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A personalized route planner is elaborated to support commuting, where soft measures are applied to influence the intentions of individual travel behavior. In order to do that a utility function is created, which consists of four attributes (travel time, travel cost, environmental effect, and health effect) to reflect on user preferences and considers four transport modes (walking, cycling, public transport, and car) as alternatives. The outcome of the utility function is a suggested transport mode based on the attributes, where the travelers may provide a feedback, whether they would really choose the suggested transport mode. During the analysis, statistical methods are used to determine the most substantial factors affecting transport mode choice and trip characteristics. Based on the analysis, travel time is still the most determinant attribute in transport mode choice. Considering the results, the web application suggests in most cases cycling as the best mode choice, and almost half of all users agree to choose the best transport mode, which is suggested by the application. The acceptance rate is much higher in case of public transportation and walking. The applicability of reduction, tunneling, suggestion, personalization, and simulation strategies are demonstrated. The elaborated method supports finding a solution to change travel behavior by understanding the affecting factors of the individual decision-making process, which might help promoting the choice of environmentally friendly transport modes.
Domokos Esztergár-Kiss; Yuliia Shulha; Attila Aba; Tamás Tettamanti. Promoting sustainable mode choice for commuting supported by persuasive strategies. Sustainable Cities and Society 2021, 74, 103264 .
AMA StyleDomokos Esztergár-Kiss, Yuliia Shulha, Attila Aba, Tamás Tettamanti. Promoting sustainable mode choice for commuting supported by persuasive strategies. Sustainable Cities and Society. 2021; 74 ():103264.
Chicago/Turabian StyleDomokos Esztergár-Kiss; Yuliia Shulha; Attila Aba; Tamás Tettamanti. 2021. "Promoting sustainable mode choice for commuting supported by persuasive strategies." Sustainable Cities and Society 74, no. : 103264.
Transportation and mobility in smart cities are undergoing a grave transformation as new ways of mobility are introduced to facilitate seamless traveling, addressing travelers’ needs in a personalized manner. A novel concept that has been recently introduced is Mobility-as-a-Service (MaaS), where mobility services are bundled in MaaS Plans and offered to end-users through a single digital platform. The present paper introduces a recommender system for MaaS Plans selection that supports travelers to select bundles of mobility services that fit their everyday transportation needs. The recommender filters out unsuitable plans and then ranks the remaining ones on the basis of their similarity to the users’ characteristics, habits and preferences. The recommendation approach is based on Constraint Satisfaction Problem (CSP) formalisms combined with cosine similarity techniques. The proposed method was evaluated in experimental settings and was further embedded in real-life pilot MaaS applications. The experimental results showed that the proposed approach provides lists of MaaS PlanMaaS Plans that users would choose in a real-life MaaS setting, in most of the cases. Moreover, the results of the real-life pilots showed that the majority of the participants chose an actual MaaS Plan from the top three places of the recommendation lists.
Konstantina Arnaoutaki; Efthimios Bothos; Babis Magoutas; Attila Aba; Domokos Esztergár-Kiss; Gregoris Mentzas. A Recommender System for Mobility-as-a-Service Plans Selection. Sustainability 2021, 13, 8245 .
AMA StyleKonstantina Arnaoutaki, Efthimios Bothos, Babis Magoutas, Attila Aba, Domokos Esztergár-Kiss, Gregoris Mentzas. A Recommender System for Mobility-as-a-Service Plans Selection. Sustainability. 2021; 13 (15):8245.
Chicago/Turabian StyleKonstantina Arnaoutaki; Efthimios Bothos; Babis Magoutas; Attila Aba; Domokos Esztergár-Kiss; Gregoris Mentzas. 2021. "A Recommender System for Mobility-as-a-Service Plans Selection." Sustainability 13, no. 15: 8245.
