Enabling traffic safety assessment of VANETs by means of accident simulations

Killat, Moritz; Gaugel, Tristan; Hartenstein, Hannes

doi:10.1109/pimrc.2008.4699955

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…Fatema [28] investigated the lane-changing behavior based on acceleration and gap. Apart from parametric statistical approach, many researchers also built non-parametric models which can provide higher prediction accuracy for merging behavior (e.g., [10]). …”

Section: Literature Reviewmentioning

confidence: 99%

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Modeling Vehicle Merging Behavior in Work Zone Merging Areas During the Merging Implementation Period

Weng

Xue

Yan

2016

IEEE Trans. Intell. Transport. Syst.

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Using the classification and regression tree (CART) method, this study aims to model the vehicle merging behavior at work zone merging areas during the merging implementation period. Hereafter, the merging implementation period is defined as the period from the starting time to the completion time of a merging maneuver. From the safety perspective, the times to collision (TTC) between the merging vehicle and its neighboring vehicles are regarded as the factors affecting vehicle merging decisions. The results show that a larger delay, a shorter remaining distance to the work zone, a smaller TTC to the merging lead vehicle, and a higher merging vehicle speed may encourage drivers to complete merging maneuvers early. It is also found that the merging vehicle tends to continue merging when the TTCs between the merging vehicle and its neighboring vehicles in the through lane are too small. In addition, another CART model without the use of TTC is built for comparison. The finding indicates that the use of TTC can not only contribute to a perfect result but also highlight the merging safety situation more clearly. The merging rules of this study are ready to be incorporated into the merging assistance system for guiding a safety merging at work zone merging areas.Index Terms-Merging, classification and regression tree, timeto-collision, merging implementation period. 1524-9050

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Section: Literature Reviewmentioning

confidence: 99%

“…Hence, the use of these systems could provide a more convenient and safer driving. Note that one of the key components VANETs is the merging decision assistance system [10]. In general, the aim of merging decision assistance system is to advise drivers taking a safer merging behavior for reducing the vehicle crash risk.…”

Section: Introductionmentioning

confidence: 99%

Modeling Vehicle Merging Behavior in Work Zone Merging Areas During the Merging Implementation Period

Weng

Xue

Yan

2016

IEEE Trans. Intell. Transport. Syst.

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“…Widely-used traffic simulations like PTV Vissim (see [119], [120], [121]), SUMO (see [122], [123]), PELOPS (see [24]), or IPG Carmaker (see [124]), are able to simulate traffic flow, but with limitations on the insight of driver behavior modeling. Studies that use these traffic simulations to model critical and accident situations are (so far) tests of feasibility rather than actual simulations of real-world conflict situations (see [35], [125], [126], [127], [128]). Subsequently, a classification of currently used modules in driver behavior models is presented.…”

Section: A Driver Behavior Modulesmentioning

confidence: 99%

What Do Traffic Simulations Have to Provide for Virtual Road Safety Assessment? Human Error Modeling in Traffic Simulations

Siebke

Mai

Prokop

2022

IEEE Trans. Intell. Transport. Syst.

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Will Advanced Driving Assistance Systems (ADAS) and Highly Automated Driving (HAD) perform in the expected manner? Will they actually make road traffic safer, or will they potentially introduce new critical situations or road accidents? It is almost impossible to address these questions solely through real-world tests. A promising tool to provide appropriate answers in a time-and cost-efficient way without exposing subjects to risk are virtual assessment methods. Reliable safety assessments are only possible, if the traffic simulations provide realistic traffic, including critical situations and road accidents. This paper provides a review of how human error contributes to critical situations and accidents in road traffic. The focus is on the causes and mechanisms of human error, which driver behavior models must address in order to simulate realistic traffic. For this purpose, Rasmussen's error taxonomies are applied to the traffic context and extended with further research. The paper shows the causes of those human errors and that the underlying mechanisms thereof should be taken into account in order to obtain more transparent and realistic driver behavior models. It is shown, which concepts for modelling realistic traffic exist and how virtual safety assessment could benefit from this development. In addition, the driver behavior model DReaM (Driver Reaction Model) is presented to address the issues resulting from existing cognitive driver models.

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Vehicular Mobility Modeling for VANET

Härri¹

2009

Vanet

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Enabling traffic safety assessment of VANETs by means of accident simulations

Cited by 7 publications

References 8 publications

Modeling Vehicle Merging Behavior in Work Zone Merging Areas During the Merging Implementation Period

Modeling Vehicle Merging Behavior in Work Zone Merging Areas During the Merging Implementation Period

What Do Traffic Simulations Have to Provide for Virtual Road Safety Assessment? Human Error Modeling in Traffic Simulations

Vehicular Mobility Modeling for VANET

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