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20182026
most citedSafe, Efficient, and Comfortable Velocity Control based on Reinforcement Learning for Autonomous Driving

469 citations · 1.3k across the 28 of their papers we have counts for

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Showing 2026 · quant-phShow all

5 papers · 2 filters

quant-ph2026

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…

quant-ph2026

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…

quant-ph2026

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…

quant-ph2026

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.…

quant-ph2026

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…