International Transportation (71) 1 | 2019 30 Development of electromobility services Electromobility, Charging infrastructure, Charging planning The widespread of environmentally friendly drivetrains and alternative fuels is expected in the upcoming decades. Therefore, this research was done to aid the alteration from a conventional car to electric cars to fit the extant transport system and electrical network. I have developed novel operational methods for electromobility services, including charging station locating and charging planning methods. The research was conducted from a system and process-oriented point of view. The results may contribute to facilitate and prepare the alteration of the transport system. Bálint Csonka N owadays, the environment and the emission gained huge attention during the planning and the operation of transport. Accordingly, the widespread of environmentally friendly drivetrains and alternative fuels is expected in the upcoming decades. Electrification is the most prominent option among the many alternative technologies because of its advantageous characteristic (e. g., durability); however, other concerns also arise (e.g., Pan-European transportation matters For the 16th consecutive time the European Platform of Transport Sciences - EPTS - awards the “European Friedrich-List-Prize”. This prize, dedicated to young transport researchers, is named to honour the extraordinary contributions of Friedrich List, the visionary of transport in Europe of the 19th century, being a distinguished economist and respected transport scientist committed to the European idea. The European Friedrich-List-Prize is awarded for out-standing scientific papers in each of the categories Doctorate paper and Diploma paper, addressing topics in the transport field within a European context. The award will be conferred during the 19th European Transport Congress at the University of Maribor, Slovenia, on 7 October 2021. The results will be introduced both in the “Internationales Verkehrswesen” November issue and online at www.international-transportation.com. In the following you find a random selection of this year’s submissions summarized in drafts. Source: University of Maribor SCIENCE & RESEARCH European Friedrich-List-Prize European Friedrich-List-Prize SCIENCE & RESEARCH International Transportation (71) 1 | 2019 31 environmental effect of batteries). In many countries, various actions have been taken to support electrification in road transport, namely the use of electric vehicles, the deployment of charging infrastructure, and the development of information and communication technologies. The operation characteristic differs from the habitual and may cause the aversion of new technologies [1], which may be mitigated by applying intelligent and personalised information systems. More and more charging units are needed to serve the growing energy demand of electric cars at the same service level. The locating problem of charging stations arises, especially in the early phase when the deployment and operation of charging stations cannot be done on a market basis. Therefore, the characteristic of the charging network (e.g., location, charging power) has a significant influence on the spread of electric car use. As well as an intelligent transportation system manages the mobility demand, the additional energy demand should be managed by novel information services. Therefore, a charging planning method was elaborated to mitigate the adverse effect of charging demand on the electrical network. In this paper, the main findings of my PhD research are summarised with a focus on three key areas: electric car user information service, charging station locating and charging planning. Integrated information service At first, the main differences between electrical car use and conventional car use were identified. The differences may cause inconvenience and aversion for users. The main differences were limited range, charging, the highest purchase price. The functions of the information service were derived from the differences to mitigate the adverse effects. The functions are as follows: •• Support for new vehicle selection: information on electric cars is provided before purchase. Furthermore, the information service may evaluate electric vehicles considering the operation cost and CO 2 emission based on the charging infrastructure, road network, and user’s travel demand. •• Journey planning: the personalised and vehiclised journey is determined. The novelty of the journey planner is that the characteristics of electric vehicles and charging networks may be considered, and the charging is included. •• Charging assistance: helps to start and finish the charging process and provides information on the status of charging during the session. Charging time is reduced by providing information on the charging process to help the user finish charging. The charging may be finished automatically as soon as the user’s demands are met. A detailed description of the integrated information service can be found in [2]. Charging station locating Intra-city and inter-city charging demand were distinguished. In the case of intra-city charging, the vehicles may be charged during parking. Therefore, the long charging time may not cause inconvenience if the charging station is close to the destination. In the case of intercity charging, the charging session interrupts the journey. Therefore, fast charging is utmost of importance. Because of the differences, separated charging station locating methods were elaborated for urban areas and national roads. Urban areas A two-level weighted sum model had been elaborated to determine the areas where the willingness to use an electric car is high and public locations where users would frequently charge (figure 1). On the macroscopic level, the distribution of charging stations among territory segments in the investigated territory considering the potential of electric car use was performed. The potential was determined based on the number of registered electric cars, average income, tourism importance, and other influencer effects such as subsidies on parking and charging. On the microscopic level, the territory segments are divided into hexagons. The hexagon size was based on the willingness to walk between the charging station and the destination. The installation potential was calculated for each hexagon. The installation potential was determined based on the general parking demand at location types, willingness to walk, residential area type, the number of points of interest and the population in the hexagon. Various scenarios were determined using different weights. A detailed method can be found in [3]. National roads A weighted multicriteria location optimisation method with ranking and selection was elaborated. The selection of proposed fast-charging station sites from the candidate sites was performed on several layers. It was desired and assumed that the inter-city traffic is concentrated on the main national roads. Hence, road categories were put in focus and assigned to layers. E.g., motorways and main roads may be considered on different layers. Unlike in several other studies [4], O-D flows were not considered to provide an applicable method if the origin-destination (O-D) data are unavailable. Thus, the focus was put on the spatial coverage and not on origin-destination flows. Figure 1: Territory segments on macroscopic and hexagons on microscopic level - the subjects of evaluation Own work SCIENCE & RESEARCH European Friedrich-List-Prize International Transportation (71) 1 | 2019 32 The candidate site with the highest installation potential was selected. The installation potential is calculated considering the traffic volume, the total population of nearby settlements, service level at the site, and the location of existing fast-charging stations. Already selected candidate sites are considered as existing fastcharging stations. The method was verified using O-D data for several electric car range scenarios. It was found that a high share of served traffic volume can be achieved even at a low electric car range by emphasising the importance of traffic volume. A detailed method can be found in [5]. Charging planning In the literature, centralised [6] and decentralised [7] charging planning methods can be found. In the case of centralised planning, the calculation is performed at a centre based on the characteristics of supply and demand. The aim is to achieve a global optimum. In the case of decentralised control, the aim is to achieve local (EV user) optimum. Namely, the optimisation of charging sessions is performed separated. Thus, only one electric vehicle’s charging demand is considered at once. I have elaborated a decentralised charging planning method to minimise the user’s charging cost. The charging plan includes when and where to charge. The charging plan was determined based on the supply and demand (figure 2). A two-way energy stream between the vehicle and the electrical network was considered. The efficiency of the method was tested for several scenarios considering various charging strategies and dynamic tariff systems. It was found that the elaborated charging planning method is an efficient tool to minimise the charging cost