Introducing autonomous vehicles (AVs) on the market is likely to bring changes in the mobility of travelers. In this work, extensive research is conducted to study the impact of different levels of automation on the mobility of people, and full driving automation needs further study because it is still under development. The impacts of AVs on travel behavior can be studied by integrating AVs into activity-based models. The contribution of this study is the estimation of AVs’ impacts on travelers’ mobility when different travel demands are provided, and also the estimation of AVs’ impact on the modal share considering the different willingness of pay to travel by AVs. This study analyses the potential impacts of AVs on travel behavior by investigating a sample of 8500 travelers who recorded their daily activity plans in Budapest, Hungary. Three scenarios are derived to study travel behavior and to find the impacts of the AVs on the conventional transport modes. The scenarios include (1) a simulation of the existing condition, (2) a simulation of AVs as a full replacement for conventional transport modes, and (3) a simulation of the AVs with conventional transport modes concerning different marginal utilities of travel time in AVs. The simulations are done by using the Multi-Agent Transport Simulation (MATSim) open-source software, which applies a co-evolutionary optimization algorithm. Using the scenarios in the study, we develop a base model, determine the required fleet size of AVs needed to fulfill the demand of the different groups of travelers, and predict the new modal shares of the transport modes when AVs appear on the market. The results demonstrate that the travelers are exposed to a reduction in travel time once conventional transport modes are replaced by AVs. The impact of the value of travel time (VOT) on the usage of AVs and the modal share is demonstrated. The decrease in the VOT of AVs increases the usage of AVs, and it particularly decreases the usage of cars even more than other transport modes. AVs strongly affect the public transport when the VOT of AVs gets close to the VOT of public transport. Finally, the result shows that 1 AV can replace 7.85 conventional vehicles with acceptable waiting time.
Jamil Hamadneh; Domokos Esztergár-Kiss. The Influence of Introducing Autonomous Vehicles on Conventional Transport Modes and Travel Time. Energies 2021, 14, 4163 .
AMA StyleJamil Hamadneh, Domokos Esztergár-Kiss. The Influence of Introducing Autonomous Vehicles on Conventional Transport Modes and Travel Time. Energies. 2021; 14 (14):4163.
Chicago/Turabian StyleJamil Hamadneh; Domokos Esztergár-Kiss. 2021. "The Influence of Introducing Autonomous Vehicles on Conventional Transport Modes and Travel Time." Energies 14, no. 14: 4163.
Travelers conduct onboard activities while using the tools they bring with them onboard to convert part of their travel time to a productive time. Productive travel time contributes to the reduction in the disutility of travel time. This paper discusses the influence of travelers’ onboard activities and the tools carried by travelers on the perceived trip time. 10 onboard activities and 12 tools carried by travelers are introduced and studied in this work. A questionnaire focusing on the main trip of each respondent in urban areas is conducted, where a sample size of 525 participants is collected. Statistical methods such as central tendency, chi-square, exploratory factor analysis (EFA), rank-based nonparametric test, and multivariate analysis of variance (MANOVA) are applied. The main findings are the following: almost all of the onboard activities and the tools carried by travelers impact the trip time positively (i.e., the perception is enhanced). For each transport mode, the most frequent onboard activities that impact the trip time positively is obtained, and the connection between each onboard activity and each tool carried by travelers is found (i.e., moderate to strong association). EFA uncovers the underlying relationship between those onboard activities and those tools carried by travelers that influence travelers’ perception. In this case, instead of the full list, fewer onboard activities and tools carried by travelers are produced to simplify the finding of their impacts on the perceived trip time. The participation in onboard activity is ranked across certain groups, such as the tendency of women to be engaged in onboard activities is higher than men’s tendency. Regarding the positive impact on trip time, a statistical difference is demonstrated between groups, where the use of the tools carried by travelers is varied across the transport mode, trip purpose, and trip time, gender, age, education, and job variable. Besides, the involvement in onboard activities is statistically dependent across the transport mode, gender, income, and car ownership variable. The output of this study helps decision-makers and mobility planners in understanding the behavior of travelers onboard in more detail, such as the availability of onboard tools affecting the choice of transport mode.
Jamil Hamadneh; Domokos Esztergár-Kiss. The Effects of Multitasking and Tools Carried by Travelers Onboard on the Perceived Trip Time. Journal of Advanced Transportation 2021, 2021, 1 -25.
AMA StyleJamil Hamadneh, Domokos Esztergár-Kiss. The Effects of Multitasking and Tools Carried by Travelers Onboard on the Perceived Trip Time. Journal of Advanced Transportation. 2021; 2021 ():1-25.
Chicago/Turabian StyleJamil Hamadneh; Domokos Esztergár-Kiss. 2021. "The Effects of Multitasking and Tools Carried by Travelers Onboard on the Perceived Trip Time." Journal of Advanced Transportation 2021, no. : 1-25.
