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This deliverable is a direct successor of Deliverable 7.1, which has introduced all vehicles, test tracks, used hardware, and proposed system architectures of the different used components. D7.1 has also introduced several system requirements for each component and for each use case described in D2.1, which must be implemented. D7.2 shows the system architecture implementation for the different components of the infrastructure part as well as for the vehicle part. It is shown how both parts communicate in the real-world following D5.2 by presenting the finally used ASN.1 message definitions (in the Annex) and details about the communication software. In the project, real-world implementations have been performed at four partners. UMH was responsible for setting up the communication software required in all implementations. DLR assembled all use cases in several scenarios on the test track located in Peine-Eddesse in northern Germany. Dynniq implemented a C-ITS based highway merging as specified in use case 2.1 on public roads on the highway A13 in The Netherlands. HMETC finally took a closer look at ToC/MRM distribution in urban areas as specified in the combined use case 4.1-5 on a test track located in Griesheim, Germany. Besides the implementation, feasibility assessments of all TransAID measures have been performed. For this, each use case has been divided into test scenarios, which have been implemented in the real-world prototypes, demonstrated and assessed. Each test scenario is linked to related requirements set up in D7.1. During the feasibility assessment, the compliance with all requirements has been checked by project partner HMETC, who is taking the role of an OEM here. In addition, the overall "look and feel" of the prototype and the performance in each test scenario has been rated and described. In summary, nearly all requirements were fully met. Only in few cases the implementation deviates from the earlier requirement specification, sometimes due to new findings in the project, sometimes as not all implementations could be showcased due to the COVID-19 pandemic. Altogether, it could be shown that the TransAID measures can be put into real-world to help future automated vehicles to better cope with possible threats and to gain higher performance on the road. Nevertheless, further research is required to bring the measures to a higher Technology Readiness Level, up to series production. This is especially true for HMI design for vehicles and VMS (as this was not in scope of the project), vehicle automation behaviour in case of ToCs and MRMs, and I2V-MCM deconflicting.

