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Auswirkungen des teil- und hochautomatisierten Fahrens auf die Kapazität der Fernstraßeninfrastruktur
Abstract and Figures
Teil- und Hochautomatisiertes Fahren wird unseren Straßenverkehr in der Zukunft beeinflussen.
Das Ziel dieses Forschungsprojektes ist es, zu ermitteln, welche positiven oder negativen Folgen
die aufkommende Technik des automatisierten Fahrens auf die Kapazität des deutschen Fernstraßennetzes
hat und wie sich diese Effekte über die Zeit entwickeln werden. Der vorliegende
Bericht gibt Vorgehen, Annahmen und Ergebnisse des Forschungsprojektes wieder.
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... This revolution in road traffic is associated with major influences on mobility behaviour and further traffic related improvements like enhanced traffic safety, increased capacity and reduced emissions (Milakis et al., 2017). However, it is expected, that there will be a longlasting transition period, in which automated as well as conventional vehicles will drive in mixed traffic and it is not clear, whether automated driving will lead to a decrease or an increase in traffic capacity and how the occurrence of congestion will be affected within this time period (Haberl et al., 2017;Krause et al., 2017). Therefore, we have developed a microscopic traffic flow simulation platform suited for road operators and engineers in the automobile industry without extensive knowledge in traffic flow simulation (TFS) to simulate different mixed traffic scenarios. ...
Microscopic traffic flow simulation is used in various domains nowadays. Traffic engineers analyse the impact on traffic flow using simulation tools and in automobile industry simulation is used for developing and analysing automated driving functions and their functionalities. We developed a simulation platform with pre-defined applications, allowing operators to test the impact of automated driving on traffic flow by varying mixed traffic scenarios. As calibration of the base case for different domains is a time-consuming process, we present in this paper a 3-step calibration process, which allows efficient model calibration by focusing on macroscopic traffic flow dynamics as well as microscopic driving behaviour.
... On the other hand, more complex approaches showed that vehicles equipped with adaptive cruise control (ACC) or cooperative ACC follow gaps that are largely comparable to human-driven time headways (for comfort and safety reasons) (Makridis et al., 2018). This can even lead to a decrease in capacity for certain penetration rates of Avs in the fleet mix (Calvert et al., 2017 ;Krause et al., 2017). Finally, detailed simulation-based analyses showed that operational aspects of traffic flow such as organization including lane changing, work-zone approach, or speed harmonization must be considered to provide a good and reliable estimation of travel time impacts of automation. ...
Automated driving is widely assumed to play a major role in future mobility. In this paper, we focus on “high driving automation” (SAE level 4) and analyze potentials in terms of more efficient traffic flows, travel times, and user benefits as well as potential impacts on urban neighborhoods and potentials for sustainable urban development. Along selected use cases of automated vehicles in the region of Karlsruhe, Germany, we show that at least moderate user benefits can be expected from travel time savings, with the extent depending on the defined operational design domain of the vehicles and the routes taken. With regard to residential development of urban neighborhoods, there are opportunities for repurposing public space. However, these are limited and require parallel regulatory measures to become effective.
... Input assumptions on the impact of AVs on road capacity. Whereas, on the one hand, studies (e.g., [12,40,41]) assume that AVs can drive closer together and, therefore, the road capacity increases, on the other hand, some studies (e.g., [41]) conclude that there will be a reduction of travel speeds and an increase of travel time during off-peak because AVs must strictly adhere to traffic rules with regard to visibility, stopping distance, permissible maximum speed, etc. ...
Developments in the field of automated mobility will greatly change our mobility and the possibilities to get from one place to another. This paper presents different scenarios for personal mobility in Austria, anticipating the possibilities and developments in the field of automated vehicles (AVs). The scenarios were developed using a systematically formalized scenario technique and expand the social and political discourse on automated mobility, which is currently characterized by a lack of experience and visibility as an established transport service. Using system dynamics modeling techniques, i.e., the Metropolitan Activity Relocation Simulator (MARS), impacts of the scenarios on the Austrian transportation system are estimated. The simulations show that, without suitable transport policy measures, automated mobility will lead to a significant increase in the volume of individual traffic and to modal shift effects with lower traffic volumes for public transport, walking and cycling. In addition, without a link between AVs and post-fossil propulsion systems, increases in pollutant emissions can also be expected. In contrast, the simulation results of an increased use of AVs in public transport show positive effects for the support of a more sustainable mobility. Hence, transport policy measures accompanying the introduction and development of automated vehicles will be needed in the future to reach a sustainable development.
