| 1. |
- Carbajales, Carlos, et al.
(författare)
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Structure-Based Design of New KSP-Eg5 Inhibitors Assisted by a Targeted Multicomponent Reaction
- 2014
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Ingår i: ChemBioChem. - : Wiley. - 1439-4227 .- 1439-7633. ; 15:10, s. 1471-1480
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Tidskriftsartikel (refereegranskat)abstract
- An integrated multidisciplinary approach that combined structure-based drug design, multicomponent reaction synthetic approaches and functional characterization in enzymatic and cell assays led to the discovery of new kinesin spindle protein (KSP) inhibitors with antiproliferative activity. A focused library of new benzimidazoles obtained by a Ugi + Boc removal/cyclization reaction sequence generated low-micromolar-range KSP inhibitors as promising anticancer prototypes. The design and functional studies of the new chemotypes were assessed by computational modeling and molecular biology techniques. The most active compounds-20 (IC50=1.49 mu m, EC50=3.63 mu m) and 22 (IC50=1.37 mu m, EC50=6.90 mu m)-were synthesized with high efficiency by taking advantage of the multicomponent reactions.
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| 2. |
- Carrasco Limeros, Sandra, et al.
(författare)
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Towards trustworthy multi-modal motion prediction: Holistic evaluation and interpretability of outputs
- 2024
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Ingår i: CAAI Transactions on Intelligence Technology. - : WILEY. - 2468-6557 .- 2468-2322. ; 9:3, s. 557-572
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Tidskriftsartikel (refereegranskat)abstract
- Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path planning. This task is very complex, as the behaviour of road agents depends on many factors and the number of possible future trajectories can be considerable (multi-modal). Most prior approaches proposed to address multi-modal motion prediction are based on complex machine learning systems that have limited interpretability. Moreover, the metrics used in current benchmarks do not evaluate all aspects of the problem, such as the diversity and admissibility of the output. The authors aim to advance towards the design of trustworthy motion prediction systems, based on some of the requirements for the design of Trustworthy Artificial Intelligence. The focus is on evaluation criteria, robustness, and interpretability of outputs. First, the evaluation metrics are comprehensively analysed, the main gaps of current benchmarks are identified, and a new holistic evaluation framework is proposed. Then, a method for the assessment of spatial and temporal robustness is introduced by simulating noise in the perception system. To enhance the interpretability of the outputs and generate more balanced results in the proposed evaluation framework, an intent prediction layer that can be attached to multi-modal motion prediction models is proposed. The effectiveness of this approach is assessed through a survey that explores different elements in the visualisation of the multi-modal trajectories and intentions. The proposed approach and findings make a significant contribution to the development of trustworthy motion prediction systems for autonomous vehicles, advancing the field towards greater safety and reliability.
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| 3. |
- Hu, Songlin, et al.
(författare)
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L2 -Gain-Based Path Following Control for Autonomous Vehicles Under Time-Constrained DoS Attacks
- 2024
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; , s. 1-13
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Tidskriftsartikel (refereegranskat)abstract
- Autonomous vehicles (AVs) are being enhanced by introducing wireless communication to improve their intelligence, reliability and efficiency. Despite all of these distinct advantages, the open wireless communication links and connectivity make the AVs' vulnerability to cyber-attacks. This paper proposes an L-2 -gain-based resilient path following control strategy for AVs under time-constrained denial-of-service (DoS) attacks and external interference. A switching-like path following control model of AVs is first built in the presence of DoS attacks, which is characterized by the lower and upper bounds of the sleeping period and active period of the DoS attacker. Then, the exponential stability and L-2 -gain performance of the resulting switched system are analyzed by using a time-varying Lyapunov function method. On the basis of the obtained analysis results, L-2 -gain-based resilient controllers are designed to achieve an acceptable path-following performance despite the presence of such DoS attacks. Finally, the effectiveness of the proposed L-2 -gain-based resilient path following control method is confirmed by the simulation results obtained for the considered AVs model with different DoS attack parameters.
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| 4. |
- Hu, Xin, et al.
