Keywords

1 Introduction

Automated minibuses for public transport are expected to contribute to sustainable urban mobility. By combining automated, connected, shared and electric technologies, the automated minibuses could improve transport accessibility, efficiency and reduction of greenhouse gases (GHG) (Jones & Leibowicz, 2019). They have the potential to play a role in a shift from vehicle ownership to shared mobility services (Shaheen & Chan, 2016) and to reduce transport externalities (Lim & Taeihagh, 2018). Nonetheless, one cannot take for granted that the deployment of innovation and new technologies per se will contribute to sustainable mobility. It rather depends on certain premises, planning and policies to frame the automated minibuses deployment.

The study by Taiebat et al. (2018) points out the main gaps concerning connected and automated vehicles’ impacts; for instance, the net effect of AV technology on energy consumption and emissions in the long term remains uncertain. In addition, the broader society-level impacts and behavioural changes associated with AVs are also unclear. The study highlights that the ‘synergetic effects of vehicle automation, electrification, right-sizing, and shared mobility are likely to be more significant than anyone isolated mechanism’.

AVs, especially for private use, could lead to an increase in vehicle kilometres travelled (VKT), reductions of the public transport and slow modes share (Soteropoulos et al., 2019), whereas shared automated vehicles, when considering a high share, could reduce the number of vehicles for the current travel demand, resulting in less parking and more space in the cities (ibid). Yet, it is worth noting that the results of impact assessment for AVs are strongly dependent on model assumptions (Soteropoulos et al., 2019).

The integration of automated minibuses into the public transport of European cities also raises questions regarding their potential benefits and critical points to contribute to the sustainable urban mobility plan (SUMP) and goals towards sustainable mobility of the cities. Therefore, this chapter presents the sustainability assessment of the AVENUE project and demonstrator sites. The goal of the sustainability assessment is to integrate and interrelate the results of the social, environmental and economic impacts and to embed these results by applying the set of indicators for sustainability assessment of the automated minibuses within the AVENUE demonstrator sites. In addition, the concept of SUMP is also a building block for the sustainability assessment.

2 Research Approach

The AVENUE approach to sustainability assessment comprises the concept of SUMP and indicators for sustainable mobility assessment.

By aiming to achieve sustainable mobility, indicators are used to measure performance and progress towards established goals and objectives (Litman, 2007). Urban sustainability indicators are fundamental to support target setting and performance reviews and to enable communication among the policymakers, experts and general public (Shen et al., 2011; Verbruggen & Kuik, 1991). Therefore, a set of indicators is applied for the sustainability assessment of the deployment of the automated minibuses in AVENUE pilot sites (Nemoto et al., 2021); subsequently, mobility radars illustrate the results.

The disaggregated indicators reveal the strengths and weaknesses of each mobility indicator (World Business Council for Sustainable Development, 2015). As graph representation, the radar (also known as spider chart) enables easy communication and visualisation of the results and comparison among case studies.

3 Sustainability Assessment of the AVENUE Demonstrator Pilot Sites

The sustainability assessment builds upon the set of indicators (Table 17.1) developed by Nemoto et al. (2021, 2022). The assessment comprehends the mobility multidimensions: social, environmental, economic, governance and system performance. Further, a selection of indicators (Table 17.2) was applied based on data availability from the pilot sites. Table 17.2

Table 17.1 Set of indicators for sustainable mobility assessment of shared automated electric vehicles from Nemoto et al. (2021)
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describes the indicators, units of measurement and scales of assessment.

Table 17.2 Indicators, units and scales of assessment
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Subsequently, the next section presents a brief description of the assessed pilot sites and reports the mobility radars for each pilot site based on the empirical data from the trials. The four sites assessed comprise Groupama (Lyon), Contern (Luxembourg), Pfaffenthal (Luxembourg) and Nordhavn (Copenhagen).

3.1 Pilot Sites Assessment and Results

The indicators were applied for the sustainability assessment of four different demonstrator sites. The description of the sites and respective mobility radar are presented hereinafter. The indicators present a value from 1 to 5—with 1 for the worst performance and 5 for the best performance; therefore, the outside part of the radars represents the optimal results. It is worth noting that the data availability and sample vary from site to site. Table 17.3 summarises the main information on the pilot sites.

Table 17.3 Description of the demonstrator sites
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Next, Fig. 17.1 presents the sustainability mobility radars from AVENUE pilot sites.

Fig. 17.1
A radar chart with 10 parameters. Automated mini bus in M a a S has the highest of 5 in external costs for climate change, external costs for air pollution, and high energy efficiency. Robotaxi has 5 in external costs for climate change, external costs for air pollution, and economic profitability.

