Traffic jam driving with NMV avoidance

n recent years, the development of advanced driver assistance systems (ADAS) – mainly based on lidar and cameras – has considerably improved the safety of driving in urban environments. These systems provide warning signals for the driver in the case that any unexpected traffic circumstance is detected. The next step is to develop systems capable not only of warning the driver but also of taking over control of the car to avoid a potential collision. In the present communication, a system capable of autonomously avoiding collisions in traffic jam situations is presented. First, a perception system was developed for urban situations—in which not only vehicles have to be considered, but also pedestrians and other non-motor-vehicles (NMV). It comprises a differential global positioning system (DGPS) and wireless communication for vehicle detection, and an ultrasound sensor for NMV detection. Then, the vehicle's actuators – brake and throttle pedals – were modified to permit autonomous control. Finally, a fuzzy logic controller was implemented capable of analyzing the information provided by the perception system and of sending control commands to the vehicle's actuators so as to avoid accidents. The feasibility of the integrated system was tested by mounting it in a commercial vehicle, with the results being encouraging

An analysis of communication and navigation issues in collision avoidance support systems

Collision avoidance support systems (CASS) are nowadays one of the main fields of interest in the area of road transportation. Among the different approaches, those systems based on vehicle cooperation to avoid collisions present the most promising perspectives. Works available in the current literature have in common that the performance of such solutions strongly relies on the operation of two on-board subsystems: navigation and communications. However, the performance of these two subsystems is usually underestimated when the whole solution is evaluated. Collision avoidance support applications can be considered among the most critical vehicular services, and this is the reason why this paper focuses on the performance issues of these two subsystems. Main issues regarding navigation and communication performance are discussed along the paper, and a study of the literature in the field is completed with the evaluation of different system prototypes. Communication and navigation tests in real environments yield further conclusions discussed in the paper.The Authors would like to thank the Spanish Ministerio de Fomento and the Ministerio de Ciencia e Innovacion for sponsoring these research activities under the grants FOM/2454/2007, TIN2008-06441-C02-02 and AP2005-1437. Last one in frames of the FPU program. This work has been carried out inside the Intelligent Systems group of the University of Murcia, awarded as an excellence researching group in frames of the Spanish Plan de Ciencia y Tecnologıa de la Region de Murcia (04552/GERM/06)

Vehicle Rollover Stability And Path Planning In Adas Using Model Predictive Control

Advanced Driver Assistance Systems (ADAS) have been developed in recent years to significantly improve safety in driving and assist driver’s response in extreme situations in which quick decisions and maneuvers are required. Common features of ADAS in modern vehicles include automatic emergency braking (AEB), lane keeping assistance (LKA), electric stability control (ESC), and adaptive cruise control (ACC). While these features are developed primarily based on sensor fusion, image processing and vehicle kinematics, the importance of vehicle dynamics must not be overlooked to ensure that the vehicle can follow the desired trajectory without inducing any instability. In many extreme situations such as object avoidance, fast maneuvering of vehicles with high center of gravity might result in rollover instability, an event with a high fatality rate. It is thus necessary to incorporate vehicle dynamics into ADAS to improve the robustness of the system in the path planning to avoid collision with other vehicles or objects and prevent vehicle instability. The objectives of this thesis are to examine the efficacy of a vehicle dynamics model in ADAS to simulate rollover and to develop an active controller using Model Predictive Control (MPC) to manipulate the front-wheel steering and four-wheel differential braking forces, which are related to active steering as well as dynamic stability control for collision avoidance. The controller is designed using the model predictive control approach. A four degree-of-freedom vehicle model is simulated and tested in various scenarios. According to simulation results, the vehicle controller by the MPC controller can track the predicted path within error tolerance. The trajectories used in different simulation scenarios are generated by the MPC controller

Integrated vehicle-based safety systems first annual report

The IVBSS program is a four-year, two phase cooperative research program being conducted by an industry team led by the University of Michigan Transportation Research Institute (UMTRI). The program began in November 2005 and will continue through December 2009 if results from vehicle verification tests conducted in the second year of the program indicate that the prototype system meets its performance guidelines and is safe for use by lay drivers in a field operational test planned for July 2008. The decision to execute Phase II of the program will take place in December 2007. The goal of the IVBSS program is to assess the safety benefits and driver acceptance associated with a prototype integrated crash warning system designed to address rear-end, road departure and lane change/merge crashes on light vehicles and heavy commercial trucks. This report describes accomplishments and progress made during the first year of the program (November 2005-December 2006). Activities during the first year focused on system specification, design and development and construction of the prototype vehicles.National Highway Traffic Safety Administrationhttp://deepblue.lib.umich.edu/bitstream/2027.42/57183/1/99863.pd

Trajectory planning based on adaptive model predictive control: Study of the performance of an autonomous vehicle in critical highway scenarios

