Study on Emergency-Avoidance Braking for the Automatic Platooning of Trucks

Zheng, Rencheng; Nakano, Kimihiko; Yamabe, Shigeyuki; Aki, Masahiko; Nakamura, Hajime; Suda, Yoshihiro

doi:10.1109/tits.2014.2307160

Cited by 41 publications

(21 citation statements)

References 18 publications

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“…The most prominent hazard is, as was already described in Section 1.A, that one vehicle in the platoon runs into a preceding vehicle [12] [31], and in particular this becomes an issue when the first vehicle needs to perform an emergency brake. A variation of this is when the lead vehicle of one platoon runs into the last vehicle of another platoon [13] [14], and avoiding this becomes a part of the system's functionality when considering automated highways.…”

Section: ) Hazardous Situations and Lossesmentioning

confidence: 97%

“…Among the simulation approaches, driver simulation is the most prominent, and has been used in a series of related papers [11][30] [31][32] which investigate the capability of human drivers to take over control in case of a failure, in particular in an emergency brake situation. It has further been used to assess how the presence of platoons influence the headway distance behavior of manual drivers [18].…”

Section: ) Specific Aspectsmentioning

confidence: 99%

“…Other potential hazards related to avoiding collisions include driving off the road as a consequence of trying to avoid a collision by steering [31]. This is a situation that could appear when the lead truck suddenly changes lane to avoid a stopped vehicle or debris in the roadway ahead.…”

Section: ) Hazardous Situations and Lossesmentioning

confidence: 99%

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Safety in Vehicle Platooning: A Systematic Literature Review

Axelsson

2017

IEEE Trans. Intell. Transport. Syst.

117

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Section: ) Hazardous Situations and Lossesmentioning

confidence: 97%

Section: ) Specific Aspectsmentioning

confidence: 99%

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Safety in Vehicle Platooning: A Systematic Literature Review

Axelsson

2017

IEEE Trans. Intell. Transport. Syst.

117

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“…The maximum deceleration for the follower vehicles was set to 9 m/s 2 ; hence, vehicles have a higher braking capability than what is performed by the leader. This is a different setup from the real-world experiments in [45], where the driving conditions of the vehicles were different. In a first experiment, maximum deceleration was inhomogeneous among the different trucks and they were driving on different lanes to avoid a real crash, whereas in a second experiment, following trucks had a stronger braking capability than front trucks.…”

Section: F Impact Of Communication On Cacc Performancementioning

confidence: 99%

Toward Communication Strategies for Platooning: Simulative and Experimental Evaluation

Segata

Bloessl

Joerer

et al. 2015

IEEE Trans. Veh. Technol.

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Platooning, which is the idea of cars autonomously following their leaders to form a road train, has huge potential to improve traffic flow efficiency and, most importantly, road traffic safety. Wireless communication is a fundamental building block: It is needed to manage and maintain the platoons. To keep the system stable, strict constraints in terms of update frequency and communication reliability must be met. We investigate different communication strategies by explicitly taking into account the requirements of the controller, exploiting synchronized communication slots, and transmit power adaptation. As a baseline, we compared the proposed approaches to two state-of-the-art adaptive beaconing protocols that have been designed for cooperative awareness applications, namely, the European Telecommunications Standards Institute (ETSI) Decentralized Congestion Control (DCC) and Dynamic Beaconing (DynB). Our simulation models have been parameterized and validated by means of realworld experiments. Our results demonstrate that the combination of synchronized communication slots with transmit power adaptation is perfectly suited for cooperative driving applications, even on very crowded freeway scenarios.

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“…Other ADAS do not only recognize driving situations and warn the driver, but also intervene actively in order to prevent possible collisions. A common example of the latter type is Emergency Brake Assist [4], which applies full braking if driver fails to respond to obstacles in front of the vehicle.…”

Section: Introductionmentioning

confidence: 99%

A Station with Multiple Head-Mounted Displays for Learning Advanced Driver Assistance Systems

Abdelgawad¹,

Gausemeier²,

Stöcklein³

et al. 2017

Preprint

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Advanced driver assistance systems (ADAS) are technologies that provide drivers with essential information or take over difficult and repetitive tasks. They contribute to improving road safety and increasing driving comfort. Apart from the technical development challenges, training and demonstration of ADAS in safe environments are important concerns for automobile manufacturers and suppliers. This paper presents the concept and prototypical implementation of an innovative training station for learning ADAS with driving simulators. The training station has a scalable and modular architecture, so that more than one driving simulator can be connected to a common instructor unit. Fully immersive visualization is provided by utilizing head-mounted displays for the participating driving simulators. The instructor unit consists of a computer with a developed software tool for session control, monitoring, and evaluation. Moreover, the instructor can use a head-mounted display and participate within the same virtual environment of a selected trainee. A simulation model for an autonomous driving system was implemented and a group of test persons were involved to show the usability and validity of the developed training station for ADAS learning and demonstration.

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Study on Emergency-Avoidance Braking for the Automatic Platooning of Trucks

Cited by 41 publications

References 18 publications

Safety in Vehicle Platooning: A Systematic Literature Review

Safety in Vehicle Platooning: A Systematic Literature Review

Toward Communication Strategies for Platooning: Simulative and Experimental Evaluation

A Station with Multiple Head-Mounted Displays for Learning Advanced Driver Assistance Systems

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