arXiv subjects

Junyi Ji

Publications and source records attributed to Junyi Ji.

35 records · Page 2Linked to original sources

arXiv2024

On the Constrained CAV Platoon Control Problem

The main objective of the connected and automated vehicle (CAV) platoon control problem is to regulate CAVs' position while ensuring stability and accounting for vehicle dynamics. Although this problem has been studied in the literature, existing research has some limitations. This paper presents two new theoretical results that address these limitations: (i) the synthesis of unrealistic high-gain control parameters due to the lack of a systematic way to incorporate the lower and upper bounds on the control parameters, and (ii) the performance sensitivity to the communication delay due to inaccurate Taylor series approximation. To be more precise, taking advantage of the wellknown Pade approximation, this paper proposes a constrained CAV platoon controller synthesis that (i) systematically incorporates the lower and upper bounds on the control parameters, and (ii) significantly improves the performance sensitivity to the communication delay. The effectiveness of the presented results is verified through conducting extensive numerical simulations. The proposed controller effectively attenuates the stop-and-go disturbance -- a single cycle of deceleration followed by acceleration -- amplification throughout the mixed platoon (consisting of CAVs and human-driven vehicles). Modern transportation systems will benefit from the proposed CAV controls in terms of effective disturbance attenuation as it will potentially reduce collisions.

eess.SY↗

arXiv2024

A Middle Way to Traffic Enlightenment

This paper introduces a novel approach that seeks a middle ground for traffic control in multi-lane congestion, where prevailing traffic speeds are too fast, and speed recommendations designed to dampen traffic waves are too slow. Advanced controllers that modify the speed of an automated car for wave-dampening, eco-driving, or other goals, typically are designed with forward collision safety in mind. Our approach goes further, by considering how dangerous it can be for a controller to drive so slowly relative to prevailing traffic that it creates a significant issue for safety and comfort. This paper explores open-road scenarios where large gaps between prevailing speeds and desired speeds can exist, specifically when infrastructure-based variable speed limit systems are not strictly followed at all times by other drivers. Our designed, implemented, and deployed algorithm is able to follow variable speed limits when others also follow it, avoid collisions with vehicles ahead, and adapt to prevailing traffic when other motorists are traveling well above the posted speeds. The key is to reject unsafe speed recommendations from infrastructure-based traffic smoothing systems, based on real-time local traffic conditions observed by the vehicle under control. This solution is implemented and deployed on two control vehicles in heavy multi-lane highway congestion. The results include analysis from system design, and field tests that validate the system's performance using an existing Variable Speed Limit system as the external source for speed recommendations, and the on-board sensors of a stock Toyota Rav4 for inputs that estimate the prevailing speed of traffic around the vehicle under control.

cs.RO↗

arXiv2024

General time-reversal equivariant neural network potential for magnetic materials

This study introduces time-reversal E(3)-equivariant neural network and SpinGNN++ framework for constructing a comprehensive interatomic potential for magnetic systems, encompassing spin-orbit coupling and noncollinear magnetic moments. SpinGNN++ integrates multitask spin equivariant neural network with explicit spin-lattice terms, including Heisenberg, Dzyaloshinskii-Moriya, Kitaev, single-ion anisotropy, and biquadratic interactions, and employs time-reversal equivariant neural network to learn high-order spin-lattice interactions using time-reversal E(3)-equivariant convolutions. To validate SpinGNN++, a complex magnetic model dataset is introduced as a benchmark and employed to demonstrate its capabilities. SpinGNN++ provides accurate descriptions of the complex spin-lattice coupling in monolayer CrI$_3$ and CrTe$_2$, achieving sub-meV errors. Importantly, it facilitates large-scale parallel spin-lattice dynamics, thereby enabling the exploration of associated properties, including the magnetic ground state and phase transition. Remarkably, SpinGNN++ identifies a new ferrimagnetic state as the ground magnetic state for monolayer CrTe2, thereby enriching its phase diagram and providing deeper insights into the distinct magnetic signals observed in various experiments.

