Vehicle Dynamics Control for Rollover Prevention

Vehicle rollover accidents are a particularly dangerous form of road accident. Existing vehicle dynamics controllers primarily deal with yaw stability, and are of limited use for dealing with problems of roll instability. This thesis deals with the development of a new type of vehicle dynamics control system, capable of preventing rollover accidents caused by extreme maneuvering. A control strategy based on limitation of the roll angle while following a yaw rate reference is presented. Methods for rollover detection are investigated. A new computationally–efficient control allocation strategy based on convex optimization is used to map the controller commands to the individual braking forces, taking into account actuator constraints. Simulations show that the strategy is capable of preventing rollover of a commercial van during various standard test maneuvers

Model-Based Vehicle Dynamics Control for Active Safety

The functionality of modern automotive vehicles is becoming increasingly dependent on control systems. Active safety is an area in which control systems play a pivotal role. Currently, rule-based control algorithms are widespread throughout the automotive industry. In order to improve performance and reduce development time, model-based methods may be employed. The primary contribution of this thesis is the development of a vehicle dynamics controller for rollover mitigation. A central part of this work has been the investigation of control allocation methods, which are used to transform high-level controller commands to actuator inputs in the presence of numerous constraints. Quadratic programming is used to solve a static optimization problem in each sample. An investigation of the numerical methods used to solve such problems was carried out, leading to the development of a modified active set algorithm.Vehicle dynamics control systems typically require input from a number of supporting systems, including observers and estimation algorithms. A key parameter for virtually all VDC systems is the friction coefficient. Model-based friction estimation based on the physically-derived brush model is investigated

Toward interoperable bioscience data

© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature Genetics 44 (2012): 121-126, doi:10.1038/ng.1054.To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.The authors also acknowledge the following funding sources in particular: UK Biotechnology and Biological Sciences Research Council (BBSRC) BB/I000771/1 to S.-A.S. and A.T.; UK BBSRC BB/I025840/1 to S.-A.S.; UK BBSRC BB/I000917/1 to D.F.; EU CarcinoGENOMICS (PL037712) to J.K.; US National Institutes of Health (NIH) 1RC2CA148222-01 to W.H. and the HSCI; US MIRADA LTERS DEB-0717390 and Alfred P. Sloan Foundation (ICoMM) to L.A.-Z.; Swiss Federal Government through the Federal Office of Education and Science (FOES) to L.B. and I.X.; EU Innovative Medicines Initiative (IMI) Open PHACTS 115191 to C.T.E.; US Department of Energy (DOE) DE-AC02- 06CH11357 and Arthur P. Sloan Foundation (2011- 6-05) to J.G.; UK BBSRC SysMO-DB2 BB/I004637/1 and BBG0102181 to C.G.; UK BBSRC BB/I000933/1 to C.S. and J.L.G.; UK MRC UD99999906 to J.L.G.; US NIH R21 MH087336 (National Institute of Mental Health) and R00 GM079953 (National Institute of General Medical Science) to A.L.; NIH U54 HG006097 to J.C. and C.E.S.; Australian government through the National Collaborative Research Infrastructure Strategy (NCRIS); BIRN U24-RR025736 and BioScholar RO1-GM083871 to G.B. and the 2009 Super Science initiative to C.A.S

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

publisher: Elsevier articletitle: Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes journaltitle: Cell articlelink: https://doi.org/10.1016/j.cell.2018.05.046 content_type: article copyright: © 2018 Elsevier Inc

Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK.

BACKGROUND: A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. METHODS: This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. FINDINGS: Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0-75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4-97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; pinteraction=0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8-80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3-4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. INTERPRETATION: ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials. FUNDING: UK Research and Innovation, National Institutes for Health Research (NIHR), Coalition for Epidemic Preparedness Innovations, Bill & Melinda Gates Foundation, Lemann Foundation, Rede D'Or, Brava and Telles Foundation, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midland's NIHR Clinical Research Network, and AstraZeneca

Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK

Background A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. Methods This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. Findings Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0–75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4–97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; pinteraction=0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8–80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3–4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. Interpretation ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials

On active set algorithms for solving bound-constrained least squares control allocation problems

Control allocation problems, in which optimal actuator values are assigned based on desired control actions and actuator constraints, are typically formulated as constrained optimization problems. Initially, only approximate solutions to the problems were deemed tractable for real-time applications. Recently however, active set algorithms have been identified as a means for solving control allocation problems in real-time applications. In this paper a modified active set algorithm for the solution of bound-constrained least-squares problems is presented, which has numerous advantages particularly for time-varying control allocation problems. A vehicle dynamics control system for rollover mitigation is used as an example

Optimal control allocation in vehicle dynamics control for rollover mitigation

Vehicle dynamics control systems, previously only intended for yaw stabilization, are now being extended to incorporate rollover mitigation via braking. Current systems typically use a heuristic approach to control allocation, often utilizing only a subset of the available actuators. In this article a computationally-efficient, optimization-based control allocation strategy is used to map controller commands to braking forces on all four wheels, taking into account actuator constraints. Simulations show that the strategy is capable of preventing vehicle rollover for various standard test manoeuvres

Vehicle dynamics control and controller allocation for rollover prevention

Vehicle rollover accidents are a particularly dangerous form of road accident. Commercial vehicles are especially prone to rollover accidents due to their high centres of gravity. A nonlinear control strategy is presented which guarantees asymptotic tracking of a yaw rate reference while bounding the roll angle, thus preventing rollover. A new computationally-efficient control allocation strategy is used to map controller commands to braking forces, taking into account actuator constraints. Simulations show that the strategy is capable of preventing rollover of a commercial van during various standard test maneuver