Search

Electric Vehicle (EV) public charging is important to meet the exploding charging demand and to address the range anxiety issue. In this paper, we focus on the EV public charging market with heterogeneous charging stations (CSs) under the time-based billing model. We jointly consider the charging time optimization for EVs, the EV-CS pairing, and the pricing mechanism for CSs. A hierarchical game, which mathematically corresponds to an equilibrium problem with equilibrium constraints (EPEC), is then developed to formulate the three coupled problems. In the proposed hierarchical game, each CS sets the charging price to maximize its own revenue first, then the EVs choose their desired CSs and determine the charging time. We analyze the optimal charging time strategies for EVs, and a many-to-one matching algorithm is applied to solve the EV-CS pairing problem. Besides, a block coordinate descent (BCD) based algorithm is applied for each CS to solve the pricing problem. Simulation results show that our proposed schemes can achieve the performance improvement of the charging system. [ABSTRACT FROM AUTHOR]

A trajectory planning is a technique that is widely used to automatically generate an expected geometric path that a vehicle needs to follow within a certain future time horizon. We propose a way to generate trajectories of multiple vehicles for a short-term planning with the formal guarantee of the collision avoidance using a SAT (Satisfiability) solver. We assume that each vehicle sends the local status (e.g., speed or position) and its planned trajectory to the server (e.g., road-side units or cloud servers). The server collects the information, and determines if the group of vehicles would encounter any collision within a fixed amount of time. Then, the server calculates the modified trajectories, and sends them back to the vehicles to avoid collisions. Calculating such trajectories is generally a complex problem, which makes it challenging to find them within a short amount of time. Given a driving scenario where multiple vehicles are engaged, we propose two methods to reduce the computation time to generate the trajectories. Firstly, we introduce the grouping method which systematically identifies vehicles that are not engaged in the collision scenario, and removes the related parameters from the SAT solving process. Our case study of the ramp merging driving scenario shows the grouping method saves the computation time by 40% compared to solving the constraints with the original parameters. Secondly, we introduce the collision check point method that chooses some waypoints to maintain their previous control input to reduce the problem complexity. Our experiment shows up to 98% computation time reduction compared to the approach without this method. [ABSTRACT FROM AUTHOR]

With the development of autonomous vehicular technologies, the execution tasks become more memory-consuming and computation-intensive. Simultaneously, a certain portion of tasks are latency-sensitive, such as collaborative perception, path planning, collaborative simultaneous localization and mapping, real-time pedestrian detection, etc. Because of the limited computation resources inside vehicles and restricted transmission bandwidth, edge computing can be an effective way to assist with the tasks execution. Considering from the perspective of business, the reservation or subscription cost is cheaper than real time requests. In order to minimize the expense of consuming edge services, the desirable situation is to reserve the resources as much as needed. However, the configuration of vehicular network is variational in practice due to the diversity of road maps, different time range like peak time and off-peak time, and the various task types, which makes it challenging to figure out a general machine learning model that is suitable for any case. Therefore, to predict the resource consumption in edge nodes accurately in different scenarios, we propose a two-stage meta-learning based approach to adaptively choose the appropriate machine learning algorithms based on the meta-features extracted on database. Besides, due to the deficiency of dataset for edge resource consumption, we program in game engine unity to generate the 3D model of Manhattan area. Meanwhile, we change the factors like different road maps and number of vehicles so as to get closer to practices. In the evaluation part, we adopt root mean square error, mean absolute percentage, and mean GEH as evaluation metrics to assess the performance of each model. Also, a quantitative analysis for the total cost and waste is also conducted. Eventually, we can find that the proposed meta-learning based method outperforms the non-meta ones. [ABSTRACT FROM AUTHOR]