and decrease the fluctuation of the electricity demand. Depending on the dynamic rates, the method may significantly reduce charging costs. A detailed method can be found in [3]. Conclusion The elaborated concept of the integrated information system is the basis of the implementation, and it provides a framework for electromobility services that support electric car use. The novel functions, the necessary input data groups, the components, and the relationship among them had been revealed, which are beneficial for the operators of future electromobility services. The elaborated charging station locating methods support the deployment along national roads and in urban areas in the early phase, while the deployment cannot be done on a market basis, and the locations have a substantial influence on electric vehicle use. The location selection was made in consideration of the estimated charging demand. The e-Mobi Elektromobilitás Ltd applied the methods. The precondition of the elaborated charging planning method is the different electricity rates at charging stations. Thus, the user may benefit from the use of charging optimisation. Reducing the grid load fluctuation by decentralised charging optimisation a dynamic electricity rate based on the free capacity is necessary. However, such a dynamic electricity rate is not resolved yet; there is a huge potential in the application of charging optimisation. ■ REFERENCES [1] Büscher, M.; Coulton, P.; Efstratiou, C.; Gellersen, H.; Hemment, D.; Mehmood, R.; Sangiorgi, D. (2009): Intelligent mobility systems: some socio-technical challenges and opportunities. In: International Conference on Communications Infrastructure. Systems and Applications in Europe, pp. 140-152. www.doi.org/ 10.1007/ 978-3-642-11284-3_15 [2] Csonka, B.; Csiszár, C. (2019): Integrated Information Service for Plug-In Electric Vehicle Users Including Smart Grid Functions. In: Transport 34(1), pp. 135-145. https: / / doi. org/ 10.3846/ transport.2019.8548 [3] Csiszár, C.; Csonka, B.; Földes, D.; Wirth, E.; Lovas, T. (2019): Urban public charging station locating method for electric vehicles based on land use approach. In: Journal of Transport Geography 74, pp. 173-180. https: / / doi.org/ 10.1016/ j.jtrangeo.2018.11.016 [4] Capar, I.; Kuby, M.; Leon, V. J.; Tsai, Y-j. (2013): An arc cover-path-cover formulation and strategic analysis of alternative-fuel station locations. In: European Journal of Operational Research 227, pp. 142-151. https: / / doi.org/ 10.1016/ j.ejor.2012.11.033 [5] Csiszár, C.; Csonka, B.; Földes, D.; Wirth, E.; Lovas, T. (2020): Location optimisation method for fast-charging stations along national roads. In: Journal of Transport Geography 88, 102833. https: / / doi.org/ 10.1016/ j.jtrangeo.2020.102833 [6] Klaimi, J.,; Rahim-Amoud, R.; Merghem-Boulahia, L.; Jrad. A. (2018): A novel loss-based energy management approach for smart grids using multi-agent systems and intelligent storage systems. In: Sustainable Cities and Society 39, pp. 344-357. https: / / doi. org/ 10.1016/ j.scs.2018.02.038 [7] Mal, S.; Chattopadhyay, A.; Yang, A.; Gadh. R. (2012): Electric vehicle smart charging and vehicle-to-grid operation. In: International Journal of Parallel, Emergent and Distributed Systems 28(3), pp. 249-265. https: / / doi.org/ 10.1080/ 17445760.2012.663757 Bálint Csonka, PhD Research associate, Department of Transport Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Budapest (HU) csonka.balint@kjk.bme.hu Figure 2: Charging planning method input and output Own work European Friedrich-List-Prize SCIENCE & RESEARCH International Transportation (71) 1 | 2019 33 Estimation of turning rates in roundabouts, applying state-space estimation methods Traffic estimation, Roundabout, Turning rate, Traffic count, Kalman Filter, Constrained Kalman Filter The aim of this paper is the examination and comparison of different estimation methods used for determining turning rates (OD-matrix) in roundabouts. A traditional iteration-based approach as well as state-space estimators are validated on real-world traffic data. For the estimation procedures, the traffic flows (measured at each leg of the intersection) are the input. In this way, the manual origin-destination traffic count at an intersection can be substituted by automated traffic detection at the cross-sections together with an adequately implemented estimation process. Mánuel Gressai R oad traffic infrastructure planning or development is initiated based on reliable traffic modeling. The input of the modeling is the vehicular flows on road links and turning rates at intersections. Traffic volumes at cross-sections can be straightforwardly measured manually or with help of a wide variety of traffic sensors. At the same time, turning flows or turning rates can be collected by human resources solely, which is quite costly. Therefore, if turning flows are collected, typically more than one person is needed to perceive all movements. The more, observing turnings in roundabouts is extremely problematic due to the special geometry and size of this type of junction. Figure 1 demonstrates the possible turning movements at a roundabout for vehicles arriving at Entrance 1. V 1j is the turning traffic flow from Entrance 1 to exit j, whereas V 1,in and V 1,out are the total traffic volumes entering and exiting at the corresponding junction leg. Using the volumes in figure 1, turning rates can be defined as follows: (1) where n D is the number of exits. Counting traffic on the legs of a roundabout and adequately estimating turning rates based on the collected data has the potential to substitute labor-intensive turning flow counts. This could reduce the cost of determining turning rates at an intersection significantly. In this paper, cross-sectional counts are used as a basis to estimate turning rates at a roundabout. This proposes a possible solution to overcome the obstacles posed by turning movement observation. This paper is divided into 5 sections. A description of the examined estimation methods follows the introduction. Next, the testing of different estimation methods is presented. The methods are then compared using different error metrics. Finally, a case study is established to determine whether the tuning of the best performing estimator depends on the traffic conditions, or it can be considered robust under different circumstances. Recommendations and future directions for the research are stated, and conclusions are drawn the last section. Estimation methods This section covers different methods used for turning rate estimation. Biproportional procedure is discussed as a traditional iterative algorithm, then the Kalman Filter and its extension with constraint handling are introduced as well as the Moving Horizon Estimation. The biproportional procedure (BP) is an iterative algorithm [1], where the variation of two coefficients causes the variation of turning flows in each iteration. The BP procedure aims to estimate the elements of the current OD-matrix based on the current flows on each leg and the prior OD-matrix. State-space based estimators such as the Kalman Filter include a model of the system and noises [2]. Some procedures are apt to manage constraints concerning- the- estimated values (e.g., for each turning rate to be- non-negative). Moreover, these methods estimate Figure 1: Possible turning movements at a four-legged roundabout from one direction Own work SCIENCE & RESEARCH European Friedrich-List-Prize International Transportation (71) 1 | 2019 34 the- mean and standard deviation for all states in each interval. The Kalman Filter (KF) uses the estimated states (turning rates) in the previous step and the measurements in the current step to estimate the current state. The constrained Kalman Filter (cKF) contains an optimization after each step for the estimated values to satisfy previously defined constraints. The constraint handling section contains a weighing matrix which can be set to an identity matrix (I) or the error covariance matrix (P) in each step [3, 4]. Based on these options, cKF-I and cKF-P methods were defined. The MHE not only contains an optimization problem to minimize the state and measurement noises, but it can also consider the estimated values of more than one previous steps [5]. The horizon length ranged from 1 to 4 during the tests, and these cases were named MHE1, MHE2, MHE3, and MHE4, respectively. Applying the estimation methods Real turning movement volumes were counted at two different roundabouts for the research. In this way, after the calculation of turning rates, real data was available for validation and comparison of the proposed estimation algorithms. The 30-minute counts were divided into 1, 2, and 5-minute intervals, so that the estimation methods could be tested for different data input frequencies. The estimation algorithms introduced in the paper are based on the counted number of vehicles expressed in PCE (Passenger Car Equivalent [6]). The input of the estimators is the traffic flows, but the real turning rates are also known. This makes it possible to compare the estimated turning rates with the real data using error metrics. Four different error metrics [7] have been applied during the evaluation of estimation procedures: •• mean absolute error (MAE), •• root