36 research outputs found
An Efficient V2X Based Vehicle Localization Using Single RSU and Single Receiver
High accuracy vehicle localization information is critical for intelligent transportation systems and future autonomous vehicles. It is challenging to achieve the required centimeter-level localization accuracy, especially in urban or global navigation satellite system denied environments. Here we propose a vehicle-to-infrastructure (V2I)-based vehicle localization algorithm. First, it is low-cost and hardware requirements are simplified, the minimum requirement is a single roadside unit and single on-board receiver. Second, it is computationally efficient, the available V2I information is formulated as an over-determined system. Then, the vehicle position is estimated in a closed-form manner via the widely used weighted linear least squares (WLLS) method and meter level accuracy is achievable. Furthermore, the numerical performance of WLLS is consistent with the theoretical results in larger signal-to-noise ratio region
Road Traffic Law Adaptive Decision-making for Self-Driving Vehicles
Self-driving vehicles have their own intelligence to drive on open roads.
However, vehicle managers, e.g., government or industrial companies, still need
a way to tell these self-driving vehicles what behaviors are encouraged or
forbidden. Unlike human drivers, current self-driving vehicles cannot
understand the traffic laws, thus rely on the programmers manually writing the
corresponding principles into the driving systems. It would be less efficient
and hard to adapt some temporary traffic laws, especially when the vehicles use
data-driven decision-making algorithms. Besides, current self-driving vehicle
systems rarely take traffic law modification into consideration. This work aims
to design a road traffic law adaptive decision-making method. The
decision-making algorithm is designed based on reinforcement learning, in which
the traffic rules are usually implicitly coded in deep neural networks. The
main idea is to supply the adaptability to traffic laws of self-driving
vehicles by a law-adaptive backup policy. In this work, the natural
language-based traffic laws are first translated into a logical expression by
the Linear Temporal Logic method. Then, the system will try to monitor in
advance whether the self-driving vehicle may break the traffic laws by
designing a long-term RL action space. Finally, a sample-based planning method
will re-plan the trajectory when the vehicle may break the traffic rules. The
method is validated in a Beijing Winter Olympic Lane scenario and an overtaking
case, built in CARLA simulator. The results show that by adopting this method,
the self-driving vehicles can comply with new issued or updated traffic laws
effectively. This method helps self-driving vehicles governed by digital
traffic laws, which is necessary for the wide adoption of autonomous driving
Increased Expression of Collagen-binding Heat Shock Protein 47 in Human and Experimentally-induced Rat Crescentic Glomerulonephritis: its Possible Role in Fibrotic Process
The 47-kD heat shock protein 47 (HSP47), a major collagen-binding stress protein, is thought to play an important role in fibrotic diseases. To investigate the role of HSP47 in the fibrotic process of crescent formation in renal glomeruli, involvement of HSP47 was examined in both human and experimental crescentic glomerulonephritis (GN). Renal biopsy sections of 15 cases of crescentic GN and 5 cases of minimal change nephrotic syndrome were examined for the expression of HSP47. Experimental crescentic GN was induced by anti-glomerular basement membrane antibody in rats. HSP47 expression was examined in crescents at various stages of formation (days 7, 14, 21, 28 and 42). In human renal biopsy sections, increased expression of HSP47 was noted in the cellular stage of crescent formation. Double immunostaining demonstrated that the majority of ホア-smooth muscle actin-positive cells in the crescent expressed HSP47. However, its expression was less in fibrous crescents, which were predominantly composed of type III collagen. In the rat model of crescent GN, increased expression of HSP47, both at mRNA and protein levels, was noted in the early stages of cellular crescents. However, its expression was decreased in the late stages of fibrous crescents. Based on the collagen synthesis ability of HSP47, we speculate that overexpression of HSP47 in cellular crescents may contribute to the excessive synthesis/ assembly of collagens and subsequently lead to irreversible fibrous crescent formation
A survey on 5G massive MIMO Localization
Massive antenna arrays can be used to meet the requirements of 5G, by exploiting different spatial signatures of users. This same property can also be harnessed to determine the locations of those users. In order to perform massive MIMO localization, refined channel estimation routines and localization methods have been developed. This paper provides a brief overview of this emerging field