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 (^5MedC) in DNA fragments that contain multiple ^5MedC residues, we designed and synthesized two <i>N</i>-halogeno-<i>N</i>-sodiobenzenesulfonamide reagents that provide a new chemical method for probing ^5MedC in DNA sequences. When the strategy we provided was combined with β-glucosyltransferase, ^5MedC could be distinguished from 5-hydroxymethyl-2′-deoxycytidine (^5hmdC) and deoxycytidine (dC) through the introduction of a glucose moiety to the hydroxyl group of ^5hmdC