Optimizing the Distance-Gap between Cars by Constant Time to Collision Planning

Bălaş, Marius M.; Balaş, Valentina E.; Duplaix, Jean

doi:10.1109/isie.2007.4374616

Cited by 9 publications

(10 citation statements)

References 4 publications

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“…Therefore, the proposed algorithm can be easily implemented because the integration of normal distribution can be readily solved from the well-organized studies (for example, it is indirectly computed from the integral of the standard normal distribution which is already known). Fundamentally, the efficiency of proposed method is made possible from the fact that nonlinear formula of y hit in (12), (13) can be transformed to linear combination form of (14) by applying the results of the proposed TTC estimator.…”

Section: Gaussian Mixture Based Collision Probabilitymentioning

confidence: 99%

“…The predicted collision position has same value during roughly the first 5 seconds of both target scenarios because of having constant y velocity and is changed with increasing the target velocity. As represented in (13), the variation of y velocity is reflected in the computation of the predicted collision position by the TTC value.…”

Section: Evaluation On Ttc Estimationmentioning

confidence: 99%

“…Most simplest way is to make use of time-to-collision (TTC) [11][12][13] to notify dangerous situations. In general, this type of existing algorithm calculates the TTC directly using FMCW radar measurements or target state estimates provided by the automotive target tracking unit.…”

Section: Introductionmentioning

confidence: 99%

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Gaussian mixture approach to decision making for automotive collision warning systems

Han

Sang

Whang

et al. 2015

Int. J. Control Autom. Syst.

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This paper proposes a practical probabilistic approach to collision decision making which is necessary for advanced automotive collision warning system (CWS) using FMCW radar. Most decision making algorithms assess the probable collisions based on the predicted collision position which is usually expressed as a nonlinear function of threat vehicle's position and velocity provided by FMCW radar. Since the predicted collision position has highly nonlinear statistics in general, it is one of main obstacles to improving the reliability of the collision probability computation and to developing real-time decision making algorithms. This motivates us to devise a Gaussian mixture method for collision probability calculation with the help of linear recursive time-to-collision (TTC) estimation. The suggested TTC estimator provides an accurate TTC estimate with small estimation error variance hence it enables us to approximate the probability density function of the predicted collision position as the weighted sum of just a few Gaussian distributions. Therefore, our approach could drastically reduce the inherent nonlinearity of collision decision making problem and computational complexity in collision probability calculation. Through the simulations for the typical engagement scenarios between the host and threat vehicles, the performance and effectiveness of the proposed algorithm is compared to those of the existing ones which require heavy computational burden.

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Section: Gaussian Mixture Based Collision Probabilitymentioning

confidence: 99%

Section: Evaluation On Ttc Estimationmentioning

confidence: 99%

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Gaussian mixture approach to decision making for automotive collision warning systems

Han

Sang

Whang

et al. 2015

Int. J. Control Autom. Syst.

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show abstract

“…Tested by simulations in different applications, FSAIC proved to be highly versatile. Some of the applications were: ABS braking [3], imposed distance braking [4], car following [5], etc. There are two reasons for the extreme versatility of FSAIC, both linked to the WK issue: a) the design of its adaptive corrector includes a set of general knowledge on the linear PID controllers' adjustment and on the linear systems' stability; b) the technique of the planning was used in order to harmonize the controller to each specific process [6]; the planners' design was assisted by functional computer models of the nonlinear processes.…”

Section: World Knowledgementioning

confidence: 99%

World Knowledge for Control Applications

Bălaş

Balaş

2007

Intelligent Engineering Systems, 2007 International Conference On

Self Cite

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“…The scheme mainly focuses on Collision Warning System(CWS)in low-stage and Autonomous Intelligent Cruise Control ( AICC ) [6] [7][8] [9] in advanced stage. The basic thought of CWS is sending out alarm when radar detecting latent danger, which can strive valuable time for automotive driver to avoid collision, otherwise, AICC controls automatically automotive speeding, decelerating and braking by detecting automotive space and relative velocity, which can control automotive space and relative velocity in safe range.…”

Section: Introductionmentioning

confidence: 99%

Answering-measure radar for expressway automotive anti-collision system application

Zhang

Yang

Yan

et al. 2008

2008 3rd IEEE Conference on Industrial Electronics and Applications

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Based on the characteristic of closure management for expressway and the demand of low cost for economic car in China, a new automotive anticollision managing model is proposed, which can be implemented by the supervisory and managerial department. A scheme for automotive anti-collision radar is given based on answering-measure, some critical performances of the radar have been analyzed and the measuring performance of radar is tested, according to the testing result, the radar realizes the function of measuring and automotive anti-collision in expressway.

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Optimizing the Distance-Gap between Cars by Constant Time to Collision Planning

Cited by 9 publications

References 4 publications

Gaussian mixture approach to decision making for automotive collision warning systems

Gaussian mixture approach to decision making for automotive collision warning systems

World Knowledge for Control Applications

Answering-measure radar for expressway automotive anti-collision system application

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