The Short-Term Potential of Artificial Intelligence for Traffic Management

Abstract

The field of Artificial Intelligence (AI) seems promising for traffic and transport. All kinds of possibilities and applications are suggested, but are these suggestions feasible and when will they become available? To address this question for traffic management, a picture of the field and its latest, state-of-the-art innovations is painted and opportunities for the future are investigated. Applications that have already been implemented or tested as pilots are described, as well as those applications that domain experts expect to be developed within one to five years, with a focus on applications that generate the greatest improvements in terms of traffic flow, safety, and sustainability. Also, the study looks at what the possible pitfalls and challenges could be during development and implementation.
The research method consisted of several elements. Interviews were conducted with experts in the field of AI and traffic management and the interviewees were asked about possible opportunities and obstacles. In addition to the interviews, relevant and current sources describing applications of AI in traffic management were studied. The focus was on the added value of applications that have already been implemented. Based on the information gathered, a selection of the most promising future applications was made and these applications were discussed in a workshop.
The current applications of AI in traffic management show that the focus is now on performing one specific task, using a limited number of data sources. It also shows there is great future potential for AI-based applications that combine multiple data sources or address multiple complex tasks in a combined fashion. This could, for example, lead to new insights about traffic being derived from data; insights that are not readily apparent with existing methods and a single data source.