Govt plans AI upgrade for bus management system

The Delhi Government, which has been seeking to expand its public bus fleet, is planning to upgrade its existing Bus Management System (BMS) by integrating artificial intelligence (AI) and machine learning to provide better public transport services, officials said on Saturday.

Currently, the Delhi Transport Corporation (DTC) has around 6,269 buses, of which more than 4500 are electric. These buses are operated from 52 bus depots across the city.

The proposal comes a month after Chief Minister Rekha Gupta said the Government is looking to increase its bus fleet to 14,000 by 2028-29, and that the number of bus depots could go up to 90.

“With the number of electric buses increasing in DTC, the Government plans to hire a company to study the current operational structure of the system and then scale up to create an AI-enabled Bus Management Software for management and monitoring of operation of electric and CNG or other fuelled buses,” an official said.

The DTC has issued a tender requesting proposals from different types of experts in this field, he added.

According to the project plan, the Bus Management System (BMS) will provide functionality for issuance, allocation and management of Electronic Ticketing Machines (ETMs).

The system will also enable depot-wise and duty-wise mapping of ETMs to buses, drivers, and conductors, along with tracking of issuance, return, status, and usage.

“The BMS will have to be fully integrated with fare collection systems to ensure seamless data synchronisation, validation of ticketing data, reconciliation of revenue and operational monitoring and reporting without manual interventions. The software will also be required to schedule DTC bus routes if any changes are made in real time by the traffic police,” the plan read.

The proposed Bus Management System (BMS) for Delhi's public bus fleet will incorporate AI and Machine Learning (ML) capabilities to improve efficiency, punctuality and maintenance.

“The system will also feature AI-based electric bus charging optimisation, fleet utilisation optimisation, operational anomaly detection, monitoring of CCTV and passenger count, predictive maintenance and battery degradation prediction, among other capabilities,” the plan read.

According to the proposal, the BMS will include AI-based features such as improved ETA prediction using historical and real-time traffic data, bus delay prediction, route optimisation, fleet allocation, depot allocation and crew scheduling.