José Javier Anaya

Vehicle to pedestrian communications for protection of vulnerable road users

Vehicle and pedestrian collisions often result in fatality to the vulnerable road users, indicating a strong need of technologies to protect such vulnerable road users. Wireless communications have potential to support road safety by enabling road users to exchange information. In contrast to vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications for avoidance of inter-vehicle collisions, very limited efforts are made on communication mechanisms for pedestrian safety. This paper addresses the issue in a concrete way. We first formulate the requirement of the minimum information exchange distance for providing road users to have the necessary amount of time to perceive the situation and react. We then report our field tests and measurement based analysis to investigate if a Wi-Fi system can satisfy the application requirement. We also introduce a pedestrian protection application, V2ProVu, which provides the functionalities of the Wi-Fi communications, risk calculation, and hazard alarming. Our study discloses several useful insights including 1) information exchange for a velocity of 80 km/h has to be made before vehicle to pedestrian (V2P) distance is below 72 meters and 2) while this requirement is not too hard for radio communications technologies, the V2P communication range is greatly reduced if the signal is blocked by a human body.

Modeling the Driving Behavior of Electric Vehicles Using Smartphones and Neural Networks

The modeling of eco-driving behaviors is a key issue in the research of Intelligent Transportation Systems. Most efforts have been made regarding internal combustion vehicles, and few works have been reported in the field of electric vehicles. On the other hand, these behavior analyses are usually conducted through naturalistic driving researches that involve the use of instrumented vehicles, available in a small number, which reduces the impact of the results. This paper presents a system for estimating the remaining charge of an electric vehicle by considering the driving behavior measured using a smartphone. For this purpose, first of all, data measured by the smartphone and by the onboard instrumentation were compared in order to demonstrate that both sources are equivalent and that the former is sufficiently accurate. The driving profiles obtained were then used to estimate the expected battery consumption of the electric vehicle using a Neural Network to represent the model that uses the information provided from the smartphone as input, such as speed, acceleration and jerk. The system has been tested with 10 drivers with a prediction capability of the expected battery consumption higher than 95%. These results show that a smartphone is a tool with a sufficient degree of fidelity to capture data from drivers, and so avoid expensive, complex systems like instrumented vehicles, and it can also be used for estimating energy consumption and predicting the remaining battery charge.

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.

Vehicle to Vehicle GeoNetworking using Wireless Sensor Networks

Vehicular communications will be the next quality step in the development of automotive technologies. Defining these communications is currently in the final step of development, the focus being on standardization and field tests of network devices and Advanced Driver Assistance Systems. However, some issues regarding vehicular communications that require a specific research effort are still open and represent a challenge if the technology is to be ultimately implemented and marketed. One of these challenges is to develop effective GeoNetworking in vehicular communications. This concept means that the Vehicle Ad-hoc NETwork (VANET) data package transmission is organized according to the topographical location of the different network nodes (vehicles), with the data flow being organized optimally so as to cover the surroundings of each vehicle. The core of this GeoNetworking system is the GeoRouting algorithm that supports the optimal routing of the data packages and reorganizes the network structure in accordance with the positions of the nodes. In this paper we present a novel GeoRouting algorithm for unicast communications, based on the evolution of the previous results of vehicular mesh networks using IEEE 802.15.4 Wireless Sensor Networks (WSN) technology. This algorithm has been designed, implemented and validated under controlled conditions and tested in real vehicles on real roads with free-flow traffic. The results suggest that the features of this routing algorithm can be inserted into any vehicular architecture to provide functioning GeoNetworking that will support a wide range of Advanced Driving Assistance System (ADAS) applications.

Vehicle Tracking for an Evasive Manoeuvres Assistant Using Low-Cost Ultrasonic Sensors

Many driver assistance systems require knowledge of the vehicle environment. As these systems are increasing in complexity and performance, this knowledge of the environment needs to be more complete and reliable, so sensor fusion combining long, medium and short range sensors is now being used. This paper analyzes the feasibility of using ultrasonic sensors for low cost vehicle-positioning and tracking in the lane adjacent to the host vehicle in order to identify free areas around the vehicle and provide information to an automatic avoidance collision system that can perform autonomous braking and lane change manoeuvres. A laser scanner is used for the early detection of obstacles in the direction of travel while two ultrasonic sensors monitor the blind spot of the host vehicle. The results of tests on a test track demonstrate the ability of these sensors to accurately determine the kinematic variables of the obstacles encountered, despite a clear limitation in range.

