This paper proposes an optimized trajectory planner and motion planner framework, which aim to deal with obstacle avoidance along a reference road for autonomous driving in unstructured environments. ...The trajectory planning problem is decomposed into lateral and longitudinal planning sub-tasks along the reference road. First, a vehicle kinematic model with road coordinates is established to describe the lateral movement of the vehicle. Then, nonlinear optimization based on a vehicle kinematic model in the space domain is employed to smooth the reference road. Second, a multilayered search algorithm is applied in the lateral-space domain to deal with obstacles and find a suitable path boundary. Then, the optimized path planner calculates the optimal path by considering the distance to the reference road and the curvature constraints. Furthermore, the optimized speed planner takes into account the speed boundary in the space domain and the constraints on vehicle acceleration. The optimal speed profile is obtained by using a numerical optimization method. Furthermore, a motion controller based on a kinematic error model is proposed to follow the desired trajectory. Finally, the experimental results show the effectiveness of the proposed trajectory planner and motion controller framework in handling typical scenarios and avoiding obstacles safely and smoothly on the reference road and in unstructured environments.
A new and expedient photocatalytic protocol for the construction of quinolin-2(1
H
)-ones
via
Markovnikov-type sulfonylation/6-endo-trig cyclization/selective C(O)-CF
3
bond cleavage starting from
N
...-alkyl-
N
-(2-ethynylphenyl)-2,2,2-trifluoroacetamides and sulfinic acids has been developed. It is as an unprecedented protocol for the preparation of 4-sulfonylquinoline-2(1
H
)-ones with high efficiency, mild reaction conditions, acceptable yields and a wide range of substrates.
A novel and convenient photocatalytic cyclization of terminal alkynes for the construction of 4-sulfonylquinoline-2(1
H
)-ones by radical Markovnikov addition/6-endo-trig cyclization/selective C(O)-CF
3
bond cleavage was disclosed.
This study presents a convenient approach to the synthesis of indole- and benzofuran-based benzylic sulfones using unactivated alkynes containing aryl iodides and sodium sulfinates under visible ...light irradiation. The procedure involves a sequential series of dehalogenation, carbo-cyclization, and radical sulfonylation. Plausible insights into the reaction mechanism are derived from control experiments, leading to the proposal of a radical cascade reaction pathway.
Acquiring road information is important for smart cities and sustainable urban development. In recent years, significant progress has been made in the extraction of urban road information from remote ...sensing images using deep learning (DL) algorithms. However, due to the complex shape, narrowness, and high span of roads in the images, the results are often unsatisfactory. This article proposes a Seg-Road model to improve road connectivity. The Seg-Road uses a transformer structure to extract the long-range dependency and global contextual information to improve the fragmentation of road segmentation and uses a convolutional neural network (CNN) structure to extract local contextual information to improve the segmentation of road details. Furthermore, a novel pixel connectivity structure (PCS) is proposed to improve the connectivity of road segmentation and the robustness of prediction results. To verify the effectiveness of Seg-Road for road segmentation, the DeepGlobe and Massachusetts datasets were used for training and testing. The experimental results show that Seg-Road achieves state-of-the-art (SOTA) performance, with an intersection over union (IoU) of 67.20%, mean intersection over union (MIoU) of 82.06%, F1 of 91.43%, precision of 90.05%, and recall of 92.85% in the DeepGlobe dataset, and achieves an IoU of 68.38%, MIoU of 83.89%, F1 of 90.01%, precision of 87.34%, and recall of 92.86% in the Massachusetts dataset, which is better than the values for CoANet. Further, it has higher application value for achieving sustainable urban development.
Selectively producing a variety of valuable compounds using controlled chemical reactions starting from a common material is an appealing yet complex concept. Herein, a photocatalytic approach for ...the selective synthesis of (E)-β-aminovinyl sulfones and (E)-β-amidovinyl sulfones from allenamides and sodium sulfinates was established. This reaction exhibits the traits of an eco-friendly solvent and adjustable amide cleavage, and can accommodate a diverse range of substrates with exceptional functional group tolerance. Based on control experiments and deuterium labeling experiments, a plausible radical reaction pathway is proposed.
