This is the first in a series of posts surrounding Song Sang Koh’s research for The LiFE Project.
Song Sang Koh’s research focuses on the optimisation of urban transport networks through the use of artificial intelligence. His combination of reinforcement learning and a neural network will allow a better understanding of the transport network, leading to better traffic management. This in turn will minimise the total travel time of every driver within the urban transport network, leading to a decrease in fuel consumption and a reduction in carbon emissions. Koh conducts his research at John Moores University in Liverpool, working in partnership with Red Ninja Studios.
Over the past decade, sustainability and resilience have become a major concern in urban development. Globally, more people live in urban areas than in rural areas, with 54 percent of the world’s population living in urban areas in 2014, and a projected 66 percent of the world’s population living in urban areas by 2050. With ever-growing populations, cities around the world struggle to transform their infrastructure and make necessary changes in order to meet the daily basic needs from both an economical and environmental perspective. It has caused severe damage to the environment, such as an increase in the consumption of natural resources. It also contributes to air pollution, noise, and dust, which can be hazardous to urban citizens. Therefore, resilient transport network development plays an important role in the urbanisation and sustainability of the cities of tomorrow.
In general, sustainable development aims at creating and maintaining our options for prosperous social and economic development. It emphasises an optimal balance between social needs, economic needs, and environmental needs. However, resilience development aims to provide the capacity to absorb the impact of accidents and maintain the availability of the network’s function during the occurrence of unforeseen events.
Sustainability and resilience are key factors in urban transportation networks to ensure it will meet the basic needs of society and individuals, without seriously damaging the environment or decreasing roadway safety. For instance, traffic congestion is always a major issue within urban planning, especially as there is an increase in the number of vehicles on the roadway without an equivalent upgrade to urban infrastructure. Although many different methods of route optimisation have been widely studied, the majority of these are designed solely for individual users and lack consideration from an urban perspective in terms of sustainability and resilience. Furthermore, local authorities to date still lack efficient technical solutions to manage or distribute the traffic in an urban transportation network.
To fulfil such research gaps, it is essential to explore the sustainability and resilience of transport networks, including the development of new routing algorithms which take into consideration the wider transportation network and alternative systems.