UC2 Cross-border Shuttle Optimization (Slovenia, Italy, Croatia, Austria)
Description
Use case 2 (UC2) pioneers a next-generation demand-responsive transport (DRT) system spanning Slovenia, Italy, Croatia, and Austria. Aimed at improving underserved links between urban centres and major airports, UC2 builds on a proven reservation-based model to deliver an intelligent, scalable shuttle platform. The platform leverages real-time data, predictive analytics, and continuous planning to enhance long-distance shared mobility, reduce emissions, and improve cost-efficiency across borders.
Scenarios and Testing
UC2 features a hybrid testing approach combining real-life operations with simulation-based experiments. The evaluation is structured around three strategic cross-border shuttle routes:
- Ljubljana (Slovenia) – Trieste (Italy)
- Ljubljana (Slovenia) – Zagreb (Croatia)
- Maribor (Slovenia) – Vienna (Austria)
Each route was selected based on operational relevance, existing demand patterns, and logistical complexity. Testing focuses on comparing benchmark (static) planning with dynamic planning approaches enabled by the CONDUCTOR platform.
Experiments will assess system behavior under varying conditions, including:
- Sudden demand surges (e.g., due to flight delays or cancellations)
- Disruptive traffic events (e.g., accidents, roadworks)
- Last-minute bookings and ad-hoc transport requests
- Seasonal peaks in travel volume
Both operational (on-the-ground) testing and simulations will evaluate system performance, robustness, and scalability.
Key Features
Demand-Responsive Transport Platform
A modular, cloud-based system enabling the orchestration of shuttle fleets in real time, integrating microservices for booking, planning, and monitoring.
Planning and Routing Optimisation
AI-powered algorithms continuously update the optimal travel plans, minimizing travel time, distance, and emissions.
Ad-Hoc Continuous Planning
Dynamically assigns last-minute passengers to partially filled vehicles, increasing fleet efficiency and service availability.
Demand Prediction Models
Models forecast travel needs up to one year ahead, using time-based resolution for short-, medium-, and long-term planning.
Traffic Event Assessment
Monitors disruptions with assisted rerouting and reallocation of resources.
Integration of Heterogeneous Data
Incorporates airport schedules, weather conditions, road traffic data, and booking patterns into a unified decision-making layer.
Key Performance Indicators
Rate of manual interventions in shuttle service route plans
Fleet kilometres per daily plan
Ratio of accepted to rejected requests
Fuel consumption per passenger dropped off
Average costs per kilometre per passenger dropped off
Availability and number of last-minute data inputs
Average planning cost per route plan
Services enabled and number of services tested
Expected Benefits
- Increased Accessibility: Improved regional connectivity for passengers in Slovenia and neighboring countries.
- Lower Environmental Impact: Optimized routing and higher occupancy reduce total emissions.
- Enhanced Passenger Experience: Shorter waiting and travel times with flexible booking options.
- Operational Efficiency: Reduced deadhead kilometers and idle time through continuous planning and demand forecasting.
- Scalability: A robust framework suitable for replication in other European multimodal transport systems.
- Cross-border Mobility Advancement: Facilitates seamless movement across EU borders with integrated ticketing and scheduling.
Contribution to the CONDUCTOR Project
UC2 contributes to CONDUCTOR’s overall vision by providing a real-world laboratory for testing:
- Multimodal, cross-border DRT applications
- AI-powered dynamic planning mechanisms
- Predictive analytics integrated into operational planning
- Hybrid simulation and field validation methodologies
Deployment Architecture
The deployment architecture for UC2 consists of the following core components:
- Centralised Cloud Platform: Hosts the planning engine, optimisation modules, data management systems, and user interfaces (passenger and operator).
- Microservice Infrastructure: Supports modular services including booking, dispatch, vehicle monitoring, demand forecasting, and routing.
- Data Integration Layer: Interfaces with external sources such as:
- Airport timetables (Ljubljana, Trieste, Zagreb, Vienna)
- Real-time weather APIs
- Traffic and road condition feeds
- Historical and real-time booking data
- Onboard Systems: Vehicles are equipped with location tracking and communication units that interact with the central platform for routing updates and status reporting.
- Decision Intelligence Engine: Orchestrates real-time decisions using AI-based models and predictive algorithms.
- User Interaction Channels:
- Mobile and web booking platforms for passengers
- Dashboard for operators and dispatchers