cond-mat.mtrl-sci↗

arXiv2023

Triple-Well Charge Density Wave Transition Driven by Cooperation between Peierls-like Effect and Antiferromagnetic Order in FeGe

Kagome materials provide a promising platform to explore intriguing correlated phenomena including magnetism, charge density wave (CDW), and nontrivial band topology. Recently, a CDW order was observed in antiferromagnetic kagome metal FeGe, sparking enormous research interests in intertwining physics of CDW and magnetism. Two of the core questions are (i) what are the driving forces of the CDW transition in FeGe and (ii) whether magnetism play a critical role in the transition. Such questions are critical as conventional mechanisms of van Hove singularities and Fermi surface nesting fail to explain the stable pristine phase, as well as the role of magnetism. Here, supported by density functional theory and tight-binding models, we unravel the triple-well CDW energy landscape of FeGe, indicating that both the pristine and CDW phases are locally stable. We point out that an entire downward shift of Ge band, instead of the previously proposed Fe bands, competes with the lattice distortion energy, driving the triple-well CDW transition. It is indeed a cooperation between the Peierls-like effect and the Fermi energy pinning phenomenon, which is distinct from the conventional Peierls effect that drives a double-well transition. Moreover, we demonstrate that the antiferromagnetic order also plays a critical role in driving the CDW transition, through weakening the Fe-Ge hybridization by exchange splitting and lowering the position of Ge-bands with respect to the Fermi energy. Our work thus not only deepens the understanding of the CDW mechanism in FeGe, but also indicates an intertwined connection between the emergent magnetism and CDW in kagome materials.

cond-mat.mtrl-sci↗

arXiv2023

Virtual trajectories for I-24 MOTION: data and tools

This article introduces a new virtual trajectory dataset derived from the I-24 MOTION INCEPTION v1.0.0 dataset to address challenges in analyzing large but noisy trajectory datasets. Building on the concept of virtual trajectories, we provide a Python implementation to generate virtual trajectories from large raw datasets that are typically challenging to process due to their size. We demonstrate the practical utility of these trajectories in assessing speed variability and travel times across different lanes within the INCEPTION dataset. The virtual trajectory dataset opens future research on traffic waves and their impact on energy.

eess.IV↗

arXiv2023

Online Min Cost Circulation for Multi-Object Tracking on Fragments

Multi-object tracking (MOT) or global data association problem is commonly approached as a minimum-cost-flow or minimum-cost-circulation problem on a graph. While there have been numerous studies aimed at enhancing algorithm efficiency, most of them focus on the batch problem, where all the data must be available simultaneously to construct a static graph. However, with the growing number of applications that generate streaming data, an efficient online algorithm is required to handle the streaming nature of the input. In this paper, we present an online extension of the well-known negative cycle canceling algorithm for solving the multi-object tracking problem with streaming fragmented data. We provide a proof of correctness for the proposed algorithm and demonstrate its efficiency through numerical experiments.

cs.DS↗

arXiv2023

Automatic vehicle trajectory data reconstruction at scale

In this paper we propose an automatic trajectory data reconciliation to correct common errors in vision-based vehicle trajectory data. Given "raw" vehicle detection and tracking information from automatic video processing algorithms, we propose a pipeline including (a) an online data association algorithm to match fragments that describe the same object (vehicle), which is formulated as a min-cost network circulation problem of a graph, and (b) a one-step trajectory rectification procedure formulated as a quadratic program to enhance raw detection data. The pipeline leverages vehicle dynamics and physical constraints to associate tracked objects when they become fragmented, remove measurement noises and outliers and impute missing data due to fragmentations. We assess the capability of the proposed two-step pipeline to reconstruct three benchmarking datasets: (1) a microsimulation dataset that is artificially downgraded to replicate upstream errors, (2) a 15-min NGSIM data that is manually perturbed, and (3) tracking data consists of 3 scenes from collections of video data recorded from 16-17 cameras on a section of the I-24 MOTION system, and compare with the corresponding manually-labeled ground truth vehicle bounding boxes. All of the experiments show that the reconciled trajectories improve the accuracy on all the tested input data for a wide range of measures. Lastly, we show the design of a software architecture that is currently deployed on the full-scale I-24 MOTION system consisting of 276 cameras that covers 4.2 miles of I-24. We demonstrate the scalability of the proposed reconciliation pipeline to process high-volume data on a daily basis.

cs.DS↗

arXiv2023

So you think you can track?

