Enabling the use of a planning agent for urban traffic management via enriched and integrated urban data

• Published in: Transportation research. Part C, Emerging technologies Emerging technologies, 2019-01, Vol.98, p.284-297
• Main Authors: Antoniou, Grigoris, Batsakis, Sotiris, Davies, John, Duke, Alistair, McCluskey, Thomas L., Peytchev, Evtim, Tachmazidis, Ilias, Vallati, Mauro
• Format: Article
• Language: English
• Subjects: Data hub; Ontology; Planning agent; Traffic control
• ISSN: 0968-090X; 1879-2359
• DOI: 10.1016/j.trc.2018.12.005

•A planning agent which addresses exceptional traffic conditions in urban regions.•A variety of traffic-related data can be represented using semantic technologies.•The strategies output were judged to be useful for exceptional situations.•The first demonstration of its kind integrating a semantic layer with an AI agent. Improving a city’s infrastructure is seen as a crucial part of its sustainability, leading to efficiencies and opportunities driven by technology integration. One significant step is to support the integration and enrichment of a broad variety of data, often using state of the art linked data approaches. Among the many advantages of such enrichment is that this may enable the use of intelligent processes to autonomously manage urban facilities such as traffic signal controls. In this paper we document an attempt to integrate sets of sensor and historical data using a data hub and a set of ontologies for the data. We argue that access to such high level integrated data sources leads to the enhancement of the capabilities of an urban transport operator. We demonstrate this by documenting the development of a planning agent which uses such data as inputs in the form of logic statements, and when given traffic goals to achieve, outputs complex traffic signal strategies which help transport operators deal with exceptional events such as road closures or road traffic saturation. The aim is to create an autonomous agent which reacts to commands from transport operators in the face of exceptional events involving saturated roads, and creates, executes and monitors plans to deal with the effects of such events. We evaluate the intelligent agent in a region of a large urban area, under the direction of urban transport operators.