RoadRunner: Infrastructure-less vehicular congestion control

RoadRunner is an in-vehicle app for traffic congestion control without costly roadside infrastructure, instead judiciously harnessing vehicle-to-vehicle communications, cellular connectivity, and onboard computation and sensing to enable large-scale traffic congestion control at higher penetration and finer granularity than previously possible. RoadRunner limits the number of vehicles in a congested region or road by requiring each to possess a token for entry. Tokens can circulate and be reused among multiple vehicles as vehicles move between regions. We built RoadRunner as an Android app utilizing LTE, 802.11p, and 802.11n radios, deployed it on 10 vehicles, and measured cellular access reductions of up to 84% and response time improvements of up to 80%. In a microscopic agent-based traffic simulator, RoadRunner achieved travel speed improvements of up to 7.7% over an industry-strength electronic road pricing system.Singapore-MIT Alliance for Research and TechnologyAmerican Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi

Development of an Android OS Based Controller of a Double Motor Propulsion System for Connected Electric Vehicles and Communication Delays Analysis

Developments of technologies that facilitate vehicle connectivity represent a market demand. In particular, mobile device (MD) technology provides advanced user interface, customization, and upgradability characteristics that can facilitate connectivity and possibly aid in the goal of autonomous driving. This work explores the use of a MD in the control system of a conceptual electric vehicle (EV). While the use of MD for real-time control and monitoring has been reported, proper consideration has not been given to delays in data flow and their effects on system performance. The motor of a novel propulsion system for an EV was conditioned to be controlled in a wireless local area network by an ecosystem that includes a MD and an electronic board. An intended accelerator signal is predefined and sent to the motor and rotational speed values produced in the motor are sent back to the MD. Sample periods in which the communication really occurs are registered. Delays in the sample periods and produced errors in the accelerator and rotational speed signals are presented and analyzed. Maximum delays found in communications were of 0.2 s, while the maximum error produced in the accelerator signal was of 3.54%. Delays are also simulated, with a response that is similar to the behavior observed in the experiments

Distributed mobile platforms and applications for intelligent transportation systems

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 70-75).Smartphones are pervasive, and possess powerful processors, multi-faceted sensing, and multiple radios. However, networked mobile apps still typically use a client-server programming model, sending all shared data queries and uploads through the cellular network, incurring bandwidth consumption and unpredictable latencies. Leveraging the local compute power and device-to-device communications of modern smartphones can mitigate demand on cellular networks and improve response times. This thesis presents two systems towards this vision. First, we present DIPLOMA, which aids developers in achieving this vision by providing a programming layer to easily program a collection of smartphones connected over adhoc wireless. It presents a familiar shared data model to developers, while underneath, it implements a distributed shared memory system that provides coherent relaxed-consistency access to data across different smartphones and addresses the issues that device mobility and unreliable networking pose against consistency and coherence. We evaluated our prototype on 10 Android phones on both 3G (HSPA) and 4G (LTE) networks with a representative location-based photo-sharing service and a synthetic benchmark. We also simulated large scale scenarios up to 160 nodes on the ns-2 network simulator. Compared to a client-server baseline, our system shows response time improvements of 10x over 3G and 2x over 4G. We also observe cellular bandwidth reductions of 96%, comparable energy consumption, and a 95.3% request completion rate with coherent caching. With RoadRunner, we apply our vision to Intelligent Transportation Systems (ITS). RoadRunner implements vehicular congestion control as an in-vehicle smartphone app that judiciously harnesses onboard sensing, local computation, and short-range communications, enabling large-scale traffic congestion control without the need for physical infrastructure, at higher penetration across road networks, and at finer granularity. RoadRunner enforces a quota on the number of cars on a road by requiring vehicles to possess a token for entry. Tokens are circulated and reused among multiple vehicles as they move between regions. We implemented RoadRunner as an Android application, deployed it on 10 vehicles using 4G (LTE), 802.11p DSRC and 802.11n adhoc WiFi, and measured cellular access reductions up to 84%, response time improvements up to 80%, and effectiveness of the system in enforcing congestion control policies. We also simulated large-scale scenarios using actual traffic loop-detector counts from Singapore.by Jason Hao Gao.S.M