mean square error (RMSE), •• mean absolute percentage error (MAPE), and •• symmetric mean absolute percentage error (SMAPE). These metrics were also used during the tuning of the state-space estimators. The weighing between the state noise and measurement noise covariance matrices determines the attributes of the estimation. The tuning was carried out by searching for the minimum of errors. Based on the results, it can be stated that the longer the interval, the more accurate the estimation. The 5-minute interval led to the smallest errors in the case of every examined method. This clearly means that on longer time intervals, the algorithms can better smooth their estimations. Based on this, 1or 2-minute sampling intervals are not suggested to be applied in this practical problem. Table 1 lists the average error measures for all examined estimation methods in the case of 5-minute interval sizes. A ranking in the MAE values is also assigned to the procedures. In this case, the cKF and the MHE outperform the BP method and the unconstrained Kalman Filter. The comparison revealed that, although the performance of the MHE is generally slightly higher than that of the constrained Kalman Filter, tuning the MHE is often problematic. Therefore, the constrained Kalman Filtering is suggested as the best estimation procedure, taking the tuning circumstances and the performance into account. Simulation-based case study A case study was also carried out, the basis of which is another real-world traffic count. The examination was then extended to a simulation environment created in PTV Vissim modeling software. In this case, the 4-hour traffic measurements consisted of 15-minute intervals. Every method was tuned to the available traffic data sets. In case of the 15-minute intervals, the constrained Kalman Filter (cKF-P) turned out to estimate with the smallest errors. After the GEH validation [8, 9], a simulation model was established, and different traffic circumstances were created in the modeled environment. The cKF-P proved to be the most effective estimator; therefore, its performance was tested in the different scenarios, without changing the tuning. Three traffic parameters were altered to create the scenarios: •• traffic volumes, •• the proportions of the main road and side road volumes (traffic ratio), •• the position of the main road (opposite or adjacent legs). The created scenarios are as follows: •• S0: control scenario, the average of morning and afternoon traffic counts; •• S1: S0 scenario’s OD matrix, multiplied by 1.3; •• S2: 1: 2 traffic ratio, main road is opposite legs (2, 4); •• S3: 1: 6 traffic ratio, main road is opposite legs (2, 4); •• S4: 1: 2 traffic ratio, main road is adjacent legs (2, 3); •• S5: 1: 6 traffic ratio, main road is adjacent legs (2, 3). Comparing the errors of the scenarios with the control case, the following observations can be made: •• the alteration of traffic parameters did not affect the performance of the constrained Kalman Filter substantially; •• the increase of traffic volumes did not cause anomalies in the estimation; •• concerning the main and side road volume ratios, the cKF-P was more accurate when the side road volume proportions were lower; •• adjacent main road legs resulted in larger errors; •• in case of opposite main road legs, estimation performance was affected more by the traffic ratios. Intervals: 5 min Method MAE RMSE MAPE SMAPE Rank (MAE) BP 0.0670 0.1050 27.89% 11.53% 5 KF 0.0742 0.1118 32.51% 11.95% 7 cKF-I 0.0692 0.1048 27.84% 11.66% 6 cKF-P 0.0608 0.0945 24.72% 10.29% 3 MHE1 0.0599 0.0928 26.84% 10.92% 1 MHE2 0.0602 0.0942 25.81% 10.66% 2 MHE3 0.0633 0.1027 31.36% 11.74% 4 MHE4 0.0745 0.1054 32.39% 13.68% 8 Table 1: MAE rank for the examined methods (5-min intervals) European Friedrich-List-Prize SCIENCE & RESEARCH International Transportation (71) 1 | 2019 35 Conclusions The main contribution of the paper is the validated comparison of different methods on real-world data sensed by drone and then counted manually. Analyzing the results, the following conclusions can be drawn: •• in general, longer intervals result in more accurate estimations; •• managing constraints improves the accuracy of the state-space estimators significantly; •• the adequately tuned constrained Kalman Filter and MHE outperform the unconstrained Kalman Filter and the traditional iterative procedure. The comparison was followed by a simulation-based case study. Tuning the state-space estimators determined that, for the examined roundabout and circumstances, the constrained Kalman Filter (cKF-P) was the most adequate method. After building the model and validating it, different scenarios were created as an input for the cKF-P. The case study led to these conclusions: •• in general, different traffic situations did not affect the performance of the estimation significantly; •• the tuning of the cKF-P can be considered robust; •• increasing traffic volumes did not cause anomalies in the estimation performance; •• the estimation is more accurate, when the side road traffic volume proportions are lower; •• the estimation is more accurate, when the main road runs on opposite legs. The continuation of this research is twofold. On the one hand, managing different road vehicle categories is an important research aim, as road planning companies generally require traffic counts with four different vehicle classes. On the other hand, a more sophisticated tuning can be developed for the state-space estimators. This can involve determining different parameters for the main road and the side road, or even traffic responsive tuning. As the result of the research, it can be stated, that state-space estimation methods combined with automatic cross-section traffic counts provide a real alternative to paper-based, manual intersectional traffic counts in case of roundabouts. ■ REFERENCES [1] Ben-Akiva, M.; Macke, P. P.; . Hsu, P. (1985): Alternative methods to estimate route-level trip tables and expand on-board surveys. In: Transportation Research Record. [2] Kalman, R. E. (1960): A new approach to linear filtering and prediction problems. In: Journal of Basic Engineering (ASME). [3] Gupta, N.; Hauser, R. (2007): Kalman filtering with equality and inequality state constraints. Oxford University Computing Laboratory. [4] Simon, D. (2010): . Kalman filtering with state constraints: a survey of linear and nonlinear algorithms. In: IET Control Theory & Applications. [5] Haugen, F. A. (2018): A brief introduction to optimization methods. [6] Lay, M. (2009): Handbook of Road Technology. Spon Press. Abingdon, UK. [7] Chen, C.; Twycross, J.; Garibaldi. J. M. (2017): A new accuracy measure based on bounded relative error for time series forecasting. In: PloS one. [8] Feldman, O. (2012): The GEH measure and quality of the highway assignment models. In: Association for European Transport and Contributors, pp. 1-18. [9] TfL (Transport for London): Traffic Modelling Guidelines: In: TfL Traffic Manager and Network Performance Best Practice Version 3.0. 2010. Mánuel Gressai Research associate, Department of Control for Transportation and Vehicle Systems, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Budapest (HU) gressai.manuel@edu.bme.hu Road transport price Correlation of rates for road transport services in domestic transport in-Poland Economic transport, Data analyst, Road transport, Freight forwarding, Transport management The work focuses on the study of the correlation between the GDP of geographical regions and transport rates. Analyzed what influences the price of transport the thesis was put forward that transports whose loads are located in economically developed regions cost more than those whose loads are in less developed regions. The research used data on transports carried out in Poland. The results were compared with the GDP ratio given for each NUTS3 sub-region. A correlation was found and the thesis made at the beginning was confirmed. Artur Budzyński T he main aim of this article is to investigate how the GDP of the NUTS geographical sub-regions affects the price of a transport service. Thesis put forward is that there is a correlation between the transport rates and the areas of loading these shipments. It is assumed that transport from more economically developed SCIENCE & RESEARCH European Friedrich-List-Prize International Transportation (71) 1 | 2019 36 regions is more expensive than the less developed ones. The aim of the work is to list the transports offered on transport taking particular account of the place loading and the transport rate per kilometre of the route. The work discusses the issues valuation of transport rates by people operating in enterprises transport and forwarding and the methods used so far. Then it will be demonstrated correlation between rates and districts. The research methods that will be used is compilation of these routes and calculations using: deviation, average, comparison. [1] Transport is the driving force of the Polish economy. Poland is in a very good connection strategic at the intersection of European transport corridors. It is a trans-European transport network. Coordinates and binds investments infrastructural. Everything is regulated by the Regulation of the European Parliament and Council of the European