**1. Introduction**

MaaS can be considered as a tool to improve users' mobility and, as stated by [1, 2] "MaaS provides an alternative way to move more people and goods in a way that is faster, cleaner, and less expensive than current options". In particular, also

according to [1], "MaaS is a user-centric, intelligent mobility distribution model in which all mobility service providers' offerings are aggregated by a sole mobility provider, the MaaS provider and supplied to users through a single digital platform".

Overall, MaaS application allows to optimize a trip for transit factors such as convenience, carbon emissions, and reliability. In general, the following virtuous impacts may be associated to MaaS concept:


Currently, MaaS services have been implemented in several countries such as Germany (MOOVEL, Qixxit, BeMobility, HannoverMobil), Netherlands (Mobility Mixx, NS-Business card, Radiuz Total Mobility), Finland (WHIM, Tuup), Sweden (UBIGO), France (EMMA, Optymod), Austria (Smile, WienMobil lab), USA (SHIFT) and Singapore.

A list of key fundamentals to support such a virtuous MaaS ecosystem is reported by the Maas Alliance, a public-private partnership established in 2015 by the UE encouraging and catalyzing pilot projects. Moreover, several contribution give interesting insights, such as [3, 4].

Importantly, the MaaS Alliance, in the White Paper [5], states that: "due to ecological and capacity advantages, the traditional modes of public transport, like bus, tram and metro/underground, should remain as the backbone of MaaS in urban areas". On the other hand, the integration of traditional modes of public transport with other faster, cheap and continuous services can provide new lifeblood and a new look to public transport and can be the key solution to aid sustainable modes of transport [6].

Unfortunately, if the vision of what MaaS should be is clear, the real challenge is what MaaS could become if its development completely relies on private operators. [7] reported that the main risk of a purely commercial approach to MaaS is to disincentivize sustainable trips, stating that "The success in some markets of new services, including apps for private-hire vehicles and ride-sharing, clearly has the potential to disrupt existing urban mobility services and could also encourage a shift towards car use away from more sustainable modes." Therefore, in the same study it has been concluded that "City and regional authorities need to be involved in the development of policy around MaaS at EU and national level, through new models of governance and with public sector leadership, to avoid environmental, economic and social dysfunctions."

According to the four workshops organized for the MAASiFiE project to define a European 2025 MaaS roadmap, the policy & regulation between public and private participants is seen as the most significant driver for MaaS development [8]. Along the same line, the Maas Alliance recognizes that a limited regulation can compromise the way MaaS applications impact on urban environment and compromise the public interest (e. g. decrease congestion, pollution, etc.).

However, if the problem is clear the solution is not so easy to find. One step forward was taken by the Finnish government adopting in April 2017 the Act on Transport Services (also known as Transport Code), the first known regulatory effort on this matter. However, the Code main aim is to boost the establishment of requirements for MaaS services (integration, interoperability, etc.) and the availability of data [9].

**5**

itly considered.

*Adaptive Travel Mode Choice in the Era of Mobility as a Service (MaaS): Literature Review…*

In addition, starting from the vision of how MaaS should work, a great effort need to be used in proposing models and methodologies enabling such working. MaaS platform should be supported by a simulation environment which, starting from historical and observed data, should be able to reproduce the actual state of the multi-modal transportation system and forecast the future states. This is strictly needed to "offer" updated, reliable and personalized MaaS solutions to the users. Current platforms rely on simplified hypotheses on users' travel behavior models, on transport system simulation models and on the short-midterm traffic forecasting models. Summarizing, the following drawbacks seem to characterize MaaS

• MaaS development is mainly driven by private operators; hence, they are mainly developed as business solutions in an open market, where different competitors offer their services, without a clear regulatory framework and

• Uncertainty about the way decision makers and governmental agencies may push towards specific, system-oriented transportation planning strategy due to

• MaaS platforms do not rely on consistent and reliable modelling framework able to forecast future system state and consistently modify their offer.

• Existing analyses have not clearly demonstrated the environmental and social

It is, therefore, important to preliminarily define the conceptual framework in which any MasS service should be figure out. To this aim, five pillars can be

i.MaaS service should be an open market but regulated by decision makers/ governmental agencies and characterized by a specific and organized regula-

ii.the traditional modes of public transport, like bus, tram and metro/under-

iii.MaaS service should guarantee sustainability and equity and lead toward a

iv.MaaS service should offer a smart integration of single-step transport modes

v.MaaS service should be intrinsically dynamic adapting its characteristics to

In this context, MaaS requires the ability to model mobility and travel choices. The issue is not trivial especially for travel choices [10]. First, it is necessary to model individual choices, secondly, both predictive and adaptive choices must be considered and third, the intrinsic dynamic of the choice behavior must be explic-

Indeed, the understanding and quantification of travellers' mode choices is crucial for the prediction and management of multimodal traffic networks, and

ground, should remain as the backbone of MaaS in urban areas;

without a clear vertical/horizontal integration.

the lack of a clear regulatory framework.

sustainability of a MaaS service.

car-free transportation system;

offered by different providers;

the day-to-day and the en-route travel needs.

tory framework;

*DOI: http://dx.doi.org/10.5772/intechopen.98432*

implementation:

identified.

## *Adaptive Travel Mode Choice in the Era of Mobility as a Service (MaaS): Literature Review… DOI: http://dx.doi.org/10.5772/intechopen.98432*

In addition, starting from the vision of how MaaS should work, a great effort need to be used in proposing models and methodologies enabling such working.

