A Two-Stage Real-Time Path Planning: Application to the Overtaking Manuever

This paper proposes a two-stage local path planning approach to deal with all kinds of scenarios (i.e. intersections, turns, roundabouts). The first stage carries out an off-line optimization, considering vehicle kinematics and road constraints. The second stage includes all dynamic obstacles in the scene, generating a continuous path in real-time. Human-like driving style is provided by evaluating the sharpness of the road bends and the available space among them, optimizing the drivable area. The proposed approach is validated on overtaking scenarios where real-time path planning generation plays a key role. Simulation and real results on an experimental automated platform provide encouraging results, generating real-time collision-free paths while maintaining the defined smoothness criteria.INRIA and VEDECOM Institutes under the Ph.D. Grant; 10.13039/501100011688-Electronic Components and Systems for European Leadership (ECSEL) Project AutoDriv

Iso-damping fractional-order control for robust automated car-following

This work deals with the control design and development of an automated car-following strategy that further increases robustness to vehicle dynamics uncertainties. The control algorithm is applied on a hierarchical architecture where high and low level control layers are designed for gap-control and desired acceleration tracking, respectively. A fractional-order controller is proposed due to its flexible frequency shape, fulfilling more demanding design requirements. The iso-damping loop property is sought, which yields a desired closed-loop stability that results invariant despite changes on the controlled plant gain. In addition, the graphical nature of the proposed design approach demonstrates its portability and applicability to any type of vehicle dynamics without complex reconfiguration. The algorithm benefits are validated in frequency and time domains, as well as through experiments on a real vehicle platform performing adaptive cruise control.This research is supported by the Vehicle Technology Office (VTO), U.S. Department of Energy, under the Energy Efficient Mobility Systems (EEMS) initiative of the SMART Mobility Program, through the Lawrence Berkeley National Laboratory. The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the data presented herein

A driverless vehicle demonstration on motorways and in urban environments

International audienceThe constant growth of the number of vehicles in today's world demands improvements in the safety and efficiency of roads and road use. This can be in part satisfied by the implementation of autonomous driving systems because of their greater precision than human drivers in controlling a vehicle. As result, the capacity of the roads would be increased by reducing the spacing between vehicles. Moreover, greener driving modes could be applied so that the fuel consumption, and therefore carbon emissions, would be reduced. This paper presents the results obtained by the AUTOPIA program during a public demonstration performed in June 2012. This driverless experiment consisted of a 100-kilometre route around Madrid (Spain), including both urban and motorway environments. A first vehicle – acting as leader and manually driven – transmitted its relevant information – i.e., position and speed – through an 802.11p communication link to a second vehicle, which tracked the leader's trajectory and speed while maintaining a safe distance. The results were encouraging, and showed the viability of the AUTOPIA approach

Autonomous vehicle control systems for safe crossroads

This article presents a cooperative manoeuvre among three dual mode cars – vehicles equipped with sensors and actuators, and that can be driven either manually or autonomously. One vehicle is driven autonomously and the other two are driven manually. The main objective is to test two decision algorithms for priority conflict resolution at intersections so that a vehicle autonomously driven can take their own decision about crossing an intersection mingling with manually driven cars without the need for infrastructure modifications. To do this, the system needs the position, speeds, and turning intentions of the rest of the cars involved in the manoeuvre. This information is acquired via communications, but other methods are also viable, such as artificial vision. The idea of the experiments was to adjust the speed of the manually driven vehicles to force a situation where all three vehicles arrive at an intersection at the same time

Measurement of the B0s→μ+μ− Branching Fraction and Effective Lifetime and Search for B0→μ+μ− Decays

A search for the rare decays Bs0→μ+μ- and B0→μ+μ- is performed at the LHCb experiment using data collected in pp collisions corresponding to a total integrated luminosity of 4.4  fb-1. An excess of Bs0→μ+μ- decays is observed with a significance of 7.8 standard deviations, representing the first observation of this decay in a single experiment. The branching fraction is measured to be B(Bs0→μ+μ-)=(3.0±0.6-0.2+0.3)×10-9, where the first uncertainty is statistical and the second systematic. The first measurement of the Bs0→μ+μ- effective lifetime, τ(Bs0→μ+μ-)=2.04±0.44±0.05  ps, is reported. No significant excess of B0→μ+μ- decays is found, and a 95% confidence level upper limit, B(B0→μ+μ-)<3.4×10-10, is determined. All results are in agreement with the standard model expectations.A search for the rare decays $B^0_s\to\mu^+\mu^-$ and $B^0\to\mu^+\mu^-$ is performed at the LHCb experiment using data collected in $pp$ collisions corresponding to a total integrated luminosity of 4.4 fb$^{-1}$. An excess of $B^0_s\to\mu^+\mu^-$ decays is observed with a significance of 7.8 standard deviations, representing the first observation of this decay in a single experiment. The branching fraction is measured to be ${\cal B}(B^0_s\to\mu^+\mu^-)=\left(3.0\pm 0.6^{+0.3}_{-0.2}\right)\times 10^{-9}$, where the first uncertainty is statistical and the second systematic. The first measurement of the $B^0_s\to\mu^+\mu^-$ effective lifetime, $\tau(B^0_s\to\mu^+\mu^-)=2.04\pm 0.44\pm 0.05$ ps, is reported. No significant excess of $B^0\to\mu^+\mu^-$ decays is found and a 95 % confidence level upper limit, ${\cal B}(B^0\to\mu^+\mu^-)<3.4\times 10^{-10}$, is determined. All results are in agreement with the Standard Model expectations

Measurements of prompt charm production cross-sections in pp collisions at s=5 \sqrt{s}=5 TeV

