Carlos Iglesias Fernández

Road curb and lanes detection for autonomous driving on urban scenarios

This paper addresses a framework for road curb and lanes detection in the context of urban autonomous driving, with particular emphasis on unmarked roads. Based on a 3D point cloud, the 3D parameters of several curb models are computed using curvature features and Conditional Random Fields (CRF). Information regarding obstacles is also computed based on the 3D point cloud, including vehicles and urban elements such as lampposts, fences, walls, etc. In addition, a gray-scale image provides the input for computing lane markings whenever they are present and visible in the scene. A high level decision-making system yields accurate information regarding the number and location of drivable lanes, based on curbs, lane markings, and obstacles. Our algorithm can deal with curbs of different curvature and heights, from as low as 3 cm, in a range up to 20 m. The system has been successfully tested on images from the KITTI data-set in real traffic conditions, containing different number of lanes, marked and unmarked roads, as well as curbs of quite different height. Although preliminary results are promising, further research is needed in order to deal with intersection scenes where no curbs are present and lane markings are absent or misleading.

Autonomous Navigation and Obstacle Avoidance of a Micro-bus

At present, the topic of automated vehicles is one of the most promising research areas in the field of Intelligent Transportation Systems (ITS). The use of automated vehicles for public transportation also contributes to reductions in congestion levels and to improvements in traffic flow. Moreover, electrical public autonomous vehicles are environmentally friendly, provide better air quality and contribute to energy conservation. The driverless public transportation systems, which are at present operating in some airports and train stations, are restricted to dedicated roads and exhibit serious trouble dynamically avoiding obstacles in the trajectory. In this paper, an electric autonomous mini-bus is presented. All datasets used in this article were collected during the experiments carried out in the demonstration event of the 2012 IEEE Intelligent Vehicles Symposium that took place in Alcalá de Henares (Spain). The demonstration consisted of a route 725 metres long containing a list of latitude-longitude points (waypoints). The mini-bus was capable of driving autonomously from one waypoint to another using a GPS sensor. Furthermore, the vehicle is provided with a multi-beam Laser Imaging Detection and Ranging (LIDAR) sensor for surrounding reconstruction and obstacle detection. When an obstacle is detected in the planned path, the planned route is modified in order to avoid the obstacle and continue its way to the end of the mission. On the demonstration day, a total of 196 attendees had the opportunity to get a ride on the vehicles. A total of 28 laps were successfully completed in full autonomous mode in a private circuit located in the National Institute for Aerospace Research (INTA), Spain. In other words, the system completed 20.3 km of driverless navigation and obstacle avoidance.

Curvature-based curb detection method in urban environments using stereo and laser

This paper addresses the problem of curb detection for ADAS or autonomous navigation in urban scenarios. The algorithm is based on clouds of 3D points. It is evaluated using 3D information from a pair of stereo cameras and a LIDAR. Curbs are detected based on road surface curvature. The curvature estimation requires a dense point cloud, therefore the density of the LIDAR cloud has been augmented using Iterative Closest Point (ICP) based on the previous scans. The proposed algorithm can deal with curbs of different curvature and heights, from as low as 3 cm, in a range up to 20 m (whenever that curbs are connected in the curvature image). The curb parameters are modeled using straight lines and compared to the ground-truth using the lateral error as the key parameter indicator. The ground-truth sequences were manually labeled on urban images from the KITTI dataset and made publicly available for the scientific community.

Stereo-based pedestrian detection in crosswalks for pedestrian behavioural modelling assessment

In this paper, a stereo- and infrastructure-based pedestrian detection system is presented to deal with infrastructure-based pedestrian safety measurements as well as to assess pedestrian behaviour modelling methods. Pedestrian detection is performed by region growing over temporal 3D density maps, which are obtained by means of stereo reconstruction and background modelling. 3D tracking allows to correlate the pedestrian position with the different pedestrian crossing regions (waiting and crossing areas). As an example of an infrastructure safety system, a blinking luminous traffic sign is switched on to warn the drivers about the presence of pedestrians in the waiting and the crossing regions. The detection system provides accurate results even for nighttime conditions: an overall detection rate of 97.43% with one false alarm per each 10 minutes. In addition, the proposed approach is validated for being used in pedestrian behaviour modelling, applying logistic regression to model the probability of a pedestrian to cross or wait. Some of the predictor variables are automatically obtained by using the pedestrian detection system. Other variables are still needed to be labelled using manual supervision. A sequential feature selection method showed that time-to-collision and pedestrian waiting time (both variables automatically collected) are the most significant parameters when predicting the pedestrian intent. An overall predictive accuracy of 93.10% is obtained, which clearly validates the proposed methodology.

