technologies: Challenges in Smart Cities and Intelligent Transportation Systems

The Role of 5G Technologies: Challenges in Smart Cities and Intelligent Transportation Systems

Reducing Unnecessary Alerts in Pedestrian Protection Systems Based on P2V Communications

Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble

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