Method This paper endeavors to introduce a new approach to modal split estimation. In the frame of the research, a customized model of the recently created Best-Worst Method (BWM) is applied to evaluate mode choice alternatives by transport experts. The integrated BWM model is tested on a real-world case study in Budapest, the capital of Hungary, where a small number of selected experts estimate the modal split of three different groups clustered based on the distance of their commuting. Results The results clearly demonstrate the popularity of public transport among all groups, while car is estimated to be used primarily by short- and mid-distance commuters. The coherence of the responses is tested along with sensitivity analysis and rank correlation comparison. Moreover, the final results are compared to the official modal split data of the city. Recommendations Based on the findings, it can be concluded that the application of BWM results in competitive accuracy compared to the mainstream methodologies, moreover BWM needs significantly less cost and time effort during the survey procedure.
Szabolcs Duleba; Sarbast Moslem; Domokos Esztergár-Kiss. Estimating commuting modal split by using the Best-Worst Method. European Transport Research Review 2021, 13, 1 -12.
AMA StyleSzabolcs Duleba, Sarbast Moslem, Domokos Esztergár-Kiss. Estimating commuting modal split by using the Best-Worst Method. European Transport Research Review. 2021; 13 (1):1-12.
Chicago/Turabian StyleSzabolcs Duleba; Sarbast Moslem; Domokos Esztergár-Kiss. 2021. "Estimating commuting modal split by using the Best-Worst Method." European Transport Research Review 13, no. 1: 1-12.
The introduction of shared autonomous vehicles into the transport system is suggested to bring significant impacts on traffic conditions, road safety and emissions, as well as overall reshaping travel behaviour. Compared with a private autonomous vehicle, a shared automated vehicle (SAV) is associated with different willingness-to-adopt and willingness-to-pay characteristics. An important aspect of future SAV adoption is the presence of other passengers in the SAV—often people unknown to the cotravellers. This study presents a cross-country exploration of user preferences and WTP calculations regarding mode choice between a private non-autonomous vehicle, and private and shared autonomous vehicles. To explore user preferences, the study launched a survey in seven European countries, including a stated-preference experiment of user choices. To model and quantify the effect of travel mode attributes and socio-demographic characteristics, the study employs a mixed logit model. The model results were the basis for calculating willingness-to-pay values for all countries and travel modes, and provide insight into the significant heterogeneous, gender-wise effect of cotravellers in the choice to use an SAV. The study results highlight the importance of analysis of the effect of SAV attributes and shared-ride conditions on the future acceptance and adoption rates of such services.
Amalia Polydoropoulou; Ioannis Tsouros; Nikolas Thomopoulos; Cristina Pronello; Arnór Elvarsson; Haraldur Sigþórsson; Nima Dadashzadeh; Kristina Stojmenova; Jaka Sodnik; Stelios Neophytou; Domokos Esztergár-Kiss; Jamil Hamadneh; Graham Parkhurst; Shelly Etzioni; Yoram Shiftan; Floridea Di Ciommo. Who Is Willing to Share Their AV? Insights about Gender Differences among Seven Countries. Sustainability 2021, 13, 4769 .
AMA StyleAmalia Polydoropoulou, Ioannis Tsouros, Nikolas Thomopoulos, Cristina Pronello, Arnór Elvarsson, Haraldur Sigþórsson, Nima Dadashzadeh, Kristina Stojmenova, Jaka Sodnik, Stelios Neophytou, Domokos Esztergár-Kiss, Jamil Hamadneh, Graham Parkhurst, Shelly Etzioni, Yoram Shiftan, Floridea Di Ciommo. Who Is Willing to Share Their AV? Insights about Gender Differences among Seven Countries. Sustainability. 2021; 13 (9):4769.
Chicago/Turabian StyleAmalia Polydoropoulou; Ioannis Tsouros; Nikolas Thomopoulos; Cristina Pronello; Arnór Elvarsson; Haraldur Sigþórsson; Nima Dadashzadeh; Kristina Stojmenova; Jaka Sodnik; Stelios Neophytou; Domokos Esztergár-Kiss; Jamil Hamadneh; Graham Parkhurst; Shelly Etzioni; Yoram Shiftan; Floridea Di Ciommo. 2021. "Who Is Willing to Share Their AV? Insights about Gender Differences among Seven Countries." Sustainability 13, no. 9: 4769.
