Jaehoon (Paul) Jeong, Taehwan Hwang, and Eunseok Lee SANA: Safety-Aware Navigation App for Pedestrian Protection in Vehicular Networks ICTC 2014, Busan, Korea October 23, 2014 Jaehoon (Paul) Jeong, Taehwan Hwang, and Eunseok Lee Computer Science & Engineering, Sungkyunkwan University

Contents I Vehicular Cyber-Physical Systems II Safety-Aware Navigation App (SANA) III Energy-Efficient Scheduling for SANA IV Evaluation Plan V Conclusion

Vehicular Cyber-Physical Systems (1/2)

Vehicular Cyber-Physical Systems (2/2)

Smart Vehicle in VCPS

VCPS Smart Services in Road Networks Jaehoon Jeong and Eunseok Lee, "Vehicular Cyber-Physical Systems for Smart Road Networks", KICS Information and Communications Magazine, Survey Paper, vol. 31, no. 3, March 2014.

Network Architecture in VCPS

Safety-Aware Navigation App (SANA) Road-Side Unit (RSU) How can we achieve the accuracy for collision detection and smartphone’s energy-efficiency simultaneously?

Motivation (1/3) Distracted Walking Most accident reason of pedestrian crossing the street 50 percent of all pedestrian deaths is among kids ages 19 and under. Take Action to Prevent Distracted Walking, http://www.safekids.org/take-action-prevent-distracted-walking

GPS power consumptions Motivation (2/3) Battery Issue Location-Based Services eat the battery 20 times faster than normal stand-by consumption. GPS power consumptions Pradip Suresh Mane and Vaishali Khairnar, “Power Efficient Location Based Services on Smart Phones”, IJETAE, vol 3, Issue 10, October 2013.

Working Time vs. Lifetime Motivation (3/3) Our Goal in SANA Prolong Lifetime of Pedestrian’s Mobile Devices (e.g., smartphone and smart watch) by using Mobility Information through VCPS. Working Time vs. Lifetime Jaehoon Jeong and Eunseok Lee, "Vehicular Cyber-Physical Systems for Smart Road Networks", KICS Information and Communications Magazine, Survey Paper, vol. 31, no. 3, March 2014.

SANA : Safety-Aware Navigation App Step 1 Predict possible collisions among vehicles and pedestrians. Step 2 Perform energy-efficient scheduling through filtering out irrelevant vehicles. Collision Prediction through Filtering out Irrelevant Vehicles Trajectory-Based Collision Prediction

Pedestrian Protection Area – Warning Area  

Pedestrian Protection Area – Pre-Warning Area  

Pedestrian Protection Area – Cases for Scheduling SANA Scheduling according to Contexts Pedestrian’s Mobile Status by Vehicle Paths 1. Sleep 2. Warning 3. Wake-Up 4. Pre-Warning

Energy-Efficient Scheduling for SANA Work-and-Sleep Schedule for Communications At time t1, Pedestrian communicates with RSU for the duration to get work and sleep schedule. At time t2 and t3, Pedestrian communicates with Vehicle 1 and Vehicle 2 to exchange the location and direction information to prevent possible collision, respectively. Energy [mJ] Time [sec] t1+δ t2+δ t3+δ t3 t2 t1 sleep 1 sleep 2 sleep 3 communicate with Vehicle 1 with Vehicle 2 with RSU Work & Sleep Schedule of Pedestrian’s Mobile Device

User Response Experiment in SANA Result 2-Step Warning (Pre-warning and Warning) reduces user response by 1.45 seconds.

VEINS for SANA Simulation Evaluation Plan Evaluation Performance Index Successful Prediction Rate Sleep Time Vehicles in Network Simulation (Veins) Integrate OMNet++ & SUMO Support simulation in real world maps Full IEEE 802.11p implementation. Specify location and speed of vehicles. Research Issue Minimize false warning False Negative False Positive VEINS for SANA Simulation in Real Road map

Conclusion We propose SANA for Safety-Aware Navigation App to protect pedestrians from vehicles in streets. SANA is Smartphone App integrated into Navigator App (e.g., Waze and Tmap). SANA uses a communication scheduling algorithm to save smartphone battery By using the mobility information of vehicles and pedestrians through VCPS. As future, we will implement our SANA in both simulation and Android App.

Vision: VCPS as Innovative Technology. Internet of Things (IoT) Interaction 1. Driving Safety 2. Data Service 3. Driving Efficiency