Abstract-During peak hours in urban areas, unpredictable traffic congestion caused by en route events (e.g., vehicle crashes) increases drivers' travel time and, more seriously, decreases their travel time reliability. In this paper, an original and highly practical vehicle rerouting system, which is called Next Road Rerouting (NRR), is proposed to aid drivers in making the most appropriate next road choice to avoid unexpected congestions. In particular, this heuristic rerouting decision is made upon a cost function that takes into account the driver's destination and local traffic conditions. In addition, the newly designed multiagent system architecture of NRR allows the positive rerouting impacts on local traffic to be disseminated to a larger area through the natural traffic flow propagation within connected local areas. The simulation results based on both synthetic and realistic urban scenarios demonstrate that, compared with the existing solutions, NRR can achieve a lower average travel time while guaranteeing a higher travel time reliability in the face of unexpected congestion. The impacts of NRR on the travel time of both rerouted and nonrerouted vehicles are also assessed, and the corresponding results reveal its higher practicability.

The latest 5G mobile networks have enabled many exciting Internet of Things (IoT) applications that employ Unmanned Aerial Vehicles (UAVs/drones). The success of most UAV-based IoT applications is heavily dependent on artificial intelligence (AI) technologies, for instance, computer vision and path planning. These AI methods must process data and provide decisions while ensuring low latency and low energy consumption. However, the existing cloud-based AI paradigm finds it difficult to meet these strict UAV requirements. Edge AI, which runs AI on-device or on edge servers close to users, can be suitable for improving UAV-based IoT services. This paper provides a comprehensive analysis of the impact of edge AI on key UAV technical aspects (i.e., autonomous navigation, formation control, power management, security and privacy, computer vision, and communication) and applications (i.e., delivery systems, civil infrastructure inspection, precision agriculture, search and rescue operations, acting as aerial wireless BSs and drone light shows). As guidance for researchers and practitioners, the paper also explores UAV-based edge AI implementation challenges, lessons learned, and future research directions.

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As urbanization has been spreading across the world for decades, the traffic congestion problem becomes increasingly serious in most of the major cities. Among the root causes of urban traffic congestion, en route events are the main source of the sudden increase of the road traffic load, especially during peak hours. The current solutions, such as on-board navigation systems for individual vehicles, can only provide optimal routes using current traffic data without considering any traffic changes in the future. Those solutions are thus unable to provide a better alternative route quickly enough if an unexpected congestion occurs. Moreover, using the same alternative routes may lead to new bottlenecks that cannot be avoided. Thus a global traffic load balance cannot be achieved. To deal with these problems, we propose a Multi Agent System (MAS) that can achieve a trade-off between the individual and global benefits by giving the vehicles optimal turn suggestions to bypass a blocked road ahead. The simulation results show that our strategy achieves a substantial gain in average trip time reduction under realistic scenarios. Moreover, the negative impact of selfish re-routing is investigated to show the importance of altruistic re-routing applied in our strategy.

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Abstract-Due to the severe impact of road traffic congestion on both economy and environment, several vehicles routing algorithms have been proposed to optimize travelers itinerary based on real-time traffic feeds or historical data. However, their evaluation methodologies are not as compelling as their key design idea because none of them had been tested under both real transportation map and real traffic data. In this paper, we conduct a deep performance analysis and comparison of four typical vehicles routing algorithms under various scalability levels (i.e. trip length and traffic load) based on realistic transportation simulation. The ultimate goal of this work is to suggest the most suitable routing algorithm to use in different transportation scenarios, so that it can provide a valuable reference for both traffic managers and researchers when they deploy or optimize a large scale centralized Traffic Management System (TMS). The obtained simulation results reveal that dynamic A* is the best routing algorithm if the TMS has sufficient memory or storage capacities, otherwise static A* is also a great alternative.

Photoaging of skin occurs partially due to decreased synthesis and increased degradation of dermal collagen. Antiphotoaging therapy aims to counteract these effects. This study aimed to investigate whether secretory factors from dedifferentiated adipocytes (DAs) could alleviate photoaging in human dermal fibroblasts (HDFs) and in mice and to clarify the underlying mechanism. DAs were acquired and verified based on cellular biomarkers and multilineage differentiation potential. The concentrations of several cytokines in conditioned medium from DAs (DA-CM) were determined. In vivo pathological changes, collagen types I and III, and matrix metalloproteinase (MMP)-1 and -3 were evaluated following the injection of 10-fold concentrated DA-CM into photoaged mice. In vitro, the effect of DA-CM on stress-induced premature senescence in HDFs was investigated by 5-ethynyl-2¢-deoxyuridine (EdU) staining and b-galactosidase staining. The influence of DA-CM and transforming growth factor-b 1 (TGF-b 1 ) on the secretion of collagen types I and III, MMP-1, and MMP-3 in HDFs was evaluated by ELISA. In vivo, we found that subcutaneously injected 10-fold concentrated DA-CM increased the expression of collagen types I and III. In vitro, DA-CM clearly mitigated the decreased cell proliferation and delayed the senescence status in HDFs induced by ultraviolet B (UVB). HDFs treated with DA-CM exhibited higher collagen types I and III secretion and significantly lower MMP-1 and MMP-3 secretion. The TGF-b 1 -neutralizing antibody could partially reduce the recovery effect. Our results suggest that DAs may be useful for aging skin and their effects are mainly due to secreted factors, especially TGF-b 1 , which stimulate collagen synthesis and alleviate collagen degradation in HDFs.