The currently available transport modeling tools are used to evaluate the effects of behavior change. The aim of this study is to analyze the interaction between the transport mode choice and travel behavior of an individual—more specifically, to identify which of the variables has the greatest effect on mode choice. This is realized by using a multinomial logit model (MNL) and a nested logit model (NL) based on a utility function. The utility function contains activity characteristics, trip characteristics including travel cost, travel time, the distance between activity place, and the individual characteristics to calculate the maximum utility of the mode choice. The variables in the proposed model are tested by using real observations in Budapest, Hungary as a case study. When analyzing the results, it was found that “Trip distance” variable was the most significant, followed by “Travel time” and “Activity purpose”. These parameters have to be mainly considered when elaborating urban traffic models and travel plans. The advantage of using the proposed logit models and utility function is the ability to identify the relationship among the travel behavior of an individual and the mode choice. With the results, it is possible to estimate the influence of the various variables on mode choice and identify the best mode based on the utility function.
Wissam Al-Salih; Domokos Esztergár-Kiss. Linking Mode Choice with Travel Behavior by Using Logit Model Based on Utility Function. Sustainability 2021, 13, 4332 .
AMA StyleWissam Al-Salih, Domokos Esztergár-Kiss. Linking Mode Choice with Travel Behavior by Using Logit Model Based on Utility Function. Sustainability. 2021; 13 (8):4332.
Chicago/Turabian StyleWissam Al-Salih; Domokos Esztergár-Kiss. 2021. "Linking Mode Choice with Travel Behavior by Using Logit Model Based on Utility Function." Sustainability 13, no. 8: 4332.
The present study focuses on the relationship between the Covid-19 pandemic and mobility patterns. By using data from an international survey, transport users’ socio-demographic features and travel characteristics during the pre-pandemic and pandemic time are analyzed.Afterward, the pandemic commuting travel behavior is modeled. The multinomial model shows that public transport users are 31.5, 10.6, and 6.9 times more likely to change their commuting transportation mode than car users, motorcycle users, and walkers, respectively. The results demonstrate that travel distance and income level are the two most influential factors in pandemic decision-making. These results confirm the reflection of spatial-economic inequalities during the pandemic. Active modes, motorcycle, and personal car are perceived by the participants as the least risky urban transportation modes during the pandemic. Thus, a considerable growth in individual transportation modes, up to 26% increase for commuting and up to 15% for leisure activities, can be recognized.
Ali Enes Dingil; Domokos Esztergár-Kiss. The Influence of the Covid-19 Pandemic on Mobility Patterns: The First Wave’s Results. Transportation Letters 2021, 1 -13.
AMA StyleAli Enes Dingil, Domokos Esztergár-Kiss. The Influence of the Covid-19 Pandemic on Mobility Patterns: The First Wave’s Results. Transportation Letters. 2021; ():1-13.
Chicago/Turabian StyleAli Enes Dingil; Domokos Esztergár-Kiss. 2021. "The Influence of the Covid-19 Pandemic on Mobility Patterns: The First Wave’s Results." Transportation Letters , no. : 1-13.
Autonomous Vehicles (AVs) have been designed to make changes in the travel behaviour of travellers. These changes can be interpreted using transport models and simulation tools. In this study, the daily activity plans were used to study the possibility of increasing the utility of travellers through minimizing the travel time by using AVs. Three groups of travellers were selected based on the benefits that they can obtain when AVs are on the market. The groups are (a) long-trip travellers (b) public transport riders, and (c) travellers with specified characteristics. Each group is divided into one or more scenarios based on the definition of each group and the collected data. A total of seven scenarios were derived from the collected data and simulated twice to include the existing transport modes and the presence of AVs. The simulations were conducted using Multi-Agents Transport Simulation (MATSim) that applies the concept of a co-evolutionary algorithm. MATSim simulates the current plans and the ones where AVs replace all or part of the existing conventional transport modes in the daily activity plans. The results have shown a reduction in the trip time: 13% to 42% for group (a), 33% for group (b), and 16% to 28% for group (c) compared with the original trip times. In conclusion, it can be claimed that AVs could reduce the travel time in all cases, which provides benefits for people to increase their utilities.
Jamil Hamadneh; Domokos Esztergár-Kiss. Potential Travel Time Reduction with Autonomous Vehicles for Different Types of Travellers. Promet - Traffic&Transportation 2021, 33, 61 -76.
AMA StyleJamil Hamadneh, Domokos Esztergár-Kiss. Potential Travel Time Reduction with Autonomous Vehicles for Different Types of Travellers. Promet - Traffic&Transportation. 2021; 33 (1):61-76.