Sustainability mobility radars from AVENUE pilot sites—with 1 for the worst performance and 5 for the best performance: (a) Groupama (Lyon); (b) Contern (Luxembourg); (c) Pfaffenthal (Luxembourg); (d) Nordhavn (Copenhagen)

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The results from the sustainability assessment (Nemoto et al., 2023) reveal the strong and weak points of the deployment of automated minibuses. Some common results among the sites pointed out that the automated minibuses score poorly on ‘energy efficiency’ (with the exception of Pfaffenthal) and ‘low contribution to climate change’ due to the low vehicle occupancy. With the exception of Pfaffenthal (Luxembourg), all sites presented very low occupancy. This result can be an indication of low demand for the offered mobility services. However, we should be cautious in this conclusion due to the unknown impacts of the Covid-19 restrictions. In addition, the energy efficiency could also be affected negatively in case the automated minibuses were equipped with more hardware and technical features, such as sensors, cameras, Lidars and communications.

As electric vehicles, automated minibuses seem to be a good alternative to tackle ‘local air pollution’. However, they are not a significant solution to tackle ‘local noise pollution’, as their noise level does not differ that much from other motorised modes of transport from 30 km/h speed. It considers that regarding the background noise and traffic density, EV does not differ from ICEV in the usual traffic, except for urban traffic during the night in low-speed areas (Jochem et al., 2016).

As temporary pilot trials, the automated minibuses present low system integration. Nonetheless, they show a high potential in the near future to have information, booking and payment integration within the public transport services, considering that in most cases, they are already deployed by public transport operators. In addition, it is expected that in the future, the automated minibus could be integrated into MaaS systems.

Concerning the technical performance elements (speed, frequency, occupancy rate and km driven autonomously), all sites struggle with low speed and low occupancy rates. The percentage of fully automated driven kilometres is 80–94%. The manual interventions that took place were mainly caused by wrongly parked cars and trucks.

The use of renewable energy for the use phase varies significantly according to the electricity mix of each region or country. In this case, Nordhavn in Copenhagen has the best score (with 62.4% of renewable sources in the electricity mix), and Contern and Pfaffenthal in Luxembourg are the lowest.

Currently, the ride on the automated minibus is free of charge. Therefore, passengers’ affordability performs high. In the future, it is envisaged to integrate the automated minibus in the ticketing of public transport.

Overall, the economic profitability is still low due to the elevated costs with feasibility studies and legal authorisations, infrastructure works, high annual depreciation and salaries for on-board safety drivers (Antonialli et al., 2021).

Concerning the indicators of social acceptance, respondents show goodwill to use the automated minibus (scoring 3.80 in Lyon and Copenhagen and 3.5 in Luxembourg), while the perception of the readiness of the technology is lower (2.5 in Lyon, 2.4 in Luxembourg and 2.5 in Copenhagen). Based on real experiences, the users in Copenhagen pointed a good satisfaction (3.96) with the ride and the automated minibus services (comfort, information, punctuality, speed).

The indicator on ‘reduction of risk of induced demand’ scored low in Nordhavn; this is explained by the users’ survey, which shows that the automated minibuses have been replacing walking and cycling (17% and 45%, respectively). In parts, this can be explained due to the vehicles’ low speed.

All in all, the indicators reflect an incipient phase of deployment and development of the technology. In the short term, key factors for improvement are:

  1. 1.

    The minibuses’ occupancy, a key factor in fostering environmentally friendly mobility. The automated minibuses should be deployed to cover real mobility gaps and to provide rides with great potential to replace private cars. These factors are crucial to guarantee higher occupancy and reduction of the risks of induced demand and increase in vehicle kilometres travelled.

  2. 2.

    Better mobility services integration, as the integration of information, booking and payment.

  3. 3.

    Offer of permanent lines/services, on-demand services and higher speed as a factor to improve flexibility and reduce travel time.

  4. 4.

    Monitoring and planning the deployment in order to replace car trips.

In the medium and long term, the economic profitability of deploying the automated minibuses should become more attractive with the development of a legal framework and lower costs with feasibility studies, authorisations and exemption of safety drivers.

Concerning the SUMP concept, it is worth noting that automated vehicles and minibuses will not be sustainable per se, but rather their mode of deployment is very important, and factors such as shared mobility, ride-matching capacity and efficiency, system integration and means of transport it will replace proper policies and regulations. The automated minibuses should be integrated into urban public transport or within MaaS perspective and fundamentally aligned with the city’s goals, planning and strategies for sustainable mobility. Also significant is to keep an integrated vision of the mobility system and, as highlighted by the SUMP approach, to develop all modes of transport in an integrated manner. Thus, the automated minibuses are a piece within the mobility ecosystem that could support intermodality, MaaS, mobility hubs and the use of soft modes of transport.

Concerning SUMP principles, the deployment of this new mode of transport and new mobility technologies requires more than ever long-term vision and planning, development of all transport modes in an integrated manner, cooperation across institutions, stakeholders and citizens’ participation, performance assessment and monitoring towards established sustainability goals.

Therefore, the SUMP principles and the four steps/guidelines are a valuable tool for planning and implementing automated minibuses aiming at people’s mobility needs and better quality of life. In this regard, the indicators are a tool to measure and monitor the progress and achievement of sustainable mobility planning and goals.

4 The Mobility Radar to Assess Two Potential Scenarios

This section explores the application of the indicators for two potential scenarios: (i) automated minibus integrated in MaaS and (ii) AV deployed as robotaxis. According to these two scenarios (detailed in Chap. 14), the level of integration of the automated minibus varies significantly and, as consequence, the potential impacts on mobility systems as well.