(författare)
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Dynamic Event-Triggered Adaptive Formation With Disturbance Rejection for Marine Vehicles Under Unknown Model Dynamics
- 2023
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Ingår i: IEEE Transactions on Vehicular Technology. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9545 .- 1939-9359. ; 72:5, s. 5664-5676
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Tidskriftsartikel (refereegranskat)abstract
- This paper investigates the dynamic event-triggered adaptive neural coordinated disturbance rejection for marine vehicles with external disturbances as the sinusoidal superpositions with unknown frequencies, amplitudes and phases. The vehicle movement mathematical models are transformed into parameterized expressions with the neural networks approximating nonlinear dynamics. The parametric exogenous systems are exploited to express external disturbances, which are converted into the linear canonical models with coordinated changes. The adaptive technique together with disturbance filters realize the disturbance estimation and rejection. By using the vectorial backstepping, the dynamic event-triggered adaptive neural coordinated disturbance rejection controller is derived with the dynamic event-triggering conditions being incorporated to reduce execution frequencies of vehicle's propulsion systems. The coordinated formation control can be achieved with the closed-loop semi-global stability. The dynamic event-triggered adaptive disturbance rejection scheme achieves the disturbance estimation and cancellation without requiring the a priori marine vehicle's model dynamics. Illustrative simulations and comparisons validate the proposed scheme.
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| 5. |
- Li, Yicheng, et al.
(författare)
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Creating navigation map in semi-open scenarios for intelligent vehicle localization using multi-sensor fusion
- 2021
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Ingår i: Expert systems with applications. - : Elsevier. - 0957-4174 .- 1873-6793. ; 184
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Tidskriftsartikel (refereegranskat)abstract
- In order to pursue high-accuracy localization for intelligent vehicles (IVs) in semi-open scenarios, this study proposes a new map creation method based on multi-sensor fusion technique. In this new method, the road scenario fingerprint (RSF) was employed to fuse the visual features, three-dimensional (3D) data and trajectories in the multi-view and multi-sensor information fusion process. The visual features were collected in the front and downward views of the IVs; the 3D data were collected by the laser scanner and the downward camera and a homography method was proposed to reconstruct the monocular 3D data; the trajectories were computed from the 3D data in the downward view. Moreover, a new plane-corresponding calibration strategy was developed to ensure the fusion quality of sensory measurements of the camera and laser. In order to evaluate the proposed method, experimental tests were carried out in a 5 km semi-open ring route. A series of nodes were found to construct the RSF map. The experimental results demonstrate that the mean error of the nodes between the created and actual maps was 2.7 cm, the standard deviation of the nodes was 2.1 cm and the max error was 11.8 cm. The localization error of the IV was 10.8 cm. Hence, the proposed RSF map can be applied to semi-open scenarios in practice to provide a reliable basic for IV localization.
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| 6. |
- Liu, Wanli, et al.
(författare)
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A Novel Multifeature Based On-Site Calibration Method for LiDAR-IMU System
- 2020
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Ingår i: IEEE Transactions on Industrial Electronics. - : IEEE. - 0278-0046 .- 1557-9948. ; 67:11, s. 9851-9861
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Tidskriftsartikel (refereegranskat)abstract
- Calibration is an essential prerequisite for the combined application of light detection and ranging (LiDAR) and inertial measurement unit (IMU). However, current LiDAR-IMU calibration usually relies on particular artificial targets or facilities and the intensive labor greatly limits the calibration flexibility. For these reasons, this article presents a novel multifeature based on-site calibration method for LiDAR-IMU system without any artificial targets or specific facilities. This new on-site calibration combines the point/sphere, line/cylinder, and plane features from LiDAR scanned data to reduce the labor intensity. The main contribution is that a new method is developed for LiDAR extrinsic parameters on-site calibration and this method could incorporate two or more calibration models to generate more accurate calibration results. First of all, the calibration of LiDAR extrinsic parameters is performed through estimating the geometric features and solving the multifeature geometric constrained optimization problem. Then, the relationships between LiDAR and IMU intrinsic calibration parameters are determined by the coordinate transformation. Lastly, the full information maximum likelihood estimation (FIMLE) method is applied to solve the optimization of the IMU intrinsic parameters calibration. A series of experiments are conducted to evaluate the proposed method. The analysis results demonstrate that the proposed on-site calibration method can improve the performance of the LiDAR-IMU.
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| 7. |
- Liu, Wi, et al.