The TransAID project defines, develops and evaluates traffic management measures based on V2X equipped road infrastructure, primarily via simulations,to eliminate or mitigate the negative effects of Transition of Control (ToC) along Transition Areas in future mixed traffic scenarios where automated, cooperative, and conventional vehicles will coexist.This document aggregates, integrates, and analyses the results of the TransAID work packages. For each aspect of TransAID the major findings are presented and discussed.As a basis for the simulation studies several vehicle models were implemented successfully to create the right behaviour for lane changing(including cooperative versions), car following (including (C)ACC)and ToC/MRM algorithms. These models were created using a solid theoretical background, however, the availability of real-world data for input and calibration was very limited. From the baseline simulation runs we found that ToCs do not significantly disrupt traffic flow performance unless CAVs establish increased car-following headways during the ToC preparation phase. Disruptions escalate in case of CACC driving, increased share of CAVs in the fleet mix, and the occurrence of multiple ToCs within a narrow temporal window and spatial domain. Furthermore, in the case that a ToC is unsuccessful or not possible, unmanaged MRMs (taking place in lane and not being guided towards safe spots) can induce significant traffic disruption as well. On the other hand, simulation results indicated that cooperative lane changes minimize the frequency of ToC/MRM and their consequent adverse impacts on trafficflow operations. The benefits of cooperative lane changing are amplified with increasing share of CAVs and especially upstream of lanedrop locations.Building upon the vehicle models, simulations and the defined use cases, specific traffic measureswere developed to mitigate the effects of ToC events in transition areas. The traffic measures were implemented to study their effectiveness. Specifically, for each of the selected use cases the effects of the TransAID measures are evaluated regarding emissions, safety and efficiency. There is a trade-off between traffic safety versus traffic efficiency (as measured via throughput and travel times). It is often inherently difficult or even impossible to optimise both in the same context. Hence, typically a policy choice needs to be made, as to which of the two will have to be prioritised. Otherwise, results either improved or remained similar for all use cases and KPIs, with the exception of use case 3.1 (see Section 2.2.2 for details and Table 1at the end of Chapter 6). All use cases have in common that a reduction of MRMs is possible by providing infrastructure advice. Such advice, and the availability of safe spots, clearly reduces the number of stopped vehicles blocking the road.There is also a heavy dependence of the results on the mixture of vehicle types, in addition to the observation that less efficient traffic management performance is obtained for a higher LOS. The latter is in part logical, as for higher LOS there is more prominent congestion and the physical limits of the infrastructure remain a hard obstacle. By itself this is not a problem for TransAID, as the focus of the traffic management schemes is to prevent/postpone traffic breakdowns before they occur. While implementing and testing the traffic measures TransAIDalso identified or created the needed message sets and protocols to implement the measures using V2X communications. To that end, no new message sets wereneeded, but (minor) extensions to CAM, DENM, MCM and MAPEM were necessary. Especially MCM from the Manoeuvre Coordination Service (MCS) is key to multiple types of use case. Therefore, it is necessary to define a MCS that is valid for all types of scenarios. Aligned with the work of ETSI and by actively contributing, TransAID has proposed a MCS where the infrastructure takes an active role to facilitate the manoeuvres of vehicles and to increase the overall traffic flow and safety. The traffic management measures designed in TransAID also require that CAVs and road infrastructure units have an accurate perception of the environment. In addition to the MCS, TransAID has contributed to the evaluation and evolution of ETSI's Collective Perception Service (CPS) for cooperative perception. We have demonstrated that cooperative perception can improve CAVs perception capabilities when the trade-off between the perception capabilities and communications performance is balanced. Furthermore, the reliability of V2X communications has been addressed in TransAID using different and complementary techniques: compression, congestion control and acknowledgements.Besides the V2X communication, the communication to unequipped vehicles was of importanceand consisted of two parts. On the one hand, infrastructure needs to inform unequipped vehicles about issues on the road. On the other, automated vehicles themselves should provide information about their actual state to their surroundings, to avoid negative impacts.With regards to the infrastructure information, it needs to be mentioned that visual information on signs, variable or static, will never be as precise as V2X communication could be, esp. when looking to individual advices. Nevertheless, infrastructure can provide valuable information also to unequipped vehicles by signage, e.g., in terms of speed limits, distance (gap) advice or dynamic lane assignments.It will be required to create additional road signs dealing with automated vehicles, at least showing that, e.g.,an area is prohibited for automated vehicles or an area where only automated vehicles are allowed.Regarding signals from automated vehicles, TransAID's solution of having LED light strips at the back of AVswill be beneficial in any case, but the exact content of such lights needs to be defined by performing more detailed analyses of such components. This goes to all external and dynamic HMI components of automated vehicles. In this light, it will be crucial to have an intuitive way of understanding the automation related additional information. One key question in this area is if driving with enabled automation should be indicated by an additional external light, and if so, where should this light be and whatcolour?Combining the work on the traffic measures and communications, the iTETRIS framework was used to evaluate the selected use cases while deploying the traffic measures using V2X. The goal was to see if the V2X communications impacted the effectiveness of the measures in any way.After adding V2X, the simulation results forthe project's first and second iteration use cases showed very similar results to the previous evaluation. All traffic measures were found robust enough to show the same results as with idealV2X, even in light of increased traffic demand and thus more V2X enabled vehicles.There were some minor differences between the realistic V2X and ideal V2X implementations, but those could be traced back to easily fixed technical aspects (see Section 2.4 for details). As a final step in our use case assessment,the feasibility of measures and communications introduced were implemented in real-world demonstrators. The real-world implementation was done by performing three different feasibility assessments. Two of them have been performed on test tracks in Germany, and one on public roads in The Netherlands. On the test tracks, several detailed tests of all scenarios have been performed, revealing that all traffic management measures could be successfully integratedand applied to automated vehicles in all use cases and scenarios. This includes the successful setup of the RSI and the automated vehicles. It has to be mentioned, though, that the implementation was done in a prototypic way.The development of related series products would require much more testing under real world conditions, which will be challenging at the current time since no highly automated vehicles are present on the roads. Nevertheless, it is very important to start the investigations at present times. As already described in Section 3.3, standardisation of messages is happening already now, and it was very important to include the role of the infrastructure at this stage. The detailed results of the real-world implementations per use case can be found in Section 2.5.In addition to the design and technical implementation of traffic measures in simulation and the real-world, TransAID gained some insights on issues of a less technical nature. For example, it was determined a close collaboration between OEMs and (N)RAs would be beneficial in the identification and managing of TAs. To facilitate such a collaboration TransAID proposes a traffic management frameworkin the form of an intermediary service provider, acting as a trusted (and possibly mandated) third party. The framework allows TransAID to be scaled up and generalised. We approached this from both a technical and a business-oriented perspective. For TransAID to become part of a complete traffic management system, we focused on the technical side on how to detect transition areas, select (and possibly combine) services, and then detect when they are most appropriately timed for deployment. To this end, detection can be done via the infrastructure (e.g. road sensors or even digital communication infrastructure), via the OEMs, or by comparing an infrastructure's newly-defined ISAD level (Infrastructure Support levels for Automated Driving; see Section 1.4.2) to theoperational design domain (ODD, see Section 1.4.1) of the vehicle.Considering the mentioned technical challenges (detecting TAs, selecting services, and timing their deployment), the intermediary service bridges all these parties in such a way that the detection of TAs is performed in a centralised way, and OEMs and (national) road authorities ((N)RAs) have a single point of contact for providing and receiving information about TAs.Another point where OEMs and (national) authorities could collaborate,is the legislation related to automated driving since an important gap in current modelling and legalisation is how (C)AVs would/should react when (given) advice and/or actions conflict with traffic laws. With the real-time coordinated instructions of a TMC, (C)AVs should drive adequately during their journeys. However, it is necessary to concern to what extent such instructions should/can be made, especially when considering legal issues.In addition, legal aspects like the definition of special signage for automated vehicles and their handlingalso need to be considered, as those aspects will take time. This also means signage at the roadside, including VMS content, and signage from automated vehicles to surrounding traffic.Collaboration is also required regarding the definition and standardisation of V2X messages and protocols. The mechanisms proposed in TransAID to improve the reliability of V2X messages can be key in the near future. In general, V2X communications solutions require to be incorporated into standards to be effectively deployed. That is the case for, for example, collective perception solutions, message generation rules for manoeuvre coordination, V2X message compression or broadcast acknowledgement mechanisms. In TransAID we have been intensively working to promote and disseminate all the proposed solutions in top-tier journals and international conferences, as well as in organisations like ETSI and C2C-CC. The above shows a broad range of aspects studied by TransAID in the very dynamic and rapidly evolving field of automated driving.To provide links to additional information and to place the work of TransAID into context, Chapter 5 provides an overview or close related initiatives.

