Hans Andersen

Autonomous golf cars for public trial of mobility-on-demand service

We detail the design of autonomous golf cars which were used in public trials in Singapores Chinese and Japanese Gardens, for the purpose of raising public awareness and gaining user acceptance of autonomous vehicles. The golf cars were designed to be robust, reliable, and safe, while operating under prolonged durations. Considerations that went in to the overall system design included the fact that any member of the public had to not only be able to easily use the system, but to also not have the option to use the system in an unintended manner. This paper details the hardware and software components of the golf cars with these considerations, and also how the booking system and mission planner facilitated users to book for a golf car from any of ten stations within the gardens. We show that the vehicles performed robustly throughout the prolonged operations with a small localization variance, and that users were very receptive from the user survey results.

Numerical Approach to Reachability-Guided Sampling-Based Motion Planning Under Differential Constraints

This paper presents a new method for motion planning under differential constraints by incorporating a numerically solved discretized representation of reachable state space for faster state sampling and nearest neighbor searching. The reachable state space is solved for offline and stored into a “reachable map” which can be efficiently applied in online planning. State sampling is performed only over states encompassed by the reachable map to reduce the number of unsuccessful motion validity checking queries. The nearest neighbor distance function is revised such that only reachable states are considered, with states which are unreachable or only reachable beyond a designated time horizon disregarded. This method is generalized for application to any control system, and thus can be used for vehicle models where analytical solutions cannot be found. Greater improvement is expected for more constrained systems where motion checking cost is relatively high. Simulation results are discussed for case studies on a holonomic model and a Dubins car model, both with maximum speed limitation and time included as a dimension in the configuration space, where planning speed (measured by tree growth rate) can be improved through reachability guidance in each system by at least a factor of 3 and 9, respectively.

A parallel autonomy research platform

We present the development of a full-scale “parallel autonomy” research platform including software and hardware. In the parallel autonomy paradigm, the control of the vehicle is shared; the human is still in control of the vehicle, but the autonomy system is always running in the background to prevent accidents. Our holistic approach includes: (1) a drive-by-wire conversion method only based on reverse engineering mounting of relatively inexpensive sensors onto the vehicle implementation of a localization and mapping system, (4) obstacle detection and (5) a shared controller as well as (6) integration with an advanced autonomy simulation system (Drake) for rapid development and testing. The system can operate in three modes: (a) manual driving, (b) full autonomy, where the system is in complete control of the vehicle and (c) parallel autonomy, where the shared controller is implemented. We present results from extensive testing of a full-scale vehicle on closed tracks that demonstrate these capabilities.

Modelling and control of a 2-link mobile manipulator with virtual prototyping

Mobile manipulators are nowadays popular in various fields, including military missions, civil defense, rescue, and social services. Along with the wide use of such robots, the associated control problems require more and more attention to the nonlinearity and uncertainties of the dynamic models. In this paper, targeting the challenges of trajectory control for applications in which the robots have to overcome complex terrain conditions, we present a rapid virtual prototyping using Matlab-Simulink with embedded design and implementation of two control strategies - feedforward nonlinear control and adaptive control for controlling the end-effector of a two-link robot arm with/without well-known models. Simulation results show the efficacy of the feedforward nonlinear controller and adaptive controller developed. Comparisons of the performances are made to provide an analytical evaluation as well as a general reference for selecting controllers in different cases.

Pedestrian Notification Methods in Autonomous Vehicles for Multi-Class Mobility-on-Demand Service

In this paper, we describe methods of conveying perception information and motion intention from self driving vehicles to the surrounding environment. One method is by equipping autonomous vehicles with Light-Emitting Diode (LED) strips to convey perception information; typical pedestrian-driver acknowledgement is replaced by visual feedback via lights which change color to signal the presence of obstacles in the surrounding environment. Another method is by broadcasting audio cues of the vehicles motion intention to the environment. The performance of the autonomous vehicles as social robots is improved by building trust and engagement with interacting pedestrians. The software and hardware systems are detailed, and a video demonstrates the working system in real application. Further extension of the work for multi-class mobility in human environments is discussed.

Autonomous personal mobility scooter for multi-class mobility-on-demand service

In this paper, we describe the design and development of an autonomous personal mobility scooter that was used in public trials during the 2016 MIT Open House, for the purpose of raising public awareness and interest about autonomous vehicles. The scooter is intended to work cooperatively with other classes of autonomous vehicles such as road cars and golf cars to improve the efficacy of mobility-on-demand transportation solutions. The scooter is designed to be robust, reliable, and safe, while operating under prolonged durations. The flexibility in fleet expansion is shown by replicating the system architecture and sensor package that has been previously implemented in a road car and golf cars. We show that the vehicle performed robustly with small localization variance. A survey of the users shows that the public is very receptive to the concept of the autonomous personal mobility device.

Multi-class autonomous vehicles for mobility-on-demand service

Mobility-on-Demand (MoD) services can be enhanced through use of Autonomous Vehicles (AVs) to reduce manpower costs (among other benefits), and use of multiple classes of vehicles to expand service coverage and accessibility. This work presents a functional proof of concept MoD system accessible via mobile phone to utilize three classes of vehicles in combination: a road car, buggy, and mobility scooter. A common software architecture and primary sensor suite allows for flexible replication to additional vehicles regardless of vehicle model or even class type. Benefits of using these three classes in a combined service are discussed, and details are provided concerning the unique aspects of the conversion and systems integration for each vehicle. Various safety features are implemented to ensure safe user interaction with all AVs. The complete MoD system is tested in uncontrolled pedestrian environments as well as on road with real vehicular traffic.

Self-driving vehicle acknowledgement of pedestrian presence conveyed via Light-Emitting Diodes

This paper describes a method of conveying perception information from a self-driving golfcart to nearby pedestrians via a Light-Emitting Diode (LED) strip. By equipping autonomous vehicles (AVs) with this feature, their performance as social robots is improved by building trust and engagement with interacting pedestrians; typical pedestrian-driver acknowledgement is replaced by visual feedback via lights which light blue for no nearby obstacle presence, and red for nearby obstacles. Various schemes for mapping detected obstacles to the LED display are discussed, the software and hardware systems are detailed, and a video demonstrates the working system in real application.

Geometric path tracking algorithm for autonomous driving in pedestrian environment

This paper proposes an alternative formulation to the pure pursuit path tracking algorithm for autonomous driving. The current approach has tendencies to cut corners, and therefore results in poor path tracking accuracy. The proposed method considers not only the relative position of the pursued point, but also the orientation of the path at that point. A steering control law is designed in accordance with the kinematic equations of motion of the vehicle. The effectiveness of the algorithm is then tested by implementing it on an autonomous golf cart, driving in a pedestrian environment. The experimental result shows that the new algorithm reduces the root mean square (RMS) cross track error for the same given pre-programmed path by up to 46 percent, while having virtually no extra computational cost, and still maintaining the chatter free property of the original pure pursuit controller.

Realizing Robust Control of Autonomous Vehicles

We present our work on autonomous vehicles in an urban environment to provide mobility-on-demand as a solution to the first and last mile problem. The software architecture for our vehicles is reviewed with focus on new developments of speed and steering control algorithms to ensure robust performance for autonomous driving. For speed control, a brake/throttle switching controller based on velocity error and desired acceleration is implemented to achieve fast speed response without excessive switching. An iterative learning algorithm is used to train feedforward signals which are then used to compensate the repeated disturbances over a fixed route. For steering control, a revised pure pursuit steering control algorithm is designed to improve path tracking performance. The methods are validated though on-road experiments which demonstrate a speed control that is robust against changing road grade and a steering control that has smaller cross-track errors.