Heavy-duty truck platooning on hilly terrain highways: Methods for assessment and improvement

Platooning heavy-duty trucks is a proven method to reduce fuel consumption on flat ground, but a significant portion of the U.S. highway system covers hilly terrain. The effort described in this paper uses experimentally gathered single truck data from a route with hilly terrain and an experimentally-validated two-truck platoon simulation framework to analyze control methods for effective platooning on hilly terrain. Specifically, this effort investigates two platoon control aspects: (1) the lead truck’s vehicle speed control and (2) the platoon’s transmission shifting algorithm. Three different types of lead truck speed control strategies are analyzed using the validated platoon model. Two are commercially available cruise control strategies – conventional constant set speed cruise control (CCC) and flexible set speed cruise control (FCC). The third lead truck speed control strategy was developed by the authors in this paper. It uses look-ahead grade information for an entire route to create an energy-optimal speed profile for the lead truck which is called long-horizon predictive cruise control (LHPCC). Then, a two-truck platoon transmission shifting strategy that coordinates the shift events – Simultaneous Shifting (SS) – is introduced and compared to a commercially available shifting strategy using the validated platoon model. This shifting strategy demonstrates further improvements in the platoon performance by improving the platoon gap control. A summary of these simulations demonstrates that the performance of the platoon can be improved by three methods: adding speed flexibility to the lead truck speed control method, using look-ahead road grade information to generate energy-optimal speed targets for the lead truck, and coordinating the timing of the transmission shifts for each truck in the platoon.

Through the Eyes on the Ground: Re-positioning Rural Agrarian Actors as Leaders in the Local Food Movement during the COVID-19 Pandemic

Despite Costa Rica’s efforts to promote international tourism, the economy continues to struggle with unprecedented unemployment rates due to the COVID-19 pandemic. This is especially concerning for tourism-dependent regions, such as the Monteverde Zone, where most residents have abandoned land-based livelihoods in favor of tourism. This study uses photovoice to illustrate the ways that small-scale food producers have adapted to the unique challenges of the COVID-19 global pandemic in a region that was already experiencing a loss of agrarian identity. Overall, local food producers have been affected by the diminished tourism economy through the closing of restaurants and the decrease in tourists, causing them to experience crop loss. Food producers have adapted to the economic impacts of the pandemic by re-investing their efforts into a local economy. As part of this shifting strategy, some food producers have begun to expand, diversify, and embrace an approach to growing food that is in line with building more resilient models of food production and engaging with their clients in different ways. Using community-based participatory methods, this study illustrates how food producers have adapted to changes brought on by the pandemic, re-positioning some of these rural agrarian actors as prominent figures in the local food movement.

Precursor-Based Earthquake Prediction Research: Proposal for a Paradigm-Shifting Strategy

The article discusses the controversial topic of the precursor-based earthquake prediction, based on a personal perspective intending to stir the current still waters of the issue after twenty years have passed since the influential debate on earthquake prediction hosted by Nature in 1999. The article challenges the currently dominant pessimistic view on precursor-based earthquake prediction resting on the “impossible in principle” paradigm. Instead, it suggests that a concept-based innovative research strategy is the key to obtain significant results, i.e., a possible paradigm shift, in this domain. The basic concept underlying such a possible strategy is the “precursory fingerprint” of individual seismic structures derived from the uniqueness of the structures themselves. The aim is to find as many unique fingerprints as possible for different seismic structures worldwide, covering all earthquake typologies. To achieve this, a multiparameter approach involving all possible sensor types (physical, chemical, and biological) of the highest available sensitivity and artificial intelligence could be used. The findings would then be extrapolated to other similar structures. One key issue is the emplacement location of the sensor array in privileged “sensitive” Earth surface sites (such as volcanic conduits) where the signal-to-noise ratio is maximized, as suggested in the article. The strategy envisages three stages: experimental phase, validation, and implementation. It inherently could be a costly, multidisciplinary, international, and long-term (i.e., multidecade) endeavor with no guaranteed success, but less adventurous and societally more significant to the currently running and well-funded SETI Project.