(författare)
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Design a Novel Target to Improve Positioning Accuracy of Autonomous Vehicular Navigation System in GPS Denied Environments
- 2021
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Ingår i: IEEE Transactions on Industrial Informatics. - : IEEE. - 1551-3203 .- 1941-0050. ; 17:11, s. 7575-7588
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Tidskriftsartikel (refereegranskat)abstract
- Accurate positioning is an essential requirement of autonomous vehicular navigation system (AVNS) for safe driving. Although the vehicle position can be obtained in Global Position System (GPS) friendly environments, in GPS denied environments (such as suburb, tunnel, forest or underground scenarios) the positioning accuracy of AVNS is easily reduced by the trajectory error of the vehicle. In order to solve this problem, the plane, sphere, cylinder and cone are often selected as the ground control targets to eliminate the trajectory error for AVNS. However, these targets usually suffer from the limitations of incidence angle, measuring range, scanning resolution, and point cloud density, etc. To bridge this research gap, an adaptive continuum shape constraint analysis (ACSCA) method is presented in this paper to design a new target with optimized identifiable specific shape to eliminate the trajectory error for AVNS. First of all, according to the proposed ACSCA method, we conduct extensive numerical simulations to explore the optimal ranges of the vertexes and the faces for target shape design, and based on these trials, the optimal target shape is found as icosahedron, which composes of 10 vertexes, 20 faces and combines the properties of plane and volume target. Moreover, the algorithm of automatic detection and coordinate calculation is developed to recognize the icosahedron target and calculate its coordinates information for AVNS. Lastly, a series of experimental investigation were performed to evaluate the effectiveness of our designed icosahedron target in GPS denied environments. The experimental results demonstrate that compared with the plane, sphere, cylinder and cone targets, the developed icosahedron target can produce better performances than the above targets in terms of the clustered minimum registration error, ambiguity and range of field-of-view; also can significantly improve the positioning accuracy of AVNS in GPS denied environments.
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| 8. |
- Ma, Yulin, et al.
(författare)
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A novel multi-mode hybrid control method for cooperative driving of an automated vehicle platoon
- 2021
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 8:7, s. 5822-5838
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Tidskriftsartikel (refereegranskat)abstract
- A multi-mode hybrid automaton is proposed for setting vehicle platoon modes with velocity, distance, length, lane position and other state information. Based on a vehicle platoon shift movement under different modes, decisions are made based on key conditional actions such as sudden acceleration changes because of vehicle distance changes, emergency braking to avoid collisions and free-lane changing choices adapted to various traffic conditions, so as to ensure effortless movement and safety in multi-mode shift. With a 3-degree (longitudinal, lateral, and yaw directions) of freedom coupled model, a hybrid vehicle platoon controller is proposed using non-singular terminal sliding mode control to ensure fast and steady tracking on the hybrid automaton outputs during the multi-mode shift process. Convergence of the hybrid controller in finite time is also analyzed with the Lyapunov exponential stability. The analysis result proves that the proposed controller not only ensures the stability of the individual vehicle and the vehicle platoon, but also ensures stability of the multi-mode shift movement system. The proposed cooperative driving strategy for vehicle platoon is evaluated using simulations, where varying traffic conditions and the influence of cutting off are considered in conjunction with demonstration simulations of a vehicle platoon’s cruising, following, lane changing, overtaking and moving in/out of garage functions.
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| 9. |
- Ma, Yong, et al.
(författare)
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CCIBA*: An Improved BA* Based Collaborative Coverage Path Planning Method for Multiple Unmanned Surface Mapping Vehicles
- 2022
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:10, s. 19578-19588
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Tidskriftsartikel (refereegranskat)abstract
- The main emphasis of this work is placed on the problem of collaborative coverage path planning for unmanned surface mapping vehicles (USMVs). As a result, the collaborative coverage improved BA* algorithm (CCIBA*) is proposed. In the algorithm, coverage path planning for a single vehicle is achieved by task decomposition and level map updating. Then a multiple USMV collaborative behavior strategy is designed, which is composed of area division, recall and transfer, area exchange and recognizing obstacles. Moverover, multiple USMV collaborative coverage path planning can be achieved. Consequently, a high-efficiency and high-quality coverage path for USMVs can be implemented. Water area simulation results indicate that our CCIBA* brings about a substantial increase in the performances of path length, number of turning, number of units and coverage rate.
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| 10. |
- Zhao, Yujiao, et al.
(författare)
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Path Following Optimization for an Underactuated USV Using Smoothly-Convergent Deep Reinforcement Learning
- 2021
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 22:10, s. 6208-6220
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Tidskriftsartikel (refereegranskat)abstract
- This paper aims to solve the path following problem for an underactuated unmanned-surface-vessel (USV) based on deep reinforcement learning (DRL). A smoothly-convergent DRL (SCDRL) method is proposed based on the deep Q network (DQN) and reinforcement learning. In this new method, an improved DQN structure was developed as a decision-making network to reduce the complexity of the control law for the path following of a three-degree of freedom USV model. An exploring function was proposed based on the adaptive gradient descent to extract the training knowledge for the DQN from the empirical data. In addition, a new reward function was designed to evaluate the output decisions of the DQN, and hence, to reinforce the decision-making network in controlling the USV path following. Numerical simulations were conducted to evaluate the performance of the proposed method. The analysis results demonstrate that the proposed SCDRL converges more smoothly than the traditional deep Q learning while the path following error of the SCDRL is comparable to existing methods. Thanks to good usability and generality of the proposed method for USV path following, it can be applied to practical applications.
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