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MAVEN Deliverable 7.2: Impact Assessment - Technical Report

Pribyl, Ondrej and Matowicki, Michal and Blokpoel, Robbin and Schindler, Julian and Leich, Andreas and Lücken, Leonhard and Trumpold, Jan and Hoadley, Suzanne and Rondinone, Michele and Vreeswijk, Jaap and Prikryl, Jan and Wesemeyer, Daniel (2019) MAVEN Deliverable 7.2: Impact Assessment - Technical Report. Project Report.

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This deliverable focuses on an important topic within the MAVEN project - evaluation of the project impact. This is an important step that will allow us to say what the results and impact of the different technologies, functionalities as well as assumptions are. It covers different dimensions of the impact assessment as stated in the Deliverable D7.1 - Impact assessment plan [10]. The field tests proved that the technology in the vehicle works together with the infrastructure and the solution is technically feasible. This was demonstrated also during particular events and is reported in the attached test protocols. At the same time, the emulation and simulation in Dominion software proved the functionality, for example with respect to the cooperative perception or safety indicators. The tests also proved that the key performance indicator "minimum time to the collision" decreases when applying the cooperative sensing. Also, the number of human interventions needed was zero in all the tests. This deliverable also discussed selected results of a detailed user survey aiming at understanding the expected impacts and transition of automated vehicles. The overall number of respondents reached 209. The responses have revealed some interesting facts. For example, over 80% of the respondents believe that CAVs will decrease the number of traffic accidents. Similarly, about 70% of the respondents expect improvements in traffic congestions. Over 82% of respondents declared that they would accept some detour when driving if it helps the overall traffic situation. The literature review, however, indicated that autonomous vehicles will have either a positive or a negative effect on the environment, depending on the policies. For example, opening cars as a mode of transport to new user groups (seniors, children etc.) together with improvements of the traffic, flow parameters can increase the traffic volume on roads. Policy makers shall focus on the integration of the CAVs into a broader policy concept including car or ride-sharing, electromobility and others. In order to evaluate the transition, for example, the influence of different penetration rates of CAVs on the performance, a microscopic traffic simulation was performed. Here the particular MAVEN use cases, as well as their combination, was addressed. The results of the simulation are rather promising. The potential for improvements in traffic performance is clearly there. It was demonstrated that a proper integration of CAVs into city traffic management can, for example, help with respect to the environmental goals (Climate Action of the European Commission) and reduce CO2 emissions by up to 12 % (a combination of GLOSA and signal optimization). On corridors with a green wave, a capacity increase of up to 34% was achieved. The conclusions from this project can be used not only by other researchers but mainly by traffic managers and decision-makers in cities. The findings can get a better idea about the real impacts of particular use cases (such as green wave, GLOSA and others) in the cities. An important added value is also the focus on the transition phase. It was demonstrated that already for lower penetration rates (even 20% penetration of automated vehicles), there are significant improvements in traffic performance. For example, the platooning leads to a decrease of CO2 emissions of 2,6% or the impact indicator by 17,7%.

Item URL in elib:https://elib.dlr.de/133902/
Document Type:Monograph (Project Report)
Title:MAVEN Deliverable 7.2: Impact Assessment - Technical Report
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Matowicki, MichalCzech Technical UniversityUNSPECIFIEDUNSPECIFIED
Schindler, JulianUNSPECIFIEDhttps://orcid.org/0000-0001-5398-8217UNSPECIFIED
Leich, AndreasUNSPECIFIEDhttps://orcid.org/0000-0001-5242-2051UNSPECIFIED
Lücken, LeonhardUNSPECIFIEDhttps://orcid.org/0000-0001-6103-6531UNSPECIFIED
Trumpold, JanUNSPECIFIEDhttps://orcid.org/0000-0001-6032-0709UNSPECIFIED
Prikryl, JanCzech Technical UniversityUNSPECIFIEDUNSPECIFIED
Wesemeyer, DanielUNSPECIFIEDhttps://orcid.org/0000-0002-7411-5551UNSPECIFIED
Date:18 July 2019
Refereed publication:Yes
Open Access:Yes
Keywords:Cooperative automated driving; impact assessment; GLOSA; platooning; co2 reduction; safety
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - NGC KoFiF (old)
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems > Development of vehicle functions
Institute of Transportation Systems > Development of system functions
Institute of Transportation Systems > Data Management and Knowledge Discovery
Deposited By: Schindler, Julian
Deposited On:29 Jan 2020 11:43
Last Modified:20 Jun 2021 15:53

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