Chicago/Turabian StyleJamil Hamadneh; Domokos Esztergár-Kiss. 2021. "Potential Travel Time Reduction with Autonomous Vehicles for Different Types of Travellers." Promet - Traffic&Transportation 33, no. 1: 61-76.
Mobility as a Service (MaaS) is a new transport concept which integrates, manages, and distributes private and public mobility alternatives by using intelligent digital technologies. Recently, research and implementations have been widely conducted. In order to reveal future implications, it is crucial to analyze the available MaaS services by using systematic methodology. Cluster analysis was applied to create typical groups of MaaS services and to define the common features of the systems, which may highlight future trends. In order to identify the most relevant MaaS initiatives, the typical parameters of the services were taken into account and a dataset was developed. More than 30 MaaS services from 14 countries were investigated, and the features and the functionalities of these services were analyzed. The findings demonstrate that there is potential for the development of the applications in terms of their payment features, their personalization, and the provision of all attainable elements of MaaS. The number of operators is constantly increasing. However, it is uncertain whether public or private MaaS operators will be dominant on the market. Three cluster groups were created with specific features and directions of development. The Route planners group involves a few modes of transport, but it provides an extensive service. While the Third parties group has primarily private MaaS operators, the Public systems group usually includes public MaaS operators. This comprehensive study might be useful to MaaS operators and regulators for understanding the typical features and the development directions of the market.
Domokos Esztergár-Kiss; Tamás Kerényi; Tamás Mátrai; Attila Aba. Exploring the MaaS market with systematic analysis. European Transport Research Review 2020, 12, 1 -16.
AMA StyleDomokos Esztergár-Kiss, Tamás Kerényi, Tamás Mátrai, Attila Aba. Exploring the MaaS market with systematic analysis. European Transport Research Review. 2020; 12 (1):1-16.
Chicago/Turabian StyleDomokos Esztergár-Kiss; Tamás Kerényi; Tamás Mátrai; Attila Aba. 2020. "Exploring the MaaS market with systematic analysis." European Transport Research Review 12, no. 1: 1-16.
The technology that allows fully automated driving already exists and it may gradually enter the market over the forthcoming decades. Technology assimilation and automated vehicle acceptance in different countries is of high interest to many scholars, manufacturers, and policymakers worldwide. We model the mode choice between automated vehicles and conventional cars using a mixed multinomial logit heteroskedastic error component type model. Specifically, we capture preference heterogeneity assuming a continuous distribution across individuals. Different choice scenarios, based on respondents’ reported trip, were presented to respondents from six European countries: Cyprus, Hungary, Iceland, Montenegro, Slovenia, and the UK. We found that large reservations towards automated vehicles exist in all countries with 70% conventional private car choices, and 30% automated vehicles choices. We found that men, under the age of 60, with a high income who currently use private car, are more likely to be early adopters of automated vehicles. We found significant differences in automated vehicles acceptance in different countries. Individuals from Slovenia and Cyprus show higher automated vehicles acceptance while individuals from wealthier countries, UK, and Iceland, show more reservations towards them. Nontrading mode choice behaviors, value of travel time, and differences in model parameters among the different countries are discussed.
Shelly Etzioni; Jamil Hamadneh; Arnór Elvarsson; Domokos Esztergár-Kiss; Milena Djukanovic; Stelios Neophytou; Jaka Sodnik; Amalia Polydoropoulou; Ioannis Tsouros; Cristina Pronello; Nikolas Thomopoulos; Yoram Shiftan. Modeling Cross-National Differences in Automated Vehicle Acceptance. Sustainability 2020, 12, 9765 .
AMA StyleShelly Etzioni, Jamil Hamadneh, Arnór Elvarsson, Domokos Esztergár-Kiss, Milena Djukanovic, Stelios Neophytou, Jaka Sodnik, Amalia Polydoropoulou, Ioannis Tsouros, Cristina Pronello, Nikolas Thomopoulos, Yoram Shiftan. Modeling Cross-National Differences in Automated Vehicle Acceptance. Sustainability. 2020; 12 (22):9765.
Chicago/Turabian StyleShelly Etzioni; Jamil Hamadneh; Arnór Elvarsson; Domokos Esztergár-Kiss; Milena Djukanovic; Stelios Neophytou; Jaka Sodnik; Amalia Polydoropoulou; Ioannis Tsouros; Cristina Pronello; Nikolas Thomopoulos; Yoram Shiftan. 2020. "Modeling Cross-National Differences in Automated Vehicle Acceptance." Sustainability 12, no. 22: 9765.
