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This work investigates traffic control via controlled connected and automated vehicles (CAVs) using novel controllers derived from the linear-quadratic regulator (LQR) theory. CAV-platoons are modeled as moving bottlenecks impacting the surrounding traffic with their speeds as control inputs. An iterative controller algorithm based on the LQR theory is proposed along with a variant that allows for penalizing abrupt changes in platoon speeds. The controllers use the Lighthill-Whitham-Richards (LWR) model implemented using an extended cell transmission model (CTM) which considers the capacity drop phenomenon for a realistic representation of traffic in congestion. The impact of various parameters of the proposed controller on the control performance is analyzed. The effectiveness of the proposed traffic control algorithms is tested using a traffic control example and compared with existing proportional-integral (PI) and model predictive control (MPC) controllers from the literature. A case study using the TransModeler traffic microsimulation software is conducted to test the usability of the proposed controller as well as existing controllers in a realistic setting and derive qualitative insights. It is observed that the proposed controller works well in both settings to mitigate the impact of the jam caused by a fixed bottleneck. The computation time required by the controller is also small making it suitable for real-time control.

 

The decision to establish a network of researchers centers on identifying shared research goals. Ecologically specific regions, such as the USA’s National Ecological Observatory Network’s (NEON’s) eco-climatic domains, are ideal locations by which to assemble researchers with a diverse range of expertise but focused on the same set of ecological challenges. The recently established Great Lakes User Group (GLUG) is NEON’s first domain specific ensemble of researchers, whose goal is to address scientific and technical issues specific to the Great Lakes Domain 5 (D05) by using NEON data to enable advancement of ecosystem science. Here, we report on GLUG’s kick off workshop, which comprised lightning talks, keynote presentations, breakout brainstorming sessions and field site visits. Together, these activities created an environment to foster and strengthen GLUG and NEON user engagement. The tangible outcomes of the workshop exceeded initial expectations and include plans for (i) two journal articles (in addition to this one), (ii) two potential funding proposals, (iii) an assignable assets request and (iv) development of classroom activities using NEON datasets. The success of this 2.5-day event was due to a combination of factors, including establishment of clear objectives, adopting engaging activities and providing opportunities for active participation and inclusive collaboration with diverse participants. Given the success of this approach we encourage others, wanting to organize similar groups of researchers, to adopt the workshop framework presented here which will strengthen existing collaborations and foster new ones, together with raising greater awareness and promotion of use of NEON datasets. Establishing domain specific user groups will help bridge the scale gap between site level data collection and addressing regional and larger ecological challenges.

 

Abstract Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology.