Article
Engineering, Electrical & Electronic
Omkar Pradhan, Lawrence J. Scally, Albin J. Gasiewski, Ali Gorashi, Dean Pizio, David Kraft
Summary: This article presents the design and attenuation measurements of an open-path terahertz transmissometer system operating near the 325-GHz water vapor absorption line. The system aims to validate and improve existing propagation models for THz remote sensing, radiolocation, communications, and related applications. The system is capable of measuring attenuation, phase, and amplitude statistics in diverse atmospheric conditions during continuous long-duration operations.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2023)
Article
Telecommunications
Ala Alobeidyeen, Hanyi Yang, Lili Du
Summary: This research develops a discrete mathematical simulation framework to track information dissemination dynamics via Vehicle-to-Vehicle (V2V) communication in a road traffic network. It establishes information network flow models (INFMs) to track information wavefront spreading dynamics at intersections and on road segments. The experiments show that the framework accurately tracks the information front spreading and reveals a correlation between information spreading dynamics and traffic congestion evolution.
VEHICULAR COMMUNICATIONS
(2023)
Article
Engineering, Mechanical
Bing Wang, Min Gou, Yuexing Han
Summary: The study examines the interaction between epidemic and information transmission over separate migration routes. Information transmission has a limited impact on suppressing the epidemic, and further increase in transmission rate beyond a critical value does not affect the epidemic. Individual migration routes and frequencies play a crucial role in information transmission and epidemic spread, while the initial population distribution is also a fundamental factor influencing epidemic dynamics.
NONLINEAR DYNAMICS
(2021)
Article
Engineering, Electrical & Electronic
Sajjad Hussain
Summary: This paper investigates diffraction around building corners in a non line-of-sight vehicle-to-vehicle scenario at a typical urban street intersection. It is found that mobile vehicles moving towards a street intersection cause rapid changes in geometrical parameters, leading to different diffraction coefficients for different building materials. The results suggest that the total diffracted power from materials with rough surfaces may become comparable to power from a perfect electrical conductor near the street intersection.
PHYSICAL COMMUNICATION
(2021)
Article
Physics, Multidisciplinary
Jiang Wu, Renxian Zuo, Chaocheng He, Hang Xiong, Kang Zhao, Zhongyi Hu
Summary: This study proposes an aware-susceptible-infected model (ASI) to examine the impact of information literacy on the spreading process in multiplex networks using the microscopic Markov chain method. The results show that individuals with high information literacy are more responsive to information adoption. Additionally, the effectiveness of epidemic information in suppressing transmission depends on individuals' abilities to translate awareness into protective behaviors and varies according to community characteristics. This study highlights the importance of individual heterogeneity in information literacy in epidemic spreading within different communities.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Transportation Science & Technology
Brendan T. Gould, Philip N. Brown
Summary: The emerging technology of Vehicle-to-Vehicle (V2V) communication promises to improve road safety by allowing vehicles to warn each other of road hazards. However, research suggests that informing only some drivers of road conditions may increase congestion. Our model shows that V2V information sharing can increase the frequency of accidents and social costs.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Chemistry, Analytical
Gabriella Tognola, Martina Benini, Marta Bonato, Silvia Gallucci, Marta Parazzini
Summary: This study assessed the variability of radiofrequency exposure among road users in urban settings due to vehicle-to-vehicle communication operating at 5.9 GHz. A novel hybrid procedure that combines deterministic and stochastic approaches was developed to overcome limitations of previous studies. The study found that the absorbed dose of radiofrequencies remained below the regulatory limit for whole-body exposure, even with multiple transmitting cars and antennas.
Article
Physics, Multidisciplinary
J. S. Njem Njem, C. N. Takembo, Z. T. Njitacke, S. I. Fewo, T. C. Kofane
Summary: In this paper, the emergence and propagation of traveling modulated nerve impulse signal in a network of meristive photosensitive neural networks was studied. By analyzing the model equation and transforming it into a wave equation, the conditions for explicitly describing the nature of the nerve impulse propagating in the network were deduced. The study found that the dynamics of the information signal can be modeled by the coupled complex Ginzburg-Landau equation with breathing solitonic solutions, and breathing solitonic nerve impulse is confirmed as one of the precursors of information transport mode in neural networks.
EUROPEAN PHYSICAL JOURNAL PLUS
(2023)
Letter
Optics
Yasaman Ghasempour, Yasith Amarasinghe, Chia-Yi Yeh, Edward Knightly, Daniel M. Mittleman
Summary: This paper investigates the usage of reflected non-line-of-sight (NLOS) paths for communication in directional networks at frequencies above 100 GHz. The study explores how high-gain directional antennas bring new challenges and opportunities for exploiting NLOS paths, demonstrating that NLOS paths can offer higher data rates under certain circumstances, distinguishing THz wireless systems from those operating at lower frequencies.
Article
Optics
Wenhua He, Saikat Guha, Jeffrey H. Shapiro, Boulat A. Bash
Summary: This paper theoretically analyzes spatial-mode-multiplexed, decoy-state BB84 quantum key distribution systems with transmitter modes being either a collection of phase-tilted, flat-top focused beams (FBs) or Laguerre-Gaussian (LG) modes. Despite the QKD rate penalty suffered by FBs relative to LG modes in vacuum propagation, their potential ease of implementation makes them an attractive alternative. Furthermore, in the presence of turbulence, FB modes may outperform LG modes.
Article
Optics
Yahya Baykal, Hamza Gercekcioglu
Summary: Field correlations of partially coherent optical beams in underwater turbulence are studied in this paper. The variations of field correlations with changes in the degree of source coherence, receiver point position, propagation distance, and other factors are examined, and it is found that reducing the source coherence leads to a decrease in the field correlations at the receiver plane.
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION
(2022)
Article
Engineering, Electrical & Electronic
Ke Guan, Juan Moreno, Bo Ai, Cesar Briso-Rodriguez, Bile Peng, Danping He, Andrej Hrovat, Zhangdui Zhong, Thomas Kuerner
Summary: This article focuses on developing realistic 5G mmWave channel models for high-speed trains, addressing the need for high-speed wireless connectivity with multiple GHz bandwidths. By defining reference scenarios to parameterize channel models for railway use at mmWave band, the accuracy of simulations reflecting the detailed influence of railway objects is validated. The future direction points towards terahertz (THz) communications powering the full version of smart rail mobility.
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE
(2021)
Article
Engineering, Civil
V Zago, L. J. Schulze, G. Bilotta, N. Almashan, R. A. Dalrymple
Summary: The proposed method based on kernel gradient correction effectively addresses the issue of excessive nonphysical energy dissipation in Smoothed Particle Hydrodynamics (SPH) when modeling free surface waves. By ensuring momentum conservation through the use of an averaged correction matrix, the drawbacks of kernel gradient corrections, such as instabilities, are overcome. Experimental results demonstrate advantages in both result quality and simulation time compared to approaches based on large smoothing factors.
COASTAL ENGINEERING
(2021)
Article
Computer Science, Hardware & Architecture
Chenquan Gan, Anqi Liu, Qingyi Zhu, Ye Zhu, Yong Xiang, Jun Liu
Summary: This paper proposes an information dissemination model that takes into account the social ties between users. Through experiments, it is shown that this model has a faster propagation speed and a larger propagation range. It is also found that strong social ties can promote the transmission of device information and user awareness.
Article
Chemistry, Analytical
Catalin Beguni, Alin-Mihai Cailean, Sebastian-Andrei Avatamanitei, Alin-Dan Potorac, Eduard Zadobrischi, Mihai Dimian
Summary: Due to its unique advantages, the integration of VLC in vehicle safety applications has become a major research topic. This article proposes a novel approach to increase vehicular VLC systems' communication range by improving the VLC system based on the benefits that can be achieved through the VLC transmitter. The concept is based on LED current overdriving and a modified VPPM, which provide higher optical power and improved SNR for the VLC receiver.
Review
Engineering, Civil
Hao Zhou, Jorge Laval, Anye Zhou, Yu Wang, Wenchao Wu, Zhu Qing, Srinivas Peeta
Summary: This paper reviews the current state of the art in machine learning longitudinal motion planning (mMP) for autonomous vehicles (AVs), focusing on its impact on traffic congestion. It identifies gaps in current datasets regarding congestion scenarios and necessary input features for training mMP. The study also surveys major methods in both imitation learning and non-imitation learning, as well as highlights emerging technologies adopted by leading AV companies like Tesla, Waymo, and Comma.ai.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Transportation
Anye Zhou, Jian Wang, Srinivas Peeta
Summary: This study proposes a robust platoon control strategy for Connected and Autonomous Vehicles (CAVs) to mitigate the impacts of falsified information and ensure safe operation.
JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Hao Zhou, Anye Zhou, Jorge Laval, Yongyang Liu, Srinivas Peeta
Summary: This paper proposes a relaxation model to incorporate into ACC systems and validates its feasibility through simulation and road tests. The study also finds that relaxation ACC can reduce speed perturbations, stabilize lane-changing traffic, and increase average flow speed and capacity after a bottleneck occurs.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Computer Science, Cybernetics
Shubham Agrawal, Srinivas Peeta, Irina Benedyk
Summary: This study evaluates drivers' cognition and psychology under real-time travel information provision by measuring their brain electrical activity patterns. The findings indicate that drivers exert more cognitive effort in processing information in complex driving environments, insufficient information may increase their attention, and route recommendation may lead to stress and anxiety.
BEHAVIOUR & INFORMATION TECHNOLOGY
(2023)
Article
Transportation Science & Technology
Hao Zhou, Anye Zhou, Tienan Li, Danjue Chen, Srinivas Peeta, Jorge Laval
Summary: This study fills the gap in existing literature on commercial adaptive cruise control systems by investigating the impact of low-level control design on overall system stability. The study finds that slow low-level control undermines system stability under small frequencies and improves stability under large frequencies, while fast low-level control results in a varying gain process that benefits stability. The findings are verified through numerical and experimental analysis.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Civil
Yufei Xu, Yu Wang, Srinivas Peeta
Summary: This paper proposes a method using the transformer model and the pNEUMA dataset to predict vehicle trajectories in congested urban traffic. By utilizing the self-attention mechanism, this model can systematically analyze the impacts of vehicular interactions on the future trajectory of the target vehicle. Numerical studies demonstrate the effectiveness of the proposed approach and compare it with traditional LSTM models.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Engineering, Civil
Wei Sun, Guangzhao Dai, Xiaorui Zhang, Xiaozheng He, Xuan Chen
Summary: In this study, a novel vehicle re-identification method, TBE-Net, is proposed which integrates global appearance and local region features through a multi-branch embedding network. By utilizing feature complementary learning and part-aware ability, the proposed TBE-Net improves the accuracy of vehicle re-identification.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Yongfu Li, Bangjie Chen, Hang Zhao, Srinivas Peeta, Simon Hu, Yibing Wang, Zuduo Zheng
Summary: This paper proposes a new car-following model that accurately captures the behaviors of connected and automated vehicles. By considering different communication topologies and time delays, the model achieves good convergence performance and accurately predicts the velocity, acceleration, and position of the vehicles.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Economics
Jian Wang, Xiaozheng He, Srinivas Peeta, Wei Wang
Summary: This study proposes a NRMFD algorithm integrated with the EBA method to solve the CNDP under UE. The algorithm determines a feasible descent direction in each iteration and computes a feasible step size using the EBA method to improve convergence speed.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Environmental Studies
Xiaozheng He, Yu Wei, Jose Holguin-Veras
Summary: This paper proposes a simple imputation technique using the Brownian bridge structure to fill in missing speed data in low-resolution truck GPS datasets. The results demonstrate that the technique improves estimation accuracy in estimating fuel consumption and emissions using low-resolution GPS data.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Engineering, Civil
Xia Yang, Chenyang Wang, Xiaozheng He, Hedi Zhang, Guangming Xu
Summary: With the rapid growth of e-commerce and direct-to-consumer deliveries, the last-mile problem has become more noticeable. Smart parcel lockers, with their advantages in economies of scale and 24/7 contactless self-service, play a crucial role in solving this problem. However, due to poor planning, limited expansion, and unclear profit models, smart parcel locker suppliers in China have been experiencing significant economic losses. This study proposes a bilevel programming model to optimize the location of community smart parcel lockers, aiming to maximize the profit for the supplier and user satisfaction. The results provide theoretical support and practical guidance for third-party smart parcel locker suppliers to plan their investment budgets and optimize locker locations for maximum profit.
JOURNAL OF ADVANCED TRANSPORTATION
(2023)
Article
Computer Science, Artificial Intelligence
Anye Zhou, Yongyang Liu, Einat Tenenboim, Shubham Agrawal, Srinivas Peeta
Summary: This study investigates the car-following behavior of human-driven vehicles (HDVs) in mixed-flow traffic with connected and autonomous vehicles (CAVs) using a driving simulator. The study shows that the behavior of HDVs can impact the control performance and efficiency of CAVs. The effects of traffic congestion level and demographic characteristics are also considered. The results suggest that the stable CAV control setting is preferred by most HDV drivers but may lead to driver distraction.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Automation & Control Systems
Yongyang Liu, Anye Zhou, Yu Wang, Srinivas Peeta
Summary: In a mixed-flow traffic environment, predicting and intervening in lane-change behaviors of human-driven vehicles (HDVs) can enable cooperative platooning control and reduce traffic oscillations. A proactive longitudinal control strategy (PLCS), based on deep reinforcement learning, is proposed to counteract disruptive lane changes by HDVs and maintain the smoothness of traffic flow.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Engineering, Civil
Pengcheng Wang, Xinkai Wu, Xiaozheng He
Summary: This research explores the vulnerability of nonlinear vehicle platoons characterized by oscillatory behavior caused by external perturbations. A vibration-theoretic approach is proposed to characterize the platoon vulnerability and obtain the resonance frequency. The closed-form formulas of damping intensity and resonance frequency are derived through rigorous analysis. Simulation results show that overdamped platoons are more robust against perturbations, while underdamped platoons can be destabilized easily by perturbations at the resonance frequency.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Mechanical
Yu Wei, Xiaozheng (Sean) He
Summary: Rapid advances in vehicle automation and communication technologies enable connected autonomous vehicles (CAVs) to cross intersections cooperatively, which could significantly improve traffic throughput and safety at intersections. This study proposes an adaptive vehicle control method to facilitate the formation of a virtual platoon and the cooperative crossing of CAVs, factoring demand variations at an isolated intersection.
INTERNATIONAL JOURNAL OF MECHANICAL SYSTEM DYNAMICS
(2022)
Article
Transportation Science & Technology
Yue Zhao, Liujiang Kang, Huijun Sun, Jianjun Wu, Nsabimana Buhigiro
Summary: This study proposes a 2-population 3-strategy evolutionary game model to address the issue of subway network operation extension. The analysis reveals that the rule of maximum total fitness ensures the priority of evolutionary equilibrium strategies, and proper adjustment minutes can enhance the effectiveness of operation extension.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Hongtao Hu, Jiao Mob, Lu Zhen
Summary: This study investigates the challenges of daily storage yard management in marine container terminals considering delayed transshipment of containers. A mixed-integer linear programming model is proposed to minimize various costs associated with transportation and yard management. The improved Benders decomposition algorithm is applied to solve the problem effectively and efficiently.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Zhandong Xu, Yiyang Peng, Guoyuan Li, Anthony Chen, Xiaobo Liu
Summary: This paper studied the impact of range anxiety among electric vehicle drivers on traffic assignment. Two types of range-constrained traffic assignment problems were defined based on discrete or continuous distributed range anxiety. Models and algorithms were proposed to solve the two types of problems. Experimental results showed the superiority of the proposed algorithm and revealed that drivers with heightened range anxiety may cause severe congestion.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Chuanjia Li, Maosi Geng, Yong Chen, Zeen Cai, Zheng Zhu, Xiqun (Michael) Chen
Summary: Understanding spatial-temporal stochasticity in shared mobility is crucial, and this study introduces the Bi-STTNP prediction model that provides probabilistic predictions and uncertainty estimations for ride-sourcing demand, outperforming conventional deep learning methods. The model captures the multivariate spatial-temporal Gaussian distribution of demand and offers comprehensive uncertainty representations.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Benjamin Coifman, Lizhe Li
Summary: This paper develops a partial trajectory method for aligning views from successive fixed cameras in order to ensure high fidelity with the actual vehicle movements. The method operates on the output of vehicle tracking to provide direct feedback and improve alignment quality. Experimental results show that this method can enhance accuracy and increase the number of vehicles in the dataset.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Mohsen Dastpak, Fausto Errico, Ola Jabali, Federico Malucelli
Summary: This article discusses the problem of an Electric Vehicle (EV) finding the shortest route from an origin to a destination and proposes a problem model that considers the occupancy indicator information of charging stations. A Markov Decision Process formulation is presented to optimize the EV routing and charging policy. A reoptimization algorithm is developed to establish the sequence of charging station visits and charging amounts based on system updates. Results from a comprehensive computational study show that the proposed method significantly reduces waiting times and total trip duration.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)