Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT

In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV). The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets. This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols. The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety

교통약자 대상 강건 비상제동장치 개발

학위논문 (석사)-- 서울대학교 대학원 공과대학 기계항공공학부, 2017. 8. 이경수.본 연구는 교통약자를 대상으로 하는 자동비상제동 알고리즘을 개발하고자 진행된 연구이다. 자동비상제동장치란 센서로부터 얻은 환경정보를 기반으로 운전자가 예상하지 못한 사고를 회피하거나 사고의 피해를 완화할 수 있도록 차량을 제동해주는 장치이다. 이러한 자동비상제동장치가 점차 양산되고 보급되기 시작한 이후 사람들은 이러한 자동비상제동장치를 이용하여 교통 약자와 관련된 사고까지 예방하기 위한 노력들을 수행하고 있다. 교통 약자는 일반적으로 보행자, 자전거 등의 원동기를 장착하지 않은 도로 사용자로 정의된다. 교통 약자는 비록 그 속도가 차량에 비해 느리지만, 실제 사고가 발생할 경우 그 피해가 커질 우려가 있다. 따라서 이러한 교통 약자와 관련된 사고를 줄이기 위한 노력이 필요하다. 사고가 발생하기 이전에 위험을 인지하기 위해서는 자차량 및 대상 교통 약자의 거동을 예측할 필요가 있다. 이를 위해서는 자차량 및 교통 약자의 거동을 모사할 수 있는 동역학 모델이 필요하다. 차량의 경우 운전자가 사고를 회피할 수 있는지 확인하기 위해서는 실제로 운전자가 사고를 회피할 때 일반적으로 사용하는 회피 거동에 대한 모사 역시 필요하다. 이를 위하여 자차량의 거동은 등가속도 모델을 이용하여 표현하였다. 또한 교통 약자의 경우 보행자와 자전거를 구분하는데 한계가 있기 때문에 대상 교통 약자의 종류 구분 없이 안전 성능을 확보할 수 있어야 한다. 따라서 보행자 및 자전거의 거동은 동일한 등속 직선 운동 모델을 이용하여 표현하고자 하였다. 이렇게 예측된 정보들을 바탕으로 운전자가 사고를 회피할 수 있는지 판단하고자 하였다. 만약 운전자가 사고를 회피하고자 할 때 일정 수준의 안전거리를 확보하지 못할 경우 자동비상제동장치가 작동하여 차량을 제동하도록 하였다. 이 때 자동비상제동장치의 강건 성능을 확보하기 위하여 측정 시에 발생하는 불확실성 및 정보 예측 시에 발생하는 불확실성을 고려하여 안전 거리를 정의하였다. 이렇게 개발된 자동비상제동장치의 성능을 확인하기 위하여 차량 시뮬레이션 툴인 Carsim과 MATLAB/Simulink를 기반으로 시뮬레이션 평가를 수행하였다. 이 때 개발한 자동비상제동장치의 강건 성능을 검증하기 위하여 시뮬레이션을 동일 시나리오에 대해 100회 반복 수행 하였으며, 비교를 위하여 불확실성을 고려하지 않은 자동비상제동장치를 함께 평가하였다.A robust autonomous emergency braking (AEB) algorithm for vulnerable road users (VRU) is studied. Autonomous emergency braking (AEB) is a system which helps driver to avoid or mitigate a collision using sensor information. After many kinds of AEB system is produced by automakers, researchers and automakers are currently focusing on VRU-related collisions. Vulnerable road users (VRU) usually defined as non-motorized road users such as pedestrian and cyclist. Although VRU are relatively slower than vehicle, VRU related collisions should be prevented due to their fatalities. Therefore, many researchers are trying to develop a VRU-AEB. In order to assess the risk of collision before it occurs, the motion of host vehicle and target VRU should be predicted. For this, dynamic models of host vehicle and target VRU is required. In the case of host vehicle, in order to judge whether a driver can avoid a collision or not, drivers evasive maneuver also should be predicted as well as normal driving maneuver. For this, the motion of the host vehicle is predicted using constant acceleration model. In the case of target VRU, since the identification between pedestrian and cyclist is difficult, safety performance of AEB should be guaranteed even if the type of the target is unclear. Therefore, the behavior of pedestrian and cyclist is described using a single constant velocity model. These predicted information is then used to judge whether a collision is inevitable or not. If a driver cannot avoid a collision with pre-defined limits and safety margin, then the proposed AEB system is activated to decelerate the vehicle. To guarantee the robust safety performance of AEB system, measurement uncertainty and prediction uncertainty are also considered while defining the safety margin. To evaluate the safety performance of proposed AEB system, simulation study is conducted via vehicle simulation tool Carsim and MATLAB/Simulink. To investigate the robust safety performance of the proposed AEB system, simulation study is repeated 100 times with same traffic scenario with uncertainties. Performance of the proposed AEB system is compared with the deterministic AEB which is introduced in this work.Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Autonomous Emergency Braking System – Global Trend 4 1.3 Thesis Objectives and Outline 9 Chapter 2 Previous Researches 10 Chapter 3 Autonomous Emergency Braking Algorithm for Vulnerable Road Users 17 Chapter 4 Host Vehicle Motion Prediction 19 4.1 Host Vehicle State Estimation 20 4.2 Host Vehicle Evasive Maneuver Prediction 24 Chapter 5 Target VRU Motion Prediction 28 5.1 Target VRU State Estimation 29 5.2 Target VRU Motion Prediction 34 Chapter 6 Threat Assessment 35 6.1 Collision Judgement 35 6.2 Safety Boundary for Collision Judgement 39 6.3 Emergency Braking Mode Decision 42 Chapter 7 Simulation Result 43 Chapter 8 Conclusion 50 Bibliography 51 국문초록 59Maste