An atom-economic method of preparing allylic sulfones
via
hydrosulfonylation of allenes with sulfinic acids under Pd(0)-catalysis was reported. This process has a high degree of regio- and ...stereoselectivity, and provides the target product with a moderate to excellent yield. A wide range of nitrogen- or oxygen-containing linear
E
-allylic sulfones have been synthesized. With the support of experimental research, a possible mechanism was proposed.
A simple palladium-based catalytic system for hydrosulfonylation of allenamides was established. Various nitrogen-containing linear allylic sulfones can be generated in moderate to excellent yield with
E
-selectivity and 100% atom utilization.
It is difficult for traditional therapies to further improve the prognosis of hepatocellular carcinoma (LIHC), and immunotherapy is considered to be a promising approach to overcome this dilemma. ...However, only a minority of patients benefit from immunotherapy, which greatly limits its application. Therefore, it is particularly urgent to elucidate the specific regulatory mechanism of tumor immunity so as to provide a new direction for immunotherapy. NOP2/Sun RNA methyltransferase 3 (NSUN3) is a protein with RNA binding and methyltransferase activity, which has been shown to be involved in the occurrence and development of a variety of tumors. At present, the relationship between NSUN3 and immune implication in LIHC has not been reported. In this study, we first revealed that NSUN3 expression is upregulated in LIHC and that patients with high NSUN3 expression have a poor prognosis through multiple databases. Pathway enrichment analysis demonstrated that NSUN3 may be participated in cell adhesion and cell matrix remodeling. Next, we obtained a set of genes coexpressed with NSUN3 (NCGs). Further LASSO regression was performed based on NCGs, and a risk score model was constructed, which proved to have good predictive power. In addition, Cox regression analysis revealed that the risk score of NCGs model was an independent risk factor for LIHC patients. Moreover, we established a nomogram based on the NCGs-related model, which was verified to have a good predictive ability for the prognosis of LIHC. Furthermore, we investigated the relationship between NCGs-related model and immune implication. The results implied that our model was closely related to immune score, immune cell infiltration, immunotherapy response, and multiple immune checkpoints. Finally, the pathway enrichment analysis of NCGs-related model showed that the model may be involved in the regulation of various immune pathways. In conclusion, our study revealed a novel role of NSUN3 in LIHC. The NSUN3-based prognostic model may be a promising biomarker for inspecting the prognosis and immunotherapy response of LIHC.
This paper presents a model predictive trajectory optimization and tracking framework to avoid collisions for autonomous vehicles in highly constrained environments. Firstly, a vehicle model is ...established in road coordinate system to describe the relationship between the vehicle and the reference road. Secondly, a numerical optimization method is applied to smoothen the reference path generated by waypoints. Then, a multilayer searched method is used to establish a safe driving corridor in highly constrained environments. In addition, an optimal path optimization and tracking framework based on model predictive control is formulated to improve the driving safety and comfort. The proposed framework considers the constraints of path boundaries and vehicle dynamics to provide the optimal control command. Furthermore, the speed profile is optimized based on the longitudinal motion model in space domain to ensure the constraints of speed limits and vehicle acceleration. Finally, the proposed algorithms are evaluated through experiments in various scenarios to demonstrate the effectiveness.
The tire-road peak adhesion coefficient (TRPAC), which cannot be directly measured by on-board sensors, is essential to road traffic safety. Reliable TRPAC estimation can not only serve the vehicle ...active safety system, but also benefit the safety of other traffic participants. In this paper, a TRPAC fusion estimation method considering model uncertainty is proposed. Based on virtual sensing theory, an image-based fusion estimator considering the uncertainty of the deep-learning model and the kinematic model is designed to realize the accurate classification of the road surface condition on which the vehicle will travel in the future. Then, a dynamics-image-based fusion estimator considering the uncertainty of visual information is proposed based on gain scheduling theory. The results of simulation and real vehicle experiments show that the proposed fusion estimation method can make full use of multisource sensor information, and has significant advantages in estimation accuracy, convergence speed and estimation robustness compared with other single-source-based estimators.
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