469 citations · 1.3k across the 28 of their papers we have counts for
30 papers
Fewer Qubits, Better Choices: Coupling-Aware Sub-QUBO Selection for Quantum-Assisted Traffic Zone Partitioning
Qianwen Guo, Ruimin Ke
Near-term quantum optimizers accommodate roughly a hundred binary variables, requiring large Quadratic Unconstrained Binary Optimization problems to be decomposed into hardware-siz…
SimTIO: A Simulation-Grounded Multi-Agent LLM Framework for Compositional Traffic Intervention Optimization
Shuyang Li, Ruimin Ke
Traffic analysts must translate diagnosed bottlenecks into executable interventions without allowing local improvements to degrade network-wide performance. This study presents Sim…
GHR-VLM: Making Zero-Shot Transit Video Analytics Realizable with Grounded Hybrid Reasoning
Kaicong Huang, Weiheng Oh, Jack M. Reilly +2
Transit video understanding can provide valuable fine-grained data that conventional passenger counters and fare systems cannot capture. However, supervised video models require ta…
Risk-Adaptive Edge--Cloud Visual Reasoning for Communication-Efficient Autonomous Driving
Meng Ma, Shuyang Li, Naigang Wang +1
Cloud-hosted vision-language models (VLMs) offer greater contextual reasoning capabilities than smaller onboard models, but frequent visual uploads increase communication overhead…
Cooperative Platoon Routing and Dispatching via Edge-Assisted Hybrid Quantum Optimization
Talha Azfar, Ruimin Ke
Cooperative platooning can reduce the energy use of Connected and Autonomous Vehicle (CAV) fleets, but the routing problem becomes difficult when vehicles must meet on the same roa…
FedQML-Edge: Compact Quantum Feature Sketches for Communication-Constrained Roadside Federated Learning
Talha Azfar, Ruimin Ke
Roadside units (RSUs) supporting connected and autonomous vehicle corridors need compact models to decide when cooperative maneuvers should be rewarded, deferred, or disabled. Raw…
CARLA-GS: Decoupling Representation, Reasoning, and Physics Simulation for Autonomous Driving Corner-Case Synthesis
Kaicong Huang, Meng Ma, Ruimin Ke
Safety evaluation for autonomous driving is dominated by rare, safety-critical interactions, motivating simulators that can deliberately synthesize corner cases with photorealistic…
Decoupled Intelligence: A Multi-Agent LLM Framework for Controllable Traffic Scenario Generation in SUMO
Shuyang Li, Ruimin Ke
The integration of Large Language Models (LLMs) with microscopic traffic simulation offers a promising path toward autonomous urban planning and intelligent transportation analysis…
Impact-Driven Quantum Decomposition for Traffic Zone Partitioning: A Hybrid Gate-Model Framework
Ruimin Ke, Talha Azfar, Kaicong Huang +1
Partitioning transportation networks into balanced and spatially coherent traffic zones is a fundamental yet computationally challenging task in intelligent transportation systems.…
Real2Sim: A Physics-driven and Editable Gaussian Splatting Framework for Autonomous Driving Scenes
Kaicong Huang, Talha Azfar, Weisong Shi +1
Reliable autonomous driving relies on large-scale, well-labeled data and robust models. However, manual data collection is resource-intensive, and traditional simulation suffers fr…
iPay: Integrated Payment Action Recognition via Multimodal Networks and Adaptive Spatial Prior Learning
Kaicong Huang, Weiheng Oh, Thomas Guggisberg +1
Automated transit payment analysis is vital for scalable fare auditing and passenger analytics, yet practice still relies on limited manual inspection. Prior vision- and skeleton-b…
Hardware-Efficient Quantum Optimization for Transportation Networks via Compressed Adiabatic Evolution
Talha Azfar, Ruimin Ke, Sean He +2
Transportation systems such as urban logistics, vehicle routing, and infrastructure planning require solving large-scale combinatorial optimization problems under complex constrain…