This work introduces a multi-camera tracking dataset consisting of 234 hours of video data recorded concurrently from 234 overlapping HD cameras covering a 4.2 mile stretch of 8-10 lane interstate highway near Nashville, TN. The video is recorded during a period of high traffic density with 500+ objects typically visible within the scene and typical object longevities of 3-15 minutes. GPS trajectories from 270 vehicle passes through the scene are manually corrected in the video data to provide a set of ground-truth trajectories for recall-oriented tracking metrics, and object detections are provided for each camera in the scene (159 million total before cross-camera fusion). Initial benchmarking of tracking-by-detection algorithms is performed against the GPS trajectories, and a best HOTA of only 9.5% is obtained (best recall 75.9% at IOU 0.1, 47.9 average IDs per ground truth object), indicating the benchmarked trackers do not perform sufficiently well at the long temporal and spatial durations required for traffic scene understanding.

cs.CV↗

arXiv2023

CAV Traffic Control to Mitigate the Impact of Congestion from Bottlenecks: A Linear Quadratic Regulator Approach and Microsimulation Study

This work investigates traffic control via controlled connected and automated vehicles (CAVs) using novel controllers derived from the linear-quadratic regulator (LQR) theory. CAV-platoons are modeled as moving bottlenecks impacting the surrounding traffic with their speeds as control inputs. An iterative controller algorithm based on the LQR theory is proposed along with a variant that allows for penalizing abrupt changes in platoons speeds. The controllers use the Lighthill-Whitham-Richards (LWR) model implemented using an extended cell transmission model (CTM) which considers the capacity drop phenomenon for a realistic representation of traffic in congestion. The impact of various parameters of the proposed controller on the control performance is analyzed. The effectiveness of the proposed traffic control algorithms is tested using a traffic control example and compared with existing proportional-integral (PI)- and model predictive control (MPC)- based controllers from the literature. A case study using the TransModeler traffic microsimulation software is conducted to test the usability of the proposed controller as well as existing controllers in a realistic setting and derive qualitative insights. It is observed that the proposed controller works well in both settings to mitigate the impact of the jam caused by a fixed bottleneck. The computation time required by the controller is also small making it suitable for real-time control.

eess.SY↗

arXiv2023

Unconventional Ferroelectricity in Violation with Neumann's Principle

The physical properties of crystals are governed by their symmetry according to Neumann's principle. However, we present a case that contradicts this principle wherein the polarization is not invariant under its symmetry. We term this phenomenon as unconventional ferroelectricity in violation of Neumann's principle (UFVNP). Our group theory analysis reveals that 33 symmorphic space groups have the potential for UFVNP, with 26 of these symmorphic space groups belonging to non-polar groups. Notably, the polarization component in UFVNP materials is quantized. Our theory can explain the experimentally proven in-plane polarization of the monolayer α-In2Se3, which has C3v symmetry. Additionally, we employ first-principles calculations to demonstrate the existence of UFVNP in Td phase AgBr, which was not initially anticipated to exhibit polarization. Thus, UFVNP plays an integral role in characterizing and exploring the possible applications of ferroelectrics, significantly expanding the range of available materials for study.