Assistive Pedestrian Crossings by Means of Stereo Localization and RFID Anonymous Disability Identification

Assistive technology usually refers to systems used to increase, maintain, or improve functional capabilities of individuals with disabilities. This idea is here extended to transportation infrastructures, using pedestrian crossings as a specific case study. We define an Assistive Pedestrian Crossing as a pedestrian crossing able to interact with users with disabilities and provide an adaptive response to increase, maintain or improve their functional capabilities while crossing. Thus, the infrastructure should be able to locate the pedestrians with special needs as well as to identify their specific disability. In this paper, user location is obtained by means of a stereo-based pedestrian detection system. Disability identification is proposed by means of a RFID-based anonymous procedure from which pedestrians are only required to wear a portable and passive RFID tag. Global nearest neighbor is applied to solve data association between stereo targets and RFID measurements. The proposed assistive technology is validated in a real crosswalk, including different complex scenarios with multiple RFID tags.

A Comparative Analysis of Decision Trees Based Classifiers for Road Detection in Urban Environments

In this paper a comparative analysis of decision trees based classifiers is presented. Two different approaches are presented, the first one is a speficic classifier depending on the type of scene. The second one is a general classifier for every type of scene. Both approaches are trained with a set of features that enclose texture, color, shadows, vegetation and other 2D features. As well as 2D features, 3D features are taken into account, such as normals, curvatures and heights with respect to the ground plane. Several tests are made on five different classifiers to get the best parameters configuration and obtain the importance of each features in the final classification. In order to compare the results of this paper with the state of the art, the system has been tested on the KITTI Benchmark public dataset.

Ict employment, over-education and gender in Spain. Do Information and Communication Technologies improve the female labour situation?

This paper investigates the extent to which ICT-related employment is improving the labour situation of women in Spain by reducing female over-education. Outcomes indicate no reduction in female over-education, nor does a womans marital status produce any significant differences. However, the best result is observed for ICT occupations linked to higher job quality characteristics.

Automatic information extraction of traffic panels based on computer vision

Computer vision systems used on road maintenance, either related to signs or to the road itself, are playing a major role in many countries because of the higher investment on public works of this kind. These systems are able to collect a wide range of information automatically and quickly, with the aim of improving road safety. In this context, the suitability of the information contained on the road signs located above the road, typically known as traffic panels, is vital for a correct and safe use by the road user. This paper describes an approach to the first steps of a developing system which will be able to make an inventory and to check the reliability of the information contained on the traffic panels, and whose final aim is to take part on an automatic visual inspection system of signs and panels.

Sectorial structure, qualification characteristics and patterns of labour mobility

The paper has two main objectives: First, to research if workers show significant differences in labour opportunities. Second, to test the hypothesis that tertiarisation has important effects explaining it. Our hypothesis is double: - tertiarization has relevant effect on the structure of labour demand by skills. - the labour opportunities of workers can be influenced by the skills developed in the previous jobs and their concordance between sectoral changes. From a methodology point of view, our approach implies to study labour transition data of workers, sectoral change and its qualification implications. In order to research the previous argument, we analyse the labour mobility within European Countries. Therefore, data used in the paper come from the European Community Household Panel (ECHP). All descriptive analysis have been carried out and, in the order hand, the results from dynamic logit panel data model point out that the relation of workers with tertiarization and its implications [approximated by their previous labour situation (sector and skill)] are significant explaining differences observed in labour transitions and its characteristics.The paper has two main objectives. First, to investigate whether workers show significant differences in labour opportunities. Second, to test the hypothesis that tertiarisation has important effects explaining it. The hypotheses are: (1) tertiarisation has relevant effects on the structure of labour demand by skills; (2) the labour opportunities of workers can be influenced by the skills developed in their previous jobs and their concordance between sectoral changes. From a methodological point of view, the approach implies a study of labour transition data of workers, sectoral change and its qualification implications. In order to research the previous argument, the authors analyse labour mobility within European countries. Therefore, data used in the paper come from the European Community Household Panel (ECHP). All descriptive analyses have been carried out and the results from dynamic logit panel data model suggest that the relation of workers to tertiarisation and its implications – approximated by their previous labour situation (sector and skill) – are significant, explaining differences observed in labour transitions and its characteristics.

Comparison between UHF RFID and BLE for Stereo-Based Tag Association in Outdoor Scenarios

Stereo-based object detection systems can be greatly enhanced thanks to the use of wireless identification technology. By combining tag localization with its identification capability, new features can be associated with each detected object, extending the set of potential applications. The main problem consists in the association between wireless tags and objects due to the intrinsic limitations of Received Signal Strength Indicator-based localization approaches. In this paper, an experimental comparison between two specific technologies is presented: passive UHF Radio Frequency IDentification (RFID) and Bluetooth Low Energy (BLE). An automatic calibration process is used to model the relationship between RSSI and distance values. A robust data association method is presented to deal with complex outdoor scenarios in medium sized areas with a measurement range up to 15m. The proposed approach is validated in crosswalks with pedestrians wearing portable RFID passive tags and active BLE beacons.