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Fast advances in autonomous driving technology trigger the question of suitable operational models for future autonomous vehicles. A key determinant of such operational models’ viability is the competitiveness of their cost structures. Using a comprehensive analysis of the respective cost structures, this research shows that public transportation (...
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... The figure depicts the average consumer surplus return as a function of the access distance and three different valueof-time categories. The figure is based on 20,000 simulated trips, and for Fig. 2, we have maintained the average operating cost of = 5.9 , which corresponds to Bösch et al. (2018) and Rich et al. (2023). ...
In recent years, there has been an upsurge in intelligent mobility solutions that provide door-to-door services. Although these services offer convenience to certain individuals, it is frequently overlooked that they can lead to welfare losses when accounting for the reduced health benefits that result from reduced physical activity. In this paper, we derive a welfare function of introducing first- and last-mile public transport services. By comparing possible health gains from walking with corresponding accessibility losses, we identify the distance boundaries under which the service fails to be socially beneficial. The results are based on a simulation study and draw on further insights from a recent agent-based model from Copenhagen focusing on first- and last-mile public transport. Although the model is intentionally stylized and may not apply universally to all scenarios featuring diverse population densities, demographic profiles, or transport network layouts, the fundamental conclusion presented in the paper is that first-mile services have minimal welfare impact for average trip distances below 1 km, appears robust even under conservative assumptions. In this case, the probability of failure is almost 100% for any realistic parametrization. This finding implies that planners and researchers should focus on the design of main transit networks and the access and egress of active modes to and from the stations. In particular, door-to-door services covering shorter distances should not be the priority of public funding unless in particular situations or contexts.
... This trip represents the average distance of single main trip of more than 8 thousand travelers in Budapest. To have a starting point for the travel cost calculation for cars, AVs, and SAVs, a study prepared by Bösch, Becker [61] is applied. The researchers show that the passenger fees range from $0.15 to $0.44 (i.e., 42HUF to 123HUF) per km when using SAVs and $0.6-1$ (i.e., 168HUF to 280HUF) per km for using AVs. ...
Travelers on board of transport modes conduct active and passive activities to mitigate the negative impact of traveling. Multitasking on board of conventional transport modes is studied by several researchers, but limited efforts are focusing on multitasking in case of autonomous vehicles (AVs) and shared autonomous vehicles (SAVs). In this paper, the effects of multitasking on behavior of travelers on board of conventional cars (cars), AVs, and SAVs are analyzed. Furthermore, finding the impact of several factors on the travel time, the acceptability of SAVs, and conducting onboard activities are assessed. The study considers solely main trip purposes within urban areas. A stated preference (SP) survey is distributed in Budapest, Hungary, and 276 participants are collected. An SP includes discrete choice experiment (DCE) that is designed to mimic the realistic situation when AV is on the market. The DCE considers the attributes and attributes levels of the alternatives where rationality is maintained in the design. A transport mode choice model, which includes several variables influencing the choice of a transport mode, is developed. In addition, an SP includes Likert scale and sociodemographic sections. Likert scale and exploratory factor analysis (EPA) are used to understand the impact of some factors on the travel time, the acceptability of SAVs as transport modes, and conducting onboard activities. The multinomial logit (MNL) model is applied, where a transport mode choice model of cars, AVs, and SAVs is developed. The results of the developed model show that travelers are willing to choose AVs over cars, and SAVs over AVs. Moreover, travelers with high income are more willing to use AVs over SAVs and more likely to use cars than SAVs. Besides, people from the older age group prefer using SAVs more than other age groups. The results demonstrate the probability of selecting a transport mode with active activities on board is larger than the probability of choosing a transport mode with passive activities. Besides, the findings of EFA and Likert scale analyses demonstrate that the waiting time has the largest negative effect on the travel time, seat availability affects the conduction of onboard activities, and the internal design of SAVs influences the use of SAVs as transport modes. The results of current research can be beneficial to transport planners, transport operators, and vehicle manufacturers.
... with ∈ { , } is set to 0.25 euros/km and 0.27 euros/km, respectively, representing the unit operational costs for using CTs and PVs. These values are calculated according to the methodology proposed by Bösch et al. (2018). ...
... Here, only the parameters that could be controlled by TNCs are tested. The operational costs of CTs and PVs, and the value of travel time using PVs are not varied for sensitivity analysis as these parameters could be well estimated (Bösch et al., 2018;Kouwenhoven et al., 2014). ...
... There is an additional cost premium for traveling by PR or SR (pmX), respectively. The specific monetary values are derived from cost estimates for automated modes (Bösch et al., 2018). The score function follows a well- Table 2 Game payoff matrix for a multimodal choice scenario between private ride, shared ride and transit. ...
... This limitation suggests that the expected adoption of Shared Rides (SR) may be overestimated, as willingness to pay in mode choice studies is significantly influenced by income effects (Ha et al., 2020), revealing that higher-earning travelers tend to prefer private over shared modes. Bösch et al. (2018) have also suggested that cost differences between different automated modes will likely decrease compared to the present. These limitations could be addressed in future studies through alternative experimental designs. ...
