Definition of an Enhanced Map-Matching Algorithm for Urban Environments with Poor GNSS Signal Quality.

Vehicle positioning is a key factor for numerous information and assistance applications that are included in vehicles and for which satellite positioning is mainly used. However, this positioning process can result in errors and lead to measurement uncertainties. These errors come mainly from two sources: errors and simplifications of digital maps and errors in locating the vehicle. From that inaccurate data, the task of assigning the vehicle's location to a link on the digital map at every instant is carried out by map-matching algorithms. These algorithms have been developed to fulfil that need and attempt to amend these errors to offer the user a suitable positioning. In this research; an algorithm is developed that attempts to solve the errors in positioning when the Global Navigation Satellite System (GNSS) signal reception is frequently lost. The algorithm has been tested with satisfactory results in a complex urban environment of narrow streets and tall buildings where errors and signal reception losses of the GPS receiver are frequent.

Intravehicular, Short- and Long-Range Communication Information Fusion for Providing Safe Speed Warnings.

Inappropriate speed is a relevant concurrent factor in many traffic accidents. Moreover, in recent years, traffic accidents numbers in Spain have fallen sharply, but this reduction has not been so significant on single carriageway roads. These infrastructures have less equipment than high-capacity roads, therefore measures to reduce accidents on them should be implemented in vehicles. This article describes the development and analysis of the impact on the driver of a warning system for the safe speed on each road section in terms of geometry, the presence of traffic jams, weather conditions, type of vehicle and actual driving conditions. This system is based on an application for smartphones and includes knowledge of the vehicle position via Ground Positioning System (GPS), access to intravehicular information from onboard sensors through the Controller Area Network (CAN) bus, vehicle data entry by the driver, access to roadside information (short-range communications) and access to a centralized server with information about the road in the current and following sections of the route (long-range communications). Using this information, the system calculates the safe speed, recommends the appropriate speed in advance in the following sections and provides warnings to the driver. Finally, data are sent from vehicles to a server to generate new information to disseminate to other users or to supervise drivers' behaviour. Tests in a driving simulator have been used to define the system warnings and Human Machine Interface (HMI) and final tests have been performed on real roads in order to analyze the effect of the system on driver behavior.

Distributed pedestrian detection alerts based on data fusion with accurate localization.

Among Advanced Driver Assistance Systems (ADAS) pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner) and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided.

Autonomous manoeuvring systems for collision avoidance on single carriageway roads.

The accurate perception of the surroundings of a vehicle has been the subject of study of numerous automotive researchers for many years. Although several projects in this area have been successfully completed, very few prototypes have actually been industrialized and installed in mass produced cars. This indicates that these research efforts must continue in order to improve the present systems. Moreover, the trend to include communication systems in vehicles extends the potential of these perception systems transmitting their information via wireless to other vehicles that may be affected by the surveyed environment. In this paper we present a forward collision warning system based on a laser scanner that is able to detect several potential danger situations. Decision algorithms try to determine the most convenient manoeuvre when evaluating the obstacles' positions and speeds, road geometry, etc. Once detected, the presented system can act on the actuators of the ego-vehicle as well as transmit this information to other vehicles circulating in the same area using vehicle-to-vehicle communications. The system has been tested for overtaking manoeuvres under different scenarios and the correct actions have been performed.