185 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Universitat de Miguel Hernández d'ElxES7 papers
- Toyota Research Institute4 papers
- Columbia UniversityUS2 papers
- North Carolina State UniversityUS2 papers
- Rochester Institute of TechnologyUS2 papers
- The University of Texas at DallasUS2 papers
- Toyota Motor Corporation (Switzerland)CH2 papers
- Toyota Motor North America Research & Development (United States)US2 papers
- Universidade de VigoES2 papers
- University of FloridaUS2 papers
- University of Illinois Urbana-ChampaignUS2 papers
- University of North Carolina at CharlotteUS2 papers
33 papers
Support of Teleoperated Driving with 5G Networks
M. Carmen Lucas-Estañ, Baldomero Coll-Perales, Mohammad Irfan Khan +4
Teleoperated driving (ToD) can support autonomous driving under complex or unexpected traffic scenarios that an autonomous vehicle may not understand or be able to handle. In ToD,…
FORESEE: A Cooperative Lane Change Model for Connected and Automated Driving
Rafael Molina-Masegosa, Sergei S. Avedisov, Miguel Sepulcre +3
This paper presents FORESEE, a novel cooperative lane change model for connected and automated driving. FORESEE leverages Vehicle-to-Everything (V2X) data to anticipate traffic con…
Direct-V2X Support with 5G Network-based Communications: Performance, Challenges and Solutions
M. C. Lucas-Estañ, B. Coll-Perales, T. Shimizu +5
This study analyzes the feasibility of supporting critical V2X services using 5G network-based Vehicle-to-Network-to-Vehicle (V2N2V) communications. The study evaluates the end-to-…
5G Network Architecture and Configuration Choices to Support Teleoperated Driving at Scale
M. C. Lucas-Estañ, B. Coll-Perales, M. I. Khan +4
Teleoperated driving (ToD) enables the remote driving or control of vehicles. For this purpose, vehicles must transmit video feeds to the ToD control center so that the remote oper…
Impact of ADAS and V2X Penetration Rates on Cooperative Active Safety
M. C. Lucas-Estañ, B. Coll-Perales, M. I. Khan +2
A major driver of connected and automated driving is cooperative active safety. The effectiveness of cooperative safety applications depends on the ability of vehicles to detect tr…
Data-driven model order reduction for structures with piecewise linear nonlinearity using dynamic mode decomposition
Akira Saito, Masato Tanaka
Piecewise-linear nonlinear systems appear in many engineering disciplines. Prediction of the dynamic behavior of such systems is of great importance from practical and theoretical…
Advanced Assistance for Traffic Crash Analysis: An AI-Driven Multi-Agent Approach to Pre-Crash Reconstruction
Gerui Xu, Boyou Chen, Huizhong Guo +6
Traffic collision reconstruction traditionally relies on human expertise and can be accurate, but pre-crash reconstruction is more challenging. This study develops a multi-agent AI…
RTAMT -- Runtime Robustness Monitors with Application to CPS and Robotics
Tomoya Yamaguchi, Bardh Hoxha, Dejan Nickovic
In this paper, we present Real-Time Analog Monitoring Tool (RTAMT), a tool for quantitative monitoring of Signal Temporal Logic (STL) specifications. The library implements a flexi…
PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis
Dipkamal Bhusal, Md Tanvirul Alam, Monish K. Veerabhadran +3
Deep neural networks for classification are vulnerable to adversarial attacks, where small perturbations to input samples lead to incorrect predictions. This susceptibility, combin…
Demonstrating Mobile Manipulation in the Wild: A Metrics-Driven Approach
Max Bajracharya, James Borders, Richard Cheng +11
We present our general-purpose mobile manipulation system consisting of a custom robot platform and key algorithms spanning perception and planning. To extensively test the system…
Layout Sequence Prediction From Noisy Mobile Modality
Haichao Zhang, Yi Xu, Hongsheng Lu +2
Trajectory prediction plays a vital role in understanding pedestrian movement for applications such as autonomous driving and robotics. Current trajectory prediction models depend…