Union on EU guidelines for the development of the Trans-European Transport Network (TNT). Currently, there are 46 states on the European continent and two de facto independent states. The European Union has 28 states in its structures. Individual countries are divided into postal codes. Postal codes are a series of numbers or numbers and letters. They make it possible to identify the address. The code starts with two letters identifying the country where it is located. There are several types of how the rest of the postal code is written. The most convenient for the work of an operator in logistics and forwarding is the system of dividing the country into ten districts first (first digit), then each district is divided into ten more districts (second digit). The method facilitates grouping regions into larger ones. Examples are Germany and Poland. The transport rate is a specified amount that the client pays the contractor for the performance of transport. The pricing of a given route depends on many factors. The main division that is important for the study of correlation is the division into the costs of the working day of the road set and the driver, and those depending on the mileage. Fuel and tolls are mileage dependent. Tire wear is also largely dependent on the distance travelled. The OCP carrier’s insurance is purchased once a year, so it does not depend on how many kilometres the set covers. It is worth noting that the costs of employing a driver are fixed and depend on how much he works. Sometimes the practices used to bill the driver by kilometres travelled are illegal. This is stated in the Regulation of the European Union Commission 2016/ 403, Annex I, point 32 of the table. This is classified as a very serious breach that could lead to a loss of goodwill. A good reputation is necessary to have a transport license and perform the work of a road carrier. From this division it can be concluded that longer routes in international relations have a lower rate than shorter ones. TimoCom is one of the most important freight exchanges in Europe. Up to 750,000 offers of free loading space and loads are submitted every day. The company offers a transport barometer for mobile devices, supported by Android and iOS systems. The application collects the number of offers reported by users and calculates the proportions between free loads and cargo space. The disadvantage of the application is that it does not analyze the rates that are offered on the given relationships. You can only get information about the demand and supply between the given countries. Also, it is not possible to divide the country into smaller parts. The detailed view allows you to see the dependencies in previous years [2]. Route data was collected to test the correlation. The analysed orders are domestic, i. e. the place of loading and unloading is in Poland. These are full truck loads, i.e. they occupy 13.6 meters of cargo on a semi-trailer. Only loads that are carried by a standard type of semi-trailer with a minimum height of 2.6 meters are taken into account. The weight of the transported goods is 24 tons. Transport of dangerous goods that could inflate rates was excluded. The collected data on transports are: place of loading, place of unloading, rate. For the collected data, the distance between the place of loading and unloading using TimoCom transport machines was calculated. Maps calculate the route taking into account the height of the set and the total weight. It is a much more precise tool than, for example, Google Maps. The next step will be to assign regions compliant with the NUTS classification to transports. The classification was introduced in Poland on November 26, 2005. The reason for introducing NUTS was the accession of new countries to the European Union, including Poland. There are currently 97 NUTS units in Poland. They are divided into 3 categories: NUTS 1, NUTS 2, NUTS 3. NUTS 1 is the largest and these are microregions grouping voivodships. There are 7 of them. Due to their large size, the correlation between them has not been tested. NUTS 2 are regions, voivodships or parts of them. There are 17 of them in Poland. The smallest unit is NUTS 3, i. e. subregions. There are 73 units of them. Due to the fact that these are the smallest areas for which statistics are conducted, the focus was on analysing them at work. The next step is to group the transports according to the first two digits of the zip code and calculate the arithmetic mean from each. It is worth noting that there are 99 postal codes in Poland. There is no code starting with 79. The results of the calculations are in figure1. The arithmetic mean of the transport rates is PLN 3.15 rounded to the nearest whole grosz. However, the median of these rates is PLN 3.11. The most expensive transports were loaded in the following postal codes: 00; 04; 01; 02; 03 - they are all located in the subregion of the city of Warsaw. The postal code from which the cheapest transports departed is 89, it is located in the Świecie subregion. 39 postal codes are above the arithmetic mean of rates, which is around 39 %. Similarly, 60 is below which is 61 % of codes. The collected results of the arithmetic means from all codes were grouped into ten intervals and assigned to each color. Then, a map was created with a division into postal codes and the colour was selected in accordance with the rate at which transports left it on average. The next step is to group the transports according to the first digits of the postal code and calculate the arithmetic mean from each. The arithmetic mean amounts to PLN 3.16, rounded to the nearest grosz. The median is Figure 1: Graphical presentation of transport rates with division into postal codes Own source European Friedrich-List-Prize SCIENCE & RESEARCH International Transportation (71) 1 | 2019 37 PLN 3.15 rounded to the nearest pennies. 6 postal codes have a greater value than the average, which is 60 %. On the other hand, 4 postal codes have a lower value, which is 40 %. Gross Domestic Product - GDP in short is one of the most important data about the work of society. This measure is recognized by economists. It is the money value of all goods and services produced. It can be assumed that GDP is growing in a developing economy. High GDP indicates a highly developed economy, low GDP a poorly developed one. The work uses the data of the Central Statistical Office on gross domestic product with a breakdown into geographical subregions according to the NUTS 3 classification. The collected data is presented in the form of a graph in figure 2. Only those subregions where the places of loading of the analyzed transports are located were taken into account. The values assigned to 56 subregions were obtained. The arithmetic mean of gross domestic product was PLN 25,704 million. The median of these values was PLN 17,846 million. 19 subregions have a value above the arithmetic mean, which is rounded to 34 %. Similarly, 37 subregions have a value below the arithmetic mean, which is 66 % [3]. A more precise examination of the above parameters requires also calculating the variance and standard deviation. The standard deviation amounted to 14,205. The largest and significantly different deviation is recorded in the Warszawa subregion, it is over fourteen times higher than the average standard deviation. One of the largest, but not so different from the average, is the deviation for highly developed subregions: Kraków, Trójmiasto, Wrocław, Warsaw West. This is an expected and logically meaningful relationship. In the subregions with the lowest deviation, there are no cities where they are, as was the case with the largest ones. Subregions in the vicinity of large cities dominate: Rzeszów, Kraków and Piotrków. In this case, it was decided to divide the sub-regions not according to the amount of GDP, but according to the standard deviation. The ratio of GDP to transport rates was calculated, broken down into all two-digit postal codes. The arithmetic mean of these ratios is rounded to the whole of 7507. The median is 7477. 