A Survey on Datasets for Decision-making of Autonomous Vehicle

Autonomous vehicles (AV) are expected to reshape future transportation systems, and decision-making is one of the critical modules toward high-level automated driving. To overcome those complicated scenarios that rule-based methods could not cope with well, data-driven decision-making approaches have aroused more and more focus. The datasets to be used in developing data-driven methods dramatically influences the performance of decision-making, hence it is necessary to have a comprehensive insight into the existing datasets. From the aspects of collection sources, driving data can be divided into vehicle, environment, and driver related data. This study compares the state-of-the-art datasets of these three categories and summarizes their features including sensors used, annotation, and driving scenarios. Based on the characteristics of the datasets, this survey also concludes the potential applications of datasets on various aspects of AV decision-making, assisting researchers to find appropriate ones to support their own research. The future trends of AV dataset development are summarized

CRL4 antagonizes SCFFbxo7-mediated turnover of cereblon and BK channel to regulate learning and memory

Intellectual disability (ID), one of the most common human developmental disorders, can be caused by genetic mutations in Cullin 4B (Cul4B) and cereblon (CRBN). CRBN is a substrate receptor for the Cul4A/B-DDB1 ubiquitin ligase (CRL4) and can target voltage- and calcium-activated BK channel for ER retention. Here we report that ID-associated CRL4CRBNmutations abolish the interaction of the BK channel with CRL4, and redirect the BK channel to the SCFFbxo7ubiquitin ligase for proteasomal degradation. Glioma cell lines harbouring CRBN mutations record density-dependent decrease of BK currents, which can be restored by blocking Cullin ubiquitin ligase activity. Importantly, mice with neuron-specific deletion of DDB1 or CRBN express reduced BK protein levels in the brain, and exhibit similar impairment in learning and memory, a deficit that can be partially rescued by activating the BK channel. Our results reveal a competitive targeting of the BK channel by two ubiquitin ligases to achieve exquisite control of its stability, and support changes in neuronal excitability as a common pathogenic mechanism underlying CRL4CRBN–associated ID

An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field

Driver disability has become an increasing factor leading to traffic accidents, especially for commercial vehicle drivers who endure high mental and physical pressure because of long periods of work. Once driver disability occurs, e.g., heart disease or heat stroke, the loss of driving control may lead to serious traffic incidents and public damage. This paper proposes a novel driving intervention system for autonomous danger avoidance under driver disability conditions, including a quantitative risk assessment module named the Emergency Safety Field (ESF) and a motion-planning module. The ESF considers three factors affecting hedging behavior: road boundaries, obstacles, and target position. In the field-based framework, each factor is modeled as an individual risk source generating repulsive or attractive force fields. Individual risk distributions are regionally weighted and merged into one unified emergency safety field denoting the level of danger to the ego vehicle. With risk evaluation, a path–velocity-coupled motion planning module was designed to generate a safe and smooth trajectory to pull the vehicle over. The results of our experiments show that the proposed algorithms have obvious advantages in success rate, efficiency, stability, and safety compared with the traditional method. Validation on multiple simulation and real-world platforms proves the feasibility and adaptivity of the module in traffic scenarios

Molecular Dissection of the Relationships among Tiller Number, Plant Height and Heading Date in Rice

Appropriate plant height, tiller number and heading date are important traits for maximizing rice production. In order to understand the genetic basis of the relationships among these three plant traits, we mapped quantitative trait loci (QTLs) using a recombinant inbred population and detected two-locus interactions for plant height and tiller number at two growth stages and for heading date in two years. There were significant negative correlations between tiller number and plant height, and between tiller number at maturity and heading date. A significant positive correlation was observed between heading date and plant height at maturity. A total of 29 QTLs for the three traits were identified over the two years. Results show that QTLs and majority of two-locus interactions for plant height and tiller numbers at 35 days after transplanting were different from those at maturity, indicating that different genes and interactions control the traits at different developmental stages. A large proportion of QTLs and interactions could only be detected in one year, suggesting that QTLs and two-locus interactions for the traits were dependent on the environment. Results suggest that pleiotropy and/or close linkage of genomic regions and pleiotropy of common two-locus combinations may be the genetic basis for the close correlations among the three traits. A QTL with a large effect for heading date, which was located in RG424-RZ667 on chromosome 6, also showed large effects on tiller number and plant height at maturity

Displacement Characteristics of an Urban Tunnel in Silty Soil by the Shallow Tunnelling Method

The urban shallow tunnelling process in silty soil is easy to cause large displacement of surface and tunnel. Obviously, if the strata and the tunnel face are not treated by reasonable reinforcement method, instability and collapse phenomenon will be encountered during the tunnel excavation. There are a series of studies on construction methods of shallow tunnels, but these methods have limitations in silty soil. In this study, a comprehensive construction plan of the urban shallow tunnel in silty soil was proposed and applied to a case study in Fuzhou, Fujian Province in South China. The in situ monitoring tests and numerical simulation were employed to address displacement characteristics of surface and tunnel. Results indicated that the urban shallow tunnelling process could achieve good effect by dewatering of silty soil, reinforcing surface by vertical jet grouting piles, and advanced small pipes and circumferential grouting in the tunnel face; surface settlement during dewatering process accounted for about 30% of total surface settlement in silty soil; the excavation of the top heading, the middle, and lower benches had great effect on displacement of surface and tunnel for three-bench seven-step excavation method in silty soil; surface settlement troughs in silty soil were deeper and wider; lock-feet bolts had good effect on restricting horizontal convergence; and ratio of total crown settlement and total horizontal convergence was in range of 1.43∼1.59 when b/h was 0.88 in silty soil. The construction plan proposed in this paper is helpful for further study of shallow tunnel tunnelling process in silty soil

Improved Yield Prediction of Ratoon Rice Using Unmanned Aerial Vehicle-Based Multi-Temporal Feature Method

Pre-harvest yield prediction of ratoon rice is critical for guiding crop interventions in precision agriculture. However, the unique agronomic practice (i.e., varied stubble height treatment) in rice ratooning could lead to inconsistent rice phenology, which had a significant impact on yield prediction of ratoon rice. Multi-temporal unmanned aerial vehicle (UAV)-based remote sensing can likely monitor ratoon rice productivity and reflect maximum yield potential across growing seasons for improving the yield prediction compared with previous methods. Thus, in this study, we explored the performance of combination of agronomic practice information (API) and single-phase, multi-spectral features [vegetation indices (VIs) and texture (Tex) features] in predicting ratoon rice yield, and developed a new UAV-based method to retrieve yield formation process by using multi-temporal features which were effective in improving yield forecasting accuracy of ratoon rice. The results showed that the integrated use of VIs, Tex and API (VIs & Tex + API) improved the accuracy of yield prediction than single-phase UAV imagery-based feature, with the panicle initiation stage being the best period for yield prediction (R2 as 0.732, RMSE as 0.406, RRMSE as 0.101). More importantly, compared with previous multi-temporal UAV-based methods, our proposed multi- temporal method (multi-temporal model VIs & Tex: R2 as 0.795, RMSE as 0.298, RRMSE as 0.072) can increase R2 by 0.020–0.111 and decrease RMSE by 0.020–0.080 in crop yield forecasting. This study provides an effective method for accurate pre-harvest yield prediction of ratoon rice in precision agriculture, which is of great significance to take timely means for ensuring ratoon rice production and food security