This paper aimed to provide a set of sustainable measures suitable for workplaces according to local requirements. To support this, a specific Transportation Demand Management strategy was applied, which is called Workplace Travel Planning. The result of such a Workplace Travel Plan is a package of measures implemented by an organization to encourage sustainable commuting. This research focused on two stages of the planning process: in the analysis stage, data were gathered from the stakeholders, and travel behavior was analyzed, while in the planning stage, a specific set of measures was proposed to the workplace. The selection of those measures relies on several aspects, such as existing workplace infrastructure, employer policies, employee requirements, local infrastructure, cost of implementation, level of sustainability. The mobility questionnaires are the instruments used to retrieve the input data used in the method, while the categorization of measures contributes to the next phase of the method serving as the output options. To each measure, factors, weights, and sustainability impacts were assigned. The connection of the phases was realized by creating the utility value of the measure, which enables the ranking of the measures. The approach provides a comprehensive framework of connecting employee requirements, employer willingness, and site-specific opportunities by defining a quantitative utility function, which results in a list of most suitable measures for a specific workplace.
Domokos Esztergár-Kiss; Conrado Braga Zagabria. Method development for workplaces using mobility plans to select suitable and sustainable measures. Research in Transportation Business & Management 2020, 100544 .
AMA StyleDomokos Esztergár-Kiss, Conrado Braga Zagabria. Method development for workplaces using mobility plans to select suitable and sustainable measures. Research in Transportation Business & Management. 2020; ():100544.
Chicago/Turabian StyleDomokos Esztergár-Kiss; Conrado Braga Zagabria. 2020. "Method development for workplaces using mobility plans to select suitable and sustainable measures." Research in Transportation Business & Management , no. : 100544.
In order to model the complex requirements of users travelling in an urban environment, the relevant parameters for creating activity chains have to be identified. In this study, travel related parameters were collected and grouped into two main types: classification parameters and optimization parameters. In the case of optimization parameters, further grouping was performed where general and comfort parameters were introduced. Additionally, the possible values and data sources of the parameters were identified. A utility function was created to take into account the optimization parameters and the weights. Weights related to comfort optimization parameters were aggregated to decrease the number of required settings by the users. Finally, the features of the proposed optimization algorithm are described. With the identified parameters, aggregated weights and elaborated utility function activity chains can be optimized for users with different requirements.
Domokos Esztergár-Kiss. Trip Chaining Model with Classification and Optimization Parameters. Sustainability 2020, 12, 6422 .
AMA StyleDomokos Esztergár-Kiss. Trip Chaining Model with Classification and Optimization Parameters. Sustainability. 2020; 12 (16):6422.
Chicago/Turabian StyleDomokos Esztergár-Kiss. 2020. "Trip Chaining Model with Classification and Optimization Parameters." Sustainability 12, no. 16: 6422.
The preferences of travelers determines the utility of daily activity plans. Decision-makers can affect the preference of travelers when they force private car users to use park-and-ride (P&R) facilities as a way of decreasing traffic in city centers. The P&R system has been shown to be effective in reducing uninterrupted increases in traffic congestion, especially in city centers. Therefore, the impacts of P&R on travel behavior and the daily activity plans of both worker and shopper travelers were studied in this paper. Moreover, autonomous vehicles (AVs) are a promising technology for the coming decade. A simulation of the AV as part of a multimodal system, when the P&R system was integrated in the daily activity plans, was carried out to determine the required AV fleet size needed to fulfill a certain demand and to study the impacts of AVs on the behavior of travelers (trip time and distance). Specifically, a group of travelers, who use private cars as their transport mode, was studied, and certain modifications to their daily activity plans, including P&R facilities and changing their transport mode, were introduced. Using the MATSim open-source tool, four scenarios were simulated based on the mentioned modifications. The four scenarios included (1) a simulation of the existing transport modes of the travelers, (2) a simulation of their daily activity plans when their transport modes were changed to AVs, (3) a simulation of the travelers, when P&R facilities were included in their activity chain plans, and (4) a simulation of their daily activity plans, when both P&R and AVs were included in their activity chain plans. The result showed that using the P&R system increased overall travel time, compared with using a private car. The results also demonstrated that using AVs as a replacement for conventional cars reduced travel time. In conclusion, the impact of P&R and AVs on the travel behavior of certain travelers was evaluated in this paper.