Unveiling Energy Efficiency in Deep Learning: Measurement, Prediction, and Scoring across Edge Devices
Xiaolong Tu, Anik Mallik, Dawei Chen +4
Today, deep learning optimization is primarily driven by research focused on achieving high inference accuracy and reducing latency. However, the energy efficiency aspect is often…
Computational synthesis of locomotive soft robots by topology optimization
Hiroki Kobayashi, Farzad Gholami, S. Macrae Montgomery +7
Locomotive soft robots (SoRos) have gained prominence due to their adaptability. Traditional locomotive SoRo design is based on limb structures inspired by biological organisms and…
SoK: Modeling Explainability in Security Analytics for Interpretability, Trustworthiness, and Usability
Dipkamal Bhusal, Rosalyn Shin, Ajay Ashok Shewale +4
Interpretability, trustworthiness, and usability are key considerations in high-stake security applications, especially when utilizing deep learning models. While these models are…
An Analytical Latency Model and Evaluation of the Capacity of 5G NR to Support V2X Services using V2N2V Communications
M. C. Lucas-Estañ, B. Coll-Perales, T. Shimizu +5
5G has been designed to support applications such as connected and automated driving. To this aim, 5G includes a highly flexible New Radio (NR) interface that can be configured to…
End-to-End V2X Latency Modeling and Analysis in 5G Networks
B. Coll-Perales, M. C. Lucas-Estañ, T. Shimizu +5
5G networks provide higher flexibility and improved performance compared to previous cellular technologies. This has raised expectations on the possibility to support advanced V2X…
The Transdimensional Poisson Process for Vehicular Network Analysis
Jeya Pradha Jeyaraj, Martin Haenggi, Ahmed Hamdi Sakr +1
A comprehensive vehicular network analysis requires modeling the street system and vehicle locations. Even when Poisson point processes (PPPs) are used to model the vehicle locatio…
A Dynamic Codebook Design for Analog Beamforming in MIMO LEO Satellite Communications
Joan Palacios, Nuria González-Prelcic, Carlos Mosquera +1
Beamforming gain is a key ingredient in the performance of LEO satellite communication systems to be integrated into cellular networks. However, beam codebooks previously designed…
Optimal Precoder Design for MIMO-OFDM-based Joint Automotive Radar-Communication Networks
Ceyhun D. Ozkaptan, Eylem Ekici, Chang-Heng Wang +1
Large-scale deployment of connected vehicles with cooperative awareness technologies increases the demand for vehicle-to-everything (V2X) communication spectrum in 5.9 GHz that is…
PerceMon: Online Monitoring for Perception Systems
Anand Balakrishnan, Jyotirmoy Deshmukh, Bardh Hoxha +2
Perception algorithms in autonomous vehicles are vital for the vehicle to understand the semantics of its surroundings, including detection and tracking of objects in the environme…
Failure Tolerance of the Human Lumbar Spine in Combined Compression and Flexion Loading
S. K. Tushak, J. P. Donlon, B. D. Gepner +5
Vehicle safety systems have substantially decreased motor vehicle crash-related injuries and fatalities, but injuries to the lumbar spine still have been reported. Experimental and…
Digital Twin-Assisted Cooperative Driving at Non-Signalized Intersections
Ziran Wang, Kyungtae Han, Prashant Tiwari
Digital Twin, as an emerging technology related to Cyber-Physical Systems (CPS) and Internet of Things (IoT), has attracted increasing attentions during the past decade. Conceptual…
A Polynomial-time, Truthful, Individually Rational and Budget Balanced Ridesharing Mechanism
Tatsuya Iwase, Sebastian Stein, Enrico H. Gerding
Ridesharing has great potential to improve transportation efficiency while reducing congestion and pollution. To realize this potential, mechanisms are needed that allocate vehicle…
A hybrid beamforming design for massive MIMO LEO satellite communications
Joan Palacios, Nuria Gonzalez-Prelcic, Carlos Mosquera +2
5G and future cellular networks intend to incorporate low earth orbit (LEO) satellite communication systems (SatCom) to solve the coverage and availability problems that cannot be…