49 values of the ratios turned out to be higher than the arithmetic mean, which is rounded to 49 %. On the other hand, 50 results turned out to be lower than the arithmetic mean, which is around 51 %. It has been confirmed that economic factors have an impact on the price of a road transport service. Transports are more expensive from more developed regions than from less developed regions. The commercial application of the research results was awarded in the 17 th edition of the “My Idea for Business” competition organized by the Silesian University of Technology. The results of the work are the starting point for future research [4, 5]. ■ REFERENCES [1] Budzyński, A. (2020): Correlation of transport rates between geographical regions at Sprint Logistyka Polska Spółka Akcyjna Spółka Komandytowa. Master Thesis. Department of Transport and Aviation Engineering Silesian University of Technology. [2] Timocom. www.timocom.pl (accessed 2021-06-13). [3] Central Statistical Office. https: / / stat.gov.pl/ statystyka-regionalna/ jednostki-terytorialne/ klotykacja-nuts/ klociągacja-nuts-w-polsce (accessed 2021-06-13). [4] Silesian University of Technology: Results of the 17 th edition of the “My Idea for Business” competition. www.arch.polsl.pl/ Lists/ AktualnosciUczelniane/ PokazWiadomosc.aspx? W ebPartTitle=ListaWiadomosci&Page=7&WebPartTitle2=Wiadomosc&Filter1Field2=Identyf ikator&Filter1Value2=3833 (accessed 2021-06-13). [5] Budzyński A. (2020): Use dependencies between freight prices and economic factor as a solution in improve efficiency work in road transport. In: XII Int. Sci. Conf. & IX Int. Symposium of Young Researches „Transport Problems 2020”. Conference Proceedings. P. 95-102. Katowice: Silesian University of Technology. Faculty of Transport and Aviation Engineering. ISBN 978-83-959742-0-5. Artur Budzyński, MSc PhD Student, Silesian University of Technology, Katowice (PL) artur.budzynski@polsl.pl Warszawa Kraków trójmiejski Wrocław warszawski zachodni katowicki świecki chojnicki suwalski bialski przemyski Łódź nyski inowrocławski słupski gorzowski słupski włocławski ciechanowski szczecinecko-pyrzycki krośnieński bydgosko-toruński koszaliński ostrołęcki sandomiersko-jędrzejowski tarnowski puławski sieradzki gorzowski poznański bytomski łódzki chełmsko-zamojski nowosądecki starogardzki elbląski bielski białostocki legnicko-głogowski lubelski radomski jeleniogórski kaliski Szczecin kielecki wałbrzyski leszczyński wrocławski opolski gliwicki zielonogórski krakowski piotrkowski rzeszowski 0 50000 100000 150000 200000 250000 Standard deviation GDP [mln. PLN] Figure 2: The relation of GDP per capita and standard deviation in sub-regions Own work SCIENCE & RESEARCH European Friedrich-List-Prize International Transportation (71) 1 | 2019 38 Mobility measures and the housing sector Evaluation of the impact of mobility measures in newly planned residential areas Mobility measures, Housing sector, Mobility survey, Mobility behaviour Measures in mobility management are particularly efficient in life-cycle changes and therefore promising in combination with new housing developments. Robust evidence on the effectiveness of the various possible measures is still lacking. Based on multimethod approach, this study investigates the impacts and relevance of mobility measures for new housing developments in Austria. The results show which measures are efficient in encouraging residents to adopt a more environmentally friendly mobility behaviour. Jonas Krombach, Regine Gerike, Caroline Koszowski, Andrea Weninger I n terms of sustainable and healthy urban mobility, daily journeys should be ideally made on foot, by bike or by public transport. Nevertheless, the reality in many cities looks different - the private car still plays a dominant role in everyday mobility causing problems like air and noise pollution. The question is: how to encourage citizens to adopt a more environmentally friendly mobility behaviour? Since 80 % of all daily activities start and end at home, the place of residence is highly relevant [1, 2]. There are numerous studies available showing that urban design and the transport system influence people´s mobility behaviour [3, 4]. Applying this to residential areas, there is general presumption that the presence of mobility measures in the direct vicinity of residential areas might have some potential to influence mobility behaviour of new residents, but this has not been scientifically proven so far. Seeing this gap in research, the diploma thesis [5] - submitted for the European Friedrich-List-Award 2021 - takes a closer look at two new housing developments in Austria. The focus lays specifically on the impact and influence of mobility measures on residents as well as on the challenges faced by stakeholders who are involved in planning process of new housing developments. The term “mobility measures” used in this article describes measures in mobility management that cover infrastructural (e.g. footpath design, green spaces, bike parking facilities), informative (e.g. wayfinding system or information boards in residential areas), service (e.g. car and bike sharing service, parcel stations in residential areas) or incentive measures (e.g. free public transport tickets for residents). [6] Study areas and research methods With Quartier Riedenburg, Salzburg (QR), and Perfektastraße 58, Vienna (PS), two residential areas were identified as suitable study sites for this thesis. Both neighbourhoods were recently completed and offer a wide range of different mobility measures. Quartier Riedenburg has 316 flats and is centrally located, while on the other hand Perfektastraße 58 is relatively smaller (115-flats) and located on the outskirts of Vienna. Apart from that, two research methods were chosen for the thesis: 1. mobility surveys with residents of the neighbourhoods and 2. expert interviews with involved stakeholders (housing developers, property management municipal administration, architects, mobility provider and social organisation). [5] Part 1: Mobility survey with residents The mobility surveys, carried out in both study areas in March 2020, targeted all residents aged over 18 years. A- comprehensive questionnaire in paper format was therefore handed over personally at the resident’s front doors. The developed questionnaire included questions about the resident’s mobility behaviour before and after moving to their current residential area. In this context, the residents were also asked which mobility measures they perceive as particularly important. Due to Covid-19 measures (lockdown), both mobility surveys had been severely affected. The face-to-face distribution of the questionnaires to all households was no longer possible from mid-March 2020, which had a high impact on the sample size. In Quartier Riedenburg the sample consisted out of 82 returned questionnaires from originally 229 distributed questionnaires (response rate: 36 %), which represents a substantial proportion of all residents. In Perfektastraße 58 a total number of 20 questionnaires out of 69 distributed questionnaires were returned (response rate: 29 %). Both samples cover a wide age distribution. [5] Main results The mobility behaviour of the residents of both neighbourhoods has changed in favour of a more environmentally friendly mobility behaviour by moving into Quartier Riedenburg, respectively, Perfektastraße 58. Specifically, an increase in walking, cycling and public transport use could be observed whereas at the same time the usage of the private car dropped. In both study sides, the number of cars per household has clearly decreased in comparison with the previous housing situation (e. g. QR: reduction from 1,34 to 1,06 cars per household). Furthermore, European Friedrich-List-Prize SCIENCE & RESEARCH International Transportation (71) 1 | 2019 39 a detailed examination of the results of Quartier Riedenburg shows that the greatest shift in favour of environmentally friendly means of transport (+ 16 %) is to be found in journeys made in the immediate vicinity of the residential area. [5] In terms of the importance of individual measures a largely similar picture with equal patters can be noticed (see figure 1). Especially the measures promoting walking (e.g. green spaces) were highly ranked. Cycling measures tended to be rated more important for the residents of Quartier Riedenburg. The overall most important mobility measure in both surveys turned out to be the good connection to a nearby public transport stop. Measures with future potential are infrastructure for electric cars (e-charging stations) and parcel stations within a residential estate. Any sharing mobility measures (car, bike or moped sharing) were considered less important by the residents of both residential areas. [5] 3,12 2,50 2,19 1,50 2,50 2,07 1,94 3,95 3,50 2,28 2,58 2,94 2,21 2,53 1,73 1,53 1,73 1,91 2,31 3,18 3,00 2,44 2,76 2,94 2,75 3,26 2,94 3,44 2,45 3,55 3,50 2,85 3,16 2,77 1,99 1,68 2,65 2,03 2,06 3,74 3,20 2,43 2,42 3,61 2,23 2,40 1,55 1,55 1,61 2,27 2,78 3,60 3,12 2,18 3,66 3,71 2,63 3,53 2,98 3,18 2,99 3,71 3,47 3,23 1,00 2,00 3,00 4,00 Parcel Station within the residential estate Discounts at Local Suppliers and Facilities (e.g. Gastronomy) Shopping-Trolleys (to hire) E-Mopeds Sharing Service Infrastructure for E-Cars Discounts for Car-Sharing Membership Car-Sharing service Short Walking Distance to the Station Free/ Incentive Tickets for residents Information Material for new residents (in packages) Departure Monitors in the Entrance of Buildings Good Connection to the Urban Cycling Network Discounts for a Bike Repair Service and Repair Station Bike-Sharing Service for E-Bikes Bike-Sharing Service for Cargo Bikes Bike-Sharing Service for Classical Bicycles Power Outlets for E-Bikes Storing Facilities for Trailers Accesses to the Bicycle Rooms have a Sufficient Width Locked Bicycle Parking Facilities Lifts for Transporting Bicycles Sufficient Number of Roofed Bicycle Parking Facilities Sufficient Number of Bicycle Parking Facilities Orientation Plan and Wayfinding in the residential area Good Connection to the Urban Pedestrian Network Space for Activities Accessibility (Barrier-free residential area) Sufficient Number of Outside-Seating Elements Green Spaces Good Lighting of the Paths Straight and Direct Routing Within the Residential Area Comparison of the Importance of Mobility Measures QR PS Mean value: 1,00=not important; 2,00=rather not important ; 3,00=rather important; 4,00=important Bicycle Traffic Public