Jairo Ortega; Jamil Hamadneh; Domokos Esztergár-Kiss; János Tóth. Simulation of the Daily Activity Plans of Travelers Using the Park-and-Ride System and Autonomous Vehicles: Work and Shopping Trip Purposes. Applied Sciences 2020, 10, 2912 .
AMA StyleJairo Ortega, Jamil Hamadneh, Domokos Esztergár-Kiss, János Tóth. Simulation of the Daily Activity Plans of Travelers Using the Park-and-Ride System and Autonomous Vehicles: Work and Shopping Trip Purposes. Applied Sciences. 2020; 10 (8):2912.
Chicago/Turabian StyleJairo Ortega; Jamil Hamadneh; Domokos Esztergár-Kiss; János Tóth. 2020. "Simulation of the Daily Activity Plans of Travelers Using the Park-and-Ride System and Autonomous Vehicles: Work and Shopping Trip Purposes." Applied Sciences 10, no. 8: 2912.
Road pricing is an efficient instrument to regulate use of roads. In Budapest, Hungary, only cordon pricing has been investigated in detail. This paper reports on a study of the implications of applying different road-pricing schemes in the city using a macroscopic traffic model. Firstly, the functional relationship between pricing schemes and road transport demand was investigated. Secondly the implications of applying road-pricing schemes on travel demand, travel time, delay time, average speed and carbon dioxide emission of road users inside and outside of the pricing area, as well as revenues generated by applying the schemes, was studied. The results showed the time-based system had the best performance inside the pricing area, but generates heavy congestion in non-priced roads bordering the pricing area that would increase the travel time, delay time and carbon dioxide emission and would decrease average travel speed in the entire network. The cordon-based system was the least-effective pricing system in most of the studied parameters, while the distance-based system showed good performance both inside and outside the pricing area. Regarding the generated revenues, variable toll systems (time-based and distance-based systems) showed the potential to generate higher revenues compared to the fixed toll system (cordon-based system).
Mohammad Maghrour Zefreh; Domokos Esztergar-Kiss; Adam Torok. Implications of different road pricing schemes in urban areas: a case study for Budapest. Proceedings of the Institution of Civil Engineers - Transport 2020, 1 -12.
AMA StyleMohammad Maghrour Zefreh, Domokos Esztergar-Kiss, Adam Torok. Implications of different road pricing schemes in urban areas: a case study for Budapest. Proceedings of the Institution of Civil Engineers - Transport. 2020; ():1-12.
Chicago/Turabian StyleMohammad Maghrour Zefreh; Domokos Esztergar-Kiss; Adam Torok. 2020. "Implications of different road pricing schemes in urban areas: a case study for Budapest." Proceedings of the Institution of Civil Engineers - Transport , no. : 1-12.
The focus of this article is to introduce a method for the optimization of daily activity chains of travelers who use Electric Vehicles (EVs) in an urban environment. An approach has been developed based on activity-based modeling and the Genetic Algorithm (GA) framework to calculate a suitable schedule of activities, taking into account the locations of activities, modes of transport, and the time of attendance to each activity. The priorities of the travelers concerning the spatial and temporal flexibility were considered, as well as the constraints that are related to the limited range of the EVs, the availability of Charging Stations (CS), and the elevation of the road network. In order to model real travel behavior, two charging scenarios were realized. In the first case, the traveler stays in the EV at the CS, and in the second case, the traveler leaves the EV to charge at the CS while conducting another activity at a nearby location. Through a series of tests on synthetic activity chain data, we proved the suitability of the method elaborated for addressing the needs of travelers and being utilized as an optimization method for a modern Intelligent Transportation System (ITS).
Dimitrios Rizopoulos; Domokos Esztergár-Kiss. A Method for the Optimization of Daily Activity Chains Including Electric Vehicles. Energies 2020, 13, 906 .
AMA StyleDimitrios Rizopoulos, Domokos Esztergár-Kiss. A Method for the Optimization of Daily Activity Chains Including Electric Vehicles. Energies. 2020; 13 (4):906.
Chicago/Turabian StyleDimitrios Rizopoulos; Domokos Esztergár-Kiss. 2020. "A Method for the Optimization of Daily Activity Chains Including Electric Vehicles." Energies 13, no. 4: 906.