MaaS platform should be supported by a simulation environment which, starting from historical and observed data, should be able to reproduce the actual state of the multi-modal transportation system and forecast the future states. This is strictly needed to "offer" updated, reliable and personalized MaaS solutions to the users. Current platforms rely on simplified hypotheses on users' travel behavior models, on transport system simulation models and on the short-midterm traffic forecasting models.

Summarizing, the following drawbacks seem to characterize MaaS implementation:


It is, therefore, important to preliminarily define the conceptual framework in which any MasS service should be figure out. To this aim, five pillars can be identified.


In this context, MaaS requires the ability to model mobility and travel choices. The issue is not trivial especially for travel choices [10]. First, it is necessary to model individual choices, secondly, both predictive and adaptive choices must be considered and third, the intrinsic dynamic of the choice behavior must be explicitly considered.

Indeed, the understanding and quantification of travellers' mode choices is crucial for the prediction and management of multimodal traffic networks, and

*Models and Technologies for Smart, Sustainable and Safe Transportation Systems*

impacts may be associated to MaaS concept:

2.increasing accessibility, equity, welfare;

consumption and pollution;

3.pursuing the system optimum.

give interesting insights, such as [3, 4].

economic and social dysfunctions."

public interest (e. g. decrease congestion, pollution, etc.).

(SHIFT) and Singapore.

transport [6].

according to [1], "MaaS is a user-centric, intelligent mobility distribution model in which all mobility service providers' offerings are aggregated by a sole mobility provider, the MaaS provider and supplied to users through a single digital platform". Overall, MaaS application allows to optimize a trip for transit factors such as convenience, carbon emissions, and reliability. In general, the following virtuous

1. reducing car ownership, the use of personally owned modes, car use, energy

Currently, MaaS services have been implemented in several countries such as Germany (MOOVEL, Qixxit, BeMobility, HannoverMobil), Netherlands (Mobility Mixx, NS-Business card, Radiuz Total Mobility), Finland (WHIM, Tuup), Sweden (UBIGO), France (EMMA, Optymod), Austria (Smile, WienMobil lab), USA

A list of key fundamentals to support such a virtuous MaaS ecosystem is reported by the Maas Alliance, a public-private partnership established in 2015 by the UE encouraging and catalyzing pilot projects. Moreover, several contribution

Importantly, the MaaS Alliance, in the White Paper [5], states that: "due to ecological and capacity advantages, the traditional modes of public transport, like bus, tram and metro/underground, should remain as the backbone of MaaS in urban areas". On the other hand, the integration of traditional modes of public transport with other faster, cheap and continuous services can provide new lifeblood and a new look to public transport and can be the key solution to aid sustainable modes of

Unfortunately, if the vision of what MaaS should be is clear, the real challenge is what MaaS could become if its development completely relies on private operators. [7] reported that the main risk of a purely commercial approach to MaaS is to disincentivize sustainable trips, stating that "The success in some markets of new services, including apps for private-hire vehicles and ride-sharing, clearly has the potential to disrupt existing urban mobility services and could also encourage a shift towards car use away from more sustainable modes." Therefore, in the same study it has been concluded that "City and regional authorities need to be involved in the development of policy around MaaS at EU and national level, through new models of governance and with public sector leadership, to avoid environmental,

According to the four workshops organized for the MAASiFiE project to define a European 2025 MaaS roadmap, the policy & regulation between public and private participants is seen as the most significant driver for MaaS development [8]. Along the same line, the Maas Alliance recognizes that a limited regulation can compromise the way MaaS applications impact on urban environment and compromise the

However, if the problem is clear the solution is not so easy to find. One step forward was taken by the Finnish government adopting in April 2017 the Act on Transport Services (also known as Transport Code), the first known regulatory effort on this matter. However, the Code main aim is to boost the establishment of requirements for MaaS services (integration, interoperability, etc.) and the avail-

**4**

ability of data [9].

have become an important field of inquiry in cross-disciplinary research spanning transport engineering, computing, mathematics, psychology, and social and behavioural sciences.

The underlying assumption of most existing studies on travel mode choice is that a traveller chooses a specific mode before commencing his/her trip, which is categorized as planned behaviour. However, some studies have identified and demonstrated the influence of real-time events on mode choices,1 particularly for travellers using public transport; some examples include real-time passenger information, weather, and transport disruptions [11–13]. These real-time events may lead travellers to assess various modes in an adaptive way to the extent that the aforementioned planned behaviour plays a less significant role in the final outcome of the mode choices.

This chapter aims to give a literature overview of the existing approaches, the aims to propose an adaptive mode choice behaviour paradigm which takes into account real-time events, and provides an empirical validation of this mode choice paradigm. The real-time events include, but not limited to, availability of shared bikes at the docking station, real-time information on bus arrival time, scheduled or unexpected local disruptions, and weather conditions. This research is an important undertaking as it not only identifies a set of new factors that influence mode choices, but also presents a novel framework to study mode choice behaviour. This behavioural paradigm may pose interesting challenges from a modelling perspective and may require an integrated modelling approach for both mode choice and traffic assignment to fully capture the adaptive behaviour. The latter statement stems from the observation that many real-time factors identified above have a dynamic and stochastic nature that is related to the evolution of the system (e.g. the dynamic network loading).

The main contribution made by this paper includes:


The rest of this chapter is organized as follows. Section 2 provides an extensive review of state-of-the-art mode choice approaches. In Section 3 the bi-level mode choice behaviour paradigm that explicitly accounts for real-time events is proposed. A real-world scenario pertaining to the hypothesized adaptive behaviour is introduced in Section 4, which also presents the pilot survey study, which assesses the behavioural validity of this new concept at a qualitative level, and discusses the survey results. Section 5 introduces some remarks on the main issues of MAAS and the research perspectives regarding the proposed interpretative hypermode paradigm.