Transport Motorized Traffic Further Measures Pedestrian Traffic Figure 1: Importance of Mobility Measures (QR = Quartier Riedenburg; PS = Perfektastraße 58) Source: [5], translated SCIENCE & RESEARCH European Friedrich-List-Prize International Transportation (71) 1 | 2019 40 Part 2: Expert interviews with ten stakeholders Aside from the mobility survey, ten telephone interviews with stakeholders were organized in spring 2020. The interviews revolved around financial, organizational, operational and legal hurdles. It is crucial to make a fundamental distinction between subsidised and privately financed housing projects, because in subsidised housing projects, the budget is generally tighter and measures have to be financed under strict legal frameworks. There is a tendency that this may lead to a loss of quality in certain measures (e. g. quality of green spaces) or that measures have to be dropped out completely due to the tight legal framework (e. g. free residential tickets for public transport). [5] In terms of car parking spaces in the residential area, privately financed housing companies tend to have a more conservative approach. Building less parking space than flats is less favourite, since this may be a competitive disadvantage in housing market. In subsidised housing, on the other hand, this is seen as more of an option, since the demand for car parking spaces can be better estimated in advance. In general, the common opinion is that a reduction in the number of car parking spaces should be only carried out to a reasonable extent in order to avoid excessive parking pressure in the neighbourhood’s streets on the one hand and prevent unused underground parking garages on the other. Since a reduction furthermore has to be decided by local politics the decision is strongly dependent on the prevailing political conditions. [5] Regarding bicycle parking facilities different options clash. For housing companies, bicycle facilities on the ground floor of buildings are less favourable as they may reduce the number of possible flats on the ground floor. For architects, the ground floor area is more seen as an open space for communication. The municipal administration and mobility planners, on the other hand, are of the opinion that it makes sense to build bicycle parking facilities on ground floor level to ensure better accessibility. It is striking that there is currently no legal basis for the quality of bicycle parking facilities in Austria. The qualities can only be demanded by the municipality (e. g. in a mobility concept). [5] Concerning sharing mobility (car and bike sharing), the general opinion is that self-management of such services is only economical viable from a certain size of the housing estate. There are currently many legal hurdles to overcome, which is why it is an obstacle for many developers. [5] Finally, it is important to mention that mobility measures strongly correspond with the surrounding infrastructure. The success of mobility measures depends to a large extent on the existent infrastructure (urban mobility network) outside the residential area. As this is outside the scope of action of the housing developers, the municipality has a decisive role to play. [5] Conclusion and recommendation The results show that mobility measures in new residential areas have potential to influence resident’s mobility behaviour in a positive way. It is important that the municipal administration ensures adequate transport infrastructure in the surroundings of new housing developments in the first place, so that mobility measures within new residential areas can develop their full potential. Housing companies should see the link between mobility and housing and be open regarding mobility measures, since they can also benefit from them. [5] A recommendation in form of a prioritization of mobility measures (see figure 2) was derived in a final step [5]: •• Basic Measures (foundation) •• Advanced Measures (additional measures, depending on respective framework conditions) •• Top Measures (special measures with a high degree of complexity in planning and implementation) ■ Straight and Direct Routing Sufficiently Dimensioned Width of Paths Good Lighting of the Paths Accessibility (Barrier-free) Weather Protection Good Connection to the Urban Pedestrian Network Green Spaces Sufficient Number of Outside-Seating Elements Space for Activities PEDESTRIAN TRAFFIC BICYCLE TRAFFIC Straight and Direct Routing (to the Parking Facilities) Orientation Plan and Wayfinding in the residential area Good Connection To Local Suppliers and Facilities (e.g. Gastronomy) Sufficiently Dimensioned Width of Cycling Paths Good Lighting of the Cycling Paths Good Connection to the Urban Cycling Network Safe Paths Orientation Plan and Wayfinding in the residential area Good connection to Local Suppliers and Facilities (e.g. Gastronomy) Sufficient Number of Bicycle Parking Facilities Sufficient Dimensioned Bicycle Parking Facilities Ground Level Access to the Bicycle Parking Facilities High Quality of the Bicycle Parking Facilities Bicycle Parking Facilities for Visitors Service and Repair Station Power Outlets for E- Bikes Bike-Sharing Service Discounts for a Bike Repair Good Wayfinding to the Station Short Walking Distance to the Station Departure Monitors in the Entrance of Buildings Free/ Incentive Tickets for residents Notice Boards with Information on Public Transport Information Material for new residents (in packages) Good Equipment of Station Additional Equipment for Stations Reduction in the Number of Compulsory Car Parking Spaces Infrastructure for E-Cars Car-/ E-Moped- Sharing Shared Garages within other Neighbourhoods Parcel Station within the residential area Discounts at Local Suppliers and Facilities (e.g. Gastronomy) Mobility Counselling and Special Courses Shopping-Trolleys (to hire) Mobility Point Concierge PUBLIC TRANSPORT MOTORIZED TRAFFIC ADVANCED BASIC TOP FURTHER MEASURES Safe Cycling Paths TOP ADVANCED BASIC Source: Krombach, 2020, translated; inspired by Köfler et al., 2019 Figure 2: Prioritization of mobility measures for new housing developments Source: [5], translated, inspired by: [7] European Friedrich-List-Prize SCIENCE & RESEARCH International Transportation (71) 1 | 2019 41 Resilience of transit systems Application of behavioral theories to increase the resilience of transit systems based on user-operator interaction Public transport, Collaborative travel, Service Disruptions, SP Survey, Mobility-as-a- Service (MaaS) In an era of digitization and automation, urban mobility faces major future challenges. This doctoral research takes a holistic approach to translate behavioral theories from organizational and consumer research in the transit context, allowing a more profound understanding of transit users’ affective and cognitive decision-making processes for enhanced service quality and system resilience. The framework follows an unconventional path of exploring the potential of ‘user-operator involvement’ on transit information sharing, service disruption management, and integrated mobility solutions, from a socio-technical perspective. Rumana Sarker T ransit system mainly embodies a top-down approach, and supply-based service evaluation is a common practice. However, this often results in an overestimation of the service quality by the operator and may not represent actual use experience [1]. While service quality determines the propensity of transit use, improving it according to the user’s needs can be a crucial element to gain a positive attitude towards transit and attain a modal shift. Therefore, this doctoral research addresses the missing link between transit policies and user perceptions of the overall system by exploring the effect of useroperator involvement on three proposed key elements: 1. collaborative transit information exchange, 2. disruption management strategy, and 3. service-based mobility solutions. Transit information is one of the important service characteristics that users continuously seek to reduce travel-related stress through better scheduling, regardless of overall high or low service quality [2]. In the literature, travel information is mainly treated as a travel resource streaming from operators to transit users as consumers. However, collective knowledge can significantly contribute to dynamic planning processes that REFERENCES [1] Franz, G. (2019): Leitfaden Mobilitätsmaßnahmen im Wohnbau: Übersicht und Planungsempfehlungen für Wohnbauvorhaben in Wien. Published by: Stadt Wien - Stadtteilplanung und Flächenwidmung (MA 21), Werkstattbericht 184, Wien. ISBN: 978-3-903003- 55-2. [2] Reithofer, J.; Arbeithuber, S. (2020): Maßnahmenkatalog - Realisierung von multimodalen Mobilitätsangeboten (Mobility Points) in Wohnbauten und Stadtteilen. Magistrat der Stadtgemeinde Salzburg, Amt für Stadtplanung und Verkehr, Schriftenreihe zur Salzburger Stadtplanung, Heft 46, Salzburg. [3] Koszowski, C.; Hubrich, S.; Wittwer, R.; Gerike, R. (2019): Was motiviert zum Zufußgehen? Literaturschau und ausgewählte Ergebnisse einer empirischen Studie. In: Bauer, U. (Hrsg.): So geht´s - Fußverkehr in Städten neu denken und umsetzen. Bd. 18, Edition Difu - Stadt Forschung Praxis, Berlin. ISBN: 978-3-88118-643-8. ISSN: 1863-7949. [4] Ewing, R.; Handy, S. (2009): Measuring the Unmeasurable: Urban Design Qualities Related to Walkability. In: Journal of Urban design 14 (1), pp. 65-84. [5] Krombach, J. (2020): Integration und Einfluss von Mobilitätsmaßnahmen im Wohnbau zur Förderung umweltverträglicher Mobilität (Diploma Thesis). Technische Universität Dresden, Fakultät Verkehrswissenschaften „Friedrich List“, Institut für Verkehrsplanung und Straßenverkehr, Professur für Integrierte Verkehrsplanung und Straßenverkehrstechnik (IVST), Rosinak & Partner ZT GmbH. Wien/ Dresden. [6] De Tommasi, R.; Oetterli, D.; Schneider, S.; Hirzel, D. (2014): Mobilitätskonzepte für effiziente Areale. MIPA - Mobilitätsmanagement in Planungsprozessen von neuen Arealen. Handbuch. EnergySchweiz für Gemeinden, Zürich. [7] Köfler, H.; Lotze, B.; Gröger, L.; Henkel, S.; Seitz, P.; Waßmer, R.; Zuhse, H.; Weber, M.; Gailhofer, P. (2019): Intelligent mobil im Wohnquartier: Handlungsempfehlungen für die Wohnungswirtschaft und kommunale Verwaltungen. Verkehrsclub Deutschland e.V., Berlin. Jonas Krombach, Dipl.