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Autonomous Ride-Pooling: Transforming Urban Mobility

Author: Teemu Sihvola

Cities worldwide are on the brink of a transportation revolution with autonomous transport. With the latest in self-driving technology and shared rides, autonomous ride-pooling has the potential to transform urban mobility. However, if public transport authorities do not prepare for the swift launch of shared autonomous services, private service providers may introduce robotaxi services, potentially jeopardizing the comprehensive benefits that autonomous transport can bring. Modern transport modelling plays a crucial role in understanding the actual impacts of autonomous mobility services on quality of service, pricing, and ultimately on congestion, emissions, and operational costs.

(Picture: MOIA)

Autonomous Ride-Pooling: Transforming Urban Mobility 

Several companies are testing large-scale robotaxi and robobus services. One could say that these services are transitioning from testing to fully operational, commercial deployment with paid customers. Technical maturity of autonomous transportation has reached a level that enables the launch of large-scale autonomous ride-pooling services in the coming years, as demonstrated by MOIA’s tests in Germany. 

Autonomous driving could dramatically shift the balance between private cars and mobility services. As I predicted a decade ago on the Slush stage, with autonomous driving, households should have no incentives to own private cars anymore. Although visionaries like Elon Musk suggest that households will still purchase their own autonomous cars and rent them out when not in use, I argue that the “Airbnb model” will not work for autonomous cars because service operators can manage fleets far more efficiently. The dynamics of the transportation sector differ significantly from the hospitality industry, with critical aspects including regulatory and safety compliance and liabilities. The operating costs of private cars are likely to remain roughly unchanged with automation, but the operating costs of transport services will be reduced by roughly half, making transport services even more attractive compared to private cars [1]. 

Impact on Urban Mobility 

Autonomous ride-pooling holds the promise to significantly alter the landscape of urban transportation. Here are some key impacts it can deliver: 

1. Reduction in Traffic Congestion: By optimizing routes and maximizing vehicle occupancy, autonomous ride-pooling services can reduce the number of vehicles on the road, thereby alleviating traffic congestion. Additionally, autonomous vehicles can operate efficiently in various traffic conditions, further enhancing traffic flow. 
2. Environmental Benefits: The reduction in vehicle numbers means lower emissions and improved air quality in urban areas. 
3. Enhanced Road Safety: Autonomous vehicles are designed to follow traffic rules and regulations meticulously, potentially reducing the incidence of road accidents caused by human error. This can lead to safer roads and fewer traffic-related injuries and fatalities. 
4. Optimized Land Use: With reduced need for private vehicle ownership, cities could see a decrease in demand for parking spaces and car storage facilities. This opens opportunities for repurposing urban land for green spaces, pedestrian zones, and community amenities. 
5. Elimination of Private Vehicle Ownership Incentives: With the advent of autonomous driving, there will be little incentive for individuals to own private vehicles. This will enable economies of scale in mobility services, making them economically viable. 
6. Improved Accessibility and Mobility: Autonomous ride-pooling services can offer a flexible and reliable transportation option for people with limited access to traditional public transport, including those living in suburban or rural areas. This inclusivity is particularly important for providing mobility solutions to the elderly and individuals with disabilities. 
7. Integration with Public Transport: Autonomous ride-pooling can serve as a feeder service to high-capacity public transport systems, such as metro and tram networks, enhancing their accessibility and efficiency. This integration can lead to a more seamless and user-friendly urban transport network. 

The Role of Transport Modelling 

To accurately assess and maximize the impacts of autonomous ride-pooling and the broader transition to service-based mobility, advanced transport modelling is essential. Activity- and agent-based transport models (AABMs) play a critical role in this analysis, offering detailed insights into travel behavior and system performance under various scenarios [2]. 

Activity-based models, like our BRUTUS by Ramboll, focus on the daily activities of individuals and the travel choices they make to perform these activities. By incorporating AVs and ride-pooling into these models, planners can predict changes in travel demand, mode choice, and route preferences, ultimately assessing impacts at the transport system level. 

Agent-based models simulate the actions and interactions of individual agents (e.g., passengers, vehicles) within the transport system and provide a flexible framework for modelling the operational aspects of autonomous ride-pooling, understanding its impacts on traffic patterns, vehicle usage, and service levels. 

Using these modelling approaches allows for a comprehensive evaluation of autonomous ride-pooling services, ensuring that they are designed and implemented to optimize benefits and mitigate potential drawbacks. 

The Imperative for Public Transport Authorities 

The Helsinki Region of Transport (HSL) has already demonstrated a vision for large-scale ride-pooling services and their integration into the public transport system through the pioneering urban ride-pooling service Kutsuplus, operated between 2012 and 2015. Autonomous transport significantly reduces transport operating costs, enabling large-scale autonomous ride-pooling services without subsidies and achieving economies of scale. This will finally make the vision behind Kutsuplus reachable. 

Public transport authorities now face the critical task of defining a vision and roadmap for the deployment of autonomous transport. Autonomous transport not only facilitates ride-pooling but also enables the automation of fixed-route and scheduled public transport. This innovation presents an opportunity, and perhaps a necessity, to re-optimize the entire public transport system. 

If public transport authorities do not prepare for the launch of shared autonomous services like ride-pooling as quickly as possible, there is a risk that private service providers will introduce robotaxi services, potentially jeopardizing the benefits that autonomous transport can bring [3]. 

Selected References 

1. Bösch, Becker, Becker & Axhausen (2018). Cost-based analysis of autonomous mobility services, Transport Policy, Volume 64, 2018, Pages 76-91, ISSN 0967-070X 
2. Zwick, Wilkes, Engelhardt, Axer, Dandl, Rewald, Kostorz, Fraedrich, Kagerbauer, Axhausen (2022) Mode Choice and Ride-Pooling Simulation: A Comparison of mobiTopp, Fleetpy, and MATSim. Procedia Computer Science, Vol. 201, 2022, pp. 608–613. https://doi.org/10.1016/j.procs.2022.03.07 
3. Nunes & Hernandez. (2020). Autonomous taxis & public health: High cost or high opportunity cost?. Transportation Research Part A: Policy and Practice, 138, 28-36.