Experiments with Vehicle Platooning

Technical report, IDE1047, June 2010 Experiments with Vehicle Platooning Master’s Thesis in Embedded and Intelligent Systems Essayas Gebrewahid & Fareed Ahmed Jokhio {essgeb08, farjok08} @student.hh.se Supervisor: Veronica Gaspes School of Information Science, Computer and Electrical Engineering Halmstad University Experiments with Vehicle Platooning Master’s Thesis in Embedded and Intelligent Systems School of Information Science, Computer and Electrical Engineering Halmstad University Box 823, S-301 18 Halmstad, Sweden June 2010 Description of cover page picture : Four scenarios of the project. Scenario 1: Platoon stability Scenario 2: Joining a platoon Scenario 3: Joining a platoon at a traffic signal Scenario 4: Merging traffic at blind-crossing EXPERIMENTS WITH VEHICLE PLATOONING Abstract This thesis is concerned with an experimental platform for studying cooperative driving and techniques for embedded systems programming. Coop- erative driving systems use vehicle-to-vehicle and vehicle-to-infrastructure communication for safe, smooth and efficient transportation. Cooperative driving systems are considered as a promising solution for traffic situations such as blind crossings. For the thesis work we use a robotic vehicle known as PIE (Platform for Intelligent Embedded Systems) equipped with a wireless communication device, electrical motors and controlled via a SAM7-P256 development board. For the infrastructure side we use a SAM7-P256 development board equipped with nRF24l01. Vehicle to vehicle and base station to vehicle communication is established and different platooning scenarios are implemented. The scenarios are similar to platooning scenarios from the Grand Cooperative Driving Challenge GCDC1. The performance of the platoon control algorithm is measured in terms of throughput (a measure of string stability), smoothness and safety, where the safety requirements serve as pass/fail criteria. 1http://www.gcdc.net/ i Acknowledgements We would like to express our appreciation to our supervisor Veronica Gaspes. Thanks for giving us the opportunity to work under her supervision. She provided us with valuable information about TinyTimber, she guided us during the development of the thesis project, with her help we successfully completed this masters thesis project. Thanks to Tommy Salomonsson for providing material and valuable information about wireless communication between the robotic vehicles. Thanks to Josef Bigun for helping us with the image processing part and for getting the location of the robotic vehicles using spiral patterns. ii Contents Abstract i Acknowledgements ii List of Figures v 1 Introduction 1 1.1 Motivation . .3 1.2 Project Description . .4 1.3 System Architecture . .5 1.4 Outline of the thesis . .7 2 Background 9 2.1 Platooning Systems . .9 2.2 Embedded systems programming . 11 2.2.1 Embedded systems programming with TinyTimber . 13 2.3 Related works . 16 3 Vehicle Platooning Scenario 19 3.1 Judgement criteria . 19 iii CONTENTS 3.2 The Four Scenarios . 20 3.2.1 Scenario 1: Platoon stability . 20 3.2.2 Scenario 2: Joining a platoon . 23 3.2.3 Scenario 3: Joining a platoon at a traffic signal . 25 3.2.4 Scenario 4: Merging traffic at blind-crossing . 26 4 Implementation and results 29 4.1 Image processing . 29 4.2 Implementation of wireless communication network . 32 4.2.1 nRF24L01 Transceiver . 32 4.2.2 Wireless communication . 33 4.3 Implementation of vehicle control . 35 4.3.1 Path tracking . 36 4.3.2 Platoon control . 38 4.4 Results . 45 4.4.1 Platoon control . 45 4.4.2 Packet loss . 51 4.4.3 Path tracking control . 51 5 Conclusion and future work 53 5.1 Conclusion . 53 5.2 Future work . 53 iv List of Figures 1.1 Components of the experimental platform . .6 2.1 Playground for autonomous vehicles running in limited space. The figure is taken form project description of the course \De- sign of Embedded and Intelligent Systems" . 17 3.1 Platoon Stability . 21 3.2 Desired Spacing . 22 3.3 Joining a platoon . 24 3.4 Joining a platoon at a traffic signal . 25 3.5 Merging traffic at an intersection . 27 4.1 Block diagram of the Project . 30 4.2 Spiral pattern and colour dot on top of vehicles. 31 4.3 Control structure of platooning System. a, v and d are acceleration, velocity and inter-vehicle distance. The subscript l, p and i indicated platoon leader, immediate leader and the vehicle itself . 35 4.4 Tangential Angle and Radius of vehicle when it moves in circular path . 36 4.5 Platoon control . 39 v LIST OF FIGURES 4.6 Acceleration and deceleration graph. Red color indicates platoon leader, blue indicates participant 1 and green indicate participant 2 . 46 4.7 Velocity of Leader and Participant vehicles. Red color indicates platoon leader, blue indicates participant 1 and green indicate participant 2 . 47 4.8 Distance Error for participant vehicles. Blue indicates participant 1 and green indicates participant 2 . 48 4.9 String stability of participating vehicles. Blue indicates participant 1 and green indicates participant 2 . 