Trends in vehicle motion control for automated driving on public roads

In this paper, we describe how vehicle systems and the vehicle motion control are affected by automated driving on public roads. We describe the redundancy needed for a road vehicle to meet certain safety goals. The concept of system safety as well as system solutions to fault tolerant actuation of steering and braking and the associated fault tolerant power supply is described. Notably restriction of the operational domain in case of reduced capability of the driving automation system is discussed. Further we consider path tracking, state estimation of vehicle motion control required for automated driving as well as an example of a minimum risk manoeuver and redundant steering by means of differential braking. The steering by differential braking could offer heterogeneous or dissimilar redundancy that complements the redundancy of described fault tolerant steering systems for driving automation equipped vehicles. Finally, the important topic of verification of driving automation systems is addressed

Computationally Efficient Nonlinear One-and Two-Track Models for Multitrailer Road Vehicles

This paper presents nonlinear mathematical models of one-and two-track multitrailer vehicles. We derive nonlinear equations of motion in the form of a system of implicit ordinary differential equations (ODEs) by using Lagrangian mechanics. The system of ODEs has the minimum number of states and equations that enables efficient computations yet maintains the most important nonlinear vehicle dynamic behavior and allows actuator coordination and energy consumption evaluation. As examples, we build different models of a 4-unit long combination vehicle, i.e., two-track 11-axle and single-track 6-axle nonlinear models as well as a linear single-track 6-axle model. We compare the performance of these models to experimental data of different driving maneuvers. The nonlinear single-track model demonstrates close dynamic behavior to the experiment, which makes it an efficient alternative to the two-track model. The vehicle equations can be generated automatically by using the code provided in this paper and subsequently used for conducting frequency analysis, evaluating energy consumption, deriving performance measures from simulations, and facilitating optimal control applications that involve combined steering, braking and propulsion control

Transportation Mission-Based Optimization of Heavy Combination Road Vehicles and Distributed Propulsion, Including Predictive Energy and Motion Control

This thesis proposes methodologies to improve heavy vehicle design by reducing the total cost of ownership and by increasing energy efficiency and safety.Environmental issues, consumers expectations and the growing demand for freight transport have created a competitive environment in providing better transportation solutions. In this thesis, it is proposed that freight vehicles can be designed in a more cost- and energy-efficient manner if they are customized for narrow ranges of operational domains and transportation use-cases. For this purpose, optimization-based methods were applied to minimize the total cost of ownership and to deliver customized vehicles with tailored propulsion components that best fit the given transportation missions and operational environment. Optimization-based design of the vehicle components was found to be effective due to the simultaneous consideration of the optimization of the transportation mission infrastructure, including charging stations, loading-unloading, routing and fleet composition and size, especially in case of electrified propulsion. Implementing integrated vehicle hardware-transportation optimization could reduce the total cost of ownership by up to 35% in the case of battery electric heavy vehicles. Furthermore, in this thesis, the impacts of two future technological advancements, i.e., heavy vehicle electrification and automation, on road freight transport were discussed. It was shown that automation helps the adoption of battery electric heavy vehicles in freight transport. Moreover, the optimizations and simulations produced a large quantity of data that can help users to select the best vehicle in terms of the size, propulsion system, and driving system for a given transportation assignment. The results of the optimizations revealed that battery electric and hybrid heavy combination vehicles exhibit the lowest total cost of ownership in certain transportation scenarios. In these vehicles, propulsion can be distributed over different axles of different units, thus the front units may be pushed by the rear units. Therefore, online optimal energy management strategies were proposed in this thesis to optimally control the vehicle motion and propulsion in terms of the minimum energy usage and lateral stability. These involved detailed multitrailer vehicle modeling and the design and solution of nonlinear optimal control problems

Improve Safety by Optimal Steering Control of a Converter Dolly using Particle Swarm Optimization for Low-Speed Maneuvers

This paper offers a solution to the problem of poor path-following performance of high capacity transport (HCT) vehicles, such as A-double combinations, causing safety issue for the vulnerable road users during low-speed turning maneuvers. An advanced control strategy is developed which only demands the axles of the converter dolly of such vehicle to be actively steerable so that existing tractor and semitrailers can be used without any further modification. The control strategy described in this paper allows the change of forward speed and even to stop the vehicle completely during the turning maneuver without any performance degradation. The controller utilizes the delays of tractor front axle steering angle and the articulation angles measured not in traditional time but in path-distance domain. The optimal controller is achieved using particle swarm optimization (PSO) technique. Finally the optimal vehicle performance is compared with a baseline non-steerable converter dolly case and also with a proportional control case. Significant improvement in path-following performance is observed

The Second Conference on Lunar Bases and Space Activities of the 21st Century, volume 1

These papers comprise a peer-review selection of presentations by authors from NASA, LPI industry, and academia at the Second Conference (April 1988) on Lunar Bases and Space Activities of the 21st Century, sponsored by the NASA Office of Exploration and the Lunar Planetary Institute. These papers go into more technical depth than did those published from the first NASA-sponsored symposium on the topic, held in 1984. Session topics covered by this volume include (1) design and operation of transportation systems to, in orbit around, and on the Moon, (2) lunar base site selection, (3) design, architecture, construction, and operation of lunar bases and human habitats, and (4) lunar-based scientific research and experimentation in astronomy, exobiology, and lunar geology

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications