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@INPROCEEDINGS{Onah:1051617,
      author       = {Onah, Chinonso and Misciasci, Neel and Othmer, Carsten and
                      Michielsen, Kristel},
      title        = {{QUEST}: {QU}antum-{E}nhanced {S}hared {T}ransportation},
      address      = {Albuquerque, NM, USA},
      publisher    = {IEEE},
      reportid     = {FZJ-2026-00539},
      pages        = {2149 - 2160},
      year         = {2025},
      abstract     = {We introduce “Windbreaking-as-a-Service” (WaaS) as an
                      innovative approach to shared transportation in which larger
                      “windbreaker” vehicles provide aerodynamic shelter for
                      “windsurfer” vehicles, thereby reducing drag and energy
                      consumption. As a computational framework to solve the
                      largescale matching and assignment problems that arise in
                      WaaS, we present QUEST (Quantum-Enhanced Shared
                      Transportation). Specifically, wef ormulate t he p airing of
                      windbreakers and windsurfers - subject to timing, speed, and
                      vehicle-class constraints - as a mixed-integer quadratic
                      problem (MIQP). Focusing on a single-segment prototype, we
                      verify the solution classically via the Hungarian Algorithm,
                      a Gurobi-based solver, and brute-force enumeration of binary
                      vectors. We then encode the problem as a Quadratic
                      Unconstrained Binary Optimization (QUBO) and map it to an
                      Ising Hamiltonian, enabling the use of the Quantum
                      Approximate Optimization Algorithm (QAOA) and other quantum
                      and classical annealing technologies. Our quantum
                      implementation successfully recovers the optimal assignment
                      identified by the classical methods, c onfirming the so
                      undness of the QUEST pipeline for a controlled prototype.
                      While QAOA and other quantum heuristics do not guarantee a
                      resolution of the fundamental complexity barriers, this
                      study illustrates how the WaaS problem can be systematically
                      translated into a quantumready model. It also lays the
                      groundwork for addressing multisegment scenarios and
                      potentially leveraging quantum advantage for large-scale
                      shared-transportation instances.},
      month         = {Aug},
      date          = {2025-08-30},
      organization  = {2025 IEEE International Conference on
                       Quantum Computing and Engineering
                       (QCE), Albuquerque (NM), 30 Aug 2025 -
                       5 Sep 2025},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5111},
      typ          = {PUB:(DE-HGF)8},
      doi          = {10.1109/QCE65121.2025.00235},
      url          = {https://juser.fz-juelich.de/record/1051617},
}