Locatability-Guided Adaptive Reasoning for Image Geo-Localization with Vision-Language Models
Bo Yu, Fengze Yang, Yiming Liu +6
The emergence of Vision-Language Models (VLMs) has introduced new paradigms for global image geo-localization through retrieval-augmented generation (RAG) and reasoning-driven infe…
Background Matters Too: A Language-Enhanced Adversarial Framework for Person Re-Identification
Kaicong Huang, Talha Azfar, Jack M. Reilly +2
Person re-identification faces two core challenges: precisely locating the foreground target while suppressing background noise and extracting fine-grained features from the target…
Quantum-Assisted Vehicle Routing: Realizing QAOA-based Approach on Gate-Based Quantum Computer
Talha Azfar, Osama Muhammad Raisuddin, Ruimin Ke +1
The Vehicle Routing Problem (VRP) is a fundamental combinatorial optimization challenge with broad applications in logistics and transportation. In this work, we present a quantum-…
TransitReID: Transit OD Data Collection with Occlusion-Resistant Dynamic Passenger Re-Identification
Kaicong Huang, Talha Azfar, Jack Reilly +1
Transit Origin-Destination (OD) data are fundamental for optimizing public transit services, yet current collection methods, such as manual surveys, Bluetooth/WiFi tracking, and Au…
Enhancing Disaster Resilience with UAV-Assisted Edge Computing: A Reinforcement Learning Approach to Managing Heterogeneous Edge Devices
Talha Azfar, Kaicong Huang, Ruimin Ke
Edge sensing and computing is rapidly becoming part of intelligent infrastructure architecture leading to operational reliance on such systems in disaster or emergency situations.…
Q-RESTORE: Quantum-Driven Framework for Resilient and Equitable Transportation Network Restoration
Daniel Udekwe, Ruimin Ke, Jiaqing Lu +1
Efficient and socially equitable restoration of transportation networks post disasters is crucial for community resilience and access to essential services. The ability to rapidly…
Traffic Co-Simulation Framework Empowered by Infrastructure Camera Sensing and Reinforcement Learning
Talha Azfar, Kaicong Huang, Andrew Tracy +3
Traffic simulations are commonly used to optimize urban traffic flow, with reinforcement learning (RL) showing promising potential for automated traffic signal control, particularl…
VCAT: Vulnerability-aware and Curiosity-driven Adversarial Training for Enhancing Autonomous Vehicle Robustness
Xuan Cai, Zhiyong Cui, Xuesong Bai +4
Autonomous vehicles (AVs) face significant threats to their safe operation in complex traffic environments. Adversarial training has emerged as an effective method of enabling AVs…
ChatSUMO: Large Language Model for Automating Traffic Scenario Generation in Simulation of Urban MObility
Shuyang Li, Talha Azfar, Ruimin Ke
Large Language Models (LLMs), capable of handling multi-modal input and outputs such as text, voice, images, and video, are transforming the way we process information. Beyond just…
Quantum Computing in Intelligent Transportation Systems: A Survey
Yifan Zhuang, Talha Azfar, Yinhai Wang +4
Quantum computing, a field utilizing the principles of quantum mechanics, promises great advancements across various industries. This survey paper is focused on the burgeoning inte…
Deep Learning based Computer Vision Methods for Complex Traffic Environments Perception: A Review
Talha Azfar, Jinlong Li, Hongkai Yu +3
Computer vision applications in intelligent transportation systems (ITS) and autonomous driving (AD) have gravitated towards deep neural network architectures in recent years. Whil…
Edge Computing for Real-Time Near-Crash Detection for Smart Transportation Applications
Ruimin Ke, Zhiyong Cui, Yanlong Chen +3
Traffic near-crash events serve as critical data sources for various smart transportation applications, such as being surrogate safety measures for traffic safety research and corn…