Street Surge Technologies partnered with the Delhi Government to redesign the city’s bus network around how people actually travel. By combining mobility data, community engagement and artificial intelligence (AI), the initiative is creating a more equitable, electric and demand-responsive public transit system — expanding access to jobs, education and essential services for underserved communities.
Delhi's public transportation system has historically underserved low-income neighborhoods and women, limiting access to employment, education and healthcare while reinforcing social and economic inequalities. Traditional transit planning has relied on costly, time-intensive surveys that reach less than 1% of the population and often fail to reflect the complexity and diversity of real-world travel patterns. As a result, bus networks have struggled to align with actual demand, leaving critical gaps in service and contributing to continued dependence on private vehicles — further exacerbating congestion, air pollution and inequitable access to mobility.
- Collected mobility data from underserved neighborhoods using big data analytics, field surveys and community preference studies to capture travel patterns often overlooked by traditional transportation surveys
- Developed India's first large-scale AI-powered transit planning platform to redesign Delhi's public bus network
- Created AI-powered route optimization models to evaluate billions of possible network configurations and identify the most efficient, equitable bus routes
- Partnered with the Delhi Government, Delhi Transport Corporation, the Indian Institute of Technology (IIT) Delhi and other stakeholders to combine technical expertise, academic validation and public-sector implementation
- Established an interagency planning model that aligned bus services with metro expansion, enabling coordinated multimodal transportation planning across Delhi
- Designed a new network of 146 routes supported by 2,080 Delhi Electric Vehicle Interchange (DEVi) buses
- Prioritized first- and last-mile connectivity and improved access to metro stations
- Conducted extensive on-the-ground validation of proposed routes, bus stops, charging infrastructure and terminal locations before final implementation
- Introduced the Transit Network Health Index (NHI) to measure accessibility and network performance, institutionalizing data-driven transit planning within Delhi's transport agencies
- Integrated affordability analysis and passenger preference surveys to develop routes and fare structures that better serve women, low-income commuters and informal workers
- Expanded the AI-powered planning framework to support additional transit projects, including metro feeder services, demand forecasting and future transit network redesigns across India
- Designed a new electric bus network serving an estimated 800,000 daily riders
- Increased citywide public transport accessibility by 38%, ensuring residents in every neighborhood can access a metro station within 20 minutes
- Enabled an estimated 2.6% shift from private vehicles to public transportation, reducing traffic congestion and strengthening the city's transit network
- Reduced transportation-related carbon emissions by an estimated 280 tons per day by increasing use of public transit and electric buses
- Improved access to employment, education, healthcare and essential services for low-income residents by expanding reliable transit into previously underserved communities
- Institutionalized AI- and data-driven transit planning within the Delhi Government through adoption of the Transit NHI, creating a new model for evidence-based transportation planning
- Secured follow-on projects with the Delhi Metro Rail Corporation to optimize feeder bus services, forecast travel demand and support metro expansion planning
- Helped advance AI-powered transit planning approaches in cities across India, including Bengaluru, Chennai, Mumbai, Ahmedabad and Gandhinagar, demonstrating a scalable model for equitable and sustainable urban mobility