cond-mat.mtrl-sci↗

arXiv2023

Bilayer Stacking Ferrovalley without Breaking Time-Reversal Symmetry

Non-volatile manipulation of valley polarization in solids has long been desired for valleytronics applications but remains challenging. Here, we propose a novel strategy for non-volatile manipulating valleys through bilayer stacking, which enables spontaneous valley polarization without breaking time-reversal symmetry. We call this noval physics as bilayer stacking ferrovalley (BSFV). The group theory analysis reveals that the two-dimensional (2D) valley materials with hexagonal and square lattices can host BSFV. By searching the 2D material database, we discovered 14 monolayer 2D materials with direct gaps that are candidates for realizing BSFV. Further first-principles calculations demonstrate that BSFV exists in RhCl3 and InI bilayers. The bilayer stacking breaks their three- and four-fold rotation symmetry, resulting in 39 and 326 meV valley polarization, respectively. More interestingly, the valley polarization in our systems can be switched by interlayer sliding. Our study opens up a new direction for designing ferrovalley materials and thus greatly enriches the platform for the research of valleytronics.

cond-mat.mtrl-sci↗

arXiv2023

I-24 MOTION: An instrument for freeway traffic science

The Interstate-24 MObility Technology Interstate Observation Network (I-24 MOTION) is a new instrument for traffic science located near Nashville, Tennessee. I-24 MOTION consists of 276 pole-mounted high-resolution traffic cameras that provide seamless coverage of approximately 4.2 miles I-24, a 4-5 lane (each direction) freeway with frequently observed congestion. The cameras are connected via fiber optic network to a compute facility where vehicle trajectories are extracted from the video imagery using computer vision techniques. Approximately 230 million vehicle miles of travel occur within I-24 MOTION annually. The main output of the instrument are vehicle trajectory datasets that contain the position of each vehicle on the freeway, as well as other supplementary information vehicle dimensions and class. This article describes the design and creation of the instrument, and provides the first publicly available datasets generated from the instrument. The datasets published with this article contains at least 4 hours of vehicle trajectory data for each of 10 days. As the system continues to mature, all trajectory data will be made publicly available at i24motion.org/data.

eess.IV↗

arXiv2022

General Theory for Bilayer Stacking Ferroelectricity

Two-dimensional (2D) ferroelectrics, which is rare in nature, enable high-density non-volatile memory with low energy consumption. Here, we propose a theory of bilayer stacking ferroelectricity (BSF), in which, two stacked layers of the same 2D material, with different rotation and translation, exhibits ferroelectricity. By performing systematic group theory analysis, we find out all the possible BSF in all the 80 layer groups (LGs) and discover the rules about the creation and annihilation of symmetries in the bilayer. Our general theory can not only explain all the previous findings (including sliding ferroelectricity), but also provide new perspective. Interestingly, the direction of the electric polarization of the bilayer could be totally different from that of the single layer. In particular, the bilayer could become ferroelectric after properly stacking two centrosymmetric non-polar monolayers. By means of first-principles simulations, we demonstrate that the ferroelectricity and thus multiferroicity can be introduced to the prototypical 2D ferromagnetic centrosymmetric material CrI3 by stacking. Furthermore, we find that the out-of-plane electric polarization in bilayer CrI3 is interlocked with the in-plane electric polarization, suggesting that the out-of-plane polarization can be manipulated in a deterministic way through the application of an in-plane electric field. The present BSF theory lays a solid foundation for designing a large number of bilayer ferroelectrics and thus colorful platforms for fundamental studies and applications.

cond-mat.mtrl-sci↗

arXiv2022

Two-Dimensional Organic-Inorganic Room-Temperature Multiferroic

Organic-inorganic multiferroics are promising for the next generation of electronic devices. To date, dozens of organic-inorganic multiferroics have been reported; however, most of them show magnetic Curie temperature much lower than room temperature, which drastically hampers their application. Here, by performing first-principle calculations and building effective model Hamiltonians, we reveal a molecular orbital-mediated magnetic coupling mechanism in two-dimensional Cr(pyz)2 (pyz=pyrazine), and the role that the valence state of the molecule plays in determining the magnetic coupling type between metal ions. Based on these, we demonstrate that a two-dimensional organic-inorganic room-temperature multiferroic, Cr(h-fpyz)2 (h-fpyz= half-fluoropyrazine), can be rationally designed by introducing ferroelectricity in Cr(pyz)2 while keeping the valence state of the molecule unchanged. Our work not only reveals the origin of magnetic coupling in 2D organic-inorganic systems, but also provides a way to design room temperature multiferroic materials rationally.

