Knowledge-Based AI Framework for Mobility as a Service
Explore how Artificial Intelligence is enhancing Mobility as a Service (MaaS) through a knowledge-based framework. Learn about personalized services, data interpretation, and the integration of various mobility sources to offer convenient and sustainable commuting options for travelers.
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Presentation Transcript
An Explainable Knowledge-based AI Framework for Mobility as a Service Enayat Rajabi1,2, S awomir Nowaczyk1, Sepideh Pashami1, and Magnus Bergquist1 1 Center for Applied Intelligent Systems Research, Halmstad University, Halmstad, Sweden 2 Cape Breton University, Sydney, NS, Canada SLIDESMANIA.COM The 34thInternational Conference on Software Engineering & Knowledge Engineering July 5th, 2022
Mobility as a Service Mobility as a Service (MaaS) combines various modes of transportation and different kinds of data to present personalized services to travellers based on transport needs. The main goal of MaaS is: to make commuting convenient for travellers. to offer travellers flexible, price-worthy, reliable, and sustainable mobility services for goods shipping and delivery. to provide an integrating various services and systems such as electronic ticketing, booking, route planning, and payment services across different modes of transportation. SLIDESMANIA.COM SEKE 2022 - July 2022 2
AI in MaaS Artificial Intelligence (AI) is increasingly used these days in MaaS to develop advanced mobility services. A knowledge-based AI system can be used to: interpret huge amount of data collected from several sources provide the right information to the right user with understandable explanations collect facts, designing rules, concepts, procedures, heuristics formulas, relationships, ontologies, statistics, or other helpful information. SLIDESMANIA.COM SEKE 2022 - July 2022 3
Knowledge-based AI Framework for MaaS There are different sources of mobility knowledge, including contextual data (weather, traffic, disruptions), operational (routes, schedules, business rules, and deliveries), personal (passengers, travellers, and drivers) and transactional (booking, tickets, and payments). We propose a knowledge-based AI framework that provides customized, explainable, and enriched services based on various types of mobility data. The framework intends to integrate different mobility data types processes, analyze them, and recommend a real-time personalized service with customized explanations based on mobility users' needs. SLIDESMANIA.COM SEKE 2022 - July 2022 4
Proposed Framework SLIDESMANIA.COM SEKE 2022 - July 2022 5
A Scenario based on the Proposed Framework SLIDESMANIA.COM SEKE 2022 - July 2022 6
Conclusions and Future Works A knowledge base that can capture travellers profiles can be combined with AI to create personalized and explainable mobility services. As a proof of concept, we designed a scenario to illustrate an example of functionality of the proposed framework, although there are some challenges such as data integration. As a future work, we are going to simulate a couple of mobility scenarios based on the presented framework using sumo simulation software (https://www.eclipse.org/sumo/) . SLIDESMANIA.COM SEKE 2022 - July 2022 7
Thank you! SLIDESMANIA.COM