Automated Vehicles (AVs) are poised to disrupt travel patterns and the sustainability of transportation networks. Conventional methods for studying these changes, such as stated preference surveys and agent-based simulations, have limitations. Serious games offer a promising alternative , providing a controlled and engaging environment for investigating travel behavior. In our study, 200 participants, grouped into sessions of 10, engaged in a competitive serious game simulating 50 daily choices of travel mode and departure time across three automated options. Two scenarios were examined: one with recurring congestion and another with nonrecurring congestion. Automated transit had fixed schedules, while private and shared rides could adapt to a congested bottleneck. Results revealed that ridesharing dominated, reaching 60% mode share under recurring congestion, displacing transit, and a comparative equilibrium emerged between shared and private rides. In the nonrecurring congestion scenario, ridesharing dropped to 37%, and a comparable multimodal equilibrium developed. Participants rarely achieved the optimal score, attaining a maximum of 88% of its potential. This study highlights a policy paradox: un-regulated AV traffic can reduce transit use, exacerbate recurring congestion, yet necessitate increased transit investment to address nonrecurring congestion, confirming the Downs-Thomson paradox. Creating appealing mass transit alternatives is imperative to ensure efficiency and sustainability in the era of automated mobility.
... With regard to passenger transport, a large number of often model-based studies have already addressed the question of whether or to what extent AVs will affect transport demand and mileage (BMVI 2017;Meyer et al. 2017;WEF and BCG 2018). Many studies assume an increase in transport demand and mileage when automation levels 4 and 5 are reached (Bösch et al. 2018;Friedrich, Hartl, and Magg 2018). Overall, the available research makes it very clear that the impact on transport depends very much, on whether AVs are used individually or collectively (see section 2.1). ...
It is often assumed, at least implicitly, that responsible governance of automated vehicles (AVs) requires more knowledge about the future development of the innovation and its potential consequences. In this context, technology assessment (TA) studies often refer to the so-called Collingridge-dilemma. This paper argues that, at least in the German case, a lack of knowledge in the sense of the Collingridge-dilemma is not the central challenge for the governance of AVs. The argument is developed on the basis of different types of knowledge for TA recently introduced by Armin Grunwald. The paper shows that responsible governance of AVs requires more normative and hermeneutic knowledge to better understand the directionality of the current system. More important than focusing on the possible consequences of AVs is a better understanding of how to overcome existing obstacles to the development of a broadly shared vision with effective goals for the German mobility sector.
... Számos kutatási eredmény ismert a lakosság önvezetőtechnológia-elfogadásáról világszerte (Daziano et al 2017, Cunningham et al 2019, Keszey 2020, valamint hazánkban is , Somos -Lukovics 2023, Pronay et al. 2022. Szintén egyre több információval rendelkezünk az önvezetőflotta-használat lehetséges költségelőnyeiről a saját autó tulajdonlással szemben (Burns et al. 2013, Wadud 2017, Bösch et al 2018, Wadud -Mattioli 2021, melyek hazai adaptációja is elkészült (Kecskés -Lukovics 2023). Keveset tudunk ugyanakkor arról, hogy a lakosság milyen költségelőnyök mentén hajlandó a saját autó tulajdonlást felváltani önvezetőflotta-használatra. ...
Korunk nagyvárosainak mobilitását növekvő autódominancia jellemzi, amely egyre jobban érzékelhető urbanizációs hátrányokat (dugók, zaj, légszennyezettség, járdákon parkoló autók stb.) eredményez. Az önvezető járművek flottahasználati üzleti modellje megteremti annak elvi lehetőségét, hogy csökkentse a városok útjain közlekedő autók számát. Egyre több információval rendelkezünk az önvezetőflotta-használat költségeiről, és számos modellszámítás megállapította az önvezetőflotta-használat lehetséges költségelőnyét a saját autó tulajdonlással szemben. Keveset tudunk ugyanakkor arról, hogy a lakosság milyen költségelőnyök mentén hajlandó a saját autó tulajdonlást felváltani önvezetőflotta-használatra. Kutatásunk célja annak megismerése, hogy a magyar lakosság milyen feltételek mentén hajlandó a napi mobilitási szokásait az önvezetőflotta-használat irányába elmozdítani. Eredményeink segítségével megbecsüljük azt is, hogy az egyes modellváltozatok mentén mennyivel csökkenthető a magyar utakon levő autók száma, valamint javaslatokat teszünk ezen értékek további növelésének lehetőségeire is.
... В литературе имеется очень мало оценок, на сколько может увеличиться стоимость ТС, используемых для перевозки пассажиров, с установкой на него оборудования для полной автоматизации. Например, [18] считает, что дополнительные затраты на автоматизацию автобуса для пассажирских перевозок, не являются значительными по сравнению с ценой покупки ТС, а значит, для ТС предполагается нулевое увеличение затрат. В работе [14] отмечается, что для 6-метрового электрического автобуса рост затрат на его автоматизацию составит 36 % (на 2019 год), но ожидается, что к 2030 году это значение снизится до 7 %. ...
