M2Smart NewsLetter Vol.6 Dec 2019 JCC AT WITH
4th Joint Coordination Committee (JCC)
by Haruka Katarao, M2Smart Resident Coordinator Warm welcome by Prof. Murty and continuous support from Prof. Desai! The 4th Joint Coordination Committee (JCC) was conducted at Indian Institute of Technology (IITH) on 17 October 2019. Welcomed by Prof. Budaraju Srinivas Murty, Director of IITH, the M2Smart researchers from IITH, Nihon University and Nagoya Electric Works exchanged their research updates. We also had a participation from Japan International Cooperation Agency (JICA). Prior to the JCC meeting, the researchers gathered and discussed the detailed group activities and data sharing between Ahmedabad City and Hyderabad City and also among the researchers in order to enhance the smooth group collaborations. Pre-meeting at IITH 1 JICA Presentation at the meeting
by Tsutomu Tsuboi, M2Smart Project Leader The 4 th JCC meeting has been held in the mid-term of M2Smart project and the transition of IITH since former IITH director, Prof. U.B.Desai has become a Professor Emeritus. Thanks to his strong leadership, he will continue to support the project as New IITH Project Manager from now on.  Prof. Murty has been selected as the New Project Director from this JCC.  We checked the current issues and confirmed solutions which required several improvements of the project management and the test bed. We finished almost of the installation of the IITH test bed equipment and will start to collect test data from each test bed and real field. The project will be continued until June 2022 and produce “Hand-Book” towards low carbon urban transportation, which is also driven by "100 Smart Cites" policy by the Indian Government. In this program, all our research organizations make the state of art level research and development such as AI traffic video capturing technology, real traffic micro simulation model based on actual real traffic field big data, sensing remote controlled traffic monitoring camera, smart phone based multimodal applicatio n for analysis residential movement in the city, and prediction of traffic condition among the all tools and analysis. The next JCC will be planned by in May 2020 in Japan. Pre-meetinat IITH On November 8th, Director Murty and Professors of IITH team have visited Nagoya Electroic Works after JCC meeting. Drector Murty and his team had a meeting with the President of Nagoya Electric Works Mr. Takaaki Hattori and joined the factory tour. Nagoya Electric Works showed the current traffic information products such as VMS, Mobile VMS and Parking System. During Nagoya meeting, we exchanged not only M2Smart project but also the potential internship between IITH and Nagoya Electroic Works for mid and long-term Japan – India collaboration. We concluded to keep our relationship and more long-term collaboration between Industry field and Academia by using M2Smart project activities. Director Murty's visit to Japan
by Tetsuhiro Ishizaka, Group 2 Leader On October 16, the day before the JCC meeting, research members from Japan and India had a meeting at the Indian Institute of Technology, Hyderabad. At first, Dr. Tsuboi, Project Leader, briefly confirmed the research theme, research plan, the future schedule and the plan of operation. Then, the leaders of each research group introduced about the progress of research and exchanged opinions among all members. And then the researchers were divided into the 4 groups to have focused discussions and discuss next steps. •Group 1 [Sensing]:Multi type vehicles recognition by 3D sensor, LIDAR in IITH test bed and by AI image processing on surveillance video camera in Ahamedabad. •Group 2 [Big Data Analysis]: Started traffic flow analysis based on actual traffic data and multimodal traffic sensing analysis (BRT, Metro connectivity). •Group 3 [Multimodal Application]: Construction of traffic micro simulator, development of driving cycle for E-Rickshaws and implementation of Multimodal application (MMA) trials in Ahmedabad. •Group 