IIIT Delhi, Cornell University test new transport management system
IIIT Delhi in collaboration with Cornell University and Rocky Mountain Institute are working with Niti Aayog to identify a mobility transformation model for Indian cities
Given that road congestion continues to be Delhi’s primary problem with the city having the highest road density of 1,749 km of road length per 100 km², a faculty member at Indraprastha Institute of Information Technology, (IIIT) Delhi is working on a shared transport model for employees sharing the same origin and destination.
Pravesh Biyani of IIIT Delhi in collaboration with Rocky Mountain Institute (RMI), a US-based non-profit institute focusing on energy use, and Samhitha Samaranayake from Cornell University will analyze the economic and environmental impact of ride-sharing.
They are working in collaboration with Niti Aayog to identify a mobility transformation model for Indian cities, the key constituents of the new mobility paradigm being – “shared, electric and connected.”
“In Delhi, infrastructure is not the real problem as given the number of on-road vehicles increasing daily, infrastructure would never be enough,” says Biyani, principal investigator of the project in India. “The solution is to reduce single occupancy cars on the road which cannot happen because of a weak public transport system.”
With the aim of optimizing traffic patterns, the researchers have identified certain clusters which may house employees working across workplaces located in commercial or industrial hubs.
“We, thus, plan to create a traffic building system where buses operate on fixed routes to ensure hub-level optimization,” explains Biyani. This is, in principle, like chartered buses where employees sharing the same origin and destination use one vehicle to commute. However, this is hosted on a digital platform with a fixed passenger list and a guaranteed seat for every passenger along with provisions like a monthly pass.
Currently, trial runs are being conducted on certain routes that are used by the employees of a travel company.
“For most places, we aim to provide point-to-point service (as last-mile connectivity is one of the factors that prevent people from using public transport) but in certain areas with narrow lanes, we require passengers to walk to the main road,” explains Biyani.
Another challenge is the inability to geo-code specific employee addresses within the algorithm though a corrective feedback mechanism has been embedded within the system.
The buses on these routes are GPS-enabled with routes being tracked and passenger data being collected. This data will be applied to test the city-level model developed by Samitha Samaranayake of Cornell University to analyze how ride-sharing in a fleet of high-capacity vehicles can meet taxi (generally single occupant) demand, a model created for New York City. His research examines the potential of ride sharing services in transforming urban mobility. Presently available literature examines ride sharing in terms of car pools or shared services offered by cab aggregators. However, this model aims at examining high-capacity ridesharing scaled to larger number of passengers and greater number of trips.
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