This present document is Deliverable D3.2 entitled "Cooperative manoeuvring in the presence of hierarchical traffic management", which was prepared in the context of the WP3 framework of the TransAID project. The scope of this document encompasses the modelling and simulation of cooperative manoeuvring in the context of the microscopic traffic simulation activities conducted within TransAID. Initially, the state of the art in the domain of cooperative manoeuvring is provided and then two different cooperative manoeuvring frameworks are introduced. The first one is a decentralized framework where cooperative manoeuvring is solely based on vehicle-to-vehicle (V2V) communications, while the second one is a centralized framework that utilizes vehicle-toanything (V2X) communications. A work zone scenario is used to elaborate on the operation of the centralized approach. The logic for simulating the decentralized approach in the microscopic traffic simulator SUMO is subsequently introduced along with the corresponding functionalities that were developed within SUMO for this purpose. Cooperative manoeuvring is coupled with hierarchical traffic management by explaining how the decentralized approach can be integrated in the traffic management plans that were developed for each use case examined in the context of TransAID. Cooperative manoeuvring is coupled with traffic separation in SUMO and a timeline of cooperative manoeuvring actions in the simulation is presented. Coupling with communications is also addressed. Moreover, adaptations to the driver-vehicle models encompassing communication requirements are proposed to enable integration in iTETRIS. Finally, recommendations for finetuning of driver-vehicle models in simulation are provided based on the findings of the real-world prototype experiments.

