Autonomous Bicycles Research Articles

Can autonomy make bicycle-sharing systems more sustainable? An environmental impact analysis

Autonomous bicycles have recently been proposed as a new and more efficient approach to bicycle-sharing systems (BSS), but their environmental impacts remain unresearched. Conducting environmental impact assessments at an early technological stage is critical to influencing the design and, ultimately, environmental impacts of a system. Consequently, this paper aims to assess the environmental impact of autonomous shared bikes compared with current station-based and dockless systems under different sets of modeling hypotheses and mode-shift scenarios. The results indicate that autonomy could reduce the environmental impact per passenger kilometer traveled of current station-based and dockless BSS by 33.1 % and 58.0 %. The sensitivity analysis shows that the environmental impact of autonomous shared bicycles will mainly depend on vehicle usage rates and the need for infrastructure. Finally, this study highlights the importance of targeting the mode replacement from more polluting modes, especially as traditional mobility modes decarbonize and become more efficient.

On the performance of shared autonomous bicycles: A simulation study

As society faces global challenges such as population growth and climate change, rethinking cities is now more imperative than ever. The design of cities can not be abstracted from the design of their mobility systems. Therefore, efficient solutions must be found to transport people and goods throughout the city efficiently and ecologically. An autonomous bicycle-sharing system would combine the most relevant benefits of vehicle-sharing, autonomy, and micro-mobility, increasing the efficiency and convenience of bicycle-sharing systems and incentivizing more people to bike and enjoy their cities in an environmentally friendly way. Due to the novelty of introducing autonomous driving technology into bicycle-sharing systems and their inherent complexity, there is a need to quantify the potential impact of autonomy on fleet performance and user experience. This paper presents the results of an agent-based simulation that provides an in-depth understanding of the fleet behavior of autonomous bicycle-sharing systems in realistic scenarios, including a rebalancing system based on demand prediction. In addition, this work describes the impact of different parameters on system efficiency and service quality. Finally, it quantifies the extent to which an autonomous system would outperform current station-based and dockless bicycle-sharing schemes. The obtained results show that with a fleet size three and a half times smaller than a station-based system and eight times smaller than a dockless system, an autonomous system can improve overall performance and user experience even with no rebalancing.

Asymptotic Trajectory Tracking of Autonomous Bicycles via Backstepping and Optimal Control

This letter studies the trajectory tracking problem for an autonomous bicycle that is a non-minimum phase, strongly nonlinear system. As compared with most existing methods dealing only with approximate trajectory tracking, this letter proposes a constructive design to achieve asymptotic trajectory tracking. More specifically, under the assumption that the desired trajectory is generated by a virtual bicycle, a novel asymptotic trajectory tracking controller design scheme is presented. Firstly, the nonlinear dynamics of the autonomous bicycle is established. Secondly, it is decomposed into two interconnected subsystems: a tracking subsystem and a balancing subsystem. For the tracking subsystem, the popular backstepping approach is applied to determine the propulsive force of the bicycle. For the balancing subsystem, optimal control is applied to determine the steering angular velocity of the handlebar in order to balance the bicycle and align the bicycle with the desired yaw angle. Thirdly, to tackle the strong coupling between the tracking and the balancing systems, the small-gain technique is applied for the first time to prove the asymptotic stability of the closed-loop bicycle system. Finally, the efficacy of the proposed exact trajectory tracking control methodology is validated by numerical simulations.

Simultaneous localization and mapping for autonomous bicycles

Bicycles and similar two-wheeled vehicles are a scientifically interesting category of means of transportation, whose simultaneous localization and mapping problem, in contrast to other ground vehi...

미소운동 변환을 이용한 자율주행 자전거의 기구학 모델

This paper presents a new method of kinematic modeling for autonomous bicycle by using the differential motion transformation. Kinematic model is indispensable to trajectory planning and control for an autonomous mobile robot. The conventional methods of kinematic modeling for an autonomous bicycle depend on intuition by geometry. On the contrary, the proposed method in this paper is based on the systematic differential motion transformation, thus applicable to various types of autonomous bicycles. The differential motion transformation gives Jacobian between two coordinate frames and the velocity kinematics as a result.