Figure 17.2 presents the mobility radar for assessment of the two scenarios (Nemoto et al., 2023). This is an explorative approach, these future perspectives need further research, and the enclosed developed hypothesis will be deepened on sites in the EU-funded ULTIMO project (2022–2026).

Fig. 17.2
4 radar charts have the best performance of 5 for passengers' affordability and low local noise pollution, 4.68 for low local air pollution, and 1 for economic profitaility, low contribution to climate change, and system integration in all, among 11 parameters such as high energy efficiency.

Sustainability mobility radars for scenarios deploying automated minibus in MaaS and robotaxis

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The assessment suggests that, overall, automated minibuses in MaaS tend to present a better performance than AVs deployed as robotaxis. As electric vehicles, the external costs for climate change and air pollution of both scenarios score high, whereas automated minibuses in MaaS score much better in terms of external costs for congestion and energy efficiency, considering that the average occupancy and sharing rate for automated minibuses in MaaS are higher.

The calculation of the external costs is detailed in Chap. 14, and it comprises air pollution, climate change, well-to-tank, noise, accidents and congestion (Jaroudi, 2021).

The social acceptance for robotaxis could be higher than for the automated minibus in MaaS, since they are akin to individual mobility; they could be a faster option (shorter waiting time), cheaper and not intermodal. Therefore, the social acceptance could be higher; although this form of deployment would be less sustainable. The robotaxis are very attractive for users and compete with public transport. The passenger traffic would thus be displaced from public transport to robotaxi and increase congestion (WEforum, 2020).

The economic profitability is assessed according to the costs (Euro) per vehicle-km; therefore, in VKM the operation of robotaxis is cheaper than automated minibuses. However, when it comes to costs (Euro) passengers-km, the price for the automated minibus services is more attractive and affordable (Bösch et al., 2018).

Regarding the technical performance, robotaxis are expected to have a higher speed, with less waiting time; however, the automated minibus would present higher occupancy. And in terms of system integration, the automated minibus would be integrated in MaaS for data, information, booking, ticketing, billing for different mobility services etc. On the contrary, robotaxis would present a lower level of integration. This means that the integration of data, information and the related partners within the transport system is low, and no synergies or positive externalities can be enabled.

The sustainability assessment of the scenario is in line with MaaS and SUMP approaches, reinforcing that mobility system integration is crucial to fostering intermodality and sustainable mobility. Additionally, the development of policy instruments and push-and-pull measures is a lever for a mobility shift from private and individual mobility towards public transport-centred MaaS.

5 Limitations of the Assessment

As this study analyses pilot trials, the sustainability assessment in this study is limited to a local and small-scale deployment, in addition to the technological limitations due to the development of the automated minibuses (Levels 3 and 4 of driving automation) and software. The assessment is also limited to just one type of vehicle provided by the same vehicle manufacturer.

Further, the application of the indicators is limited to data availability and data asymmetry from the pilot sites. For instance, the AVENUE representative and user surveys among the four demonstrator cities have different samples (n), hence, varying their representativeness.

It is also important to note that all the pilot tests within AVENUE project have been directly affected by the Covid-19 pandemic. The trials had interruptions; the number of passengers dropped, as had happened to public transport in general; and in some trials, the maximum number of passengers was limited to four in order to keep the social distance. For these reasons, the data collection and data availability for assessment were affected.

For some indicators, the assessment was simplified considering standard units of measurement available in the literature and commonly applied to other modes of transport.

6 Concluding Remarks

The sustainability assessment embedded results from the AVENUE project, targeting the social, environmental and economic impact assessment.

The assessment of the pilot trials points out that at the current stage, the automated minibus does not fulfil all the premises for sustainable mobility. However, the automated minibuses prove to be feasible as new alternative mobility and with the potential to support cities to achieve sustainable mobility under certain premises (e.g. technological improvements, vehicle usability and occupancy, integration into the mobility systems and intermodality, policies and strategies for sustainable mobility).

Further variables and questions will influence the performance and assessment of the automated minibuses in urban mobility, such as which modes of transport it will replace, what will be the occupancy rate, how fast the technology and policy development will occur, at to which extent automated minibuses will be integrated into the mobility system and under which policies and incentives. Additionally, the development of policy instruments is a lever for a mobility shift from private and individual mobility towards public transport-centred MaaS. Such elements are key for system innovation, and it comprises changes in governance, from a laissez-faire approach to a ‘governing by enabling’ approach.

Finally, the perspective is that automated minibuses could be integrated into urban mobility to improve the transport network, cover mobility gaps and foster intermodality by substituting motorised vehicles and offering on-demand and door-to-door services. The automated minibuses can be seen as a game-changer by improving mobility services and offering attractive private mobility, being part of the mobility innovations that target a system innovation and a shift from private to a mobility that serves the general interest. Indeed, automated minibuses could support MaaS approach, electrification and shared mobility, and accordingly to the recommendations in our study, they can foster SUMP and the sustainable agenda of cities.