In the era of intelligent transportation systems, there is an increasing need of developing dynamic transport models to improve the realism of simulations, aiming to higher efficiency of network management interventions, as well as to more reliable real-time user information. These tasks are still today faced by operators with limited support from transport modeling with respect to the potential contribution of state-of-the-art methodologies. Moreover, great opportunities are envisaged by the availability of distributed computing, artificial intelligence and big data. Thus, new applicative solutions for transport network operators can emerge based on new modeling paradigms where dynamics play a major role in different fields, such as transit service optimization and fleet control, human travel behavior and passenger information, urban freight distribution and vehicle routing, traffic signal setting and flow forecast and highway network management and road pricing.
Domokos Esztergár-Kiss; Gudio Gentile; Agostino Nuzzolo. Special issue on dynamic models serving real-time urban transport operations. Transportmetrica A: Transport Science 2020, 16, 161 -163.
AMA StyleDomokos Esztergár-Kiss, Gudio Gentile, Agostino Nuzzolo. Special issue on dynamic models serving real-time urban transport operations. Transportmetrica A: Transport Science. 2020; 16 (2):161-163.
Chicago/Turabian StyleDomokos Esztergár-Kiss; Gudio Gentile; Agostino Nuzzolo. 2020. "Special issue on dynamic models serving real-time urban transport operations." Transportmetrica A: Transport Science 16, no. 2: 161-163.
Activity Chain Optimization (ACO) is the task of finding a minimum-cost tour that visits exactly one location for each required activity while respecting time window constraints. We develop an exact algorithm that efficiently solves the ACO problem in all practical cases that involve hundreds of locations offering up to 10–15 activities and returns the optimal route with minimal time spent traveling and waiting. We also introduce a greedy heuristic that simulates human decision-making for comparison. Our experimental results highlight the practical significance of our work as we can reduce travel and wait times on 45 realistic Budapest inner-city routing problems by 16.65% on average compared to our baseline. Our algorithms’ computational and memory requirements for solving practical ACO instances are shown to be low enough to be employed on embedded devices, e.g. smartphones and navigation systems.
Domokos Esztergár-Kiss; Viktor Remeli. Toward practical algorithms for activity chain optimization. Transportation Letters 2019, 13, 64 -76.
AMA StyleDomokos Esztergár-Kiss, Viktor Remeli. Toward practical algorithms for activity chain optimization. Transportation Letters. 2019; 13 (1):64-76.
Chicago/Turabian StyleDomokos Esztergár-Kiss; Viktor Remeli. 2019. "Toward practical algorithms for activity chain optimization." Transportation Letters 13, no. 1: 64-76.
Domokos Esztergár-Kiss; Zoltán Rózsa; Tamás Tettamanti. An activity chain optimization method with comparison of test cases for different transportation modes. Transportmetrica A: Transport Science 2019, 16, 293 -315.
AMA StyleDomokos Esztergár-Kiss, Zoltán Rózsa, Tamás Tettamanti. An activity chain optimization method with comparison of test cases for different transportation modes. Transportmetrica A: Transport Science. 2019; 16 (2):293-315.
Chicago/Turabian StyleDomokos Esztergár-Kiss; Zoltán Rózsa; Tamás Tettamanti. 2019. "An activity chain optimization method with comparison of test cases for different transportation modes." Transportmetrica A: Transport Science 16, no. 2: 293-315.
Nowadays, several journey planners are available for users with various functionalities. The aim of this research was to provide an overview of European journey planners considering the perspective of the user. Therefore, a framework of aspects was defined, which contains aspects of route planning services, booking and payment, handled data, and supplementary information. Based on these aspects, an evaluation method was elaborated to compare and rank the journey planners. The method consists of two main steps. First, the journey planners were compared (scoring) to each other, which resulted in the general evaluation number. In the scoring step, multi criteria analysis was adapted, because it produces clear and comparable results. As a second step different user groups were introduced and, using preferences of these groups (weighting), the average evaluation number was calculated. Finally, the elaborated method presented a quantified evaluation and ranking of multimodal journey planners, which supports choosing suitable journey planners for the users.
Domokos Esztergár-Kiss. Framework of Aspects for the Evaluation of Multimodal Journey Planners. Sustainability 2019, 11, 4960 .
AMA StyleDomokos Esztergár-Kiss. Framework of Aspects for the Evaluation of Multimodal Journey Planners. Sustainability. 2019; 11 (18):4960.
Chicago/Turabian StyleDomokos Esztergár-Kiss. 2019. "Framework of Aspects for the Evaluation of Multimodal Journey Planners." Sustainability 11, no. 18: 4960.