49 4.10 Vehicle movement on circular path. Yellow represents platoon leader and blue and green represent participants . 52 vi Chapter 1 Introduction Cooperative driving systems are one of the promising application fields of Intelligent Transportation Systems. In cooperative driving systems vehicles cooperate and organize their activities by exchanging information via the existing wireless communication infrastructure. A vehicle communicates with other vehicles and with roadside infrastructure to make decisions based on the current traffic situation. Due to the raise in the number of vehicles on roads, traffic congestion, high fuel consumption, air pollution and traffic accidents are common problems throughout the world. But a study made by TNO [5] shows that within the next 10 to 15 years, cooperative driving systems will reduce vehicle hour loss by 50%, traffic death rate by 25%, CO2 emission by 10% and air pollution by 20% . This can be achieved by creating a platoon of vehicles that cooperate with each other to travel with minimum inter-vehicular distance. Especially for traffic congestion, platoon of vehicles is a promissing solution. To speed up the development of cooperative driving systems GCDC arranges a contest in March 2011 in the Netherlands. This contest pre-defines four scenarios to test the efficiency of cooperative control algorithms [7]. After the competition in 2011 the GCDC organizers intend to conduct a series of international events at various continents and will gradually put more challenging traffic situations to improve cooperative driving technology in the future. GCDC is open for universities, research institutes and other companies for participation. 1 Introduction In GCDC among the four scenarios, the first three scenarios are related to vehicle platooning and the fourth is for testing the efficiency of the algorithms at blind crossing. The 2010 GCDC focused on platooning with a short inter-vehicle distance [18]. The goal of vehicle platooning is to achieve better safety, efficient vehicle driving, reduction of travelling time, reduction of traffic congestion, comfort for driver and passenger, reduction of air pollution and maximization of highway throughput. In platooning there are fewer changes in acceleration / deceleration and vehicles are driven much smoother as compared with ordinary driving, hence it provides better comfort for driver as well as passengers. With vehicle platooning it is possible to drive vehicles close to each other and not compromising on safety. Vehicle platooning reduces drag and as a result less fuel is consumed and there is less pollution. Drag is a force that opposes vehicles motion, which is generated by interaction of the vehicle body with air flow. Drag reduction is possible due to less inter-vehicle distance. In the 2010 GCDC contest the driver still had some role, like controlling the lateral movement. But on the other hand, the SARTRE (Safe Road Trains for the Environment) project[1] is developing and testing technology for automatic vehicles and they claim that Cars that drive themselves can become reality within ten years. If the SARTRE project succeeds and their claim becomes true then the technology will have the potential to improve traffic flow, it will reduce travelling times, there will be less accidents, and also less fuel consumption and hence lower CO2 emissions. In the context of cooperative driving wireless communication among vehicles plays an important role. CERES, the Centre for Research on Embedded Systems at Halmstad University in cooperation with other partners from industry, is working on a Vehicle Alert System project. The focus of the project is in the areas of wireless communication, wireless sensor networks, cooperating embedded systems and vehicular ad hoc networks (VANETs). [11] discuses that, even if two vehicles can not communicate directly, they can still share their information via other vehicles. They can also use information collected by sensors of other vehicles and can avoid accidents in hazardous locations. Lidström[11] has worked on communication disturbance detection 2 EXPERIMENTS WITH VEHICLE PLATOONING which is an approach for estimating the reliability and availability of wireless communication at hazardous locations. If correct information is available on time then safe vehicle driving can be achieved. In [12] cooperating vehicle safety systems are discussed. To maximize traffic safety, application independent cooperative functions can be used to monitor and prioritize the use of wireless communication medium [12]. In order to avoid accidents the reaction time of a driver should be faster. For platooning systems communication technology already exists and the cost of installing this technology in vehicles is not too much. For positioning systems infrastructure is already there and insurance companies are successfully using it. In 1996 at the university of California a project was carried out as part of the California PATH program in which safe platooning systems were designed for automated highway systems [4].

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