Autonomous micro-mobility simulation study

What will be the impact of shared autonomous micro-mobility systems? Will autonomy make the micro-mobility systems even more attractive? 

This work explores this and many other questions in an ad-hoc agent-based simulation that explores the fleet behavior of shared autonomous bicycles.

Micro-mobility systems like shared bikes and scooters are transforming the urban mobility landscape in cities worldwide. With the advances of the approaching technological revolution of autonomous driving technologies, these ultra-lightweight systems can become even more attractive, helping to remove cars from our cities.

An autonomous bicycle-sharing system would bring together the most relevant benefits of vehicle sharing, electrification, autonomy, and micro-mobility. Furthermore, by bringing the convenience of mobility-on-demand systems into bike-share, it would incentivize more people to bike and enjoy their cities in an environmentally friendly way.  This simulation quantifies such benefits and defines the extent to which an autonomous system could outperform current bicycle-sharing systems.

The obtained results show that with a fleet size 3.5 times smaller than a station-based system and 8 times smaller than a dockless system, an autonomous system can improve overall performance and user experience with no rebalancing. These findings indicate that the remarkable efficiency of an autonomous bicycle-sharing system could compensate for the additional cost of autonomous bicycles.

In addition, this simulation investigates the impact of different operational strategies, including no rebalancing, ideal rebalancing, and a demand-prediction-based rebalancing model. Finally, we have analyzed the different parameters' impact, such as the autonomous bicycle's speed or the battery's autonomy, on system efficiency and user experience.

This study provides valuable insights for many stakeholders: It provides fleet operators with guidelines for designing, implementing, and operating an autonomous bicycle-sharing system. It also provides insights that can assist engineers in defining the vehicle's design requirements. In addition, it can help city planners and governments understand the potential urban impacts of an autonomous bike-sharing system and determine the regulations and incentive mechanisms related to these new mobility modes.