... Instead, market share data from literature, e.g. (Fagnant and Kockelman, 2015;McKinsey & Company, 2016;Busch et al., 2017;Krail et al., 2019), are used as scenario variables which are then fed into a stock-flow-model to calculate the respective fleet shares. For the tests presented here, market take up follows the "high disruption scenario" of a McKinsey study (McKinsey & Company, 2016). ...
Rationale: Increasing digitalization and automation is expected to significantly change the transport system, mobility and settlement structures. A decade ago automated, self-driving vehicles were nothing more than an unrealistic (boyhood) dream. But today the concept of highly and fully automated vehicles is rapidly becoming a reality, with a series of real-world trial applications underway. Government plans and industry predictions expect automation to be introduced from the early 2020s onwards. Nevertheless, there is still a high level of uncertainty in which form and to what extent automated vehicles will enter the market. Furthermore, there are ongoing discussions concerning net effects of positive and negative aspects of automation. Background: The authors have been involved in several research projects analyzing potential impacts of automated driving. The EU funded project CityMobil (Towards Advanced Road Transport for the Urban Environment) was one of first to address automated driving on a large scale. As part of this project the System Dynamics based model MARS (Metropolitan Activity Relocation Simulator) was adapted to assess scenarios of automated driving in four European cities. Simulations demonstrated that automated vehicles integrated into public transport have a potential to reduce car kilometers travelled and improve carbon footprint. On the contrary, privately owned automated vehicles lead to an increase in car kilometers travelled and carbon footprint, unless propulsion technology is changed. While the focus of CityMobil was on the urban scale, the nationally funded Austrian project Shared Autonomy (Potential Effects of the Take-up of Automated Vehicles in Rural Areas – own translation) focused on rural areas. The findings of Shared Autonomy show potential contributions of automated cars to improve the environmental situation and social inclusion in rural areas. Finally, the nationally funded Austrian project SAFiP (System Scenarios Automated Driving in Personal Mobility) takes a look at the national territory of Austria. Method: The relationship between vehicle automation, travel demand and environmental effects consists of a multitude of complex cause-effect-chains. The toolbox of System Dynamics offers appropriate methods to tackle such complexities. Causal Loop Diagrams are used to analyze and discuss relevant cause-effect-chains and are used to adapt an existing Stock-Flow-Model of the Austrian land use and transport demand system. The modified Stock-Flow-Model is used for a quantitative impact assessment. Sensitivity analysis in form of Monte-Carlo-Simulations is employed to tackle the high level of uncertainty concerning key factors. Findings, results: The key factors, influencing mode choice and travel demand, are generalized costs of travel time, weighted costs of use and availability. The automation of driving, expressed as the share of highly and fully automated vehicles in the fleet, is influencing all three key factors via different cause-effect-chains and feedback loops. In SAFiP we identified four key impact sources: automated and remote parking, road capacity and travel speed, value of in-vehicle time and widening the range of users. Sensitivity tests for each of the impact sources have been carried out. Widening the range of users has the highest impact on a national level, potentially increasing car kilometers by about 17 percent in 2050. Remote parking increases car kilometers by about 5 percent in total, ranging from about 1 percent in peripheral districts to about 17 percent in Vienna.
... With a total of 988 data records, we fit a normal distribution with a mean of 36.50 km/h and an approximate range of 6.20 km/h to 67.28 km/h (95 % confidence level) for NVs. A deterministic value equals the mean of NV speed is used as the RMV initial speed for AVs, because it is expected that the variation in vehicle speed will be substantially reduced by AVs' capabilities of precise speed control (Krause et al., 2017). ...