Multi-source data fusion to support vehicle on-road analysis is a promising service offered by mobile edge computing (MEC) for vehicles. With the fusion results delivered in near real-time, vehicle users (VUs) can peek around the corner, extend sensing range, reinforce and validate local observations. Consequently, there has emerged a new market between smart mobility service providers (SMSPs) and VUs in offering and purchasing multi-source data fusion results to support vehicle on-road analysis. Each SMSP and each VU compete with their peers to maximize their own profits. Also, VUs can receive multiple fusion results from several SMSPs and combine them to achieve a better inference. In this paper, we develop a multi-leader-follower game to model this complicated coupled problem. For the single-SMSP scenario, we analyze the properties of the leader-follower (L/F) Nash equilibrium and then reformulate the game as a mathematical program with equilibrium constraints (MPEC) to obtain the equilibrium. For the multi-SMSP scenario, the game is reinterpreted as an equilibrium problem with equilibrium constraints (EPEC), for which we analyze the local Nash equilibrium (LNE) with the assistance of variational inequality (VI) theory. Then, the block coordinate descent (BCD) method, which is low-complexity, is applied to solve the EPEC. Finally, numerical results are provided to validate the theoretical analysis and show that our proposed strategies maximize the utilities for both SMSPs and VUs. [ABSTRACT FROM AUTHOR]

Modern vehicle is equipped with autonomous features, such as precollision system or adaptive cruise control to help people perform driving in a safer and more convenient way. The software complexity of those autonomous features is growing to accommodate various needs from users, which makes it more difficult to test their correctness. Virtual prototyping allows one to test the vehicle software in the virtual road environment. Even though several tools are available, original equipment manufacturers seem to be hesitating to fully integrate the virtual test as a part of the vehicle development plan. One of the obstacle is due to a lack of well-defined test criteria that can reasonably abstract the physical environment and test case generation methods that automatically visualize the virtual road environment. In this letter, we propose several associated research directions and potential approaches from the perspective of test criteria and test case generation. [ABSTRACT FROM PUBLISHER]

Medical cyber–physical systems (MCPS) are life-critical, context-aware, networked systems of medical devices. These systems are increasingly used in hospitals to provide high-quality continuous care for patients. The need to design complex MCPS that are both safe and effective has presented numerous challenges, including achieving high assurance in system software, intoperability, context-aware intelligence, autonomy, security and privacy, and device certifiability. In this paper, we discuss these challenges in developing MCPS, some of our work in addressing them, and several open research issues. [ABSTRACT FROM PUBLISHER]

DROSHA serves as a gatekeeper of the microRNA (miRNA) pathway by processing primary transcripts (pri-miRNAs). While the functions of structured domains of DROSHA have been well documented, the contribution of N-terminal proline-rich disordered domain (PRD) remains elusive. Here we show that the PRD promotes the processing of miRNA hairpins located within introns. We identified a DROSHA isoform (p140) lacking the PRD, which is produced by proteolytic cleavage. Small RNA sequencing revealed that p140 is significantly impaired in the maturation of intronic miRNAs. Consistently, our minigene constructs demonstrated that PRD enhances the processing of intronic hairpins, but not those in exons. Splice site mutations did not affect the PRD's enhancing effect on intronic constructs, suggesting that the PRD acts independently of splicing reaction by interacting with sequences residing within introns. The N-terminal regions from zebrafish and Xenopus DROSHA can replace the human counterpart, indicating functional conservation despite poor sequence alignment. Moreover, we found that rapidly evolving intronic miRNAs are generally more dependent on PRD than conserved ones, suggesting a role of PRD in miRNA evolution. Our study reveals a new layer of miRNA regulation mediated by a low-complexity disordered domain that senses the genomic contexts of miRNA loci., (© 2023 Son et al.; Published by Cold Spring Harbor Laboratory Press.)

Sleep is an essential physiological process, especially for proper brain function through the formation of new pathways and processing information and cognition. Therefore, when sleep is insufficient, this can result in pathophysiologic conditions. Sleep deficiency is a risk factor for various conditions, including dementia, diabetes, and obesity. Recent studies have shown that there are differences in the prevalence of sleep disorders between genders. Insomnia, the most common type of sleep disorder, has been reported to have a higher incidence in females than in males. However, sex/gender differences in other sleep disorder subtypes are not thoroughly understood. Currently, increasing evidence suggests that gender issues should be considered important when prescribing medicine. Therefore, an investigation of the gender-dependent differences in sleep disorders is required. In this review, we first describe sex/gender differences not only in the prevalence of sleep disorders by category but in the efficacy of sleep medications. In addition, we summarize sex/gender differences in the impact of sleep disorders on incident dementia. This may help understand gender-dependent pathogenesis of sleep disorders and develop therapeutic strategies in men and women.