Analytics for Demand Responsive Online Intelligent Transport (ADROIT)

Description

Sustainable transport is central to sustainable development, providing access to work, vital services, leisure, friends and family while enabling safe mobility at a reduced environmental impact. Providing affordable and flexible transport can reduce inequalities and empower those less able to access work and urban life. Effective transport is central to building a fairer society and low-carbon transport is central to a sustainable future. 

While many are fortunate to have access to a car, private mobility has a high carbon footprint due to the manufacturing, use, storage and disposal of vehicles. Private cars spend 96% of their time idle and are responsible for 60.7% of total CO2 emissions from road transport. However, as a society, we are attached to the convenience and comfort of car ownership.  

The project seeks to understand and build models for services that reduce CO2 emissions while mitigating societal loss. Moreover, it will support linking poorly served geographies and alleviating the challenges of the elderly and disabled to afford mobility.

This research proposes the development of the mathematical tools needed to deliver sustainable, flexible, shared mobility. The service is a hybrid of a bus and a taxi, where rides can be requested in a similar way to a taxi, while the vehicle may be servicing other customers simultaneously along the route. Specifically, this is known as a Demand Responsive Transport Service (DRTS).

This project is funded by the EPSRC. (Grant Ref: EP/X020835/1 – A scaled and sustainable demand-responsive transport service.)

Research overview

In order to design a DRTS, the project needs to address a number of challenges.  

• The service needs to be attractive and meet customer requirements. We will undertake data collection from target demographics to understand preferences and attitudes towards shared mobility and the expectations around price and service quality.  

• The service needs to be efficient and scalable. We will design novel algorithms that optimise the routing and scheduling. Solving these large-scale, hard combinatorial optimisation problems, in real-time will enable a transformation of DRTS, part of the emerging sector of scaled shared transport solutions, encouraging increased take-up of shared mobility. Similar services, such as Dial-a-Ride, exist to meet specific needs but they are reduced in scope and heavily subsidized by local councils and the Department for Transport. They lack route planning flexibility and cannot manage high demand.  

• Financially sustainable across a wide range of routes. We will develop dynamic pricing models that will integrate with the scheduling and routing. Dynamic pricing will support incentivising more efficient scheduling and enable some subsidisation of less profitable routes.  

At scale, with optimized dynamic pricing and routing, realistic demand forecasts, informed accurate behavioural models, and incentivised by policies that enhance their acceptance and induce voluntary behaviour changes, DRTS would be financially viable and more sustainable than private car use. The original transformative science in the form of efficient, complex optimization algorithms, and the rich understanding of preferences and attitudes towards shared mobility developed in this project will help enable DRTS to be both efficient and cost-effective; thus, promoting shared mobility and significantly reducing CO2 emission of local travel.

Key findings

We anticipate that the project will: 

• Provide insights into behaviours and attitudes towards shared mobility and the service experience needed to incentivise car owners to use a DRT service 

• Develop effective scheduling and routing optimisation algorithms that can run in real-time and provide efficient schedules across a mixed fleet of vehicles. 

• Advance methodologies around integrating dynamic pricing into routing and scheduling services. 

• Deliver a large-scale simulation that can be used to test a wide range of user scenarios and support implementation decisions and understanding of investment scenarios and volume of demand required to make the service sustainable. 

• Inform transportation policy with respect to initiatives designed to reduce congestion and pollution in cities. For example, how to price clean air tariffs and parking charges.

Upcoming event

On 21 November 2023, we will be running a workshop in Leeds to inform the scope and specification of the project. If you would like to attend and contribute your ideas, please RSVP to Alex Kliszcz (a.kliszcz@leeds.ac.uk) before Friday 10 November.