4 [CO2 Reduction]: Environment field test for PM2.5 in AMD; Situation of PM2.5 was clarified as a crucial observation and development of micro traffic simulation for Vasna and Paldi roads to verify the impact of CO2 emission reduction. Lastly, The data sharing plan was announced for M2smart project researchers. The shared folder was categorized into five drives. Drive1: Traffic data in Ahmedabad Drive2: Traffic data in IITH Drive3: Traffic movies of CCTV in Ahmedabad Drive4: MMA data Drive5: Shared documents for all member and each group The drive 1-4 are limited to be accessed by related group member who is permitted by group readers. Group 2 Group 1 3
by C Krishina Mohan (Group 1 Leader) and Debaditya Roy IEEE ITSC Conference in Oct 2019 IEEE Intelligent Transportation Systems Conference (ITSC) 2019 was held in Auckland, New Zealand from October 27-30, 2019. I attended the conference with Prof. C. Krishna Mohan from IIT Hyderabad to present the paper titled "Vehicle Trajectory Prediction at Intersections using Interaction based Generative Adversarial Networks". The paper was part of the Regular Session on Travel and Traffic Behavior (l) on October 29. We received a lot of queries on our paper regarding the use of Generative Adversarial Networks (GAN) for traffic modeling in lane-less traffic. Especially, there was one interesting question by Dr. Pavlo Tkachenko of Johannes Kepler University regarding how we modified the loss function of GAN to provide multiple output future trajectories for the same input trajectory. In the paper, we have used Variety Loss that evaluates the likelihood of multiple outputs for the same input generated by sampling the random noise in the generator of the GAN. These questions will help us in planning our future research better by understanding the association of vehicle type with vehicle behavior. Finding such associations can help in understanding traffic conditions that cause excess release of CO 2 in line with the mission of the M2Smart project. The keynote session on October 28 was really inspiring where Prof. Fei-Yue Wang, from the Chinese Academy of Sciences, talked about the future of Intelligent Transportation. The title of the talk was "Al and Grand Challenges for ITS: Parallel Transportation Systems and Transportation 5.0" that focused on knowledge automation for building better transportation systems that mimic human intuition and enhance safety. His talk also focused on using the small observational driving data in the real world to create realistic driving simulators in the virtual world and gaining deep intelligence from the same to enhance the driving capabilities of autonomous cars. He terms this process as "Parallel Driving in Cyber-Physical Social Systems (CPSS)" that features coevolving physical and artificial drivers [1]. The next keynote address on October 29 was by Prof. Miquel Ángel Sotelo from the University of Alcala, titled "Advanced Prediction of Intentions - an Essential Feature for Efficient and Safer Autonomous Driving". From pose estimation of pedestrians that helps in uniquely identifying pedestrian intention [2] to understanding the braking behavior of vehicles for better lane navigation [3], Prof. Sotelo showed alert systems for drivers that use the information obtained from these methods. Overall it was a talk that showed the transition of ideas from theory to practice. [1] Wang, Fei-Yue, et al. "From intelligent vehicles to smart societies: A parallel driving approach." IEEE Transactions on Computational Social Systems 5.3 (2018): 594-604. [2] Peng, Liqun, et al. "Rough Set Based Method for Vehicle Collision Risk Assessment Through Inferring Driver's Braking Actions in Near-Crash Situations." IEEE Intelligent Transportation Systems Magazine 11.2 (2019): 54-69. [3] Mínguez, Raúl Quintero, et al. "Pedestrian path, pose, and intention prediction through gaussian process dynamical models and pedestrian activity recognition." IEEE Transactions on Intelligent Transportation Systems 20.5 (2018): 1803-1814.