This document presents the work that has been performed in WP6 after D6.3, and therefore focussing on the integration sprints 3-6. It describes which parts of the system are implemented and how they are put together. To do so, it builds upon the deliverables created so far, esp. D6.3 and all other deliverables of the underlying work packages 3, 4 and 5. Another important aspect for understanding the content of this deliverable is D2.1 [4] for the scenario definition of the whole MAVEN project, and the deliverables D6.1 [5] and D6.2 [6], which give an overview on the existing infrastructure and vehicles used in MAVEN.

This deliverable is the textual description of the cooperative manoeuvre and trajectory planning and in-vehicle cooperative environment perception concepts, which have been designed by DLR and HMETC for MAVEN. An overview of the vehicle automation for DLR and HMETC on module level is given which represents briefly the main building blocks of the vehicle automation which will be used in MAVEN for simulation as well as for tests with vehicles. Based on the analysis of the existing current approaches and the state-of-the-art review, an advanced concept for cooperative trajectory planning and cooperative environment perception on modular level is presented for DLR and HMETC. Despite the differences between vehicle automation of DLR and HMETC, both must be able to cooperate with each other and build a platoon in complex urban area. In that event a unique platoon logic concept is presented by DLR which will be used by DLR and HMETC.

This present document is Deliverable D3.2 entitled 'Cooperative manoeuvring in the presence of hierarchical traffic management', which was prepared in the context of the WP3 framework of the TransAID project. The scope of this document encompasses the modelling and simulation of cooperative manoeuvring in the context of the microscopic traffic simulation activities conducted within TransAID. Initially, the state of the art in the domain of cooperative manoeuvring is provided and then two different cooperative manoeuvring frameworks are introduced. The first one is a decentralized framework where cooperative manoeuvring is solely based on vehicle-to-vehicle (V2V) communications, while the second one is a centralized framework that utilizes vehicle-toanything (V2X) communications. The logic for simulating the decentralized approach in the microscopic traffic simulator SUMO is subsequently introduced along with the corresponding functionalities that were developed within SUMO for this purpose. Cooperative manoeuvring is coupled with hierarchical traffic management by explaining how the decentralized approach can be integrated in the traffic management plans that were developed for each use case examined in the context of TransAID. Cooperative manoeuvring is coupled with traffic separation in SUMO and a timeline of cooperative manoeuvring actions in the simulation is presented. Coupling with communications is also addressed. Moreover, adaptations to the vehicle/driver models, that were developed to replicate the behaviour of cooperative and automated vehicles (CAV), are proposed based on the findings of the real-world prototype experiments. Finally, focus on the centralized approach in terms of development of relevant SUMO functionalities, and integration within the TransAID traffic management plans will be placed during the second project iteration.

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%.

The main objective of this Deliverable 2.1 is to describe and identify the use cases where disruptions of traffic flow are expected to be most severe because of transitions between automation levels, and to identify KPIs to evaluate those use cases. For those identifications, a state of the art literature review has been conducted, a workshop was held with road authority stakeholders, advisory board members have been consulted and experts have been interviewed. The findings have been combined to identify the relevant aspects for TransAID scenarios and Transition of Control (ToC) in general. The large number of aspects (or dimensions) affecting automated vehicle behaviour and possible trigger conditions in combination with the many uncertainties regarding those aspects and conditions (e.g. what exactly triggers a ToC or Minimum Risk Manoeuvre?), posed a challenge for the use case and scenario definitions. Through brainstorming using a template based on above mentioned aspects and conditions, TransAID has identified five generic services that can be applied to many situations. Because of their generic characteristic, these services are expected to mitigate negative impacts resulting from vehicles in Transition Areas, regardless of the uncertainties (i.e. even if certain conditions are different, the solutions still apply). As a result, an overview was created of example situations where transition of control occurs regularly and causes traffic flow disruptions. By means of detailed services and use case descriptions, the deliverable gives a comprehensive overview on (negative) traffic safety and traffic efficiency impacts, for both urban, inter-urban and motorway situations, and proposes a preliminary set of (high-level) traffic measures.