... Еще одним эффектом для перевозчика от использования ТС с автоматизированным управлением является экономия топлива за счет более сбалансированного стиля вождения. В работе [18] отмечается, что экономия топлива, при использовании автобусов с автоматизированным управлением, составляет 10 % по сравнению с затратами на топливо при использовании автобусов, управляемых человеком. ...
The intellectualization of water transport is accompanied by an expansion of the landscape of threats to transport security, caused by the characteristics and weaknesses of the technologies being introduced, which are the convergence of information and telecommunication technologies, automated and automatic control technologies and artificial intelligence. The peculiarity of these technologies is working with large volumes of information. Violation of the security of information processed in intelligent systems of water transport (illegal access, modification, deletion and similar unauthorized influence) causes a violation of transport security and, as a consequence, the security of critical information infrastructure and the country’s critical infrastructure, national security. Convergent technologies used in intelligent transport systems are characterized by multiple and poorly formalized manifestations of the consequences of threats. The article presents a model for assessing the risks of information security of intelligent water transport systems, based on the methods of the theory of fuzzy sets and fuzzy logic, the use of which makes it possible to take into account the above-mentioned features of the technologies being implemented. The hierarchical structure of the model and the use of fuzzy set theory and fuzzy logic methods make it possible to adapt the model to various risk criteria, types of input data and the level of detail of risk analysis. For the presented model, a methodology for assessing information security risks has been developed and an example of risk calculation is given. The developed model and methodology are intended to build an information security risk management system for autonomous shipping, implementing technologies of hybrid (augmented, extended) intelligence, providing for the use of artificial intelligence controlled by people.
... We are unable to fully take advantage of AVs while the driver is in the seat, as he must be treated as an integral component of the vehicle. However, the cockpit will be more comfortable for passengers if he is not the driver [34,35]. In this way, the driver is no longer counted as a contributor to the vehicle's fuel consumption; instead, they are treated like a passive passenger. ...
The mobility industry is currently experiencing some of the most profound changes it has seen since the advent of the automobile. This is due to a number of factors, including, but not limited to, the rapidity with which cities are developing and the push for greater environmental responsibility. The advent of autonomous vehicles has the potential to transportation alter our daily commutes and other modes of transportation significantly. However, there are still some unanswered questions about how to deal with or take advantage of this technological revolution in our daily lives. What repercussions does it have on our regular transportation requirements in addition to our commercial ones? Can user needs be met at reasonable prices with autonomous vehicles? Is there any thought given to how traffic will be affected when these vehicles are in use? Where do worries about safety fit in? This paper will provide a more in-depth analysis of these topics, as well as the missing connections between recent developments and potential future outcomes.
... Interest in FLEX systems has grown in the past decade with the emergence of smartphone-enabled ride-pooling services (e.g., Uber) and technological progress in the development of automated vehicles (AVs). With great opportunities for real-time fleet coordination and prospective lower per-vehicle operational costs (Bösch et al. 2018), many conceptual FLEX use cases for AVs have been proposed in recent years (Narayanan, Chaniotakis, and Antoniou 2020). ...
... As emerging technologies, like AVs, penetrate future transportation, the ride-sharing service provided by SAVs is anticipated to become popular due to lower cost and improved safety (Bösch et al. 2018;Clements and Kockelman 2017), and thus there is an urgent need to incorporate detailed party size distributions and seasonal shifts in coordination with agent-based simulations to reveal realistic ride-sharing efficacy and service patterns. This paper aims to explore the answers to two questions: (1) How does fleet performance vary in agent-based simulations of AVs' ridesharing service considering seasonal travel trends? ...
This paper explores the effects of day of week and season of year demand variations for shared rides, along with realistic travel party sizes, on shared autonomous vehicle (SAV) services across the Austin, Texas region. Using the agent-based POLARIS program, synthetic person-trips that reflect travel-party size (from one to four persons) and demand variations over days and months, as evident in the National Household Travel Survey data were simulated in each scenario over a 24 h travel day. Results show that realistic party sizes can bring considerable changes to SAV fleet performance, including up to 8.5% higher service rates (number of requests accepted within 15 min), 5 min shorter journey times (wait time + travel time), 28% higher vehicle occupancies on weekends, and roughly 4% lower empty fleet VMT. Weekend travel is most impacted by season of year, with weekday travel patterns looking more uniform (thanks to work and school trips). Various performance metrics for the Austin network, like total and empty VMT, change by up to 30% when considering realistic variations in party size and time of year. This paper underscores the value of recognizing day-to-day and month-to-month variations in travel demand, and the importance of agent-based model equations to reflect travel-party size. Such realism can help quantify SAV seat occupancies more accurately, highlighting the importance of shared mobility. However, it also creates demand and supply issues for operators that now need more information on party size to manage dynamic ride-sharing, or those that may wish to shift their fleet vehicles to other regions for special events to protect profits while offering reasonable wait times to customers throughout the year.