Increasing automation in automotive industry is an important contribution to overcome many of the major societal challenges. However, testing and validating a highly autonomous vehicle is one of the biggest obstacles to the deployment of such vehicles, since they rely on data-driven and real-time sensors, actuators, complex algorithms, machine learning systems, and powerful processors to execute software, and they must be proven to be reliable and safe. For this reason, the verification, validation and testing (VVT) of autonomous vehicles is gaining interest and attention among the scientific community and there has been a number of significant efforts in this field. VVT helps developers and testers to determine any hidden faults, increasing systems confidence in safety, security, functional analysis, and in the ability to integrate autonomous prototypes into existing road networks. Other stakeholders like higher-management, public authorities and the public are also crucial to complete the VTT process. As autonomous vehicles require hundreds of millions of kilometers of testing driven on public roads before vehicle certification, simulations are playing a key role as they allow the simulation tools to virtually test millions of real-life scenarios, increasing safety and reducing costs, time and the need for physical road tests. In this study, a literature review is conducted to classify approaches for the VVT and an existing simulation tool is used to implement an autonomous driving system. The system will be characterized from the point of view of its performance in some critical highway scenarios.O aumento da automação na indústria automotiva é uma importante contribuição para superar muitos dos principais desafios da sociedade. No entanto, testar e validar um veículo altamente autónomo é um dos maiores obstáculos para a implantação de tais veículos, uma vez que eles contam com sensores, atuadores, algoritmos complexos, sistemas de aprendizagem de máquina e processadores potentes para executar softwares em tempo real, e devem ser comprovadamente confiáveis e seguros. Por esta razão, a verificação, validação e teste (VVT) de veículos autónomos está a ganhar interesse e atenção entre a comunidade científica e tem havido uma série de esforços significativos neste campo. A VVT ajuda os desenvolvedores e testadores a determinar quaisquer falhas ocultas, aumentando a confiança dos sistemas na segurança, proteção, análise funcional e na capacidade de integrar protótipos autónomos em redes rodoviárias existentes. Outras partes interessadas, como a alta administração, autoridades públicas e o público também são cruciais para concluir o processo de VTT. Como os veículos autónomos exigem centenas de milhões de quilómetros de testes conduzidos em vias públicas antes da certificação do veículo, as simulações estão a desempenhar cada vez mais um papel fundamental, pois permitem que as ferramentas de simulação testem virtualmente milhões de cenários da vida real, aumentando a segurança e reduzindo custos, tempo e necessidade de testes físicos em estrada. Neste estudo, é realizada uma revisão da literatura para classificar abordagens para a VVT e uma ferramenta de simulação existente é usada para implementar um sistema de direção autónoma. O sistema é caracterizado do ponto de vista do seu desempenho em alguns cenários críticos de autoestrad

Perception Intelligence Integrated Vehicle-to-Vehicle Optical Camera Communication.

Ubiquitous usage of cameras and LEDs in modern road and aerial vehicles open up endless opportunities for novel applications in intelligent machine navigation, communication, and networking. To this end, in this thesis work, we hypothesize the benefit of dual-mode usage of vehicular built-in cameras through novel machine perception capabilities combined with optical camera communication (OCC). Current key conception of understanding a line-of-sight (LOS) scenery is from the aspect of object, event, and road situation detection. However, the idea of blending the non-line-of-sight (NLOS) information with the LOS information to achieve a see-through vision virtually is new. This improves the assistive driving performance by enabling a machine to see beyond occlusion. Another aspect of OCC in the vehicular setup is to understand the nature of mobility and its impact on the optical communication channel quality. The research questions gathered from both the car-car mobility modelling, and evaluating a working setup of OCC communication channel can also be inherited to aerial vehicular situations like drone-drone OCC. The aim of this thesis is to answer the research questions along these new application domains, particularly, (i) how to enable a virtual see-through perception in the car assisting system that alerts the human driver about the visible and invisible critical driving events to help drive more safely, (ii) how transmitter-receiver cars behaves while in the mobility and the overall channel performance of OCC in motion modality, (iii) how to help rescue lost Unmanned Aerial Vehicles (UAVs) through coordinated localization with fusion of OCC and WiFi, (iv) how to model and simulate an in-field drone swarm operation experience to design and validate UAV coordinated localization for group of positioning distressed drones. In this regard, in this thesis, we present the end-to-end system design, proposed novel algorithms to solve the challenges in applying such a system, and evaluation results through experimentation and/or simulation

System Development of an Unmanned Ground Vehicle and Implementation of an Autonomous Navigation Module in a Mine Environment