A new way of platooning in urban areas has been presented on the AAET conference last year. The theoretical approach of linking Cooperative Adaptive Cruise Control (C-ACC) to state-machine based platoon coordination has been discussed, which has been developed within the European H2020 project MAVEN (Managing Automated Vehicles Enhances Network). This approach leads to a maximum of flexibility and a dynamic platoon behavior allowing to cope with the complex situations occurring under urban conditions. Special attention of this development laid on the inclusion of communication - inside the platoon and to possible new members (V2V) and between infrastructure and the platoon (V2I and I2V) to allow coordinated movements through signalized intersections. During the last year, the theoretical approach has been put into praxis. Several steps had to be taken to reach the goal of driving on public roads in the end. First, simulations had to be performed. Then, an approach based on augmented reality has been chosen to test different scenarios on test tracks without the need of equipping several vehicles with the required hardware for C-ACC-platooning. Afterwards, more real components (traffic lights, other platooning vehicles) were added, until finally test runs could be performed on the public roads of the Tostmannplatz in Braunschweig, which is part of the Application platform for Intelligent Mobility (AIM). This paper shows the different test setups and approaches and describes early results of the tests.

In D2.1 five services have been described encompassing multiple use cases and scenarios. In this Deliverable 2.2, 5 scenarios are selected, one for each service, and worked out in more detail. The detailed timelines of the scenarios are provided describing what exactly is the sequence of events in the scenario and what the effect of the measures, which being developed in WP4, should be. Also, the simulation networks for each of the scenarios have been created and their specification is documented in this deliverable. Furthermore, the requirements for the simulations have been specified, ranging from several vehicle (type) models to the traffic composition, demand and vehicle mixes. For the second iteration of the project, 5 new or extended scenarios have been selected based on findings from the first iteration. Those findings are also used to update the overall simulation requirements and parameters (i.e. definition of actors, traffic composition, demand and vehicle/driver models). Finally, based on insights from the first iteration, several questions have been formulated which will be used during several surveys (e.g. digital polls or paper surveys during events; interviews with experts). The goal is to gain insights into legal implications, (expected) driver and/or automated vehicle behaviour and infrastructure specific aspects with respect to automated vehicles.

TransAID develops and demonstrates traffic management procedures and protocols to enable smooth coexistence of automated, connected, and conventional vehicles, especially at Transition Areas. A hierarchical approach is followed where control actions are implemented at different layers including centralised traffic management, infrastructure, and vehicles. This document summarises the results of the stakeholder consultation activities of the TransAID project. In the context of TransAID, the most relevant stakeholders are authorities and policy makers, road operators, vehicle manufacturers and suppliers, road infrastructure and traffic service providers, test and certification institutes, academia and knowledge institutes, future product owners and standardisation bodies. The consultation activities aimed to gather feedbacks on the project results, as well as to hear the stakeholders' view on the impact of prospective automated vehicles introduction. Most importantly, the stakeholders were asked about their ambitions and interests related to role and responsibilities in future scenarios of automated vehicle presence A summary of 7 stakeholder consultation events is provided in this deliverable: - TransAID-MAVEN-CoExist Stakeholder workshop, 10 October 2017, Brussels - TransAID-MAVEN-CoExist-INFRAMIX Expert meeting, 23 October 2018, Greenwich - TransAID session and survey, 8 June 2019, IEEE-IV, Paris - TransAID-U.S. CAMP expert meeting, 25 July 2019, Detroit - EU EIP workshop on ODD, 1 October 2019, Turin - TransAID-INFRAMIX stakeholder workshop, 9 October 2019, Graz - International workshop on ODD, 22 October 2019, Singapore For each stakeholder consultation event a description is given of the scope and aim, participants, plenary and break-out sessions, survey results (when applicable) and implications to the TransAID work. What can be observed from the sequence of stakeholder consultation events is that there is steady progression in the collective understanding of the relation between vehicle automation and infrastructure and the possible implications to the stakeholders involved. By now it seems that there is a common interest, also by vehicle manufacturers, to develop a comprehensive standard and/or taxonomy for classifying operational design domains (ODDs) of automated vehicle systems. The main findings from these events underline the uncertainty associated with the state-of-the-art of vehicle automation and its evolution in the coming decades. From an innovation standpoint these are exciting times, but as we have experienced, the uncertainties will not disappear soon or new uncertainties will arise. Moreover, since Cooperative, Connected and Automated Mobility and Digital and Physical Infrastructure are such new areas of innovation, the stakeholder consultation did not provide all the answers while for many subjects, nobody has the answer yet.

