Jose Escribano-Macias

Jose Escribano-Macias

Research Associate

Imperial College London

Jose is a Research Associate at the Transport Systems and Logistics Laboratory, Centre for Transport Studies at Imperial College London. His research focuses on collaborative vehicle control, optimisation of last-mile logistics, urban air mobility, and machine learning and game theoretical models. He currently works as part of Project D-Risk, which aims at improving the safety of autonomous vehicles to make them a commercial reality.

Jose joined the Centre for Transport Studies in October 2015 as part of the EPSRC Centre for Doctoral Training (CDT) in Sustainable Civil Engineering and was awarded his Ph.D. in March 2021. His thesis focused on the optimisation of humanitarian relief operations using unmanned aerial vehicles (UAVs), developing a framework to design and evaluate relief efforts. This incorporates UAV-specific constraints (such as energy consumption patterns, flight trajectories, and recharging operations), setting it apart from conventional humanitarian operations models. The models conform to the latest Civil Aviation navigation specification frameworks.

Alongside his PhD, he worked with WeRobotics on the development of UAV field-deployment protocols and as a consultant with the United Nations World Food Programme on the development of the first Humanitarian UAV Coordination Mechanism.

Jose also holds a first-class MEng degree in Civil Engineering from Imperial College London, graduating in 2015.

Interests
  • Humanitarian Logistics
  • Optimal Control
  • Aviation
Education

  • PhD in Operations Research, 2020

    Imperial College London

  • MEng in Civil & Environmental Engineering, 2015

    Imperial College London

Journal Papers

  1. (2023). Policy and Strategy Evaluation of Ridesharing Autonomous Vehicle Operation: A London Case Study. Transportation Research Record. Cite DOI
  2. (2022). Decentralised Multi-Agent Reinforcement Learning Approach for the Same-Day Delivery Problem. Transportation Research Record. Cite DOI
  3. (2022). Spatial-Temporal Flows-Adaptive Street Layout Control Using Reinforcement Learning. Sustainability. Cite DOI
  4. (2021). On the Selection of Charging Facility Locations for EV-Based Ride-Hailing Services: A Computational Case Study. Sustainability. Cite
  5. (2020). Design of hospital delivery networks using unmanned aerial vehicles. Transportation Research Record. Cite
  6. (2020). Endogenous stochastic optimisation for relief distribution assisted with Unmanned Aerial Vehicles. OR Spectrum. Cite
  7. (2020). Optimal Design of Rapid Evacuation Strategies in Constrained Urban Transport Networks. Transportmetrica A: Transport Science. Cite
  8. (2020). Optimal Hub Selection for Rapid Medical Deliveries using Unmanned Aerial Vehicles. Transportation Research Part C: Emerging Technologies. Cite DOI

Preprints

  1. Adaptive Road Configurations for Improved Autonomous Vehicle-Pedestrian Interactions using Reinforcement Learning. In review. Preprint. Cite
  2. An integrated vertiport placement model considering vehicle sizing and queuing: A London Case Study. In review. Preprint. Cite
  3. Location-routing Optimisation for Urban Logistics Using Mobile Parcel Locker Based on Hybrid Q-Learning Algorithm. arXiv, In review. Preprint. PDF Cite DOI
  4. Risk-Aware Stochastic Vehicle Trajectory Prediction with Spatial-Temporal Interaction Modelling. In review. Preprint. Cite

Conference Papers

  1. (2023). Customer Behaviour Analysis for Coordinated Delivery Service Using Mobile Parcel Lockers and Autonomous Robots: A Congestion-Game Model. Transportation Research Board 102nd Annual Meeting (TRBAM 2023). Cite
  2. (2023). Last-mile Collaboration: A Decentralized Mechanism with Bounded Performance Guarantees and Implementation Strategies. Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023). Cite
  3. (2023). Last-mile Collaboration: A Decentralized Mechanism with Bounded Performance Guarantees and Implementation Strategies. Proceedings of the 2023 Conference of the INFORMS Transportation and Logistics Society (TSL 2023). Cite
  4. (2023). Policy and Strategy Evaluation of Ridesharing Autonomous Vehicle Operation: A London Case Study. Transportation Research Board 102nd Annual Meeting (TRBAM 2023). Cite
  5. (2022). Location-routing Optimisation for Urban Logistics Using Mobile Parcel Locker Based on Hybrid Q-Learning Algorithm. Transportation Research Board 101st Annual Meeting (TRBAM 2022). Cite
  6. (2022). Novel Trajectory Prediction Algorithm Using a Full Dataset: Comparison and Ablation Studies. 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC 2022). Cite
  7. (2022). An integrated vertiport placement model considering vehicle sizing and queuing. Transportation Research Board 101st Annual Meeting (TRBAM 2022). Cite
  8. (2022). Integrated Path Planning and Task Assignment Model for On-Demand Last-Mile UAV-Based Delivery. International Conference on Computational Logistics (ICCL 2022). Cite
  9. (2022). The Competition and Inefficiency in Urban Road Last-Mile Delivery. Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022). Cite
  10. (2021). A Decentralised Multi-Agent Reinforcement Learning Approach for the Same-Day Delivery Problem. Transportation Research Board 101st Annual Meeting (TRBAM 2022). Cite
  11. (2021). Demand modelling and optimal vertiport placement for airport-purposed eVTOL services. Transportation Research Board 101st Annual Meeting (TRBAM 2022). Cite
  12. (2019). Sequential Trajectory Optimisation Using Dynamic Airspace Sectorisation. Transportation Research Board 98th Annual Meeting (TRBAM 2019). PDF Cite
  13. (2018). Integrated Trajectory-Location-Routing for Rapid Humanitarian Deliveries using Unmanned Aerial Vehicles. 2018 Aviation Technology, Integration, and Operations Conference. Cite DOI
  14. (2017). Integrated Trajectory Optimisation and Location‐Routing Method for Rapid Medical Deliveries using Unmanned Aerial Vehicles (UAVs). International Conference on Dynamics of Disasters. Cite
  15. (2017). Rapid Urban Evacuation across Constrained Transport Networks. Transportation Research Board 96th Annual Meeting. PDF Cite