Mitigating Bus Bunching using Reinforcement Learning

An ideal bus route would offer highly predictable inter-bus arrival times to travellers, in particular, overcoming the well-known ‘bus bunching’ phenomenon – “I waited ages then three came together!”. There are many sources of variability in journey times such as traffic conditions, the impact of traffic lights, and interference between buses themselves, e.g.,  queueing at … Read more

Slot-based Motorway Driving for Connected and Automated Vehicles

The Research Ireland funded ClearWay1 project is investigating new models of road management is which each vehicle is allocated a so-called ‘slot’ in which to travel for the duration of its journey. Adherence to travelling in its allocated slot ensures congestion-free travel from source to destination for each vehicle (in the absence of unexpected events). … Read more

ML-powered Parking Assistance System

Parking in busy locations eg at large-scale events (such as concerts and mass-participation sporting events) or in shopping centres at busy times (eg during ‘Christmas shopping’) often results in traffic congestion in surrounding areas (see, for example, [1], for an extreme example!). This may arise due to vehicles searching for, entering, and leaving parking spaces … Read more

Swarm Intelligence for Travel Time Reliability

Poor travel-time reliability, meaning that travel times for the same journey are highly variable and unpredictable, gives rise to similar negative impacts on the environment and the economy as does traffic congestion. Moreover, being able to offer a high degree of travel-time reliability will facilitate the uptake of sustainable road transportation including future public, shared, … Read more