Ischemic postconditioning has been found to decrease brain infarct area and spinal cord ischemic injury. In this study, we tested the hypothesis that reduces global cerebral ischemia/reperfusion-induced structural functional injury in rats.Ten-minute ischemia was induced by 4-vessel occlusion male Sprague-Dawley rats. The animals underwent consisting of 3 cycles 15-second/15-second (Post-15/15), 30-second/30-second (Post-30/30), or 60-second/15-second (Post-60/15) reperfusion/reocclusion...

Driving through dynamically changing traffic scenarios is a highly challenging task for autonomous vehicles, especially on urban roadways. Prediction of surrounding vehicles’ driving behaviors plays crucial role in vehicles. Most traditional behavior prediction models work only specific scenario and cannot be adapted to different scenarios. In addition, priori knowledge was never considered sufficiently. This study proposes novel scenario-adaptive approach solve these problems. A ontology...

Navigation and positioning technology is closely related to our routine life activities, from travel aerospace. Recently it has been found that Cataglyphis (a kind of desert ant) able detect the polarization direction skylight navigate according this information. This paper presents a real-time bionic camera-based navigation sensor. sensor two work modes: one single-point measurement mode other multi-point mode. An indoor calibration experiment done under beam standard polarized light. The...

Ground segmentation is an important preprocessing task for autonomous vehicles (AVs) with 3D LiDARs. However, the existing ground methods are very difficult to balance accuracy and computational complexity. This paper proposes a fast point cloud approach based on coarse-to-fine Markov random field (MRF) method. The method uses coarse result of improved local feature extraction algorithm instead prior knowledge initialize MRF model. It provides initial value fine dramatically reduces graph...

LiDAR occupies a vital position in self-driving as the advanced detection technology enables autonomous vehicles (AVs) to obtain much environmental information. Ground segmentation for point cloud is crucial procedure ensure AVs’ driving safety. However, some current algorithms suffer from embarrassments such unavailability on complex terrains, excessive time and memory usage, additional pre-training requirements. The Jump-Convolution-Process (JCP) proposed solve these issues. JCP converts...

Autonomous vehicle is an efficient component in active system to reduce traffic accidents. The path planning of lane change for autonomous important the field. In order generate a passing front vehicle, new method that curvature-continuous and satisfies nonholonomic constraint introduced. Firstly, we calculate safe distance vehicle. Secondly, based on piecewise quadratic Bezier curve maximum curvature curves calculated verify whether can follow this path. Then, present indicator yaw-rate...

A dynamic motion planning approach for an autonomous vehicle navigated without GPS and unmanned driven in unknown environments is presented. The bring several technology challenges, including high-speed operation, complex interaction with environment, parking unstructured lots, passing obstacles. In this approach, we combine the global path local a hierarchical structure. exploration method to navigate described detail. An vehicle, Intelligent Pioneer, was developed verify approach. Pioneer...

Use of the object proposal method as a preprocessing step for detection vision sensors has improved computational efficiency in recent years. Good methods require high recall, low cost, good localization accuracy, and repeatability. However, existing cannot always achieve balance performance. To solve this problem, we propose fast high-performance algorithm. First, construction to enhance frequency features that are combined with linear classifier learn generate set boxes. Second, strategy...

Existing collision avoidance methods for autonomous vehicles, which ignore the driving intent of detected thus, cannot satisfy requirements in urban environments because their high false detection rates collisions with vehicles on winding roads and missed rate maneuvering vehicles. This study introduces an intent-estimation- motion-model-based (IEMMB) method to address these disadvantages. First, a state vector is constructed by combining road structure moving A Gaussian mixture model used...

This paper presents a learning-based model predictive trajectory planning controller for automated driving in unstructured, dynamic environments with obstacle avoidance. We first address the problem of lacking prior knowledge unstructured by introducing risk map that maps density and motion obstacles road to an occupancy risk. Model control is then used integrate tracking into one framework bridge gap between control. Meanwhile, we use Gaussian Process (GP) regression learn residual...

In this paper, we present an improved RRT-based motion planner for autonomous vehicles to effectively navigate in cluttered environments with narrow passages. The first presents X-test that can identify passable passages, and then perform efficient obstacles-based extension operation within order generate a smooth trajectory the vehicle execute, post-process algorithm optimization is proposed. For purpose of demonstrate benefits our method, proposed implemented tested on real scenarios...

This paper describes a real-time motion planner based on the drivers’ visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty in use guidance search behavior framework RRT planner. an incremental sampling-based method that widely used solve robotic planning problems. However, often unreliable number practical applications such as vehicles for because unnatural trajectory, useless sampling, and...

The present study evaluated the potential neuroprotective effect and underlying mechanism of total flavones extracted from Chrysanthemum morifolium (TFCM) against ischemia/reperfusion (I/R) injury. An animal model cerebral ischemia was established by occluding right middle artery for 90 minutes followed reperfusion 22 hours. neurobehavioral scores, infarct area, hemispheric edema were evaluated. superoxide dismutase (SOD) activity, malondialdehyde (MDA) content, reactive oxygen species (ROS)...

Simultaneous localization and mapping is a mobile robot positioning themselves creating the map of environment at same time, which core problem vehicle achieve authentic intelligent. EKF-SLAM widely used SLAM algorithm based on extended Kaiman Alter. The proposed in this paper differential model motion, consider trajectory as many small straight Une segments. effectively reduce error compared with dead reckoning has more simplified generic kinematics model. Meanwhile, it lower requirements...

In this paper, a maneuver decision making method for autonomous vehicle in complex urban environment is studied. We decompose the problem into three steps. The first step selecting logical maneuvers, second we remove maneuvers which break traffic rules. third step, Multiple Attribute Decision Making (MADM) methods such as Analytic Hierarchy Process (AHP) and Technique Order Preference by Similarity to Ideal Solution (TOPSIS) are used process of optimum driving scenario considering safety...

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control execution technology. Navigating in unstructured complex a huge challenge for vehicles, due to the irregular shape of road, requirement real-time nonholonomic constraints vehicle. This paper presents planning method, based on Radial Basis Function (RBF) neural network, guide environments. proposed algorithm extracts drivable region from perception...

An accurate prediction of future trajectories surrounding vehicles can ensure safe and reasonable interaction between intelligent other types vehicles. Vehicle are not only constrained by a priori knowledge about road structure, traffic signs, rules but also affected posterior different driving styles drivers. The existing models cannot fully combine the prior in scene perform well specific scenario. This paper presents long short-term memory (LSTM) neural network driven knowledge. First,...

In this paper a new lane marking detection algorithm in different road conditions for monocular vision was proposed. Traditional algorithms implement the same operation conditions. It is difficult to simultaneously satisfy requirements of timesaving and robustness Our divides into two classes. One class clean road, other one with disturbances such as shadows, non-lane markings vehicles. has its advantages while robust complex road. On remapping image obtained from inverse perspective...