Path Planning Algorithm for Autonomous Urban Vehicles from the Viewpoint of Kuhn’s Philosophy and Popper’s Philosophy

Abstrak – Kendaraan otonom dapat bermanfaat untuk meningkatkan keselamatan, efisiensi, aksesibilitas dan kenyamanan transportasi. Salah satu tugas penting yang harus dilakukan oleh kendaraan otonom adalah melakukan perencanaan jalur melalui lingkungan perkotaan yang dinamis dimana terdapat kendaraan lain dan pejalan kaki. Menuruf filosofi Kuhn, sebuah keilmuan memiliki siklus hidupnya sendiri-sendiri. Siklus hidup suatu keilmuan terdiri dari fase kelahiran, fase pembuktian dan fase diterimanya keilmuan baru tersebut menjadi apa yang disebut sebagai ilmu normal. Demikian juga dengan perkembangan keilmuan perencaan jalur, algoritma perencanaan jalur untuk kendaraan otonom masih terus diteliti dan dikembangkan oleh berbagai peneliti. Studi baru terus dilakukan dalam upaya menemukan teknik perencanaan jalur yang dapat diterima secara umum, sehingga algoritma tersebut akan menjadi ilmu normal. Menutur filosofi Popper, setiap algoritma yang diusulkan harus dapat diuji menggunakan prinsip falsifikasi untuk menentukan apakah teknik yang diusulkan tersebut akhirnya bisa menjadi ilmu normal atau tidak. Maka makalah ini bertujuan untuk memberikan gambaran mengenai siklus keilmuan perencanaan jalur kendaraan otonom. Makalah ini juga bertujuan untuk membandingkan penelitian-penelitian terkini mengenai algoritma perencanaan jalur untuk kendaraan otonom di daerah perkotaan. Dalam membandingkan algoritma-algoritma tersebut akan digunakan prinsip falsifikasi Popper. Hasil perbandingan yang disajikan dalam makalah ini akan membantu mendapatkan wawasan mengenai kelebihan dan kekurangan dari masing-masing algoritma, serta akan membantu juga untuk memilih algoritma yang digunakan dalam desain sistem kendaraan otonom.   Kata Kunci : Kendaraan otonom, algoritma perencanaan jalur, lingkungan perkotaan, siklus keilmuan Khun, falsifikasi PopperAutonomous vehicles can be useful to improve safety, efficiency, accessibility and convenience of transportation. One important task that must be carried out by autonomous vehicles is to do path planning through a dynamic urban environment where there are other vehicles and pedestrians. According to Kuhn's philosophy, a science has its own life cycle. The science life cycle consists of the birth phase, the proof phase and the acceptance phase of the new science into what is called normal science. Likewise with the scientific development of path planning algorithms, path planning algorithms for autonomous vehicles are still being researched and developed by various researchers. New studies continue to be conducted in an effort to find pathway planning techniques that can be generally accepted, so that the algorithm will become a normal science. According to Popper's philosophy, each proposed algorithm must be tested using the principle of falsification to determine whether the proposed technique can eventually become a normal science or not. So this paper aims to provide an overview of the scientific cycle of planning autonomous vehicle lanes. This paper also aims to compare the latest research on path planning algorithms for autonomous vehicles in urban areas. In comparing these algorithms, the principle of Popper's falsification will be used. The comparison results presented in this paper will help gain insight into the advantages and disadvantages of each algorithm, and will also help to choose the algorithm used in the design of autonomous vehicle systems.   Keywords ­: Autonomous vehicles, path planning algorithms, urban environment, Khun’s scientific cycles, Popper’s falsificatio

A Parallel Autonomy Research Platform

We present the development of a full-scale “parallel autonomy” research platform including software and hardware. In the parallel autonomy paradigm, the control of the vehicle is shared; the human is still in control of the vehicle, but the autonomy system is always running in the background to prevent accidents. Our holistic approach includes: (1) a driveby-wire conversion method only based on reverse engineering, (2) mounting of relatively inexpensive sensors onto the vehicle, (3) implementation of a localization and mapping system, (4) obstacle detection and (5) a shared controller as well as (6) integration with an advanced autonomy simulation system (Drake) for rapid development and testing. The system can operate in three modes: (a) manual driving, (b) full autonomy, where the system is in complete control of the vehicle and (c) parallel autonomy, where the shared controller is implemented. We present results from extensive testing of a full-scale vehicle on closed tracks that demonstrate these capabilities