Application of vehicle to another entity (V2X) communications for motorcycle crash avoidance

ABSTRACT Information and communication technologies are being massively applied in the automotive field as the basis of the new generation of active safety systems. In this extensive field of technologies, vehicular communications will constitute the core of a large set of advanced driving assistance systems for improving road safety as well as helping to reduce the environmental impact of transport. These communication technologies are currently under deployment, but their mandatory installation in newly manufactured cars is foreseen in the next 5 years. This equipment will enable the new Advanced Driver Assistance Systems (ADAS) system to be installed in these vehicles. Many of these safety applications are currently under development. However, there are some road users who are not commonly included in this vehicular communication ecosystem, specifically, vulnerable road users, such as pedestrians, cyclists, and motorcyclists. Current assistance systems focused on reducing crashes with this user group are based on sensors installed in the vehicles but do not include vehicular communications. In this article, we present a novel Vulnerable Road User (VRU) warning system based on Vehicle-to-Vehicle (V2V) communications, which is capable of detecting a motorcycle circulating in the vicinity of the connected vehicles, launching sound and visual warnings, and using a smartphone as human-machine interface. The system has been designed, implemented, and tested in the laboratory as well as on real roads in real traffic flow.

Vulnerable Road Users Detection Using V2X Communications

Vehicle to vehicle (V2V) communications allow to sharing real-time information among the vehicles that circulate on the nearby road areas. These communications systems are today in an early stage of development and the effort are focused into two directions, on one hand, the development of the communications infrastructure to support the information exchange. On the other hand, the development of Advanced Driver Assistance Systems (ADAS) as well as safety systems that takes advantages of these communications. Additionally, the V2V communications systems are mainly focused to cars and trucks, showing less concern for Vulnerable Road Users, pedestrians, motorcyclists and cyclists. In this paper a novel ADAS is presented, focused to avoid accidents that involve motorcyclist and cyclists using V2V communications, incorporating them to the vehicular networking taking into account the intrinsic features of each collective and adapting to increase their safety.

Motorcycle detection for ADAS through camera and V2V Communication, a comparative analysis of two modern technologies

Two Vulnerable Road User Detection Approaches presented.Comparison tests of two state of the art technologies for ADAS application: V2V and sensor based data fusion.V2V technology able to be implemented in any vehicle, with mobile phone interface.Data fusion based on computer vision and laser scanner detection algorithm.Real tests for both subsystem proves the real time performance and the accuracy of the detections. Motorcycles are one of the most dangerous means of transportation. Its death toll is higher than in others, due to the inherent vulnerability of motorcycle drivers. The latest strategies in Advanced Driving Assistance Systems (ADAS) are trying to mitigate this problem by applying the advances of modern technologies to the road transport. This paper presents two different approaches on motorcycle protection, based on two of the most modern available technologies in ADAS, i.e. Computer Vision and Vehicle to Vehicle Communication (V2V). The first approach is based on data fusion of Laser Scanner and Computer Vision, providing accurate obstacle detection and localization based on laser scanner, and obstacle classification using computer vision and laser. The second approach is based on ad-hoc V2V technology and provides detection in case of occlusion for visual sensors. Both technologies have been tested in the presented work, and a performance comparison is given. Tests performed in different driving situations allows to measure the performance of every algorithm and the limitations of each of them based on empirical and scientific foundations. The conclusions of the presented work help foster of expert systems in the automotive sector by providing further discussion of the viability and impact from each of these systems in real scenarios.

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.

GeoNetworking based V2V Mesh Communications over WSN

An intensive effort is presently carried out in order to research and develop vehicular communication systems. Several standards, prototypes and field operational tests are under deployment all around the world, involving multiple research centers and vehicle and electronics manufacturers. However, some research lines are open today, in which vehicular communication systems with guaranteed reliability and robustness are necessary. One of these challenges is the development of an effective GeoNetworking in vehicular communications. This concept means that the vehicle ad-hoc network (VANET) bases the data package transmission in the topographical location of the different nodes (vehicles) of the network, organizing the data flow in an optimal way that covers the surroundings of each vehicle. The core of this GeoNetworking system is the GeoRouting algorithm, that supports the optimal routing of the data packages and reorganizes the network structure in function of the positions of the nodes. In this paper we present a novel GeoRouting algorithm, based in the evolution of previous results of mesh vehicular networks. This algorithm has been designed, implemented and tested in real vehicles in real roads with free flow traffic. The results suggest that the features of the designed routing algorithm can be applied as core of any kind of vehicular network to support ADAS applications.