Passenger transportation and mobility
The mobility industry has been growing rapidly in the last years, and is expected to continue to do so. Supported by advanced data analytics, new use cases and applications are emerging, and the new paradigm of multimodality in passenger travel is becoming the next big thing.
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From transportation to mobility applications
The last years have been revolutionary in passenger transportation and mobility. Fueled by the pervasiveness of mobile devices and the emergence of new business models such as ridesharing and micromobility, a myriad of new applications have appeared in the areas of navigation, journey planning, and mobility platforms. More recently, driver safety and increasing transportation costs are driving the current trends in automation and efficiency, and the emergence of Intelligent Transportation Systems (ITS).
Journey planning, travel assistant, and transportation network planning are emerging use cases fueled by increasing data analytics capabilities
Another silent revolution has been happening in parallel over the years. Transportation service providers have been collecting data on driver and passenger behavior, and transport network diagnostics. This data-rich environment enables new applications in advanced analytics such as predictive maintenance, re-route decisions, and driver safety analysis. Advanced analytics, supported by Artificial Intelligence models working on increasingly large data records, are providing richer and more accurate insights to passengers and transportation service providers. Emerging use cases in this industry are:
Specialized passenger journey planning, including not only origin-destination routes, but also preferences according to traveler profile, or specific requirements such as Electric Vehicle charging on the way.
Travel assistant, as a real-time concierge service proposing route alternatives, recommendations, and new travel options that enrich the passenger experience.
Transportation network planning and optimization for city planners and transportation service providers, using scenario forecast and agent-based modeling to optimize routes, stops, fleets, schedules and fares based on seasonal trends and disruption situations. Synthetic passenger data with mobility patterns is a novel technique to profile commuter and traveler behavior in a privacy-respectful manner. Learn more about our synthetic data solutions.
The role of multimodality
Multimodal passenger mobility has the potential to play a significant role in addressing mobility challenges such as emissions reduction goals, and capacity shortages, and in moving towards a wider, more flexible and scalable, transport network. There is still a need to better understand the potential role of transportation modes when supplementing and substituting each other from a strategic and a full, tactical mobility perspective, particularly when passenger connections are considered.
Multimodality, passenger experience and inclusion, and seamless mobility are goals of the Paris Climate Agreement and the European Commission Mobility Directorate (DG MOVE). A major area of research is focused on gaining understanding of multimodal traveler requirements, air-rail modal choice decisions, and models to better depict passengers’ door-to-door journeys. This is projected across future mobility scenarios, including significant short-haul shifts from air to rail, traffic growth with strong technological support, or moving towards a more decentralized, remote and digital mobility.
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