Francesco Biral

Supporting Drivers in Keeping Safe Speed and Safe Distance: The SASPENCE Subproject Within the European Framework Programme 6 Integrating Project PReVENT

This paper describes a novel driver-support system that helps to maintain the correct speed and headway (distance) with respect to lane curvature and other vehicles ahead. The system has been developed as part of the Integrating Project PReVENT under the European Framework Programme 6, which is named SAfe SPEed and safe distaNCE (SASPENCE). The application uses a detailed description of the situation ahead of the vehicle. Many sensors [radar, video camera, Global Positioning System (GPS) and accelerometers, digital maps, and vehicle-to-vehicle wireless local area network (WLAN) connections] are used, and state-of-the-art data fusion provides a model of the environment. The system then computes a feasible maneuver and compares it with the drivers behavior to detect possible mistakes. The warning strategies are based on this comparison. The system “talks” to the driver mainly via a haptic pedal or seat belt and “listens” to the driver mainly via the vehicle acceleration. This kind of operation, i.e., the comparison between what the system thinks is possible and what the driver appears to be doing, and the consequent dialog can be regarded as simple implementations of the rider-horse metaphor (H-metaphor). The system has been tested in several situations (driving simulator, hardware in the loop, and real road tests). Objective and subjective data have been collected, revealing good acceptance and effectiveness, particularly in awakening distracted drivers. The system intervenes only when a problem is actually detected in the headway and/or speed (approaching curves or objects) and has been shown to cause prompt reactions and significant speed correction before getting into really dangerous situations.

A Holistic Approach to the Integration of Safety Applications: The INSAFES Subproject Within the European Framework Programme 6 Integrating Project PReVENT

This paper deals with the integration of multiple advanced driver-assistance systems (ADAS) and in-vehicle information systems (IVIS) in a holistic driver-support system. The paper presents the results of a project named Integrated Safety Systems (INSAFES), which was part of PReVENT: an integrating project carried out under the European Framework Programme 6. Integration in INSAFES is tackled at three different levels in the framework of a “cognitive car” perspective: 1) at the perception level, to represent the world around the vehicle, including object-tracking between sensor fields and the detection of driver intentions; 2) at the decision level, to reproduce humanlike holistic motion plans, which serve as “reference maneuvers” to evaluate the motion alternatives that a driver faces; and 3) at the level of interaction with the driver and vehicle control ( action level), to arbitrate between the requests of functions competing for driver attention. A function that provides simultaneous longitudinal and lateral support has been developed. It gives support for safe speed, safe distance, lane change, and all-around collision avoidance all at the same time. At its core, there is a tool (evasive/reference maneuver) that constantly evaluates two possible alternatives (in lane and evasive/lane change) and compares them with the driver input to detect which one applies, which dictates warnings and driver interactions, and whether there is a better alternative. In addition, a “warning manager” has been developed, acting like a referee who lets the ADAS applications work standalone and then combines the requests of each application, prioritizes them, and manages the interaction with the user. The warning manager can be particularly useful in the case of integration of pre-existing standalone functions, which can be quickly reused. If a holistic ADAS is developed, the warning manager can still be used to combine it with IVIS functions. In fact, depending on the kind of ADAS and IVIS considered, the most suitable approach can be either to combine functions in a unified multifunctional driver-support application or to arbitrate between them through the warning manager.

Combining safety margins and user preferences into a driving criterion for optimal control-based computation of reference maneuvers for an ADAS of the next generation

This paper outlines a methodology for combining users preferred driving style and safety margins into an ADASs module for optimal reference maneuver computation. The module for optimal reference maneuver computation is part of the system decision planning chain, which links scenario interpretation to warning intervention strategies. The module objective is the computation of a reference maneuver and produce a measure of the related risk by solving an optimal control problem. In this case, the optimal control problem consists in finding the control functions that minimize the integral of a given penalty function over a planning distance subject to a set of constraints. The penalty function is the mean to implement the safe maneuver concept, which has to comply with three top-level requirements: safety-margins, user acceptance and mobility. In the present work only the safe-speed functionality is addressed and a new penalty function formulation is proposed in order to include both safety criteria and preferred driving style. In this paper it is shown that each users personal driving style can be characterized through a small set of parameters from the analysis of car longitudinal and lateral accelerations that can be easily used in optimal control formulation.

Artificial Co-Drivers as a Universal Enabling Technology for Future Intelligent Vehicles and Transportation Systems

This position paper introduces the concept of artificial “co-drivers” as an enabling technology for future intelligent transportation systems. In Sections I and II, the design principles of co-drivers are introduced and framed within general human-robot interactions. Several contributing theories and technologies are reviewed, specifically those relating to relevant cognitive architectures, human-like sensory-motor strategies, and the emulation theory of cognition. In Sections III and IV, we present the co-driver developed for the EU project interactIVe as an example instantiation of this notion, demonstrating how it conforms to the given guidelines. We also present substantive experimental results and clarify the limitations and performance of the current implementation. In Sections IV and V, we analyze the impact of the co-driver technology. In particular, we identify a range of application fields, showing how it constitutes a universal enabling technology for both smart vehicles and cooperative systems, and naturally sets out a program for future research.

