An integrated architecture for the development and assessment of ADAS

Noth, Sebastian; Edelbrunner, Johann; Iossifidis, Ioannis

doi:10.1109/itsc.2012.6338805

Cited by 9 publications

(3 citation statements)

References 3 publications

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“…A low-cost and reconfigurable driving simulator with several components to accommodate different ADAS testing or training is proposed by Hassan et al [18]. A framework for ADAS assessment and benchmarking has been developed elsewhere [19], with configurable scenarios and 3D scenes and multiple sensors input. Miao et al [20] introduce a game-engine-based simulator for modeling and computing platform for ATS.…”

Section: B Mobile Device Adasmentioning

confidence: 99%

Testing Advanced Driver Assistance Systems with a serious-game-based human factors analysis suite

Gonçalves

Rossetti

Jacob³

et al. 2014

2014 IEEE Intelligent Vehicles Symposium Proceedings

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The development of Advanced Driver Assistance Systems (ADAS) is rapidly growing. However, most of the ADAS require field test, which is expensive, unpredictable and time consuming. In this paper we propose a multiagent-based driving simulator which integrates a human factor analysis suite and enables rapid and low-cost experimentation of mobile-device ADAS. Our architecture uses a microscopic simulator and a serious-game-based driving simulator. The latter allows the user to control a vehicle and change the correspondent simulation state in the microscopic simulator. The driving simulator also connects to an Android device and sends several kinds of data, such as current GPS coordinates or transportation network data. One important feature of this architecture is its suitability to serve as an appropriate means to conduct behaviour elicitation through peer-designed agents, so as to improve modelling of various driving styles accounting for different aspects of preferences and perception abilities, as well as other performance measures related to drivers' interaction with ADAS solutions. The potentials of our approach to aid experiments in human factor analysis are still to be tested, but are undoubtedly huge and encouraging.

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Section: B Mobile Device Adasmentioning

confidence: 99%

Testing Advanced Driver Assistance Systems with a serious-game-based human factors analysis suite

Gonçalves

Rossetti

Jacob³

et al. 2014

2014 IEEE Intelligent Vehicles Symposium Proceedings

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“…Several research groups have increased their investments in areas as planning and control to reduce the time-out on the arrival of totally autonomous transportation systems. Over fifteen years ago, the first Advanced Driver Assistance Systems (ADAS) were introduced on a massive scale in the market [1]. One of the most known is the Adaptive Cruise Control (ACC), which can automatically adjust a vehicle's speed to maintain a safe following distance.…”

Section: Introductionmentioning

confidence: 99%

Dynamic trajectory generation using continuous-curvature algorithms for door to door assistance vehicles

Rastelli

Lattarulo

Nashashibi

2014

2014 IEEE Intelligent Vehicles Symposium Proceedings

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In this paper, an algorithm for dynamic path generation in urban environments is presented, taking into account structural and sudden changes in straight and bend segments (e.g. roundabouts and intersections). The results present some improvements in path generation (previously hand plotted) considering parametric equations and continuous-curvature algorithms, which guarantees a comfortable lateral acceleration. This work is focused on smooth and safe path generation using road and obstacle detection information. Finally, some simulation results show a good performance of the algorithm using different ranges of urban curves. The main contribution is an Intelligent Trajectory Generator, which considers infrastructure and vehicle information. This method is recently used in the framework of the project CityMobil2 1 , for urban autonomous guidance of Cybercars.

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“…However, despite of this disadvantage, automotive industry (AEBERHARD et al, 2015;ZEEB, 2010;CHALLEN, 2008) Source: Smith, Witt and Bakowski (2008). GIETELINK et al, 2006;GONCALVES et al, 2014;MAAG et al, 2012;BIFULCO et al, 2012;NOTH;EDELBRUNNER;IOSSIFIDIS, 2012;YOSHIMOTO;SUETOMI, 2008) have a driving simulator available to facilitate the design, development, and test of their proposals.…”

Section: Advantages and Disadvantages Of Driving Simulatorsmentioning

confidence: 99%

Cooperative driver assistance system for the lane change

Hernandez¹

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Dedico este trabalho a Deus, por seu infinito amor e bondade, e por manter sempre firme suas mãos nos momentos em que mais precisei dele, a minha amada esposa, Ayumi, pela força que dá em minha vida, e por ser o sol nascente de nossa família, a minha mãe, Nelly, por me ensinar que agindo corretamente, coisas boas sempre chegam, a minha família, por ser uma das motivações de minha vida, ao generoso povo Brasileiro "gigante pela própria natureza", por ampliar minha visão da ciência e do mundo. "Santandereanos siempre adelante, Santandereanos ni un paso atrás." (Himo de Santander-Colombia) ABSTRACT ANDRÉS EDUARDO, G. H. Cooperative driver assistance system for the lane change. 2018. 139 p. Tese (Doutorado em Ciências

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An integrated architecture for the development and assessment of ADAS

Cited by 9 publications

References 3 publications

Testing Advanced Driver Assistance Systems with a serious-game-based human factors analysis suite

Testing Advanced Driver Assistance Systems with a serious-game-based human factors analysis suite

Dynamic trajectory generation using continuous-curvature algorithms for door to door assistance vehicles

Cooperative driver assistance system for the lane change

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