Review of Environment Perception for Intelligent Vehicles

Overview of environment perception for intelligent vehicles supposes to the state-of-the-art algorithms and modeling methods are given, with a summary of their pros and cons. A special attention is paid to methods for lane and road detection, traffic sign recognition, vehicle tracking, behavior analysis, and scene understanding. Integrated lane and vehicle tracking for driver assistance system that improves on the performance of both lane tracking and vehicle tracking modules. Without specific hardware and software optimizations, the fully implemented system runs at near-real-time speeds of 11 frames per second. On-road vision-based vehicle detection, tracking, and behavior understanding. Vision based vehicle detection in the context of sensor-based on-road surround analysis. We detail advances in vehicle detection, discussing monocular, stereo vision, and active sensor–vision fusion for on-road vehicle detection. The traffic sign detection detailing detection systems for traffic sign recognition (TSR) for driver assistance. Inherently in traffic sign detection to the various stages: segmentation, feature extraction, and final sign detection

Satellite Navigation for the Age of Autonomy

Global Navigation Satellite Systems (GNSS) brought navigation to the masses. Coupled with smartphones, the blue dot in the palm of our hands has forever changed the way we interact with the world. Looking forward, cyber-physical systems such as self-driving cars and aerial mobility are pushing the limits of what localization technologies including GNSS can provide. This autonomous revolution requires a solution that supports safety-critical operation, centimeter positioning, and cyber-security for millions of users. To meet these demands, we propose a navigation service from Low Earth Orbiting (LEO) satellites which deliver precision in-part through faster motion, higher power signals for added robustness to interference, constellation autonomous integrity monitoring for integrity, and encryption / authentication for resistance to spoofing attacks. This paradigm is enabled by the 'New Space' movement, where highly capable satellites and components are now built on assembly lines and launch costs have decreased by more than tenfold. Such a ubiquitous positioning service enables a consistent and secure standard where trustworthy information can be validated and shared, extending the electronic horizon from sensor line of sight to an entire city. This enables the situational awareness needed for true safe operation to support autonomy at scale.Comment: 11 pages, 8 figures, 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS

Identification of added value ITS services using concept mapping techniques

The evolution of electronics and the growing capabilities of in-vehicle and public infrastructure equipments make feasible the development of new value added services in the field of Intelligent Transportation Systems. However, initiatives in this sense frequently failed due to the lack of agreement or coordination among service providers, public authorities and final users. This paper proposes a scientific method based on concept mapping techniques to extract these added value services. The main benefit of the proposed methodology is its ability to take into account the different points of view of the main actors involved in the field of transport. Obtained results provide general guidelines for future development of ITS services

Quantitative Performance Assessment of LiDAR-based Vehicle Contour Estimation Algorithms for Integrated Vehicle Safety Applications

Many nations and organizations are committing to achieving the goal of `Vision Zero\u27 and eliminate road traffic related deaths around the world. Industry continues to develop integrated safety systems to make vehicles safer, smarter and more capable in safety critical scenarios. Passive safety systems are now focusing on pre-crash deployment of restraint systems to better protect vehicle passengers. Current commonly used bounding box methods for shape estimation of crash partners lack the fidelity required for edge case collision detection and advanced crash modeling. This research presents a novel algorithm for robust and accurate contour estimation of opposing vehicles. The presented method is evaluated via a developed framework for key performance metrics and compared to alternative algorithms found in literature

Defining procedures and simulation tools to test high levels of automation for cars in realistic traffic, driving and boundary conditions

Il crescente livello di automazione nella guida dei veicoli su gomma rende sempre più complesse e articolate le procedure di testing e validazione dei dispositivi. La tendenza alla realizzazione di sistemi che sostituiscano il guidatore in tutto o in parte, determina un cambiamento paradigmatico nell'ambito della validazione, la quale non può più occuparsi esclusivamente del test del corretto funzionamento del dispositivo da validare, ma dovrà testare le logiche di guida e le "scelte" che opera al variare dei contesti. Come ampiamente evidenziato nella letteratura scientifica di settore1 i processi di validazione rappresenteranno il più grande ostacolo alla realizzazione e messa in produzione dei sistemi di quarto e quinto livello SAE2 di automazione. Numerose ricerche hanno dimostrato3 che il testing su strada non rappresenta una soluzione che possa dare risultati attendibili in tempi sufficientemente brevi, ma a tutt'oggi non esistono software sufficientemente complessi da realizzare simulazioni che tengano conto di tutte le variabili necessarie. La ricerca intende definire le corrette procedure di testing di veicoli ad elevato grado di automazione in condizioni di traffico realistiche, avvalendosi di software di simulazione specifici di ogni settore coinvolto nel processo, realizzando uno strumento di testing integrato sufficientemente efficace

AWARENESS AND ADOPTION OF INTELLIGENT RAILWAY TRANSPORT SYSTEM IN ZIMBABWE

The study seeks to investigate the awareness and adoption of modern technologies which are collectively called (IRTS) Intelligent Railway Transport Systems by the NRZ (National railways of Zimbabwe) of Zimbabwe. Adoption of these technologies are on an increasing trend in developed and developing countries, installation and implementation of a railway system called RailTracker in Tanzania has improved railway services in that country, in Uganda and Kenya the Rift Valley Railway (RVR) has introduced GPS technology to track trains. In India a system is used to detect defects in rolling stock while they are on the run. Where these systems have been implemented, they have significantly improved the efficiency, safety and quality of service of railway operations. In Zimbabwe the rail network is an important transport infrastructure enabling movement of goods and passengers. Primary research was carried out using questionnaires and semi structured interviews, data was collected from 67 participants comprising Engineers, Technicians, Train Drivers and Station Managers. 98% of the technical participants indicated that they were aware of IRTS however the adoption of the systems by the NRZ is at 0%. 100% of the Managers indicated that they were aware of IRTS and the company is willing to adopt them but currently no system has been installed Secondary research was conducted to identify and study similar projects elsewhere, their success as well as the difficulties encountered during their implementation. Secondary data was collected from books and the Internet. Article visualizations

Cloud Robotics and Autonomous Vehicles

Recently, a good amount of research has been focused on the development of the autonomous vehicles. Autonomous vehicles possess great potential in numerous challenging applications, for example, autonomous armoured fighting vehicles, automated highway systems, etc. To enable the usage of autonomous vehicles in such challenging applications, it is important to ensure the safety, efficiency, reliability and robustness of the system. Most of the existing implementations of the autonomous vehicles operate as standalone systems limited to onboard capabilities (computations, memory, data, etc.), which limit their potential and performance in real-world applications. The advent of the Internet and emerging advances in the cloud infrastructure suggests new methodologies where vehicles are not limited to onboard capabilities. Processing is also performed remotely on cloud to support different operations and to increase the proficiency of decision-making. This chapter surveys the research to date in the evolution of autonomous vehicles, cloud and cloud-enabled autonomous vehicles, with the limitations of existing systems, research challenges and possible future directions. The chapter can help new researchers in the field to understand and evaluate different approaches for the design of the autonomous vehicular systems