AI & Machine Learning

Transcription

1 AI & Machine Learning Application of Relevant Technologies for Indian Automotive Industry to address critical issues related to Road Safety Vinod Sood

2 The Problem 5+ lakh accidents have occurred in lakh people killed in these accidents The Challenge: Road Accidents are the leading cause of loss of life & property 1374 accidents and 400 deaths take place every day on Indian roads 77.1% of road accidents during 2015 have happened because of driver s fault (Source: Ministry of Road Transport and Highways report Road Accidents in India 2015 )

3 Reasons for Accidents on Indian Roads Speeding and Tailgating Phone usage while driving Drunken Driving Breaking Traffic Rules

4 Key Focus Areas Driver Behaviour Analysis ML on OBD++ Data (Telematics + Mobile Sensor) Active Safety System

5 OBD++ Advanced Analytics OBD++ = OBDII data + User Smart phone data Analysis done on OBDII data can also help raise awareness of the benefits of safe driving when directly reported to drivers (Example, fuel efficiency relation to driving patterns can help people drive safe and save money) These technologies can be used by Insurance companies, Traffic police Other Agencies.

6 Sensor Analytics Mobile app that can be used to train as well as collect sensor data Backend modelling to consume data and create labelled datasets for safe/unsafe driving

7 Benefits of mobile sensors Not everyone uses an ODBII adapter ODBII data does not capture distraction. Most accidents today are due to distracted driving where the driver is using their smart phone Smartphones add a new rich dimension to ODBII data on driver behavior Recommendation can be made to the driver to improve their driving habits

8 Detecting Dangerous Driving situations Distraction An enhanced crash detection system is able to monitor the driver and choose to intervene based on their level of attentiveness. Driver Emotion and Cognitive State Tracking Inattentiveness Eating, Texting, Talking, Putting on makeup, Gaze averted estimation Cognitive load Boredom, Confusion, Frustration

9 Advanced Driver Analytics Face Detection & Tracking Find the face bounding box for all faces in a video or still image Find fiducial facial landmarks Expression Detection Track 20 different facial expressions using CNN + SVM Emotion Interpretation 7 Emotions Joy, Sadness, Disgust, Fear, Contempt, Surprise, Anger Valence Engagement Attention

10 Deep Learning for Driver State Detection Input Labeled and unlabeled videos (+ voices) data metadata. Latest training used 1M+images. Convolutional Neural Networks Output 20 Facial expressions 7 Emotions Engagement Attention

11 Benefits Observing the driver continuously would help him to be alerted all the time. Driver can be advised to drive safely if it is not right emotional state to drive. Integrated with Active safety system to stop the vehicle if the driver is not in a position to drive. This may not be full proof solution but it would at least help to reduce certain percentages of fatal accident.

12 ML in Active safety Install a road facing Automotive grade Camera with good FOV along with advance ML capable Video processing HW. Video feed to be given to Cognitive system which can perform the following detection tasks Pedestrian, Motorist and Cyclist who sometimes gets missed from Human eye detection Traffic sign violation Stop sign Zebra crossing Cognitive system can make use of new CNN based approach to make near perfect prediction of critical objects

13 Summary Emotion data can help build a holistic view of the car driver to understand their emotional, physiological and mental state for personalization and road safety. Car sensors data along with mobile sensor data can be instrumental to improving driving ha Use AI based technologies to make car aware of its surrounding and help avoid possible accidents Let s use modern technology to make our roads much more safer.

14 HSC Skills in Automotive software

15 Connected Car Skills Network Intelligence End consumer driving reports based on OBD data Driving assistance software (Driveworks) AI Pilot apps Dealer and Fleet management Portals Machine Learning enhanced route/driving advice MS Connected Vehicle and Amazon IoT based development PowerBI based visualization Cortana and Alexa based Voice services Dashboard development (Custom Firmware, Apps), Dashboard App development, OTA client development MirrorLink App development, Smart phone connected car app development (Android Auto, other SDKs) over BT, BTLE, USB, WiFiDirect

16 HSC Connected Car Platform: Solution Accelerator Azure based car management portal. Features: 1. Reporting layer customized for OEMs/Dealers and End Users 2. Vehicle Management 3. Flexible service factory allowing new feature development, leveraging car data and trend data 4. Integration module with ODBII Connected vehicle mobile app: 1. Car diagnostics 2. Communicate with Cloud layer for driving score/intelligence 3. Ability to deploy new services 4. Notification system between cloud and app

17 Some of our Customers

18 Thank You