Situational Awareness Enhancement for Connected and Automated Vehicle Systems

Recent developments in the area of Connected and Automated Vehicles (CAVs) have boosted the interest in Intelligent Transportation Systems (ITSs). While ITS is intended to resolve and mitigate serious traffic issues such as passenger and pedestrian fatalities, accidents, and traffic congestion; these goals are only achievable by vehicles that are fully aware of their situation and surroundings in real-time. Therefore, connected and automated vehicle systems heavily rely on communication technologies to create a real-time map of their surrounding environment and extend their range of situational awareness. In this dissertation, we propose novel approaches to enhance situational awareness, its applications, and effective sharing of information among vehicles.;The communication technology for CAVs is known as vehicle-to-everything (V2x) communication, in which vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) have been targeted for the first round of deployment based on dedicated short-range communication (DSRC) devices for vehicles and road-side transportation infrastructures. Wireless communication among these entities creates self-organizing networks, known as Vehicular Ad-hoc Networks (VANETs). Due to the mobile, rapidly changing, and intrinsically error-prone nature of VANETs, traditional network architectures are generally unsatisfactory to address VANETs fundamental performance requirements. Therefore, we first investigate imperfections of the vehicular communication channel and propose a new modeling scheme for large-scale and small-scale components of the communication channel in dense vehicular networks. Subsequently, we introduce an innovative method for a joint modeling of the situational awareness and networking components of CAVs in a single framework. Based on these two models, we propose a novel network-aware broadcast protocol for fast broadcasting of information over multiple hops to extend the range of situational awareness. Afterward, motivated by the most common and injury-prone pedestrian crash scenarios, we extend our work by proposing an end-to-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection for vulnerable road users. Finally, as humans are the most spontaneous and influential entity for transportation systems, we design a learning-based driver behavior model and integrate it into our situational awareness component. Consequently, higher accuracy of situational awareness and overall system performance are achieved by exchange of more useful information

Response of Vulnerable Road Users to Visual Information from Autonomous Vehicles in Shared Spaces

Completely unmanned autonomous vehicles have been anticipated for a while. Initially, these are expected to drive only under certain conditions on some roads, and advanced functionality is required to cope with the ever-increasing challenges of safety. To enhance the public's perception of road safety and trust in new vehicular technologies, we investigate in this paper the effect of several interaction paradigms with vulnerable road users by developing and applying algorithms for the automatic analysis of pedestrian body language. We assess behavioral patterns and determine the impact of the coexistence of AVs and other road users on general road safety in a shared space for VRUs and vehicles. Results showed that the implementation of visual communication cues for interacting with VRUs is not necessarily required for a shared space in which informal traffic rules apply.Comment: Published paper in the IEEE Intelligent Transportation Systems Conference - ITSC 201

