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📝 Edit this file: docs/overview.md

kairos-zen: Overview

kairos-zen is an agent-based simulation model developed as part of the ZENFreight project. Built using the Kairos modelling architecture developed by the Transport Systems & Logistics Laboratory.

kairos-zen will simulate freight operations during the transition to zero-emission vehicles. It will model multiple freight operators, each managing their own mixed fleet of Battery Electric, Hydrogen Fuel Cell, and Diesel vehicles. The system will optimize multi-delivery routes and vehicle assignments while respecting real-world constraints and operator interactions.

The simulation will provide insights into:

  • Optimal fleet composition strategies across multiple operators
  • Multi-delivery route efficiency and consolidation opportunities
  • Infrastructure investment requirements and shared resource utilization
  • Operational cost comparisons between different fleet compositions

System Architecture

Core Design Principles

  1. Multi-Operator Architecture: Will simulate multiple competing or collaborating freight operators, each with independent fleet management and customer bases.

  2. Multi-Delivery Route Optimization: Vehicles will serve multiple customers per trip, optimizing consolidation and efficiency opportunities.

  3. Vectorized Operations: All entities will use AgentGroup architecture with PropertyArrays for efficient NumPy-based operations across large-scale scenarios.

  4. Pre-Execution Optimization: Multi-stop route planning and vehicle assignment will occur before simulation execution, with real-time adjustments for disruptions.

  5. Mixed Fleet Management: Will provide unified handling of different propulsion types through sparse property arrays within each operator's fleet.

  6. Regulatory Compliance: Will include built-in validation of driver hours regulations, weight limits, and operational constraints across all operators.

System Components

World (Simulation Container)
│
├── Operator 1
│   └── OperatorController
│       ├── FleetController
│       │   ├── Will manage operator's vehicle fleet
│       │   ├── Will handle multi-delivery route assignments
│       │   └── Will monitor vehicle states and performance
│       ├── Operator Configuration
│       │   ├── Fleet composition and specifications
│       │   ├── Service areas and operational parameters
│       │   └── Business rules and constraints
│       └── Features:
│           ├── BEVPropulsionFeature
│           ├── HFCEVPropulsionFeature
│           ├── DieselPropulsionFeature
│           ├── EnergyManagementFeature
│           └── MaintenanceFeature
│
├── Operator 2...N (Additional Operators)
│   └── OperatorController (Independent operator management)
│
├── DemandController
│   ├── Will manage all customer demands across operators
│   ├── Will track demand allocation and lifecycle
│   └── Will monitor service levels by operator
│
├── InfrastructureController (Shared Resources)
│   ├── ChargingNetwork (BEV) - shared or operator-specific
│   ├── HydrogenStations (HFCEV) - shared infrastructure
│   └── DepotFacilities - operator-owned facilities
│
└── NetworkController
    ├── Road network model (shared)
    ├── Distance calculations
    └── Travel time estimation

Operational Flow

Pre-Simulation Phase:

  1. Load customer demands across all operators (pre-allocated to operators)
  2. Process operator-specific demands within each fleet controller
  3. Optimize multi-delivery vehicle routes for each operator
  4. Validate feasibility against constraints and operator capabilities
  5. Load final plans into simulation

Simulation Execution Phase:

  1. Vehicles execute multi-stop delivery routes
  2. Handle dynamic events and inter-operator interactions
  3. Manage charging/refueling operations (shared infrastructure)
  4. Track performance metrics by operator and system-wide
  5. Generate comparative operational reports