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Jihyeok Seo, Jaehoon (Paul) Jeong, Hyoungshick Kim, and Jung-Soo Park Department of Software, SungKyunKwan University (SKKU) Electronics Telecommunications Research Institute (ETRI) Email: {seojh43,pauljeong,hyoung}@skku.edu, pjs@etri.re.kr March 27, 2015 SBUS: Smart e-Bus Battery SUbstitution Scheme in Vehicular Networks 1

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Contents Introduction Problem Formulation Travel Time Prediction The Design of Smart e-Bus Battery Substitution Scheme Performance Evaluation Conclusion 2

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Introduction The fossil fuel is not infinite and pollutes air. Recently, many e-Bus Systems have been actively developed in the world. 3

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In Korea, Smart e-Bus system has been developed in 2012. (http://www.mltm.go.kr/USR/NEWS/m_71/dtl.jsp?id=95071113)http://www.mltm.go.kr/USR/NEWS/m_71/dtl.jsp?id=95071113 Electric Bus (e-Bus) Quick Battery Changing Machine (QCM) -Special bus station supporting e-Bus battery replacement as middle cloud Traffic Control Center (TCC) -Cloud based management Road-Side Unit (RSU) Access point in vehicular networks Introduction Traffic information 4 from QCM 4

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Introduction 5

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Note: our goal is to minimize average waiting time for battery replacement in QCMs. 6

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Problem Formulation The Set of e-Buses The Set of QCMs Battery Replacement Scheduling Allocation of e-Buses to QCMs to minimize average battery replacement delay, while e-Buses can reach the QCMs by remaining battery energy. 7 The scheduling queue of e-Buses

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Problem Formulation The Set of e-Buses The Set of QCMs The scheduling queue of e-Buses The number of QCMs per e-Bus: m Select the lowest edges The number of e-Buses: n 8

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Problem Formulation The Set of e-Buses The Set of QCMs The number of e-Buses: n The scheduling queue of e-Buses The number of QCMs per e-Bus: m The number of e-Buses: n-1 The number of e-Buses: 2The number of e-Buses: 1 Select the lowest edge Selected the QCM! The number of e-Buses: n 9

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Problem Formulation e-Bus is a customer QCM is a server Task: selecting an idle server Arrivals of e-Buses Busy server Busy server Idle server e-Bus 10

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Travel Time Prediction Using loop detectors for real-time traffic measurement in simulator SUMO (Simulation of Urban MObility) Measuring travel time in road segments Measuring waiting time in intersections Predicting end-to-end travel time Yellow box is loop detector 11

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The Design of Smart e-Bus Battery Substitution Scheme The blue line indicates the reachable distance of e-Bus. Scheduling Algorithms Farthest: Selecting a QCM farthest away Random: Selecting a QCM randomly SBUS: Selecting a least busy QCM QCM1 QCM2 QCM3 QCM4 QCM5 QCM6 QCM7 FarthestRandomSBUS Idle QCM is Red. Busy QCM is Black. ??? 12

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Performance Evaluation Implemented Algorithms (SBUS, Random, and Farthest) -Using a real map (Gwang-Ju) through Java Open Street Map editor (JOSM). -Using the information of bus routes and schedule from Gwang-ju bus system. -Using a popular mobility simulator SUMO (Simulation of Urban MObility). A real map for e-Bus routes e-Buses are moving on Gwang-Ju in SUMO. 13

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Performance Evaluation -SBUS has shortest waiting time. -Farthest and Random have longer waiting time than SBUS. 14

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Conclusion Our SBUS algorithm aims at the minimization of waiting time at QCM stations for battery replacement. The effectiveness of SBUS is shown through simulation in comparison with two baseline algorithms. As future work, we will enhance our SBUS algorithm, considering background traffic, and evaluate it in simulation. 15