This report describes the organisation and outcome of the TransAID Symposium, held in Paris, France, on 9 June 2019, in conjunction with the IEEE Intelligent Vehicles Symposium (IV 2019), one of the major annual conferences of the IEEE Intelligent Transportation Systems Society (ITSS). In light of dissemination and obtaining stakeholder knowledge, TransAID bundled its resources with a large existing IV 2019 event to ensure a higher probability of attracting people to the workshop. As the audience of our workshop (which targeted technologies for cooperative and automated road transport) constituted a mix of academia, researchers, and industry, we were able to foster the interactive exchange between all these parties. The contents of the workshop comprised survey questions posed via the Mentimeter platform, invited speakers, and oral-paper presentations (which were thematically put into the two categories, of Connected and Automated driving, as well as security-related aspects of Cooperative ITS). Each time, an interactive discussion with the audience ensued, providing further insights into the authors' points of view. The survey results revealed that about half of the participants came from academia. Interestingly, a large group was in favour of foreseeing areas where automated driving should not be allowed, thereby directly confirming that TransAID's research questions and approach are sound and sensible. A very high proportion of the participants also spoke out towards OEMs, asking them to explain the limitations of their automated vehicles. In addition, connectivity was perceived as a mandatory requirement for Level 3 or higher automated vehicles. To conclude, a discussion followed some of the results related to the question whether (connected) automated vehicles would be allowed to break the law. This was seen as moderately acceptable when optimisation of the traffic stream was called for, but definitely for the purpose of increasing traffic safety.

This document describes the project achievements in cooperative perception algorithm development and testing. An overview of the building blocks, vehicle setups and embeddings of the perception algorithms into the test vehicle architectures used within the experiments at DLR and HMETC is given. A review of the state-of-the-art outlines the different levels of sophistication that are known from literature for the association and data fusion steps of a cooperative environment perception algorithm and reflects recent developments in the field. Real time algorithms are explained that were used in the experiments and demonstrations at the HMETC test site with both HMETC and DLR vehicles involved. Fusion experiments demonstrate detection and perception of a pedestrian not in sight of the ego vehicle sensors via a collective perception (CPM) message and combining of position estimates received via a cooperative awareness message (CAM) with the sensor detections of a test vehicle. Based on the results of the state-of-the-art review, an advanced fusion algorithm is proposed and its performance in urban traffic scenarios as well as Monte Carlo simulation scenarios evaluated. Conclusions are drawn for cooperative perception algorithm development and testing. This deliverable serves (in combination with D3.3) as basis for the testing done in WP6 with its upcoming deliverable D6.4 and the evaluation done in WP7 with its upcoming deliverable D7.2. The developments, experiments and evaluations presented in this deliverable have been executed by the MAVEN project partners HMETC and DLR in tight cooperation.

This deliverable is the textual description of the cooperative manoeuvre and trajectory planning algorithm which have been designed and implemented by DLR and HMETC for MAVEN. An overview of different modules of vehicle automation is given. The trajectory planning and tactical and strategical modules and their roles on cooperation are explained. Furthermore, cooperation with infrastructure in the form of AGLOSA and lane change and cooperation with other automated vehicle in the form of platooning is described. Functionality of the algorithms is approved by simulation results, close field tests and urban tests in close relation to WP4, WP6 and WP7.

This deliverable is a direct successor of Deliverable 7.1 [1], which has introduced all vehicles, test tracks and used hardware, and also proposed system architectures of the different used components. D7.1 has also introduced several system requirements for each component and for each scenario, which has to be implemented. D7.2 now shows the results of the first project integration phase. The system implementation is described for the different components of the infrastructure part as well as for the vehicle part. It is shown how both parts communicate in the real world during the first project iteration by presenting the used ASN.1 message definitions (in the Annex) and details about the communication software. Furthermore, a feasibility assessment has been performed by the project partner HMETC. For this, each scenario has been divided into test cases, which have been implemented in the real world prototypes, and demonstrated on a test track in northern Germany. Each test case is linked to related requirements set up in D7.1. During the feasibility assessment, the compliance with all requirements has been checked. In addition, the overall "look and feel" of the prototype and the performance in each test case has been rated and described. In summary, most of the requirements were met. Nevertheless, some deviations have been found. Most of those deviations will be fixed during the second iteration of the project, but there were also some minor points, which need to be reformulated during the second iteration. These points include some identified weaknesses and some needed re-interpretations of existing fields in the used messages. Altogether, it could be shown that the TransAID ideas can be put into real-world to help future automated vehicles to better cope with possible threats and to gain higher performance on the road.

