This study explores the concept of utilizing chaotic traffic flow as a computational resource to mitigate traffic congestion. Using a scaled miniature traffic model and computer simulations, we quantified traffic complexity through the Lyapunov exponent and analyzed the effects of various interventions on traffic dynamics. Our findings show that chaotic behavior in traffic can contribute to increased energy efficiency and improved average speeds. Specifically, we observed that as vehicle density decreased, the complexity of traffic flow can increase, leading to reduced energy consumption per vehicle. Furthermore, interventions such as route selection and signal control influenced traffic dynamics, with potential implications for traffic management strategies. This research highlights the possibility of using chaotic traffic behavior as a novel computational approach to optimize traffic flow and reduce congestion.

Recent policy initiatives aimed at advancing re-newable energy have spurred the proliferation of small-scale photovoltaic power generation installations, with a particular concentration in Japan’s mountainous terrain. These installations predominantly occupy fallow farmland. As explained herein, we embark on the modeling of land use transitions using population dynamics as the overarching framework, encompassing agricultural land and photovoltaic power generation land as important variables. The effectiveness of our proposed model is evaluated rigorously using empirical data. Our numerical simulations vividly depict the potential for harmonious land use patterns between agriculture and photovoltaic power generation, as our model demonstrates. The mathematical model further presents its utility for forecasting the amalgamation and cessation of diverse sites and infrastructure ventures slated for rural landscapes, while concurrently serving as a valuable tool for assessing associated policy initiatives.

In various regions of Japan, efforts are progressing to expand renewable energy sources into the next generation of electrical power networks. As transportation networks such as local bus routes, which are important for regional mobility, are disappearing, municipalities are working to introduce next-generation electrified mobility. The situation is increasingly coming to a resolution that includes network formation progressing in parallel with the two original goals of electric power and mobility. As described herein, photovoltaic power generation, a form of renewable energy, is examined specifically, with storage batteries installed in battery electric vehicles (BEVs) as a regulating power resource. We then specifically examine the feasibility of energy supply demand balance by a renewable energy network accompanied by BEVs, along with the simultaneous establishment of a transportation network. Specifically, we propose a mathematical model and conduct numerical simulations while using a combination of stationary and mobile storage batteries to regulate photovoltaic power generation. Particularly, we demonstrate numerically that photovoltaic power generation can be operated as an off-grid system, as disconnected from the power grid. Additionally, we demonstrate that an optimal ratio for charging BEV exists to maximize the amount of total energy storage.