cond-mat.mtrl-sci↗

arXiv2020

Tunable spin textures in polar antiferromagnetic hybrid organic inorganic perovskites by electric and magnetic fields

The hybrid organic inorganic perovskites (HOIPs) have attracted much attention for their potential applications as novel optoelectronic devices. Remarkably, the Rashba band splitting, together with specific spin orientations in k space (i.e., spin texture), has been found to be relevant for the optoelectronic performances. In this work, by using first principles calculations and symmetry analyses, we study the electric polarization, magnetism, and spin texture properties of the antiferromagnetic (AFM) HOIP ferroelectric TMCM_MnCl3 (TMCM = (CH3)3NCH2Cl, trimethylchloromethyl ammonium). This recently synthesized compound is a prototype of order disorder and displacement-type ferroelectric with a large piezoelectric response, high ferroelectric transition temperature, and excellent photoluminescence properties [You et al., Science 357, 306 (2017)]. The most interesting result is that the inversion symmetry breaking coupled to the spin orbit coupling gives rise to a Rashba-like band splitting and a related robust persistent spin texture (PST) and/or typical spiral spin texture, which can be manipulated by tuning the ferroelectric or, surprisingly, also by the AFM magnetic order parameter. The tunability of spin texture upon switching of AFM order parameter is largely unexplored and our findings not only provide a platform to understand the physics of AFM spin texture but also support the AFM HOIP ferroelectrics as a promising class of optoelectronic materials.

cond-mat.mtrl-sci↗

arXiv2020

Two-dimensional Topological Semimetals Protected by Symmorphic Symmetries

Two-dimensional (2D) band crossing semimetals (BCSMs) could be used to build a range of novel nanoscale devices such as superlenses and transistors. We find that symmorphic symmetry can protect a new type of robust 2D BCSMs, unlike the previously proposed 2D essential BCSMs protected by non-symmorphic symmetry [Young et al., Phys. Rev. Lett. 115, 126803 (2015)]. This type of symmorphic symmetry protected (SSP) 2D essential BCSMs cannot be pair annihilated without destroying the crystalline symmetries, as opposed to the 2D BCSMs caused by the accidental band crossing. Through group theory analysis, we find that 2D SSP BCSMs can only exist at the K (K') point of Brillouin zone (BZ) of four layer groups and identify nonmagnetic 2D FeB2 as a candidate. Interestingly, nonmagnetic 2D SSP BCSMs can host a single pair of band crossing points (BCPs), whereas nonmagnetic three-dimensional (3D) Weyl semimetals (WSMs) have at least two pairs of band crossing Weyl points. It is found that the single pair of BCPs are robust against any kinds of strain. Furthermore, our calculation suggests that essential 2D SSP BCSMs can be used to realize electric field control of spin-texture, thus are promising candidates for spintronic devices.

cond-mat.mes-hall↗

arXiv2019

Band splitting with vanishing spin polarizations in noncentrosymmetric crystals

The Dresselhaus and Rashba effects are well-known phenomena in solid-state physics, in which spin-orbit coupling (SOC) splits spin-up and spin-down energy bands of nonmagnetic non-centrosymmetric crystals. Here, we discover a new phenomenon, dubbed as band splitting with vanishing spin polarizations (BSVSP), in which, as usual, SOC splits the energy bands in nonmagnetic non-centrosymmetric systems; surprisingly, however, both split bands show no net spin polarization along certain high-symmetry lines in the Brillouin zone. In order to rationalize this phenomenon, we propose a new classification of point groups into pseudo-polar and non-pseudo-polar groups. By means of first-principles simulations, we demonstrate that BSVSP can take place in both symmorphic (e.g., bulk GaAs) and non-symmorphic systems (e.g., two dimensional ferroelectric SnTe). Furthermore, we propose a novel linear magnetoelectric coupling in reciprocal space, which could be employed to tune the spin polarization with an external electric field. The BSVSP effect and its manipulation could therefore pave a new way to novel spintronic devices.

cond-mat.mtrl-sci↗