There are numerous benefits to the insights gained from the exploration and exploitation of underground mines. There are also great risks and challenges involved, such as accidents that have claimed many lives. To avoid these accidents, inspections of the large mines were carried out by the miners, which is not always economically feasible and puts the safety of the inspectors at risk. Despite the progress in the development of robotic systems, autonomous navigation, localization and mapping algorithms, these environments remain particularly demanding for these systems. The successful implementation of the autonomous unmanned system will allow mine workers to autonomously determine the structural integrity of the roof and pillars through the generation of high-fidelity 3D maps. The generation of the maps will allow the miners to rapidly respond to any increasing hazards with proactive measures such as: sending workers to build/rebuild support structure to prevent accidents. The objective of this research is the development, implementation and testing of a robust unmanned ground vehicle (UGV) that will operate in mine environments for extended periods of time. To achieve this, a custom skid-steer four-wheeled UGV is designed to operate in these challenging underground mine environments. To autonomously navigate these environments, the UGV employs the use of a Light Detection and Ranging (LiDAR) and tactical grade inertial measurement unit (IMU) for the localization and mapping through a tightly-coupled LiDAR Inertial Odometry via Smoothing and Mapping framework (LIO-SAM). The autonomous navigation module was implemented based upon the Fast likelihood-based collision avoidance with an extension to human-guided navigation and a terrain traversability analysis framework. In order to successfully operate and generate high-fidelity 3D maps, the system was rigorously tested in different environments and terrain to verify its robustness. To assess the capabilities, several localization, mapping and autonomous navigation missions were carried out in a coal mine environment. These tests allowed for the verification and tuning of the system to be able to successfully autonomously navigate and generate high-fidelity maps

Study and validation of data recorded in the vehicles’ EDR in order to perform a road accident’s dynamic reconstruction

Road accident reconstruction is an issue which involves multiple and differentiated subjects. A collision contours’ determination requires the investigation and the analysis of all the evidence provided from highly distinct sources and remaining from uncertain and, sometimes, chaotic scenarios. People are vastly involved in traffic accident situations, either being drivers, victims, injured or witnesses. Therefore, accident investigation is a sensitive matter which requires objectiveness, accuracy, efficiency, and effectiveness, to draw faithful and factual conclusions about the collisions’ contours. The accidents reconstruction science’s main objective is to determine and describe the involved vehicles dynamics, which is accomplished by collecting and interconnect all the available evidence extracted from the impacts’ scenarios, from the vehicles, and from the involved people. In the past, many authors developed mathematical models which describe, approximately, the vehicles’ dynamics involved in a road traffic collision. Over the years, with the technology evolution and the advances on the area, multiple solutions have been created and enhanced to provide to accident reconstructionists better and more reliable evidence, allowing them to perform crash reconstructions with higher accuracy. These solutions include numerical methods, simulation and evaluation software, and tools for evidence collection. However, the introduction of the Event Data Recorder (EDR) on the vehicles consists of a great progression concerning the availability of valid and meaningful clues which can be used as inputs for the scientific crash reconstruction, since the EDR stores data that was unavailable and was difficult to deduce from the accident’s remaining evidence, previously. On the scope of this project, a vehicle data logging device was developed and tested regarding the validation of the EDR’s recorded data. The device’s purpose is to acquire the most relevant variables for crash reconstruction, which are also stored by the EDR, and provide a source of information for comparison and validation. This device was integrated with the respective sensors, programmed with a developed software, and tested on a vehicle. The tests for dynamic data acquisition consisted of travelling a defined path around the school campus, since there was not the opportunity to perform a real crash test with an EDR equipped vehicle

Automated driving and autonomous functions on road vehicles

In recent years, road vehicle automation has become an important and popular topic for research and development in both academic and industrial spheres. New developments received extensive coverage in the popular press, and it may be said that the topic has captured the public imagination. Indeed, the topic has generated interest across a wide range of academic, industry and governmental communities, well beyond vehicle engineering; these include computer science, transportation, urban planning, legal, social science and psychology. While this follows a similar surge of interest – and subsequent hiatus – of Automated Highway Systems in the 1990’s, the current level of interest is substantially greater, and current expectations are high. It is common to frame the new technologies under the banner of “self-driving cars” – robotic systems potentially taking over the entire role of the human driver, a capability that does not fully exist at present. However, this single vision leads one to ignore the existing range of automated systems that are both feasible and useful. Recent developments are underpinned by substantial and long-term trends in “computerisation” of the automobile, with developments in sensors, actuators and control technologies to spur the new developments in both industry and academia. In this paper we review the evolution of the intelligent vehicle and the supporting technologies with a focus on the progress and key challenges for vehicle system dynamics. A number of relevant themes around driving automation are explored in this article, with special focus on those most relevant to the underlying vehicle system dynamics. One conclusion is that increased precision is needed in sensing and controlling vehicle motions, a trend that can mimic that of the aerospace industry, and similarly benefit from increased use of redundant by-wire actuators