Safety of autonomous vehicles: A survey on Model-based vs. AI-based approaches

The growing advancements in Autonomous Vehicles (AVs) have emphasized the critical need to prioritize the absolute safety of AV maneuvers, especially in dynamic and unpredictable environments or situations. This objective becomes even more challenging due to the uniqueness of every traffic situation/condition. To cope with all these very constrained and complex configurations, AVs must have appropriate control architectures with reliable and real-time Risk Assessment and Management Strategies (RAMS). These targeted RAMS must lead to reduce drastically the navigation risks. However, the lack of safety guarantees proves, which is one of the key challenges to be addressed, limit drastically the ambition to introduce more broadly AVs on our roads and restrict the use of AVs to very limited use cases. Therefore, the focus and the ambition of this paper is to survey research on autonomous vehicles while focusing on the important topic of safety guarantee of AVs. For this purpose, it is proposed to review research on relevant methods and concepts defining an overall control architecture for AVs, with an emphasis on the safety assessment and decision-making systems composing these architectures. Moreover, it is intended through this reviewing process to highlight researches that use either model-based methods or AI-based approaches. This is performed while emphasizing the strengths and weaknesses of each methodology and investigating the research that proposes a comprehensive multi-modal design that combines model-based and AI approaches. This paper ends with discussions on the methods used to guarantee the safety of AVs namely: safety verification techniques and the standardization/generalization of safety frameworks

Autonomes Fahren – ein Top-Down-Ansatz

This paper presents a functional system architecture for an “autonomous vehicle” in the sense of amodular building block system. It is developed in a topdown approach based on the definition of the functional requirements for an autonomous vehicle and explicitly combines perception-based and localization-based approaches. Both the definition and the functional system architecture consider the aspects operating by the human being, mission accomplishment, map data, localization, environmental and self-perception as well as cooperation. The functional system architecture is developed in the context of the research project “Stadtpilot” at the Technische Universität Braunschweig.In diesem Artikel stellen wir eine funktionale Systemarchitektur für ein “autonom fahrendes Straßenfahrzeug” vor, die im Sinne eines modularen Baukastensystems entworfen ist. Sie wurde in einemTop- Down-Ansatz ausgehend von einerDefinition des Funktionsumfangs eines “autonom fahrenden Straßenfahrzeugs” entwickelt und führt explizit wahrnehmungsbasierte und lokalisierungsbasierte Ansätze zusammen. Sowohl dieDefinition des Funktionsumfanges als auch die funktionale Systemarchitektur berücksichtigen die Aspekte Bedienung, Missionsumsetzung, Karten, Lokalisierung, Umfeld- und Selbstwahrnehmung sowie Kooperation. Die Ergebnisse basieren unter anderem auf Erkenntnissen aus dem Projekt “Stadtpilot” der Technischen Universität Braunschweig

Development of an Autonomous Battery Electric Vehicle

Autonomous vehicles have been shown to increase safety for drivers, passengers and pedestrians and can also be used to maximize traffic flow, thereby reducing emissions and congestion. At the same time, governments around the world are promoting the usage of Battery Electric Vehicles (BEVs) to reduce and control the emissions of CO2. This has made the development of autonomous vehicles and electric vehicles a very active research area and has prompted a significant amount of government funding. This paper presents the detailed design of a low-cost platform for the development of an autonomous electric vehicle. In particular, it focuses on the design of the electrical architecture and the control strategy, tailored around the usage of affordable sensors and actuators. The specifications of the components are extensively discussed in relation to the performance target. The aim is to provide a comprehensive guide for the development of the remotely controlled platform, in order to lower the entry barrier for the development of autonomous electric vehicles

DEVELOPMENT OF AUTONOMOUS VEHICLE MOTION PLANNING AND CONTROL ALGORITHM WITH D* PLANNER AND MODEL PREDICTIVE CONTROL IN A DYNAMIC ENVIRONMENT

The research in this report incorporates the improvement in the autonomous driving capability of self-driving cars in a dynamic environment. Global and local path planning are implemented using the D* path planning algorithm with a combined Cubic B-Spline trajectory generator, which generates an optimal obstacle free trajectory for the vehicle to follow and avoid collision. Model Predictive Control (MPC) is used for the longitudinal and the lateral control of the vehicle. The presented motion planning and control algorithm is tested using Model-In-the-Loop (MIL) method with the help of MATLAB® Driving Scenario Designer and Unreal Engine® Simulator by Epic Games®. Different traffic scenarios are built, and a camera sensor is configured to simulate the sensory data and feed it to the controller for further processing and vehicle motion planning. Simulation results of vehicle motion control with global and local path planning for dynamic obstacle avoidance are presented. The simulation results show that an autonomous vehicle follows a commanded velocity when the relative distance between the ego vehicle and an obstacle is greater than a calculated safe distance. When the relative distance is close to the safe distance, the ego vehicle maintains the headway. When an obstacle is detected by the ego vehicle and the ego vehicle wants to pass the obstacle, the ego vehicle performs obstacle avoidance maneuver by tracking desired lateral positions

Supra-maneuver, autonomous vehicle guidance in urban settings using the example of the project Stadtpilot

