Connected Self Driving Cars

Self driving tech includes Radar, Ultrasonic, Passive video, LIDAR (Light Detection and Radar) , IoT , sensors , advanced GPS so on . Machine learning models on Computer vision is disrupting automobile industry and likely to create a multi billion dollar market in near future..

To make the traffic and transportation infrastructure more robust, “connected cars” is an overlay technlogy which will enable vehicles to communicate when in vicinty and help mitigate accident and clogging risks.

Since each car will consume and process terabytes of data , enabling intercommunication between vehicles will help in resource sharing and auto syncing updates.

Inter vehicle communications – V2V

Vehicles can communicate wirelessly (Bluetooth, LTE, 5G ultra wideband, cellular-V2X, LoRA …) via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I), including location, speed, direction. This imporves coordination among vehicular traffic and reduces congestion.

Inter car Connectivity enables automation by serving as an additional sensor for functions like acceleration , braking , streering with activated response.

Since its inception with google Waymo , Uber and Lyft in 2016-18 with CES show stoopers such as Drive.ai , nuTonomy the future of self driving cars looks bright indeed. Today ( at the time of writing this article -2020) , self -driving or autonomous cars are not only capturing personal vehicles market but also truck / transportaion service and even fleet management and cab services.

Advantages of connnected Cars

  • Allows drivers to be warned of emerging dangerous situations in envrionmnet
  • Vehicles can anonymously and securely exchange data with other vehicles

In additon to points above there are potential indirect benifits to connected vehicles too

  • Reduces accident fatalities and injuries
  • Increase vehicle effiency and decreased carbon emissions
  • Lower fright transportation costs and land use for mobility
  • intelligent parking and prioritization in checkouot lanes

Levels of autonomy in self driving cars

Level 0 – No Automation . Manually controlled while still enabling communication like warning and alrts for blind spots etc

Level 1 – Driver Assiatance . Vehicle can control streering or speed although human driver is reponsible for his saftey and operation. Adaptive cruise conrol and lane departure are an exmaple of this level .

Level 2 : Partial Automation .  vehicle is able to detect the environment, control acceleration, breaking and steering, and navigate complex traffic situations without any driver intervention. Yet driver needs to take over instantly at any time when required.

Level 3 : Request to intervene . vehicles control all features of driving and can make informed decisions such as overtaking slower moving vehicles. The expectation is that the human driver will be ready to respond to a request to intervene when issued by the automated driving system. Traffic jam chauffeur is an example 

Level 4 : High Automation . vehicle is capable of full automation in limited conditions  ie operation design domain (ODD). this  can include environmental, geographical and time-of-day restrictions and/or the requisite presence or absence of certain traffic or roadway characteristics.

Level 5 : Full Automation  .  specified automated driving features are engaged and a human driver is not necessary.

AutoDriving Car Features that require Communication

Adaptive cruise control (ACC) is an available cruise control advanced driver-assistance system for road vehicles that automatically adjusts the vehicle speed to maintain a safe distance from vehicles ahead. Also applied to Obstacle Aware Cruise control .

Blind Spot collision warning vehicle-based sensor device that detects other vehicles located to the driver’s side and rear. Warnings can be visual, audible, vibrating, or tactile

Auto steer / lane departure warning system (LDWS) warn the driver when the vehicle begins to move out of its lane on freeways or anterial roads.

Front collision warning   of impending collisions with slower moving or stationary cars. Also applies tot Side collision warnings as well as emergency braking.

Emergency Lane Departure Avoidance

Tesla HW2 camera

Real Time Media Streaming in Connected Cars and V2V

WebRTC is a robust , royality free , end to end encrypted p2p media streaming API . After its rapid adoption by all communication providers and CPaaS solutions , WebRTC also found many applications in IoT ( Internet of things ) especially creating low latency streams.

  •  Tracking your destination on the map using edge computing
  •  Initiate video chat with the guiding server
  • QT embedded based GUI development
  • Connectivity Framework

Emergency Calling

On collision the impacted Cars notify other cars of collision ahead , if required can live stream the feed on WebRTC too so they can access teh situationa nd if required can provide emregncy reponse too . In addition the cars auto call the central communicationo server which will triger callflow to bring police , insurance , medical teams oncall with car and live stream from the cars cameras .

Cars connected to Communication platform as SIP/WebRTC capable endpoints

Connected Vehicle Solution using Next Generation Telematics Protocol ( NGTP)

NGTP is an open-source framework that allows over-the-air delivery of integrated data and services to a range of connected vehicles

References :

Active research groups for Car2Car communication

  • Mcity – University of Michigan