Control and communication systems for automated vehicles cooperation and coordination

Mención Internacional en el título de doctorThe technological advances in the Intelligent Transportation Systems (ITS) are exponentially improving over the last century. The objective is to provide intelligent and innovative services for the different modes of transportation, towards a better, safer, coordinated and smarter transport networks. The Intelligent Transportation Systems (ITS) focus is divided into two main categories; the first is to improve existing components of the transport networks, while the second is to develop intelligent vehicles which facilitate the transportation process. Different research efforts have been exerted to tackle various aspects in the fields of the automated vehicles. Accordingly, this thesis is addressing the problem of multiple automated vehicles cooperation and coordination. At first, 3DCoAutoSim driving simulator was developed in Unity game engine and connected to Robot Operating System (ROS) framework and Simulation of Urban Mobility (SUMO). 3DCoAutoSim is an abbreviation for "3D Simulator for Cooperative Advanced Driver Assistance Systems (ADAS) and Automated Vehicles Simulator". 3DCoAutoSim was tested under different circumstances and conditions, afterward, it was validated through carrying-out several controlled experiments and compare the results against their counter reality experiments. The obtained results showed the efficiency of the simulator to handle different situations, emulating real world vehicles. Next is the development of the iCab platforms, which is an abbreviation for "Intelligent Campus Automobile". The platforms are two electric golf-carts that were modified mechanically, electronically and electrically towards the goal of automated driving. Each iCab was equipped with several on-board embedded computers, perception sensors and auxiliary devices, in order to execute the necessary actions for self-driving. Moreover, the platforms are capable of several Vehicle-to-Everything (V2X) communication schemes, applying three layers of control, utilizing cooperation architecture for platooning, executing localization systems, mapping systems, perception systems, and finally several planning systems. Hundreds of experiments were carried-out for the validation of each system in the iCab platform. Results proved the functionality of the platform to self-drive from one point to another with minimal human intervention.Los avances tecnológicos en Sistemas Inteligentes de Transporte (ITS) han crecido de forma exponencial durante el último siglo. El objetivo de estos avances es el de proveer de sistemas innovadores e inteligentes para ser aplicados a los diferentes medios de transporte, con el fin de conseguir un transporte mas eficiente, seguro, coordinado e inteligente. El foco de los ITS se divide principalmente en dos categorías; la primera es la mejora de los componentes ya existentes en las redes de transporte, mientras que la segunda es la de desarrollar vehículos inteligentes que hagan más fácil y eficiente el transporte. Diferentes esfuerzos de investigación se han llevado a cabo con el fin de solucionar los numerosos aspectos asociados con la conducción autónoma. Esta tesis propone una solución para la cooperación y coordinación de múltiples vehículos. Para ello, en primer lugar se desarrolló un simulador (3DCoAutoSim) de conducción basado en el motor de juegos Unity, conectado al framework Robot Operating System (ROS) y al simulador Simulation of Urban Mobility (SUMO). 3DCoAutoSim ha sido probado en diferentes condiciones y circunstancias, para posteriormente validarlo con resultados a través de varios experimentos reales controlados. Los resultados obtenidos mostraron la eficiencia del simulador para manejar diferentes situaciones, emulando los vehículos en el mundo real. En segundo lugar, se desarrolló la plataforma de investigación Intelligent Campus Automobile (iCab), que consiste en dos carritos eléctricos de golf, que fueron modificados eléctrica, mecánica y electrónicamente para darle capacidades autónomas. Cada iCab se equipó con diferentes computadoras embebidas, sensores de percepción y unidades auxiliares, con la finalidad de transformarlos en vehículos autónomos. Además, se les han dado capacidad de comunicación multimodal (V2X), se les han aplicado tres capas de control, incorporando una arquitectura de cooperación para operación en modo tren, diferentes esquemas de localización, mapeado, percepción y planificación de rutas. Innumerables experimentos han sido realizados para validar cada uno de los diferentes sistemas incorporados. Los resultados prueban la funcionalidad de esta plataforma para realizar conducción autónoma y cooperativa con mínima intervención humana.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Francisco Javier Otamendi Fernández de la Puebla.- Secretario: Hanno Hildmann.- Vocal: Pietro Cerr