In der vorliegenden Arbeit wird ein System zur manöverübergreifenden autonomen Fahrzeugführung in realer städtischer Umgebung vorgestellt, das auf der praktischen Erfahrung aus der Teilnahme an der DARPA Urban Challenge beruht und im Projekt Stadtpilot weiter vertieft wurde. Die Analyse englisch- und deutschsprachiger Veröffentlichungen hat gezeigt, dass sich die autonome Fahrzeugführung bisher vorrangig auf ausgewählte Szenarien wie autobahnähnliche Umgebungen oder Geländefahrten und auf selektierte Fahrmanöver beschränkt hat. Das Verhalten der Fahrzeuge ergibt sich dabei meist durch eine Aneinanderreihung unterschiedlicher Fahrmanöver. Die Umgebungsbedingungen des Braunschweiger Stadtrings sind hingegen für ein ausschließlich manöverbasiertes autonomes Fahren aufgrund der hohen Anzahl an gefahrenen Fahrmanövern pro Streckenlänge sowie der großen Menge an verschiedenen Situationsvarianten sehr vielfältig. Ziel ist daher eine manöverübergreifende Optimierung aufeinanderfolgender Fahrmanöver sowie eine Kombination unterschiedlicher Konzepte zur Entscheidungsfindung. Im Rahmen dieser Arbeit wurde dafür ein System zur Umsetzung von Fahrentscheidungen etabliert, das manöverübergreifend und unabhängig vom gewählten Verfahren zur Entscheidungsfindung Trajektorien in Bezug auf Krümmung und Krümmungsänderung optimiert. Die resultierenden Trajektorien minimieren im Vergleich zu klassischen Verfahren die Lenkaktivität und die Querbeschleunigung bei autonomen Fahrten. Die entwickelten Ansätze wurden mit den Versuchsfahrzeugen Caroline in der DARPA Urban Challenge und mit Leonie auf dem Braunschweiger Stadtring erfolgreich getestet. In einer Weltpremiere wurde Leonie im Oktober 2010 der Öffentlichkeit vorgestellt und befuhr ein Teilstück des Braunschweiger Stadtrings mehrfach autonom im alltäglichen Straßenverkehr. Das in dieser Arbeit vorgestellte System zur manöverübergreifenden autonomen Fahrzeugführung hat dazu einen entscheidenden Beitrag geleistet.This thesis introduces an approach for the supra-maneuver, autonomous vehicle guidance that realizes complex and precise autonomous driving maneuvers in real urban settings. The approach is based on the experience of the Technische Universität Braunschweig with its participation in the DARPA Urban Challenge and was enhanced within the ‘Stadtpilot’-project. The analysis of English and German publications and proceedings has shown that research on autonomous vehicles was up to now mainly focused on highway or off-road scenarios and selected driving scenarios. The behavior of the vehicles resulted from a sequence of different maneuvers. Compared to highly structured surroundings like highway scenarios, driving autonomously on Braunschweig’s inner ring road is too complex to fulfill all requirements with a single maneuver based approach due to its high frequency of driven maneuvers and the numerousness of varied situations. A combination of different approaches for the decision finding as well as a supra-maneuver optimization is therefore suggested. As a result, a method was introduced in the context of the ‘Stadtpilot’-project that generates curvature optimized trajectories independent from the way driving decisions are found. The trajectories minimize the steering activity and the lateral accelerations compared to established approaches. The developed method was tested successfully with the autonomous vehicle Caroline within the DARPA Urban Challenge and with Leonie on Braunschweig’s inner ring road. In a world premiere Leonie’s skills were presented in October 2010 to the public, while Leonie drove a section of Braunschweig’s inner ring road fully autonomously in normal traffic repeatedly. The introduced system of a supra-maneuver optimization of path-planned sections has contributed to this success significantly

Wireless Vehicular Communication Based Solution for Road Traffic Efficiency

Wireless vehicular communications is a cutting edge set of technologies driven by the vision of providing a suite of original applications, and supported by emerging standards such as IEEE 802.11p. In turn the popularity of these applications is one of the key factors, which will drive the uptake of these vehicular communications technologies and ultimately determine their market success. Applications for vehicular communications can be placed in three main categories - Traffic Safety, Traffic Efficiency and Value-added Services (e.g. Infotainment/Business). Our work focuses on the provision of traffic efficiency services as we believe they offer an immediate benefit and can be adopted quickly by a large number of potential users. Satellite navigation systems provide a ready made deployment platform for these types of services and have already proven popular (14.4 million portable satellite navigation systems sold in Western Europe in 2007). There is also an existing trend toward complementing satellite navigation-related technology with local area wireless communications (by 2013 34% of all portable navigation devices will feature wireless cards 2). Our emphasis is on an infrastructure-based approach as this allows early adopters of wireless enabled satellite navigation devices to receive useful services from day one, regardless of the penetration level of the technology. This thesis describes Smart City, a novel framework, which purposes the use of wireless communication to make city life greener and more efficient. A major contribution to this framework is the proposed intelligent traffic management module. A route management service, which is powered by a best route selection algorithm, is put forward as a prototypical traffic efficiency service for this module. The novel aspect is that the algorithm minimizes journey times and traffic congestion as well as fuel consumption and emissions. Testing has shown how the algorithm provides-shorter journey times, a reduction in fuel consumption and harmful emissions and also results in financial savings. We have proposed and implemented an infrastructure-based communication scheme that enables prioritization of services provided to vehicles