Freeway on-ramp merging areas are high-risk areas for motor vehicle crashes and conflicts due to the variety of driving styles, the difference in mainline and ramp traffic states, and factors related to roadway design and traffic control. The emerging Autonomous Vehicle (AV) technologies are expected to bring substantial improvements in ramp merging operations in general, including the possibility to reduce traffic conflicts and crashes by partially or fully eliminating the critical factors related to the human drivers. In order to investigate the potential safety impacts of AVs at on-ramp merging, this study first proposes a novel conflict index in theory as a specific indicator for ramp merging safety. Then, a merging conflict model is introduced to estimate the index value in various cases by considering the interactions between the mainline and ramp vehicles. In order to account for real-world uncertainties and variations in various crash-contributing factors, the proposed approach incorporates Monte-Carlo method and probabilistic distributions calibrated on the empirical freeway data. The developed approach is later applied in a case study with incremental AV market penetration rates to investigate AV safety impacts at on-ramp merging. The results show clear benefits of AVs in reducing the frequency and severity of the critical merging events. In addition, a sensitivity analysis on essential model parameters shows that the merging safety of AVs is closely related to their gap acceptance policy and the proper functioning of the driving systems, providing further insights into the future development of AVs.
Traffic congestion might be partly solved by using autonomously driving vehicles which are expected to enter the market at a significant rate within the next years (Kaltenhäuser et al. in Transp Res Part A: Policy Pract 132:882–910, 2020, [1]; Bansal and Kockelman KM in Transp Res Part A: Policy Pract 95:49–63, 2017, [2]; Nieuwenhuijsen et al. in Transp Res Part C: Emerg Techno 86:300–327, 2018, [3]). Several studies have been undertaken to examine the impact of autonomous vehicles (AVs) on road traffic. Also, autonomous vehicles and connected autonomous vehicles (CAVs) have been simulated in the literature with different operational parameters, leading to different results. Hence, in our study we examine how different parameters for the operation of AVs and CAVs influence urban traffic in the case of Munich, Germany. Furthermore, the impact of different percentages of AVs and CAVs on urban traffic is studied. For this, the traffic will be studied for the whole city, as well as for certain travel routes, e.g. in the main travel direction (into the city in the morning), in opposite direction or along the highway surrounding Munich. Last but not least, future scenarios with an enhanced travel behaviour will be studied. The results show that the headway and reaction times of the vehicles have the largest impact on urban traffic. Here, vehicles with large reaction times have a negative impact on urban traffic while short reaction times have a positive one. The results can be used to configure future AVs such that they reduce congestions and optimize urban traffic flow.
Das Verkehrsmanagement erweitert die langfristige Verkehrsentwicklungsplanung um mittel- und kurzfristig wirkende Maßnahmen. Entsprechend ist eine gemeinsame Betrachtung von Verkehrsplanung und Verkehrsmanagement sinnvoll. Ein zentraler Schritt ist die Entwicklung von Verkehrsmanagementstrategien, in denen einzelne Beeinflussungsmaßnahmen zu Bündeln zusammengefasst werden, um die Erreichung der allgemeinen verkehrspolitischen Ziele zu unterstützen oder um auf konkrete Probleme reagieren zu können. Die Verkehrsbeeinflussungsmaßnahmen können hinsichtlich der Art der Beeinflussung und der adressierten Verkehrsmittel kategorisiert werden. Entscheidend für eine erfolgreiche Planung und den reibungsfreien Betrieb eines umfassenden Verkehrsmanagements in einem Ballungsraum ist die Implementierung geeigneter Systemarchitekturen.
