Topics In Demand
Notification
New

No notification found.

GenAI impact on Next Gen Transport sector
GenAI impact on Next Gen Transport sector

February 29, 2024

104

0

The next generation of transportation relies on electronics, sustainability and experience at the core of their design, Gen AI has an influence on each mode of the envisioned next gen transportation ecosystem. There are five specific areas of focus in the market, EVs (Electric Vehicles), AVs (Autonomous Vehicles), Micro mobility (First mile connect), Hyperloops (Superfast Mass Transits) and UAM (Urban Air Mobility).  There are many in evolution and variations like eVOLT (Electric Vertical takeoff and landing) or integrated signaling for traffic control for management. There are a number of areas evolving and to name a few Multimodal Integration (Seamless route integrations), Sustainability (vehicle design), Connectivity and automation (Traffic management, Alternatives), Shared Mobility (resource sharing and vehicle footprint reduction). The transformation in the transportation sector opens up limitless opportunities for Gen Ai as an essential building block into technologies natively. 

 

Gen Ai is already revolutionizing the area of Autonomous Driving, Route optimizations, obstacle avoidance and self-management (Parking, blind spots etc.). There is however a need to expand this horizon to manage the environment effectively for hassle free transportation. There are 3 key areas we will focus upon 1. Customer Experience 2. Efficiency and Performance and 3 Security 

 

Gen AI has a pivotal role to play in the Customer Experience. 

Pre-ride experience can be down into the buying experience and experience of ride selection as two distinct areas. Gen Ai can influence the purchase decisions based on features, personal preference, economics, sustainability as well as Insurance cost optimization based on a persona and a blend of previous driving behaviors. Areas that would eventually change is to take a test drive using a VR/VR headset and the retain selection via Gen Ai based on historical data beyond social media aggregation for persona creation. 

 

 The pre-owned car market in India is projected to be USD 31.62 Billion, so data analysis and recommendation via a Gen AI system for   leasing v/s buys v/s preowned, Vehicle history analysis based on VIN as well as effectively predicting the lifespan based on the model, terrain in which the vehicle was used, accident history etc. can add value to the buyer.     

 

Ride selection is the other area where Gen AI will have a great influence on. Ride mode aggregation, environment data aggregation and prediction of the most cost effect transport across segments, Optimal time and as well as transport integration will be a key for effective transportation. Gen AI with its ability to predict best routes and cost-effective selection of transportation will play a critical role in urban transportation. There are other areas including POI, travel budget management for a trip / month will effectively be offloaded to a Gen-Ai based over the top travel apps

 

Efficiency and Performance of urban transport is the other area with an umbrella of use cases that can be served effectively via Gen Ai integration. While predictive maintenance, remote detection, and analytics of the internal components are anyway part of the standard. Gen AI can provide Real time coaching for drivers based on environment (Traffic, weather) as well as anticipated traffic flow by suggesting the acceleration and braking which are few of the key parameters governing the life of the EV. Gen Ai can help with adaptive braking as well as regenerative mechanism by determining the quantum of the temporarily stored energy as well as the mechanism to dissipate or reintroduce into the system based on the scenario. Gen AI can effectively manage the powertrain control and adjust the power delivered via optimizing the torque delivered for a specific situation based on predictions of the real time data. 

 

While a Vehicle has a range defined per change the consumption depends on the climate control and the terrain. Driving on hilly terrain consumes 10%-20% more as compared to flat surfaces. Gen AI can effectively be used to plan trips, charging frequencies, optimal distance / terrain selection based on routes. 

 

Micro mobility consisting of a network of docking stations, charging points, Transport integration, Safety and in terrain planning can easily be done using GenAi based predictions, current state of inventory at specific docking points. Time to transfer, average time of ride based on age, gender, Micro mobility mode, health conditions of the user etc. 

 

Lastly driving behavior could be persona based and driver profile management for suspension control, steering, breaking and acceleration can be adjusted and accounted for accurate predictions via Gen AI 

 

Security in next generation transportation opens a wide range of opportunities with Gen AI, some of which have already been implemented in the ease of access space like face identification and gate control. But on the other hand, the attack surface has increased with external communication including V2X which uses DSRC (Directed Short Range Communication) as well as standard WIFI and cellular technologies. GenAI can play a key role in conjunction with security systems in analyzing the patterns and making the traffic for use. ECUs heavily relies on a Real time operating system like Autosar, QNX or custom versions and there are a series of security attacks possible which a GenAI based system can detect on the traffic patterns and alert or prevent nonstandard parameter modification. A GenAi sentry to manage the valid states of various parameters which are susceptible to attacks can be managed in an isolated namespace and valid parameters passed back for the ECUs for acting upon this. 

 

While Gen AI opens up a lot of possibilities to modernize transportation, new mechanisms as well as synthetic data for effective modeling of the scenarios will take time. Hopefully with the expanding features and improving efficiencies of Gen Ai in terms of interpretation logic can greatly transform the transportation industry in the coming years.

 

 

 


That the contents of third-party articles/blogs published here on the website, and the interpretation of all information in the article/blogs such as data, maps, numbers, opinions etc. displayed in the article/blogs and views or the opinions expressed within the content are solely of the author's; and do not reflect the opinions and beliefs of NASSCOM or its affiliates in any manner. NASSCOM does not take any liability w.r.t. content in any manner and will not be liable in any manner whatsoever for any kind of liability arising out of any act, error or omission. The contents of third-party article/blogs published, are provided solely as convenience; and the presence of these articles/blogs should not, under any circumstances, be considered as an endorsement of the contents by NASSCOM in any manner; and if you chose to access these articles/blogs , you do so at your own risk.


images
Sripathy Balaji Venkataramani
Sr. Vice President - Products and Solutions

A accomplished product innovator, Concept realizations and incubation, Large Deals architect

© Copyright nasscom. All Rights Reserved.