-Ing. Project Engineer, Rosinak & Partner ZT GmbH, Vienna (AT) krombach@rosinak.at Regine Gerike, Univ.-Prof. Dr.-Ing. Head of Chair, Technische Universität Dresden, Chair of Integrated Transport Planning and Traffic Engineering, Dresden (DE), regine.gerike@tu-dresden.de Caroline Koszowski, M.Sc. Research Associate, Technische Universität Dresden, Chair of Integrated Transport Planning and Traffic Engineering, Dresden (DE) caroline.koszowski@tu-dresden.de Andrea Weninger, Dipl.-Ing. Managing director, Rosinak & Partner ZT GmbH, Dornbirn (AT) weninger@rosinak.at SCIENCE & RESEARCH European Friedrich-List-Prize International Transportation (71) 1 | 2019 42 allow users to maximize their utility from real-time information and feedback and detect the system gaps [3]. In the era of lean production and public funding reductions, transit users are valuable partners in system design, fostering bottom-up development, and offering ideas for entrepreneurship and innovation [4]. Although active user participation is starting to shape the development of new apps with commercial market potential, there is little information regarding their acceptance and use. On the other hand, transit systems are complex open systems susceptible to service disruptions such as delays, crowding, line cancellations, resulting in travel dissatisfaction and temporary ridership loss [5, 6]. Therefore, understanding user’s reactions to critical incidents and defining measures to mitigate such reactions are vital to improving transit system resilience in the case of smallscale, recurring operational disruptions [7]. Previously the link between user satisfaction and general service indicators such as service reliability, customer care, information simplicity, and system design has been extensively investigated [8, 9]. However, a significant research gap exists concerning the factors underlying transit users’ behavioral response to service disruptions and motivational factors to improve it. Furthermore, the emergence of radical technological innovations facilitates the introduction of Mobility-as-a-Service (MaaS) to overcome the limitation of fixed scheduling and routing of transit systems. MaaS is an evolving concept of ‘user instead of owner’, combining different transport modes (e.g., transit, car-sharing, bike-sharing, taxi) over one integrated app-based service. It can be on a subscription or pay-asyou-go basis for seamless travel and payment [10]. The widespread use of smartphones and travel apps serve as essential facilitators for MaaS adoption. However, the current body of knowledge does not apply behavioral theories to understand internal psychological motivators other than the utility-based choice to explain mainstream MaaS adoption. Based on the research gaps mentioned above, the research questions (RQ) are as follows: RQ1 What are the motivating factors for users’ to voluntarily share transit information? RQ2 Is there any relationship between users’ emotional or affective reactions to service disruptions and their future transit use? RQ3 What is the potential of MaaS compared to conventional transit systems from the users’ perspective? The focus group of this research mainly comprised transit users with sufficient multimodal travel activities. Three different case studies were designed and tested in Innsbruck, the capital of the Austrian province of Tyrol, and partly in Copenhagen, the capital of Denmark, facilitating comparative case studies in cities differing in size and social trust. This article briefly summarizes the most relevant research results on nurturing user-operator communication to improve transit information, monitor user satisfaction relating to service disruptions, and integrate service-based mobility solutions for a better transit experience. Figure 1 shows the research framework.- Applied Method The data were collected using the tailor-made questionnaire in English, German and Danish, combining online and onboard surveys with incentives. The onboard intercept survey was administered with the Computer Assisted Personal Interviewing method. Pilot surveys were carried out before the final administration. The indicators related to the latent constructs in the surveys were elicited using a 5-point Likert scale. The structural equation model (SEM) served to estimate the behavioral framework. The goodness-of-fit was evaluated using the chi-square test of model fit (CFI) and Root Mean Square Error of Approximation (RMSEA). A stated preference (SP) choice experiment was conducted to understand the effect of switching cost and alternative attributes among the hypothesized MaaS service and current transit alternative. The choice experiment was designed using the D-efficient design method [11]. The multinomial logit model (MNL) served to understand the utility function of the MaaS packages using the maximum loglikelihood technique. Results Nurturing user-operator communication to improve transit information 1,369 responses from Innsbruck and Copenhagen were analyzed with SEM based on the Unified Theory of Figure 1: Research Framework Own work European Friedrich-List-Prize SCIENCE & RESEARCH International Transportation (71) 1 | 2019 43 Acceptance and Use of Technology (UTAUT) [12]. The results explore the motivational factors underlying intentions to share information rather than solely engaging in receiving information while using transit apps for daily commute. The platform-related and individualrelated barriers and motivators to share information are investigated. This study shows that there is a need to receive peer information and willingness to share information from frequent transit users even in a high-quality transit environment. The most important motivational factors for information sharing are pro-sharing social norms and self-actualization weighted against effort expectancy. The effort is related to the logistic effort of using the platform than network familiarity. Trust in the information provided and social network engagement are secondary motivational factors, with perceived information quality and communication need less influential. Greater transit use and interest in the level of service (LOS) and real-time (RT) information are correlated with greater information sharing motivation. Results identify women and young travelers, mainly Gen Z (birthdate between midto-late 1990s and early 2010s), as potential users of collaborative transit apps. Also, transit users residing in Denmark, a country with high social trust, are more inclined to share information. The survey targeted “digital natives” due to their social media use for information, socializing, experiencing a sense of community, and familiarity with collaborative transport consumption. Monitoring user satisfaction relating reaction to service disruptions This research explains the choice between staying and enduring, complaining, and reducing transit use by showing that transit users’ reactions are related to the service climate, frequency of undesired incidents, and individual characteristics. This research adopted the Affective Events Theory (AET) for the first time in the transit service context [13]. Previously, AET was mostly used to explain work-related experiences. AET explains customer reactions to transit service disruptions based on a representative sample of 1,629 transit users from Innsbruck. This research evaluates users’ affective reactions to disruptive events ranging from calm to extremely angry, and behavioral responses varying from complaints (voiced) to avoiding transit use on the next trip (exit), and continuing as usual (loyalty) following Hirschman’s Exit-Voice-Loyalty framework [14]. This study addresses line cancellations, missed connections, non-functioning ticket machines, and vehicle breakdown as stimulus events [15]. Results depict that even a low proportion of unexpected service disruptions may induce anger and frustration under high-quality service conditions and result in temporary or permanent discontinued use. SEM estimation shows that better network coverage, service quality, and personnel behavior mitigate the frustration of transit users upon event occurrence. Higher transit user frustration is related to a higher frequency of service disruptions. Customer frustration decreases