Alessandra Fascioli

Vision-based intelligent vehicles: State of the art and perspectives

Abstract Recently, a large emphasis has been devoted to Automatic Vehicle Guidance since the automation of driving tasks carries a large number of benefits, such as the optimization of the use of transport infrastructures, the improvement of mobility, the minimization of risks, travel time, and energy consumption. This paper surveys the most common approaches to the challenging task of Autonomous Road Following reviewing the most promising experimental solutions and prototypes developed worldwide using AI techniques to perceive the environmental situation by means of artificial vision. The most interesting results and trends in this field as well as the perspectives on the evolution of intelligent vehicles in the next decades are also sketched out.

Artificial vision in road vehicles

The last few decades have witnessed the birth and growth of a new sensibility to transportation efficiency. In particular the need for efficient and improved people and goods mobility has pushed researchers to address the problem of intelligent transportation systems. This paper surveys the most advanced approaches to (partial) customization of the road following task, using on-board systems based on artificial vision. The functionalities of lane detection, obstacle detection and pedestrian detection are described and classified, and their possible application in future road vehicles is discussed.

Shape-based pedestrian detection

This paper presents the method for detecting pedestrian recently implemented on the ARGO vehicle. The perception of the environment is performed through the sole processing of images acquired from a vision system installed on board of the vehicle: the analysis of a monocular image delivers a first coarse detection, while a distance refinement is performed using the stereo vision technique.

Stereo vision-based vehicle detection

This paper presents the methods for sensing vehicles (localization and tracking) implemented on the ARGO vehicle. The perception of the environment is performed through the sole processing of images acquired from a stereo vision system installed on board of the vehicle.

Stereo inverse perspective mapping: theory and applications

This paper discusses an extension to the inverse perspective mapping geometrical transform to the processing of stereo images and presents the calibration method used on the ARGO autonomous vehicle. The article features also an example of application in the automotive field in which the stereo inverse perspective mapping helps to speed up the process.

Pedestrian detection for driver assistance using multiresolution infrared vision

This paper describes a system for pedestrian detection in infrared images, which has been implemented on an experimental vehicle equipped with an infrared camera. The proposed system has been tested in many situations and has proven to be efficient and with a very low false-positive rate. It is based on a multiresolution localization of warm symmetrical objects with specific size and aspect ratio; anyway, because road infrastructures and other road participants may also have such characteristics, a set of matched filters is included in order to reduce false detections. A final validation process, based on human shapes morphological characteristics, is used to build the list of pedestrian appearing in the scene. Neither temporal correlation nor motion cues are used in this first part of the project: the processing is based on the analysis of single frames only.

Visual perception of obstacles and vehicles for platooning

Presents the methods for sensing obstacles and vehicles implemented on the University of Parma experimental vehicle (ARGO). The ARGO project is briefly described along with its main objectives; the prototype vehicle and its functionalities are presented. The perception of the environment is performed through the processing of images acquired from the vehicle. Details about the stereo vision-based detection of generic obstacles are given, along with a measurement of the performance of the method; then a new approach for leading vehicles detection is described, relying on symmetry detection in monocular images. The paper concludes with a description of the current implementation of the control system, based on a gain scheduled controller, which allows the vehicle to follow the road or other vehicles.

Shape-based pedestrian detection and localization

This work presents a vision-based system for detecting and localizing pedestrians in road environments by means of a statistical technique. Initially, attentive vision techniques relying on the search for specific characteristics of pedestrians such as vertical symmetry and strong presence of edges, allow to select interesting regions likely to contain pedestrians. These regions are then used to estimate the localization of pedestrians using a Kalman filter estimator.

Pedestrian localization and tracking system with Kalman filtering

This work presents an implementation of a vision-based system for recognizing pedestrians in different environments and precisely localizing them with the use of a Kalman filter estimator configured as a tracker. Pedestrians, in various poses and with different kinds of clothing, are first recognized by the vision subsystem through the use of algorithms based on edge density and symmetry maps. The information produced in this way is then passed on to the tracker module which reconstructs an interpretation of the pedestrians positions in the scene. An appropriately configured indoor system setup with an accurate measurement of the imposed human trajectory has been realized. This setup has permitted an accurate evaluation of the accuracy of the results, when the new auxiliary tracker is activated.

Quintic G/sup 2/-splines for the iterative steering of vision-based autonomous vehicles

This paper presents a new motion planning primitive to be used for the iterative steering of vision-based autonomous vehicles. This primitive is a parameterized quintic spline, denoted as /spl eta/-spline, that allows interpolating an arbitrary sequence of points with overall second-order geometric (G/sup 2/-) continuity. Issues such as completeness, minimality, regularity, symmetry, and flexibility of these G/sup 2/-splines are addressed in the exposition. The development of the new primitive is tightly connected to the inversion control of nonholonomic car-like vehicles. The paper also exposes a supervisory strategy for iterative steering that integrates feedback vision data processing with the feedforward inversion control.