Cooperative look-ahead control for fuel-efficient and safe heavy-duty vehicle platooning

The operation of groups of heavy-duty vehicles (HDVs) at a small inter-vehicular distance (known as platoon) allows to lower the overall aerodynamic drag and, therefore, to reduce fuel consumption and greenhouse gas emissions. However, due to the large mass and limited engine power of HDVs, slopes have a significant impact on the feasible and optimal speed profiles that each vehicle can and should follow. Therefore maintaining a short inter-vehicular distance as required by platooning without coordination between vehicles can often result in inefficient or even unfeasible trajectories. In this paper we propose a two-layer control architecture for HDV platooning aimed to safely and fuel-efficiently coordinate the vehicles in the platoon. Here, the layers are responsible for the inclusion of preview information on road topography and the real-time control of the vehicles, respectively. Within this architecture, dynamic programming is used to compute the fuel-optimal speed profile for the entire platoon and a distributed model predictive control framework is developed for the real-time control of the vehicles. The effectiveness of the proposed controller is analyzed by means of simulations of several realistic scenarios that suggest a possible fuel saving of up to 12% for the follower vehicles compared to the use of standard platoon controllers.Comment: 16 pages, 16 figures, submitted to journa

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Pregnant women need a flu shot

Because you are pregnant, you are recommended to get the flu shot to protect yourself and your baby from the flu. Talk to your health care provider about getting a flu shot.CS24398

Fuel-efficient and safe heavy-duty vehicle platooning through look-ahead control

The operation of groups of heavy-duty vehicles at small inter-vehicular distances, known as platoons, lowers the overall aerodynamic drag and, therefore, reduces fuel consumption and greenhouse gas emissions. Experimental tests conducted on a flat road and without traffic have shown that platooning has the potential to reduce the fuel consumption up to 10%. However, platoons are expected to drive on public highways with varying topography and traffic. Due to the large mass and limited engine power of heavy-duty vehicles, road slopes can have a significant impact on feasible and optimal speed profiles. Therefore, maintaining a short inter-vehicular distance without coordination can result in inefficient or even infeasible speed trajectories. Furthermore, external traffic can interfere by affecting fuel-efficiency and threatening the safety of the platooning vehicles. This thesis addresses the problem of safe and fuel-efficient control for heavy-duty vehicle platooning. We propose a hierarchical control architecture that splits this complex control problem into two layers. The layers are responsible for the fuel-optimal control based on look-ahead information on road topography and the real-time vehicle control, respectively. The top layer, denoted the platoon coordinator, relies on a dynamic programming framework that computes the fuel-optimal speed profile for the entire platoon. The bottom layer, denoted the vehicle control layer, uses a distributed model predictive controller to track the optimal speed profile and the desired inter-vehicular spacing policy. Within this layer, constraints on the vehicles' states guarantee the safety of the platoon. The effectiveness of the proposed controller is analyzed by means of simulations of several realistic scenarios. They suggest a possible fuel saving of up to 12% for the follower vehicles compared to the use of existing platoon controllers. Analysis of the simulation results shows how the majority of the fuel saving comes from a reduced usage of vehicles brakes. A second problem addressed in the thesis is model predictive control for obstacle avoidance and lane keeping for a passenger car. We propose a control framework that allows to control the nonlinear vehicle dynamics with linear model predictive control. The controller decouples the longitudinal and lateral vehicle dynamics into two successive stages. First, plausible braking and throttle profiles are generated. Second, for each profile, linear time-varying models of the lateral dynamics are derived and used to formulate a collection of linear model predictive control problems. Their solution provides the optimal control input for the steering and braking actuators. The performance of the proposed controller has been evaluated by means of simulations and real experiments.QC 20150911</p

Look-ahead control for fuel-efficient and safe heavy-duty vehicle platooning

The operation of heavy-duty vehicles at small inter-vehicular distances, known as platoons, lowers the aerodynamic drag and, therefore, reduces fuel consumption and greenhouse gas emissions. Tests conducted on flat roads have shown the potential of platooning to reduce the fuel consumption of about 10%. However, platoons are expected to operate on public highways with varying topography alongside other vehicles. Due to the large mass and limited engine power of heavy-duty vehicles, road slopes have a significant impact on feasible and optimal speed profiles. For single vehicles, experiments have shown that optimizing the speed according to the road profile resulted in fuel saving of up to 3.5%. The use of such a look-ahead control framework is expected to lead to large benefits also for platooning. This thesis presents the design of safe and fuel-efficient control of heavy-duty vehicle platoons driving on realistic road profiles. The scenario where the platooning vehicles cooperate to optimize their overall fuel-efficiency is studied together with the scenario where the vehicles do not explicitly cooperate. First, we propose a control architecture that splits the cooperative platooning control problem into two layers. The top layer computes a reference speed profile that ensures fuel-efficient operation of the entire platoon based on dynamic programming. The bottom layer relies on model predictive control to safely track the reference speed. Simulations show the ability of the proposed controller to save up to 12% of fuel for following vehicles compared to existing platoon controllers and to safely react to emergency braking of the leading vehicle. Second, we propose a gear management layer that fits in the cooperative platooning control architecture and explicitly takes the gear selection into account. The underlying optimal control problem aims at minimizing the vehicle fuel consumption and the reference tracking deviations. Simulations indicate how this formulation outperforms existing alternatives, both in terms of fuel-efficiency and tracking error. Third, we address non-cooperative platooning by proposing a vehicle-following controller suitable for fuel-efficient control of heavy-duty vehicles. The proposed controller explores both the benefits given by the short inter-vehicular distance and those given by pulse-and-glide, i.e., alternating traction and coasting phases. A simulation study suggests fuel saving of up to 18% compared to the single vehicle case, and up to 7% compared to when a constant-distance vehicle-following controller is used. Last, we propose a vehicle-following controller aimed at exploiting long preview of the preceding vehicle trajectory by directly manipulating the inputs of low-level vehicle controllers. This is achieved through a model predictive controller that uses a short prediction horizon and includes a terminal state set that incorporates preview information about the preceding vehicle. Experiments indicate the ability of the controller to avoid unnecessary braking, while simulations show behavior similar to the optimal control behavior.QC 20180416</p

Fuel-efficient heavy-duty vehicle platooning by look-ahead control

The operation of groups of heavy-duty vehicles at close intervehicular distances (known as platoons) has been shown to be an effective way of reducing fuel consumption. For single vehicles, it is also known that the availability of preview information on the road topography can be exploited to obtain fuel savings. The current paper aims at the inclusion of preview information in platooning by introducing a two-layer control system architecture for so-called look-ahead platooning. Here, the layers are responsible for the inclusion of preview information and real-time vehicle control for platooning, respectively. Within this framework, a control strategy is presented, where dynamic programming is used for the calculation of fuel-optimal speed profiles, while a model predictive control approach is exploited for the real-time vehicle control. The feasibility of this approach is illustrated by means of the simulation of relevant scenarios.QC 20150402</p

Fuel-efficient heavy-duty vehicle platooning by look-ahead control

The operation of groups of heavy-duty vehicles at close intervehicular distances (known as platoons) has been shown to be an effective way of reducing fuel consumption. For single vehicles, it is also known that the availability of preview information on the road topography can be exploited to obtain fuel savings. The current paper aims at the inclusion of preview information in platooning by introducing a two-layer control system architecture for so-called look-ahead platooning. Here, the layers are responsible for the inclusion of preview information and real-time vehicle control for platooning, respectively. Within this framework, a control strategy is presented, where dynamic programming is used for the calculation of fuel-optimal speed profiles, while a model predictive control approach is exploited for the real-time vehicle control. The feasibility of this approach is illustrated by means of the simulation of relevant scenarios.QC 20150402</p

Linear model predictive control for lane keeping and obstacle avoidance on low curvature roads

This paper presents a control architecture based on a linear MPC formulation that addresses the lane keeping and obstacle avoidance problems for a passenger car driving on low curvature roads. The proposed control design decouples the longitudinal and lateral dynamics in two successive stages. First, plausible braking or throttle profiles are defined over the prediction horizon. Then, based on these profiles, linear time-varying models of the vehicle lateral dynamics are derived and used to formulate the associated linear MPC problems. The solutions of the optimization problems are used to determine for every time step, the optimal braking or throttle command and the corresponding steering angle command. Simulations show the ability of the controller to overcome multiple obstacles and keep the lane. Experimental results on an autonomous passenger vehicle driving on slippery roads show the effectiveness of the approach.QC 20140627</p