Production cross-sections of prompt charm mesons are measured using data from $pp$ collisions at the LHC at a centre-of-mass energy of $5\,$TeV. The data sample corresponds to an integrated luminosity of $8.60\pm0.33\,$pb$^{-1}$ collected by the LHCb experiment. The production cross-sections of $D^0$, $D^+$, $D_s^+$, and $D^{*+}$ mesons are measured in bins of charm meson transverse momentum, $p_{\text{T}}$, and rapidity, $y$. They cover the rapidity range $2.0 < y < 4.5$ and transverse momentum ranges $0 < p_{\text{T}} < 10\, \text{GeV}/c$ for $D^0$ and $D^+$ and $1 < p_{\text{T}} < 10\, \text{GeV}/c$ for $D_s^+$ and $D^{*+}$ mesons. The inclusive cross-sections for the four mesons, including charge-conjugate states, within the range of $1 < p_{\text{T}} < 8\, \text{GeV}/c$ are determined to be \begin{equation*} \sigma(pp\rightarrow D^0 X) = 1190 \pm 3 \pm 64\,\mu\text{b} \end{equation*} \begin{equation*} \sigma(pp\rightarrow D^+ X) = 456 \pm 3 \pm 34\,\mu\text{b} \end{equation*} \begin{equation*} \sigma(pp\rightarrow D_s^+ X) = 195 \pm 4 \pm 19\,\mu\text{b} \end{equation*} \begin{equation*} \sigma(pp\rightarrow D^{*+} X)= 467 \pm 6 \pm 40\,\mu\text{b} \end{equation*} where the uncertainties are statistical and systematic, respectively.Production cross-sections of prompt charm mesons are measured using data from pp collisions at the LHC at a centre-of-mass energy of 5 TeV. The data sample corresponds to an integrated luminosity of 8.60 ± 0.33 pb$^{−1}$ collected by the LHCb experiment. The production cross-sections of D$^{0}$, D$^{+}$, D$_{s}^{+}$ , and D$^{∗+}$ mesons are measured in bins of charm meson transverse momentum, p$_{T}$, and rapidity, y. They cover the rapidity range 2.0 < y < 4.5 and transverse momentum ranges 0 < p$_{T}$ < 10 GeV/c for D$^{0}$ and D$^{+}$ and 1 < p$_{T}$ < 10 GeV/c for D$_{s}^{+}$ and D$^{∗+}$ mesons. The inclusive cross-sections for the four mesons, including charge-conjugate states, within the range of 1 < p$_{T}$ < 8 GeV/c are determined to be $\begin{array}{l}\sigma \left( pp\to {D}^0X\right)=1004\pm 3\pm 54\mu \mathrm{b},\\ {}\sigma \left( pp\to {D}^{+}X\right)=402\pm 2\pm 30\mu \mathrm{b},\\ {}\sigma \left( pp\to {D}_s^{+}X\right)=170\pm 4\pm 16\mu \mathrm{b},\\ {}\sigma \left( pp\to {D}^{\ast +}X\right)=421\pm 5\pm 36\mu \mathrm{b},\end{array}$ where the uncertainties are statistical and systematic, respectively.Production cross-sections of prompt charm mesons are measured using data from $pp$ collisions at the LHC at a centre-of-mass energy of $5\,$TeV. The data sample corresponds to an integrated luminosity of $8.60\pm0.33\,$pb$^{-1}$ collected by the LHCb experiment. The production cross-sections of $D^0$, $D^+$, $D_s^+$, and $D^{*+}$ mesons are measured in bins of charm meson transverse momentum, $p_{\text{T}}$, and rapidity, $y$. They cover the rapidity range $2.0<y<4.5$ and transverse momentum ranges $0 < p_{\text{T}} < 10\, \text{GeV}/c$ for $D^0$ and $D^+$ and $1 < p_{\text{T}} < 10\, \text{GeV}/c$ for $D_s^+$ and $D^{*+}$ mesons. The inclusive cross-sections for the four mesons, including charge-conjugate states, within the range of $1 < p_{\text{T}} < 8\, \text{GeV}/c$ are determined to be \sigma(pp\rightarrow D^0 X) = 1004 \pm 3 \pm 54\,\mu\text{b} \sigma(pp\rightarrow D^+ X) = 402 \pm 2 \pm 30\,\mu\text{b} \sigma(pp\rightarrow D_s^+ X) = 170 \pm 4 \pm 16\,\mu\text{b} \sigma(pp\rightarrow D^{*+} X)= 421 \pm 5 \pm 36\,\mu\text{b} where the uncertainties are statistical and systematic, respectively

Introduction to the Special Issue on Intelligent and Cooperative Vehicles

Intelligent vehicles constitute one of the hot research topics on the Intelligent Transportation Systems (ITS) field. The development of Advanced Driver Assistance Systems (ADAS) based on multi-fusion information coming from on-board cameras, lidar or radar sensors is leading to more sophisticated passive and active safety systems. Additionally, the growing interest in using wireless communications to connect the vehicle either with other vehicles or the infrastructure is moving the intelligent vehicle research field toward smart interaction, moving to the Cooperative ITS (C-ITS) research field. [...

Contrôle adaptatif multi-modèles pour les applications CACC

International audienceThis paper proposes a multi-model adaptive control (MMAC) algorithm based on Youla-Kucera (YK) theory to deal with heterogeneity in cooperative adaptive cruise control (CACC) systems. The main idea of MMAC is to choose the plant in a predefined set that best approximates the system dynamics, applying the corresponding predesigned controller. A set of linear plants describing different vehicle dynamics is defined. Different CACC controllers are designed depending on these linear plants. Simulation and experimental results prove how MMAC determines the closest plant in the set, choosing the CACC system able to ensure string stability