Drivers overtaking cyclists and pedestrians: Modeling road-user behavior for traffic safety

In a world aiming to shift to more sustainable modes of transportation, vulnerable road users (VRUs) like cyclists and pedestrians are still confronted with significant barriers to safety, particularly on rural roads where overtaking maneuvers represent a frequent and dangerous interaction with motorized traffic. If drivers misjudge their kinematics, even near-crashes without physical contact can harm the perceived safety of the VRU, which may decrease the willingness to continue cycling or walking on these roads. Crash risks when overtaking VRUs exist in different overtaking phases: when approaching the VRU, steering out, passing, and eventually returning. To make overtaking VRUs safer, improvements to policymaking, infrastructure, and vehicles are needed. However, these improvements need models that can describe or predict road-user behavior in overtaking, which was the objective of this thesis. Based on data sets obtained from a test-track experiment, field-test studies, and naturalistic studies, this thesis developed behavioral models for both objective and perceived safety of drivers and VRUs in different overtaking phases. The results indicate that drivers’ and VRUs’ behavior is mainly influenced by their highest crash or injury risk. The descriptive models showed that a close oncoming vehicle could reduce a driver’s safety margins to the VRU in all phases. Furthermore, the VRU behavior may affect the driver’s behavior; for instance, through lane positioning and, for pedestrians, walking direction. Infrastructure design and policymaking should focus on preventing overtaking in areas where oncoming vehicles are hard to estimate and enforcing sufficient clearances to the cyclist, stratified by speed. The predictive models can help vehicle safety systems adapt to drivers to become more acceptable, for instance, when assisting drivers in the decision to overtake or not. They may further help optimize road networks’ objective and perceived safety

Use Of Smartphones for Ensuring Vulnerable Road User Safety through Path Prediction and Early Warning: An In-Depth Review of Capabilities, Limitations and Their Applications in Cooperative Intelligent Transport Systems

The field of cooperative intelligent transport systems and more specifically pedestrians to vehicles could be characterized as quite challenging, since there is a broad research area to be studied, with direct positive results to society. Pedestrians to vehicles is a type of cooperative intelligent transport system, within the group of early warning collision/safety system. In this article, we examine the research and applications carried out so far within the field of pedestrians to vehicles cooperative transport systems by leveraging the information coming from vulnerable road users’ smartphones. Moreover, an extensive literature review has been carried out in the fields of vulnerable road users outdoor localisation via smartphones and vulnerable road users next step/movement prediction, which are closely related to pedestrian to vehicle applications and research. We identify gaps that exist in these fields that could be improved/extended/enhanced or newly developed, while we address future research objectives and methodologies that could support the improvement/development of those identified gaps

Vehicle Trajectory Prediction and Collision Warning via Fusion of Multisensors and Wireless Vehicular Communications

Driver inattention is one of the leading causes of traffic crashes worldwide. Providing the driver with an early warning prior to a potential collision can significantly reduce the fatalities and level of injuries associated with vehicle collisions. In order to monitor the vehicle surroundings and predict collisions, on-board sensors such as radar, lidar, and cameras are often used. However, the driving environment perception based on these sensors can be adversely affected by a number of factors such as weather and solar irradiance. In addition, potential dangers cannot be detected if the target is located outside the limited field-of-view of the sensors, or if the line of sight to the target is occluded. In this paper, we propose an approach for designing a vehicle collision warning system based on fusion of multisensors and wireless vehicular communications. A high-level fusion of radar, lidar, camera, and wireless vehicular communication data was performed to predict the trajectories of remote targets and generate an appropriate warning to the driver prior to a possible collision. We implemented and evaluated the proposed vehicle collision system in virtual driving environments, which consisted of a vehicle&ndash vehicle collision scenario and a vehicle&ndash pedestrian collision scenario. Document type: Articl