Exploiting traffic data to improve asset management and citizen quality of life

Abstract

The main goal of this project was to demonstrate how large data sources such as Google Maps can be used to inform transportation-related asset management decisions. Specifically, we investigated how the interdependence between infrastructures and assets can be studied using transportation data and heat maps. This involves linking the effect of disruptions in lower-order assets to travel accessibility to private and public infrastructure. In order to demonstrate the viability of our approach, we conducted 5 case studies, 3 public and 2 private. On the public side, we collaborated with two county councils in the United Kingdom, specifically Cambridgeshire and Hertfordshire, and offered solutions to existing infrastructure-related problems proposed by them. For Cambridgeshire, we analysed the accessibility to Cambridge University’s new research centers and the criticality of roads leading to Addenbrooke’s Hospital in Cambridge. Similarly for Hertfordshire, the accessibility to different critical assets in the county were examined with the aim of supporting planning decisions. In addition, to highlight how our approach can bring benefits to private citizens, we solved two examples of commuting-related problems posed by students at the Institute for Manufacturing (IfM). We conclude that heat maps generated using the Google Maps API are powerful and efficient tools for use in infrastructure asset management. Our approach appears to be more cost-efficient and offers a higher quality of visualisation and presentation than other available tools. Furthermore, there exists the potential for a commercial spin-off: our approach can be employed in local, regional and national administrations to inform infrastructure-related decision-making, and can be used by commercial parties to improve employees’ commutes, parking, et cetera