Intersection Support System for Powered Two-Wheeled Vehicles: Threat Assessment Based on a Receding Horizon Approach

This paper reports a novel intersection support (IS) system for motorcycles developed through the SAFERIDER project (IS). The IS function described is built on a receding horizon approach that is designed for a set of predefined intersection scenarios. In the receding horizon scheme, a nonlinear optimal control problem is repetitively solved in real time, yielding a reference motion plan. The initial value of the longitudinal jerk (control input) of each plan is used as a measure of the correction that the rider has to apply to conform to an optimal-safe maneuver. This technique has the advantage of yielding a homogenous measure of the threat independent of the scenario, and it is directly linked with the control variable that the rider should use to accordingly change the vehicles longitudinal dynamics. Additionally, the receding horizon approach naturally accommodates road geometry and constraint attributes, motorcycle dynamics, rider input, and riding styles. Warning feedback is given to the rider by an appropriate combination of human-machine interface elements, such as the haptic throttle, the vibrating glove, and the visual display. This paper explains the IS concept, discusses the implementation aspects of the proposed receding horizon approach, and presents the results of pilot tests conducted on a top-of-the-range riding simulator.

Experimental Study of Motorcycle Transfer Functions for Evaluating Handling

Summary The transfer functions of a motorcycle, especially that between roll angle and steering torque, qualify input-output characteristics - that is, motion produced as a function of steering torque - and are closely related to ease of use and handling. This paper describes the measurement of the transfer functions of a typical sports motorcycle, resulting from data collected in slalom tests. These functions are then compared to analytical transfer functions derived from known models in the literature. The comparison shows fair to good agreement. Lastly, the formation of steering torque is analysed and the observed transfer functions are interpreted in this framework. It is shown that gyroscopic effects are mostly responsible for the lag between steering torque and roll angle, and that there is a velocity for which the various terms that combine to form steering torque cancel each other out, yielding a ‘maximum gain condition’ for torque to roll transfer function which drivers rated ‘good handling’.

Autonomous pallet localization and picking for industrial forklifts: a robust range and look method

A combined double-sensor architecture, laser and camera, and a new algorithm named RLPF are presented as a solution to the problem of identifying and localizing a pallet, the position and angle of which are a priori known with large uncertainty. Solving this task for autonomous robot forklifts is of great value for logistics industry. The state-of-the-art is described to show how our approach overcomes the limitations of using either laser ranging or vision. An extensive experimental campaign and uncertainty analysis are presented. For the docking task, new dynamic nonlinear path planning which takes into account vehicle dynamics is proposed.

A curvilinear abscissa approach for the lap time optimization of racing vehicles

The optimal control and lap time optimization of vehicles such as racing cars and motorcycle is a challenging problem, in particular the approach adopted in the problem formulation has a great impact on the actual possibility of solving such problem by using numerical techniques. This paper illustrates a methodology which combines some modelling technique which have been found to be numerically efficient. The methodology is based on the 3D curvilinear coordinates technique for the road modelling, the moving frame approach for the derivation of the vehicle equations of motion, the replacement of the time with the position along the track as new independent variable and the formulation and the solution of the minimum lap time problem by means of the indirect approach. The case study of a GT car is presented and simulation examples are given and discussed.

Four wheel optimal autonomous steering for improving safety in emergency collision avoidance manoeuvres

The objective of this work is to demonstrate that autonomous collision avoidance manoeuvres based on optimal control motion planning improve the safety margins and can fully exploit the vehicle dynamics. In particular we analyse the performance of a traditional two-wheel-steering vehicle (2WS) versus a four-wheel-steering vehicle (4WS) in steer-to-avoid manoeuvres. We show how the vehicle manoeuvrability is improved using 4WS that allows to avoid an obstacle quite later with respect to the traditional 2WS vehicle. A control algorithm with novel features is also proposed to autonomously track the optimised manoeuvres, which has been successfully tested on a 4WS electric vehicle.

A new direct deformation sensor for active compensation of positioning errors in large milling machines

The positioning accuracy of large boring and milling machines (with axes travel larger than 5 m) is severely affected by structural deformations. Heat induced deformations, long-period deformation of foundations, and the machining process itself, cause time-dependent structural deformations of the machine body, which are difficult to model and to predict. In order to overcome these difficulties and to enhance the positioning accuracy, a composite sensor has been designed and tested, which allows direct and continuous (up to 250 Hz) measurement of geometrical deformations on machine structural elements. The present paper i) presents the operating principles of the proposed composite sensor, which is based on an array of fiber-optics Bragg gratings (FBG), ii) discusses requisites and performances of the sensor as well as the algorithm used to calculate the deformed shape as a function of the sensor output, iii) illustrates the results of a finite elements virtual model aimed to demonstrate the feasibility and to evaluate the expected performance of the sensor, and iv) validates the model by showing the results obtained by a sensor prototype giving a real-time measurement of the deformed shape of a structural beam