Für die kommenden Jahrzehnte gehen nahezu alle Verkehrsprognosen, die keine deutliche Kehrtwende in den Rahmenbedingungen zugrunde legen, von einem weiteren Wachstum der Gesamtverkehrsnachfrage im Personen- und Güterverkehr aus. Diese Entwicklung wird auch den Stadtverkehr prägen, der zusätzlich durch eine zunehmende Konzentration der insgesamt alternden Bevölkerung in prosperierenden Metropolregionen gekennzeichnet sein dürfte. Wichtige weitere äußere Einflüsse sind auch Digitalisierung und Automatisierung. Sie lassen eine weitere Ausweitung der Angebotsformen im Verkehr erwarten, die voraussichtlich ebenfalls zu Verkehrswachstum beitragen. Damit bleiben Platzbedarf, etwa für den ruhenden Verkehr, Energieversorgung und Emissionen des Stadtverkehrs drängende Herausforderungen. Mit zunehmender Multimodalität und einer Renaissance des Fahrrads gibt es aufseiten der Nachfrage zwar auch entlastende Entwicklungen. Dennoch dürfte vor dem Hintergrund des weiter wachsenden Verkehrs die langfristig größte Herausforderung für den Verkehrssektor die Einhaltung der Klimaziele sein. Verkehrspolitik und -planung werden sich in den nächsten Jahren verstärkt an diesen Zielen orientieren müssen und hierzu alternative Verkehrsträger fördern und möglicherweise darüber hinausgehende Maßnahmen, wie etwa differenzierte Bepreisung des Straßenverkehrs, ergreifen.
Wird die Entwicklung des automatisierten und vernetzten Fahrens auf der Straße zu steigenden Treibhausgasemissionen führen oder kann sie dazu beitragen, die das gesamte Verkehrssystem bis zum Jahr 2050 klimaschonender zu gestalten? Um diese Frage zu beantworten bedarf es einer Potenzialabschätzung, die sowohl die technische Entwicklung, die Akzeptanz als auch die verkehrlichen Wirkungen der Technikfolgen berücksichtigt.
Wird die Entwicklung des automatisierten und vernetzten Fahrens auf der Straße zu steigenden Treibhausgasemissionen führen oder kann sie dazu beitragen, das gesamte Verkehrssystem bis zum Jahr 2050 klimaschonender zu gestalten? Um diese Frage zu beantworten bedarf es einer Potenzialabschätzung, die sowohl die technische Entwicklung, die Akzeptanz als auch die verkehrlichen Wirkungen der Technikfolgen berücksichtigt.
An application-oriented evaluation of the implications of fully automated driving is of growing importance, particularly with regard to future user acceptance and usage. One of the most remarkable benefits of fully automated driving discussed is the potential of alternative travel-time use. Radical changes in time valuation and a rise in productivity are being discussed, which are highly relevant when evaluating transport-related measures, infrastructure investments and mode choice behavior. However, the lack of empirical examination and the inclusion of important aspects about the usage context, constraints and perceived benefits make predictions difficult. This paper aims to bridge the gap by examining user acceptance and perceived 42 advantages of automated vehicles on the basis of four specific use cases within the course of a quantitative online survey in Germany. The study includes detailed information on respondents’ current use of, and attitudes towards, today’s available transport modes, as well as their perception of the advantages of automated vehicles. Special focus is placed on current and future travel-time use. Significant differences found in the adaption of specific use cases emphasize the importance of a differentiation of fully automated driving. Perceived benefits with respect to time use were mainly window gazing and relaxing, whereas the possibility of working seemed to be less valued. A probit model analysis examined influencing factors on the propensity of regarding working while traveling as an advantage - a strong significance of the current time use on public transport and long-distance train trips, gender and rational attitude towards public transport was revealed.
The use of private cars in Germany has not yet been analyzed from a longitudinal perspective: most travel surveys consider only a single day. Daily car usage is not identical over a given period because car owners use their vehicles for daily routines (e.g., commuting) as well as for infrequent events, such as holiday trips. Another problem of short-period surveys is that they underestimate the share of cars used for long-distance travel. The current work may help to improve the reliability and realism of statements about the extent to which German cars could be replaced by electric vehicles. The authors developed a hybrid modeling approach that aims to obtain car mileage per day for a full year. This approach is based on empirical data with different granularities. Input data are derived from the annually conducted German Mobility Panel, including a survey of fuel consumption and odometer readings, and the long-distance travel survey INVERMO. The study showed that 13.1% of the modeled German private car fleet never exceeded 100 km/day during a full year. Furthermore, cars were driven more than 100 km on 13.3 days/year on average. Mainly used cars (first cars) of a household were used for longer distances rather than second cars. A comparison of average mobility figures from the model approach with the Mobility in Germany national travel survey showed the model results as reliable and realistic.
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