Extending parking assistance for automative user interfaces

Nowadays the trend in the automotive industry is to integrate systems that go beyond the scope of just maneuvering the car. Navigation, communication, and entertainment functions have become usual in most cars. The multitude of sensors present in vehicles today can be used to collect information that can be shared with other drivers in order to make the roads safer and cleaner. A more troubling issue that affects drivers is the search for free parking spots, because of the time waste, fuel consumtion and effort. There are already solutions available that try to help drivers diminish these problems, like crowdsourcing smartphone apps, but they are still far away from being a reliable solution. The overall goal of this thesis is to find new ways of providing parking information to drivers. This information is collected from vehicles which are equipped with latest sensoric hardware capable of detecting parking spaces while driving and distribute these information to the cloud, sharing it with other drivers using smartphones or vehicle's integrated displays. Though the idea is simple, there are many challanges that need to be addressed. The thesis will also look into ways of improving parking surveillance for vehicles to make them less susceptible to vandalism and thefts, by using latest vehicle-integrated video camera systems. A study will be made to see what information drivers want to have related to parking and how this information can be displayed to them. Further, a cloud based-implementation of such a system will be presented in detail and an evaluation will be made to see how the system behaves in the real world.Der aktuelle Trend der Automobilindustrie ist es Systeme zu integrieren, die über das Ziel hinausgehen ein Fahrzeug lediglich zu fahren. Navigations-, Kommunikations- und Entertainmentfunktionen sind inzwischen üblich in vielen Fahrzeugen. Die Vielzahl an verfügbaren Sensoren, die heutzutage in Fahrzeugen verfügbar sind, ermöglichen es Informationen zu sammeln welche mit anderen Fahrern geteilt werden können, um Straßen sicherer und sauberer zu machen. Ein nervenauftreibendes Problem, welches viele Fahrer aufgrund des Zeitverlustes, des Benzinverbrauchs und des Aufwands beeinflusst, ist die Suche nach freien Parkplätzen. Es existieren bereits Lösungen, diese Probleme für den Fahrer verringern, wie z.B. Crowdsourcing Smartphone Apps, aber diese sind immer noch weit davon entfernt zuverlässige Lösungen darzustellen. Das übergreifende Ziel dieser Thesis ist es neue Möglichkeiten zu finden dem Fahrer Parkinformationen zur Verfügung zu stellen. Diese Informationen werden von Fahrzeugen gesammelt, welche mit der neuesten Sensorik ausgestattet sind, die es ermöglicht während der Fahrt Parkplätze zu detektieren und diese Informationen über die Cloud zu verteilen und somit mit anderen Fahrern über Smartphones oder integrierte Displays zu teilen. Obwohl die Idee recht einfach ist gibt es viele Herausforderungen, die bewältigt werden müssen. Dazu wurde auch eine Studie ausgetragen, um zu untersuchen welche Informationen Fahrer im Bezug auf Parken gerne zur Verfügung hätten und wie diese Informationen ihnen angezeigt werden können. Weiterhin werden in dieser Thesis Möglichkeiten evaluiert die Überwachung von Fahrzeugen durch die Verwendung von in Fahrzeug integrierten Videosystemen zu verbessern. Eine Cloud-basierte Implementierung des beschriebenen Systems wird im Detail präsentiert und eine darauf basierende Evaluierung vorgestellt, um zu sehen wie sich derartige Systeme in der realen Welt verhalten

A Distributed Service Delivery Platform for Automotive Environments: Enhancing Communication Capabilities of an M2M Service Platform for Automotive Application

Full version: Access restricted permanently due to 3rd party copyright restrictions. Restriction set on 11.04.2018 by SE, Doctoral CollegeThe automotive domain is changing. On the way to more convenient, safe, and efficient vehicles, the role of electronic controllers and particularly software has increased significantly for many years, and vehicles have become software-intensive systems. Furthermore, vehicles are connected to the Internet to enable Advanced Driver Assistance Systems and enhanced In-Vehicle Infotainment functionalities. This widens the automotive software and system landscape beyond the physical vehicle boundaries to presently include as well external backend servers in the cloud. Moreover, the connectivity facilitates new kinds of distributed functionalities, making the vehicle a part of an Intelligent Transportation System (ITS) and thus an important example for a future Internet of Things (IoT). Manufacturers, however, are confronted with the challenging task of integrating these ever-increasing range of functionalities with heterogeneous or even contradictory requirements into a homogenous overall system. This requires new software platforms and architectural approaches. In this regard, the connectivity to fixed side backend systems not only introduces additional challenges, but also enables new approaches for addressing them. The vehicle-to-backend approaches currently emerging are dominated by proprietary solutions, which is in clear contradiction to the requirements of ITS scenarios which call for interoperability within the broad scope of vehicles and manufacturers. Therefore, this research aims at the development and propagation of a new concept of a universal distributed Automotive Service Delivery Platform (ASDP), as enabler for future automotive functionalities, not limited to ITS applications. Since Machine-to-Machine communication (M2M) is considered as a primary building block for the IoT, emergent standards such as the oneM2M service platform are selected as the initial architectural hypothesis for the realisation of an ASDP. Accordingly, this project describes a oneM2M-based ASDP as a reference configuration of the oneM2M service platform for automotive environments. In the research, the general applicability of the oneM2M service platform for the proposed ASDP is shown. However, the research also identifies shortcomings of the current oneM2M platform with respect to the capabilities needed for efficient communication and data exchange policies. It is pointed out that, for example, distributed traffic efficiency or vehicle maintenance functionalities are not efficiently treated by the standard. This may also have negative privacy impacts. Following this analysis, this research proposes novel enhancements to the oneM2M service platform, such as application-data-dependent criteria for data exchange and policy aggregation. The feasibility and advancements of the newly proposed approach are evaluated by means of proof-of-concept implementation and experiments with selected automotive scenarios. The results show the benefits of the proposed enhancements for a oneM2M-based ASDP, without neglecting to indicate their advantages for other domains of the oneM2M landscape where they could be applied as well