This deliverable is the textual description of the cooperative manoeuvre and trajectory planning and in-vehicle cooperative environment perception concepts, which have been designed by DLR and HMETC for MAVEN.

Los sistemas inteligentes de transporte cooperativos (Cooperative Intelligent Transport Systems) han sido identificados como un medio prometedor para mejorar la seguridad vial y la eficiencia del tráfico. Estos sistemas se basan en el intercambio dinámico de mensajes entre vehículos (Vehicle-to-Vehicle, V2V), y entre vehículos y nodos de infraestructura (Vehicle-to-Infrastructure, V2I). Gracias a este intercambio de información, las aplicaciones cooperativas permitirán que un conductor pueda detectar situaciones de tráfico adversas o peligrosas con suficiente antelación, tanto en el tiempo como en el espacio. Para hacer frente a los estrictos requisitos de las aplicaciones cooperativas y a las condiciones adversas en las que se realizan las comunicaciones vehiculares, están siendo especificados los estándares de comunicación internacionales IEEE 802.11p y ETSI ITS G5. Estos estándares permiten realizar comunicaciones V2V y V2I directas o del tipo multi-hop. Las comunicaciones multi-hop en redes de comunicaciones vehiculares posibilitan la transmisión de mensajes hacia nodos lejanos y la distribución de información a vehículos situados en áreas de relevancia, empleando nodos intermedios como retransmisores. Sin embargo, el rendimiento de sistemas que emplean comunicaciones multi-hop depende ampliamente del diseño e implementación de protocolos de enrutamiento y diseminación eficaces y efectivos. Estos protocolos deben enfrentarse a los retos impuestos por el entorno de comunicación vehicular (la elevada movilidad de los vehículos, las condiciones variables de propagación radio y de densidad vehicular, y las escasez de recursos radio). En este contexto, esta tesis doctoral presenta y evalúa novedosos protocolos de enrutamiento y diseminación basados en el concepto de conectividad multi-hop de las calles o “multi-hop road connectivity”. La conectividad multi-hop se define como la capacidad que presenta una calle para posibilitar comunicaciones multi-hop. En la tesis, se propone un mecanismo de comunicación para estimar esta conectividad multi-hop en tiempo real y de forma distribuida. Comparado con otros mecanismos que intentan extrapolar la capacidad de retransmisión multi-hop de una calle basándose en evaluaciones de su densidad de vehículos, el mecanismo propuesto genera menores niveles de sobrecarga en el canal radio. Utilizando el mecanismo de estimación de la conectividad multi-hop propuesto, se presenta un protocolo de enrutamiento que emplea retransmisiones broadcast basadas en contención. Este enfoque basado en contención proporciona robustez al proceso de retransmisión de mensajes. Las estimaciones de la conectividad multi-hop permiten que las decisiones de enrutamiento se adapten dinámicamente a las variaciones de conectividad de la red vehicular. Además, el uso de estas estimaciones hace que la carga de comunicaciones se distribuya más uniformemente en el escenario, permitiendo de esta manera que se reduzca la probabilidad espacial de congestión del canal radio. Finalmente, la tesis propone un protocolo de diseminación híbrido que utiliza las ventajas de las comunicaciones radio heterogéneas. En particular, el protocolo propuesto combina comunicaciones celulares y comunicaciones V2V para diseminar información desde un proveedor centralizado hacia los vehículos situados en un área de relevancia. En particular, las estimaciones de la conectividad multi-hop se envían al proveedor centralizado utilizando la red celular, y los datos se procesan y fusionan para obtener una imagen global de la conectividad de la red vehicular. Este conocimiento contextual de la conectividad se emplea por el proceso de diseminación propuesto que combina inyecciones de la información mediante transmisiones celulares con una diseminación cooperativa en la red de vehículos a través de comunicaciones V2V. La información contextual permite realizar estrategias de inyección inteligentes que aumentan la fiabilidad del proceso de diseminación sin exigir una alta cantidad de recursos celulares. El conocimiento contextual de la conectividad basado en la información de conectividad multi-hop se obtiene con bajos niveles de sobrecarga de comunicaciones tanto en la red celular como en la vehicular. La eficacia y la eficiencia de todos los protocolos propuestos han sido validadas mediante simulaciones a gran escala con precisión, y conformes con los estándares de comunicación vehiculares. En este contexto, la tesis presenta una novedosa plataforma modular para la simulación de aplicaciones ITS cooperativas que ofrece estas capacidades en una única solución.

