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This paper aims to study distance determination in vehicles, which could allow an in-car system to provide feedback and alert drivers, by either prompting the driver to take preventative action or prepare the vehicle’s safety systems for an imminent collision. The success of a new system's deploying allows drivers to oppose the huge number of accidents and the material losses and costs associated with car accidents.

In this context, this paper presents estimation distance between camera and frontal vehicles based on camera calibration by combining three main steps: vanishing point extraction, lanes detection and vehicles detection in the field of 3 D real scene. This algorithm was implemented in MATLAB, and it was applied on scenes containing several vehicles in highway urban area. The method starts with the camera calibration. Then, the distance information can be calculated.

Based on experiment performance, this new method achieves robustness especially for detecting and estimating distances for multiple vehicles in a single scene. Also, this method demonstrates a higher accuracy detection rate of 0.869 in an execution time of 2.382 ms.

The novelty of the proposed method consists firstly on the use of an adaptive segmentation to reject the false points of interests. Secondly, the use of vanishing point has reduced the cost of using memory. Indeed, the part of the image above the vanishing point will not be processed and therefore will be deleted. The last benefit is the application of this new method on structured roads.

The purpose of this paper is to reduce the reconfiguration time of a field‐programmable gate array (FPGA).

The paper focuses on introducing a new temporal placement algorithm which uses a typical mathematical formalism to optimize the reconfiguration time.

Results show that the algorithm decreases considerably the reconfiguration time compared with famous temporal placement algorithms.

The paper proposes a new temporal placement algorithm which optimizes reconfiguration time of modules on the device. The studied evaluation cases show that the proposed algorithm provides very significant results in terms reconfiguration time of modules versus other well‐known algorithms used in the temporal placement field. The authors uses the eigenvalue of the Laplacian matrix.