20 research outputs found
XVTP3D: Cross-view Trajectory Prediction Using Shared 3D Queries for Autonomous Driving
Trajectory prediction with uncertainty is a critical and challenging task for
autonomous driving. Nowadays, we can easily access sensor data represented in
multiple views. However, cross-view consistency has not been evaluated by the
existing models, which might lead to divergences between the multimodal
predictions from different views. It is not practical and effective when the
network does not comprehend the 3D scene, which could cause the downstream
module in a dilemma. Instead, we predicts multimodal trajectories while
maintaining cross-view consistency. We presented a cross-view trajectory
prediction method using shared 3D Queries (XVTP3D). We employ a set of 3D
queries shared across views to generate multi-goals that are cross-view
consistent. We also proposed a random mask method and coarse-to-fine
cross-attention to capture robust cross-view features. As far as we know, this
is the first work that introduces the outstanding top-down paradigm in BEV
detection field to a trajectory prediction problem. The results of experiments
on two publicly available datasets show that XVTP3D achieved state-of-the-art
performance with consistent cross-view predictions.Comment: 11 pages, 6 figures, accepted by IJCAI 2
Recent Advances on Human Crowd Simulation
International audienceHuman crowd simulation is a new technology in the virtual reality field. Since it could simulate evacuation, it has strong demands in risk assessment for public buildings. In this paper we discuss the development of the main related research topics, including semantic description for virtual environments and crowd models which generate continuum human flow. Additionally, we introduce a system named Guarder that is designed for human crowd simulation and is suit for simulating evacuation in public buildings. We also demonstrate some simulation results of Guarder to show that it could efficiently simulate evacuation in a large-scale and complex environment
Coupling Analysis on the Thermophysical Parameters and the Performance of Liquid Cooling-Based Thermal Management System for Lithium-Ion Batteries
In order to ensure the safety and extend the lifecycle of lithium-ion power batteries in electric vehicles, a battery thermal management system based on minichannel liquid cooling is proposed to cool rectangular lithium-ion batteries, and a three-dimensional cooling system model is established. The effects of the number of channels, the thickness of heat conducting silicone grease and the thermal conductivity of the battery itself on the temperature rise and voltage drop changes during the discharge process of the battery are studied. The results show that the maximum temperature of the battery decreases with the increase of the number of channels, and the voltage drop inside the channel increases with the increase of the number of channels. The maximum temperature of the battery increases with the increase of the thickness of the thermal grease, but the increase is only 1.26 K. The maximum temperature and local temperature difference of the battery change significantly with the change of the thickness of the battery and its own thermal conductivity. The simulation results will be beneficial to the design of a battery thermal management system based on minichannel liquid cooling
Coupling Analysis on the Thermophysical Parameters and the Performance of Liquid Cooling-Based Thermal Management System for Lithium-Ion Batteries
In order to ensure the safety and extend the lifecycle of lithium-ion power batteries in electric vehicles, a battery thermal management system based on minichannel liquid cooling is proposed to cool rectangular lithium-ion batteries, and a three-dimensional cooling system model is established. The effects of the number of channels, the thickness of heat conducting silicone grease and the thermal conductivity of the battery itself on the temperature rise and voltage drop changes during the discharge process of the battery are studied. The results show that the maximum temperature of the battery decreases with the increase of the number of channels, and the voltage drop inside the channel increases with the increase of the number of channels. The maximum temperature of the battery increases with the increase of the thickness of the thermal grease, but the increase is only 1.26 K. The maximum temperature and local temperature difference of the battery change significantly with the change of the thickness of the battery and its own thermal conductivity. The simulation results will be beneficial to the design of a battery thermal management system based on minichannel liquid cooling
A Survey on Visual Traffic Simulation: Models, Evaluations, and Applications in Autonomous Driving
Virtualized traffic via various simulation models and real-world traffic data are promising approaches to reconstruct detailed traffic flows. A variety of applications can benefit from the virtual traffic, including, but not limited to, video games, virtual reality, traffic engineering and autonomous driving. In this survey, we provide a comprehensive review on the state-of-the-art techniques for traffic simulation and animation. We start with a discussion on three classes of traffic simulation models applied at different levels of detail. Then, we introduce various data-driven animation techniques, including existing data collection methods, and the validation and evaluation of simulated traffic flows. Next, we discuss how traffic simulations can benefit the training and testing of autonomous vehicles. Finally, we discuss the current states of traffic simulation and animation and suggest future research directions
Highly Selective Detection of 5‑Methylcytosine in Genomic DNA Based on Asymmetric PCR and Specific DNA Damaging Reagents
DNA methylation is
a significant epigenetic modification of the
genome that is involved in regulating many cellular processes. An
increasing number of human diseases have been discovered to be associated
with aberrant DNA methylation, and aberrant DNA methylation has been
deemed to be a potential biomarker for diseases such as cancers. A
safe, nontoxic, and sensitive method for accurate detection of 5-methylcytosine
in genomic DNA is extremely useful for early diagnosis and therapy
of cancers. In this paper, we established a novel system to detect
5-methylcytosine, which is based on bisulfite treatment, asymmetric
PCR, and specific DNA damaging reagents. Our method could be used
for identifying the loci of 5mC in genomic DNA and detecting the DNA
methylation levels in tissues as well
Application of <i>N</i>‑Halogeno‑<i>N</i>‑sodiobenzenesulfonamide Reagents to the Selective Detection of 5‑Methylcytosine in DNA Sequences
To surmount the challenges of the locus determination
and accurate
quantification of 5-methyl-2′-deoxycytidine (<sup>5Me</sup>dC) in DNA fragments that contain multiple <sup>5Me</sup>dC residues,
we designed and synthesized two <i>N</i>-halogeno-<i>N</i>-sodiobenzenesulfonamide reagents that provide a new chemical
method for probing <sup>5Me</sup>dC in DNA sequences. When the strategy
we provided was combined with β-glucosyltransferase, <sup>5Me</sup>dC could be distinguished from 5-hydroxymethyl-2′-deoxycytidine
(<sup>5hm</sup>dC) and deoxycytidine (dC) through the introduction
of a glucose moiety to the hydroxyl group of <sup>5hm</sup>dC