Smartphone-based vehicle telematics: a ten-year anniversary

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordJust as it has irrevocably reshaped social life, the fast growth of smartphone ownership is now beginning to revolutionize the driving experience and change how we think about automotive insurance, vehicle safety systems, and traffic research. This paper summarizes the first ten years of research in smartphone-based vehicle telematics, with a focus on user-friendly implementations and the challenges that arise due to the mobility of the smartphone. Notable academic and industrial projects are reviewed, and system aspects related to sensors, energy consumption, and human-machine interfaces are examined. Moreover, we highlight the differences between traditional and smartphone-based automotive navigation, and survey the state of the art in smartphone-based transportation mode classification, vehicular ad hoc networks, cloud computing, driver classification, and road condition monitoring. Future advances are expected to be driven by improvements in sensor technology, evidence of the societal benefits of current implementations, and the establishment of industry standards for sensor fusion and driver assessment

Dynamic Human Body Models in Vehicle Safety: An Overview

Significant trends in the vehicle industry are autonomous driving, micromobility, electrification and the increased use of shared mobility solutions. These new vehicle automation and mobility classes lead to a larger number of occupant positions, interiors and load directions. As safety systems interact with and protect occupants, it is essential to place the human, with its variability and vulnerability, at the center of the design and operation of these systems. Digital human body models (HBMs) can help meet these requirements and are therefore increasingly being integrated into the development of new vehicle models. This contribution provides an overview of current HBMs and their applications in vehicle safety in different driving modes. The authors briefly introduce the underlying mathematical methods and present a selection of HBMs to the reader. An overview table with guideline values for simulation times, common applications and available variants of the models is provided. To provide insight into the broad application of HBMs, the authors present three case studies in the field of vehicle safety: (i) in-crash finite element simulations and injuries of riders on a motorcycle; (ii) scenario-based assessment of the active pre-crash behavior of occupants with the Madymo multibody HBM; (iii) prediction of human behavior in a take-over scenario using the EMMA model

Aerospace Medicine and Biology. A continuing bibliography with indexes

This bibliography lists 244 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1981. Aerospace medicine and aerobiology topics are included. Listings for physiological factors, astronaut performance, control theory, artificial intelligence, and cybernetics are included

Improving driver comfort in commercial vehicles : modeling and control of a low-power active cabin suspension system

Comfort enhancement of commercial vehicles has been an engineering topic ever since the first trucks emerged around 1900. Since then, significant improvements have been made by implementing cabin (secondary) and seat suspensions. Moreover, the invention of the air spring and its application to the various vehicle's suspension systems also greatly enhanced driver comfort. However, despite these improvements many truck drivers have health related Problems, which are expected to be caused by their exposure to the environmental vibrations over longer periods of time. The most recent suspension improvements in commercial vehicles date back more than a decade and the possibilities for further improvements using passive devices (springs and dampers) seem nearly exhausted. Consequently, in line with developments in passenger cars, truck manufacturers are now investigating semi-active and active suspension systems. Herein, active suspensions are expected to give the best performance, but also come at the highest cost. Especially the high power consumption of market-ready devices is problematic in a branch where all costs need to be minimized. In this dissertation the field of secondary suspension design and controllable suspensions for heavy vehicles is addressed. More specifically, the possibilities for a low power active cabin suspension design are investigated. The open literature on this topic is very limited in comparison to that of passenger cars. However, as heavy vehicle systems are dynamically more challenging, with many vibration modes below 20 Hz, there is great research potential. The dynamic complexity becomes clear when considering the developed 44 degrees of freedom (DOF) tractor semi-trailer simulation model. This model is a vital tool for suspension analysis and evaluation of various control strategies. Moreover, as it is modular it can also be easily adapted for other related research. The main vehicle components all have their own modules. So, for example, when evaluating a new cabin suspension design, only the cabin module needs to be replaced. The model has been validated using extensive tests on a real tractor semi-trailer test-rig. The control strategy is a key aspect of any active suspension system. However, the 44 DOF tractor semi-trailer model is too complex for controller design. Therefore, reduced order models are required which describe the main dynamic properties. A quarter truck heave-, half truck roll-, and half truck pitch-heave model are developed and validated using a frequency-domain validation technique and the test-rig measurements. The technique is based on a recently developed frequency domain validation method for robust control and adapted for non-synchronous inputs, with noise on the input and output measurements. The models are shown to give a fair representation of the complex truck dynamics. Furthermore, the proposed validation method may be a valuable tool to obtain high quality vehicle models. As a first step, in search of a low power active cabin suspension system, various suspension concepts are evaluated under idealized conditions. From this evaluation, it follows that the variable geometry active suspension has great potential. However, the only known physical realization - the Delft Active Suspension - suffers from packaging issues, nonlinear stiffness characteristics, fail-safe issues and high production cost. Recently, a redesign - the electromechanical Low-Power Active Suspension (eLPAS) - was presented, which is expected to overcome most of these issues. This design is modeled, analyzed and a controller is designed, which can be used to manipulate the suspension force. Feasibility of the design is demonstrated using tests on a hardware prototype. Finally, the validated reduced order models are used to design suitable roll and pitch-heave control strategies. These are evaluated using a combination of the 44 DOF tractor semi-trailer and eLPAS models. Four eLPAS devices are placed at the lower corners of the cabin and modal input-output decoupling is applied for the controller implementation. It is shown, that driver comfort and cabin attitude behavior (roll, pitch and heave when braking, accelerating or steering) can be greatly improved without consuming excessive amounts of energy. So, overall these results enforce the notion that the variable geometry active suspension can be effectively used as low power active cabin suspension. However, there are still some open questions that need to be addressed before this design can be implemented in the next generation commercial vehicles. Durability and failsafe behavior of the eLPAS system, as well as controller robustness to variations in the vehicle parameters and environmental conditions, are some of the topics that require further study

Occupant–vehicle dynamics and the role of the internal model

With the increasing need to reduce time and cost of vehicle development there is increasing advantage in simulating mathematically the dynamic interaction of a vehicle and its occu- pant. The larger design space arising from the introduction of automated vehicles further increases the potential advantage. The aim of the paper is to outline the role of the internal model hypothesis in understanding and modelling occupant-vehicle dynamics, specifically the dynamics associated with direction and speed control of the vehicle. The internal model is the driver’s or passenger’s understanding of the vehicle dynamics and is thought to be employed in the perception, cognition and action processes of the brain. The internal model aids the estimation of the states of the vehicle from noisy sensory measurements. It can also be used to optimise cognitive control action by predicting the consequence of the action; thus model predictive control theory (MPC) provides a foundation for modelling the cognition process. The stretch reflex of the neuromuscular system also makes use of the prediction of the internal model. Extensions to the MPC approach are described which account for: interaction with an automated vehicle; robust control; intermittent control; and cognitive workload. Further work to extend understanding of occupant-vehicle dynamic interaction is outlined. This paper is based on a keynote presentation given by the author to the 13th International Symposium on Advanced Vehicle Control (AVEC) conference held in Munich, September 2016