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Integration of automated vehicles in public transport

Chapter 2
Picture of Integration of automated vehicles in public transport

When public transport operators and authorities plan to integrate fleets of Shared Personalised Automated Connected vEhicles (SPACE) into public transport, what does it mean from a technical point of view, besides buying the vehicles? In this chapter we look at which key components are required to develop and deploy the scenarios we identified in Chapter 1 of the toolkit.

This chapter presents a high level reference architecture to ensure proper integration of AV fleets into public transport systems, as well as performance, efficiency, safety and security. The objective is not to be prescriptive, but to determine the main functions and elements necessary to operate AVs in passenger service, while identifying the relationship between them.

ITSxAV - Value Chain

The below diagram shows the interactions between the actors and the main software and hardware components involved in a typical Intelligent Transportation System for Automated Vehicles (ITSxAV) architecture.

ITSxAV - Reference Architecture

SPACE has developed a high-level reference architecture that aims at ensuring a comprehensive and seamless integration of driverless vehicles with other IT systems in the mobility ecosystem using a fleet orchestration platform.

The main goal of this reference architecture is to help operators and cities make the right technical decisions from the start hence speed up the development and deployments of driverless mobility services. It also allows for cross-site, cross-vehicle type/brand and cross-operators real-life operations. Finally, the reference architecture should enable mixed fleet operation using both driven and automated vehicles using the same fleet orchestration software.

To orchestrate efficiently the fleet (i.e. to send the right vehicle to the right place at the right time) the platform is interconnected with the existing public transport back-end systems, the digital road infrastructure and the smart city data sources (e.g. Traffic Management Centers, smart parking, IoT platforms).

The platform also ensures a brand- and type-agnostic integration with the driverless vehicles and provides rich and open APIs (Application Program Interface) to develop professional and end users applications. The high-level architecture identifies the main functions and components necessary to enable real-life operation of AVs in passenger service, while identifying the relationship between them.

The architecture is designed according to the scenarios and use cases defined in Chapter 1 of the toolkit. All the building blocks of the reference architecture are essential functionalities to ensure the integration of new fleets of AVs into the public transport systems.

Interoperability is also encouraged and promoted through the reference architecture paving the way to standardized interfaces to connect the different systems.

Dispatching: Functionality that enables fleet orchestration by scheduling trips with respect to vehicle availability, exposing vehicle plans to mission management, adjusting vehicle plans based on mission execution progress and on traffic as well as optimizing delay propagation and reduction.

Routing: Functionality for finding and dynamically updating the fastest routes between locations with respect to current or predicted traffic conditions, based on desired departure or arrival times as well as vehicle-specific operational design domains.

Pooling: Functionality to pool travelers to maximize vehicle utilization and fleet efficiency while managing vehicle capacity, load and occupancy.

Matching: Functionality that allows to assign and schedule rides optimally under various time constraints while managing vehicle capacities and occupancy and to rematch rides automatically in case of delays and incidents.

Headway & Timetable Management: Functionality that allows to generate conflict-free vehicle movement plans, control headways for optimal coverage of target frequencies, find optimal timetables with respect to demand and predict energy consumption as well as plan charging intervals into the vehicle plans.

Prepositioning & Rebalancing: Functionality that allows to determine optimal prepositioning locations and catchment areas and to assign idle vehicles to prepositioning locations.

Charging: Functionality that allows to predict energy consumption of vehicles and plan optimal charging schedules and locations.

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7 words explained


Also known as flocking. A collection of (automated) vehicles that travel together, actively coordinated in formation. Platoons decrease the distances between vehicles using electronic, and possibly mechanical, coupling. Platooning allows many vehicles to accelerate or brake simultaneously.

urban setting

High density environment with an efficient high capacity public transport system with good capillarity and high frequencies.

suburban setting

Medium density environment with a good public transport system with radial connections to the city center, but lower capillarity and frequencies. This setting includes suburban cities.

small cities

Small, isolated city with an own public transport system and <100K inhabitants.


Low-density environment, small cities and villages with poor public transport services mainly connecting the villages.

SAE level

The SAE (Society of Automotive Engineers) levels define the level of vehicle autonomy, or in other words, how much human intervention is still needed for an automated vehicle to operate. Currently, five SAE levels have been defined: Level 0: Automated system issues warnings and may momentarily intervene but has no sustained vehicle control. Level 1 (hands on): Driver and automatic system share vehicle control. The driver must be ready to retake full control at any time. Level 2 (hands off): The automated system takes full control of the vehicle (accelerating, braking, and steering). The driver must monitor the driving and be prepared to intervene immediately at any time if the automated system fails to respond properly. Level 3 (eyes off): The automated system takes full control of the vehicle (accelerating, braking, and steering). The driver must monitor the driving and be prepared to intervene immediately at any time if the automated system fails to respond properly. Level 4 (mind off): As level 3, but no driver attention is ever required for safety, e.g. the driver may safely go to sleep or leave the driver's seat. Level 5 (steering wheel optional): No human intervention is required at all. An example would be a robotic taxi.


Vehicle-to-everything (V2X) communication is the passing of information from a vehicle to any entity that may affect the vehicle, and vice versa.