TSL is part of a collaborative project that was awarded a government grant worth £2m, seeking to model how Londoners might respond to fleets of self-driving, shared vehicles alongside existing transport options in London. The project will gather data to inform a state-of-the-art traffic and ridesharing simulation framework.
The SHIFT consortium also includes Oxbotica and Bosch and Transport for Londonwho will together aim to model the impacts of these potential new autonomous ride-sharing business models on London and the travel choices that people may make were they to be developed and introduced.
SHIFT will perform computer simulations on three case study boroughs, selected to represent the diverse range of commuting patterns, geographies and service configurations across London. The Imperial team will concentrate on modelling the decision processes that could affect the demand for an autonomous ride-sharing fleet, building upon earlier work carried out by TSL.
TSL models used in the SHIFT project
Optimal fleet assignment algorithms are used to match vehicles with passengers, while minimising waiting times and vehicle travel. Shared trips are possible using efficient customer matching models.
SHIFT simulations will monitor the energy consumption of vehicles in the fleet, and will be used to determine the optimal design of supporting charging infrastructure.
Impacts to other road users
Our models will be used to predict the adoption by the autonomous ridesharing services by the public and estimate shifts in traveller preferences and the interaction between competing providers.