with higher service quality and operator efficacy. Social network engagement is associated with an increased sense of being upset or angry and disruption, and voicing complaints and exit behavior are complementary. Counterintuitively, using transit for environmental reasons is an enhancing factor of frustration over service disruptions. Notably, the current study does not refer to real-time reactions to single specific events. However, it takes a retrospective view of the transit organizational climate, including service quality, network coverage and personnel behavior. Integrating multimodality for improved service MaaS raises hopes for better tailoring the transport service matching user needs. This study focuses on habitual transit users’ willingness to switch from their current yearly subscription towards a new MaaS service. It relates switching intention to new service based on the service-based switching model, explaining switching cost and service-based push-pull factors, i.e., both the perceived quality of the current service and the perceived usefulness of the future service [16]. The goalframing model is combined, explaining individuals’ actions with three motivational perspectives: normative, gain, and hedonic [17]. A stated-preference choice experiment among the transit users in the Tyrol region collecting 1,416 responses shows that attractive MaaS features are package price, e-car discount, number of transit trips, and free e-car, e-bike minutes. The inclusion of transit trips significantly increases the utility of using a MaaS scheme. However, the results show a lower intention of MaaS use compared to the current alternative. Transit satisfaction, environmental responsibility, and perceived difficulties of MaaS use, e.g. fleet availability, privacy interventions, motivate staying with transit use. Also, minimal experience with existing shared transport services is identified as a barrier in MaaS acceptance. Whereas, taste for innovation, time-saving skills, transit underutilization, and pro-cycling attitudes motivate switching to MaaS. Simplified travel with a one-stop payment option is the most perceived advantage of MaaS. The younger population and active travelers (working, studying) are likely to switch to the MaaS system. Conclusion The findings from three different case studies in this research obtained specific measures and policy implications. However, in combination, they can work efficiently in achieving a transit environment that retains ridership, reduce car dependency, manages growing mobility needs, and encourage sustainable travel. The most relevant key findings are as follows: •• User engagement in transit information sharing should not be monetary but rather satisfy the higherorder needs of social recognition, user appreciation, and self-actualization. For policymakers, these are potential measures to motivate app engagement. Hence, adding app features that enable users to see their contribution in bettering travel information, including gamification elements, may strengthen information sharing. •• Minor discrepancies in the conditions of excellent transit services can still induce anger and disappointment. The transit operator’s efficacy in handling SCIENCE & RESEARCH European Friedrich-List-Prize International Transportation (71) 1 | 2019 44 users’ situational needs is decisive for continuing transit use in the long run. Thus the ability to complain through ‘easy to use’ official channels and responsiveness to complaints should be better promoted among transit operators. These measures can ameliorate the shortcomings of the traditional customer satisfaction survey by facilitating user-generated inquiries and recognizing service dimensions based on users’ preferences and need. •• Switching from transit to MaaS is non-trivial in a medium-sized city like Innsbruck with high-quality transit service. Transit will be an essential part of MaaS, but there is a greater sensitivity to ‘free’ service units among the respondents. Hence, the MaaS pricing scheme presentation could be a success factor, and non-linear pricing effects should be further explored. Switching to MaaS is driven mainly by a taste for innovation. Therefore, the marketing strategy for MaaS should be based on innovation and emotional gains rather than on environmentalism and functional gains. Also, visibility of the existing shared services to the end-users is crucial for wider MaaS intervention. The 2050 Tyrol Energy Autonomy Program aims to generate positive attitudes towards electroand sustainable mobility [18]. This research aimed to contribute to the goal of the Tyrol region with the gained knowledge from these case studies. The opportunity to transfer the knowledge into practice is one of the main contributions of this research, as transit operators were important collaborators. It has the additional merit of examining research hypotheses in a cross-cultural setting. Moreover, the conceptualization of theories from consumer research and developing new applications is a research contribution itself. As a continuation of the research, a complex hybrid choice model estimation for an in-depth understanding of switching intention to MaaS is already in progress.- ■ Special thanks to Prof. Sigal Kaplan and Prof. Markus Mailer for providing guidance and feedback throughout the research as the supervisors. REFERENCES [1] Rietveld, P. (2005): Six reasons why supply-oriented indicators systematically overestimate service quality in public transport. In: Transport Reviews, 25 (3), pp. 319-328. [2] Bachok, S. (2007): What do passengers need out of public transport information systems? In: 29th Conference of Australian Institute of Transport Research, Adelaide, Australia. [3] Chaves, A. P.; Steinmacher, I.; Vieira, V. (2011): Social networks and collective intelligence applied to transitation systems: A survey. VIII SBSC, pp. 16-23. [4] Filippi, F.; Fusco, G.; Nanni, U. (2013): User empowerment and advanced transit solutions. In: Procedia - Social and Behavioral Sciences, 87, pp. 3-17. [5] Chakrabarti, S. (2015): The demand for reliable transit service: New evidence using stop level data from the Los Angeles Metro bus system. In: Journal of Transport Geography, 48, pp. 154-164. [6] Chakrabarti, S.; Giuliano, G. (2015): Does service reliability determine transit patronage? Insights from the Los Angeles Metro bus system. In: Transport policy, 42, pp. 12-20. [7] Christoforou, Z.; Corbille, E.; Farhi, N.; Leurent, F. (2016): Managing Planned Disruptions of Mass Transit Systems. In: Transportation Research Record, 2541 (1), pp. 46-55. [8] Friman, M.; Gärling, T. (2001): Frequency of negative critical incidents and satisfaction with public transport services. In: II. Journal of Retailing and Consumer Services, 8, pp.-105-114. [9] De Oña, J.; De Oña, R. (2015): Quality of service in public transport based on customer satisfaction surveys: A review and assessment of methodological approaches. In: Transportation Science, 49 (3), pp. 605-622. [10] Hietanen, S. (2014): Mobility as a Service. In: The new transport model, pp. 2-4. [11] Bliemer, M. C.; Rose, J. M. (2011): Experimental design influences on stated choice outputs: an empirical study in air travel choice. In: Transportation Research Part A: Policy and Practice, 45 (1), pp. 63-79. [12] Venkatesh, V.; J. Y. L. Thong, X. (2016): Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead. In: Journal of the Association for Information systems 17 (5), pp. 328-376. [13] Weiss, H. M.; Cropanzano, R. (1996): Affective Events Theory: a theoretical discussion of the structure, causes and consequences of affective experiences at work. In: Research in Organizational Behavior, 18, pp. 1-74. [14] Hirschman, A. O. (1970): Exit, Voice and Loyalty: Responses to Decline in Firms, Organizations, and States, Harvard University Press. [15] Carrel, A.; Halvorsen, A.; Walker, J. L. (2013): Passengers’ perception of and behavioral adaptation to unreliability in public transportation. In: Transportation Research Record, 2351 (1), pp. 153-162. [16] D’Alessandro, S.; Gray, D.; Carter, L. (2012): Push-pull factors in switching mobile service providers. In: Proceedings of the Australian and New Zealand marketing academy conference, pp. 1-8. [17] Lindenberg, S.; Steg, L. (2007): Normative, gain and hedonic goal frames guiding environmental behavior. In: Journal of Social Issues, 63, pp. 117-137. [18] Land Tirol (Amt der Tiroler Landesregierung) (2017): Aktionsprogramm E-Mobilität 2017-2019. www.tirol2050.at/ uploads/ tx_bh/ aktionsprogramm_e_mob.pdf (access 28 March 2019). Rumana Sarker, Dr. techn. Postdoctoral Researcher, Unit for Intelligent Transport Systems, Institute of Infrastructure University of Innsbruck (AT) rumana.sarker@uibk.ac.at 19 th European Transport Congress (ETC) 7-8 October 2021, Maribor (SL) T he European Platform of Transport Sciences - EPTS Foundation e.V. - invites to the 19th European Transport Congress (ETC), which will be held in Maribor, Slowenia, from 7-8 October 2021. The topic of the congress: “European Green Deal - Challenges and Solutions for Mobility and Logistics in Cities” Presentations will be held in English. Contacts, conference program, and more information are available at www.fgpa.um.si/ etc We are looking forward to meeting you in Maribor