by Soumya Jana (Group 4 Co-Leader) and Anand Kakarla We have attended IEEE Global Humanitarian Technology Conference  (GHTC) 2019 held at Seattle from 17th Oct to 20th Oct to present our research on 'Comprehensive Air Quality Systems For Rapidly Growing Cities In Developing Countries' and also to gain some insight on sustainable developing activities organized by IEEE. We started my conference tour with a workshop on IOT architectures.  For our air quality systems, sensor networking is one of the important aspects to obtain air quality samples remotely. This session helps me understand many of the implementation schemes of networking such as Lora, how to setup an open data base for data logging. I also personally interacted with him on how to setup such free open source cloud data base and what all resources are needed.  We attended some of the talks on machine learning papers in these three days such as fire detection for disaster scenarios and realized their diverse applications and learnt a few techniques. Finally, Anand presented current work about an architecture which helps the governments monitor the air quality efficiently. He got a few suggestions on how to improve the networking aspect to scale up sensor deployment around the city were given.  Few comments on the effectiveness of measuring CO2 from ambient measurements was also discussed in this session. An overview of our M2smart project in was discussed with some delegates of the conference. The certain members of the session appreciated the basic idea and they also shared about similar projects being run in their respective countries. GHTC conference networking session GHTC conference during keynote Dr. Jana in one of the sessions Anand presenting at GHTC conference
by Keisuke Yoshioka (Group 3), Atsushi Fukuda (Group 4 Leader), Tetsuhiro Ishizaka (Group 2 Leader) and Digvijay S.Pawar (Group 3) To understand the effect of the CO2 emission reduction by multimodal shift transportation, we are carrying out the sensitivity analysis by micro traffic simulation. A study area is around Ashram Street (about 5.0 km) in the southwestern part of Ahmedabad city. In this area, traffic congestion occurs because of commuting traffic toward the central area during peak hours. On the other hands, a south - north metro line is scheduled for opening in 2021 and we are going to provide the dynamic information of predicted required time by VMS (Variable Massaging Sign) which was installed near the APMC metro station. In this part, we will find out the relationship between the reduction of traffic volume by modal shift and the effect to the amount of CO2 emission. Micro simulation analysis consists of 4 steps as below;
STEP1: Collecting the traffic data
Collecting the traffic data is necessary for performing micro traffic simulation. Traffic data is measured by various methods which is tried in this project Group 1.
STEP2: Estimation of OD matrix
Create the OD matrix which is the input data of micro simulation by applying the extended entropy maximization method, which considers the difference of the accuracy of data acquired by various methods. Extended Entropy Maximization Method Set the Priori matrix with 3 pattern volume (heavy:500, middle:100, light:10) 1. Introduce two parameters; connecting the priori OD table and observation 2. link volume, and representing the observation reliability Estimate these parameters which minimize the cost function w Calculate each OD pattern volume with two parameters 4- Reset the priori matrix with estimated OD volume, then estimate parameters 5・ again in the same way (Repeat 100 times)
STEP3: Micro simulation
Reproduce the traffic conditions by micro traffic simulation software VISSIM and estimate CO2 emissions. The reproducibility of the simulation is verified by saturation flow rate and vehicle trajectory on a time–space diagram based on floating car data.
STEP4: Scenario analysis
Analyze the relation between the extent of the traffic mode shift and CO2 emission reduction under several scenarios due to the opening of the metro and information provision. Figure. Validation Results of Saturation flowrate in PCU at Paldi Junction Figure. Micro traffic simulation Figure. Estimation of OD matrix Currently, we are conducting the trial calculation by using some tentative traffic data.
by Dr.Digvijay S. Pawar (Group3 Leader), Chandrashekar C and Pabbathi Uday Kumar Introduction Currently we are in process of analyzing and validating the data collected through various ITS systems deployed under M2Smart Project. In this meeting, we reviewed the performance of The Infra-Red Traffic Logger (TIRTL) deployed on NH65 for counting and classifying the traffic data. The system records the traffic data in one direction i.e., from Mumbai to Hyderabad. The TIRTL is a traffic surveillance system that is non-intrusive and capable of highly advanced functionality. The general operation mechanism of TIRTL is shown in the below Figure.
General operation
TIRTL uses Electronic devices (Receiver and Transmitter) mounted on either side of the road. It uses a two-infrared beam above the road surface to detect and record the vehicle. It also passes signal to conflict warning system located on minor road near IITH exit gate for safe merging of the vehicle into major roads.
M2Smart NewsLetter Vol. 6 Dec 2019 SAT EPS M2 Smart Website: http://m2smart.org/en/ M2 Smart Facebook: https://www.facebook.com/M2Smart-Project- 1884427054904459/?epa=SEARCH_BOX