Integrating Demand-Responsive Transport and Fixed-Route Transit in Urban Peripheries: Spatial Design, Simulation, and Network Optimisation

Transitioning away from car dependency in urban peripheries is critical for transport decarbonisation. By pooling passengers in dynamically routed vehicles, Demand-Responsive Transport (DRT) offers a flexible alternative where fixed-route public transport is spatially and financially inefficient. However, real-world DRT pilots frequently fail to reduce car dependency. A fundamental issue is that DRT is often appraised as an isolated enterprise—judged by standalone ridership and cost-recovery—rather than evaluated for its systemic contribution to the wider PT network.

Using Leeds, UK, this thesis develops a data-driven framework integrating fixed and flexible transit. It employs spatial clustering of origin-destination flows to delineate peripheral DRT feeder zones, and an open-source activity-based demand pipeline to power an agent-based model. To overcome computational limits in tactical planning, it introduces a simulation-aided optimisation framework to jointly design public transport frequencies and DRT fleet sizes.

Operational simulations reveal a spatial trade-off: allowing DRT to operate unconstrained maximises standalone ridership by cannibalising existing public transport. Conversely, restricting DRT strictly to targeted feeder zones achieves a net reduction in vehicle-km travelled, despite lower pooling efficiency.

At the tactical level, when jointly designing public transport headways and DRT fleet sizes, the agent-based model provided useful behavioural validation for the optimisation algorithms by evaluating whether proposed solutions translated into desired agent behaviour. When maximising overall system efficiency, the objective produced networks that successfully made transit more attractive, allowing simulation feedback to guide the algorithm toward the desired mode shift. Conversely, the simulation exposed that optimising for spatial equity failed to improve the network’s competitiveness; the algorithms inadvertently achieved mathematical fairness by “levelling down” high-capacity radial corridors. Future research must therefore explore optimisation methods that account for network topology to protect essential transit routes.

Ultimately, evaluating DRT solely through standalone commercial viability is insufficient. While a focus on cost-recovery encourages deployments in high-density urban cores, this research demonstrates that such configurations often compete with existing transit and increase overall vehicle-km. Because the low-density urban periphery inherently limits direct cost-recovery, standalone profitability is a flawed metric for success; instead, authorities must adopt a “decide and provide” approach, deploying DRT as a purposefully integrated, cross-subsidised feeder to effectively break peripheral car dependency