The use of cooperative ITS communication systems, supporting driving through the dynamic exchange of Vehicle-to- Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) messages, is a potential candidate to improve the economical and societal welfare. The application of such systems for novel cooperative traffic management strategies can introduce a lot of beneficial effects not only for road safety, but also for the economy related to transportation systems and the environmental impact. Despite this apparent set of promising features, City Road Authorities, which hold a key-role in determining the final adoption of such systems, still look at cooperative systems without sharing a clear opinion. This is mainly due to the current lack of definitive and solid evidences of the effectiveness of such systems when applied in the real world. In order to fill this gap and let Road Authorities estimate the usefulness of such technologies in achieving the objectives dictated by cities’ traffic management policies, the EU consortium iTETRIS is developing a simulation platform for large scale testing of traffic management solutions making use of cooperative ITS systems. Thanks to its own distinguishing features, iTETRIS aims at becoming a good supporting tool for Road Authorities to implement preliminary tests on the effectiveness of ITS solutions prior to investing money for the physical deployment of the communication infrastructures allowing their functioning.

Los sistemas inteligentes de transporte cooperativos (Cooperative IntelligentTransport Systems) han sido identificados como un medio prometedor para mejorar laseguridad vial y la eficiencia del tráfico. Estos sistemas se basan en el intercambiodinámico de mensajes entre vehículos (Vehicle-to-Vehicle, V2V), y entre vehículos y nodos de infraestructura (Vehicle-to-Infrastructure, V2I). Gracias a este intercambio de información, las aplicaciones cooperativas permitirán que un conductor pueda detectar situaciones de tráfico adversas o peligrosas con suficiente antelación, tanto en el tiempocomo en el espacio. Para hacer frente a los estrictos requisitos de las aplicacionescooperativas y a las condiciones adversas en las que se realizan las comunicacionesvehiculares, están siendo especificados los estándares de comunicación internacionalesIEEE 802.11p y ETSI ITS G5. Estos estándares permiten realizar comunicaciones V2V yV2I directas o del tipo multi-hop. Las comunicaciones multi-hop en redes decomunicaciones vehiculares posibilitan la transmisión de mensajes hacia nodos lejanos y la distribución de información a vehículos situados en áreas de relevancia, empleando nodos intermedios como retransmisores. Sin embargo, el rendimiento de sistemas queemplean comunicaciones multi-hop depende ampliamente del diseño e implementaciónde protocolos de enrutamiento y diseminación eficaces y efectivos. Estos protocolos deben enfrentarse a los retos impuestos por el entorno de comunicación vehicular (la elevada movilidad de los vehículos, las condiciones variables de propagación radio y dedensidad vehicular, y las escasez de recursos radio). En este contexto, esta tesis doctoral presenta y evalúa novedosos protocolos de enrutamiento y diseminación basados en el concepto de conectividad multi-hop de las calles o “multi-hop road connectivity”. La conectividad multi-hop se define como la capacidad que presenta una calle para posibilitar comunicaciones multi-hop. En la tesis, se propone un mecanismo de comunicación para estimar esta conectividad multi-hop en tiempo real y de forma distribuida. Comparado con otros mecanismos que intentan extrapolar la capacidad de retransmisión multi-hop de una calle basándose en evaluaciones de su densidad de vehículos, el mecanismo propuesto genera menores niveles de sobrecarga en el canalradio. Utilizando el mecanismo de estimación de la conectividad multi-hop propuesto, se presenta un protocolo de enrutamiento que emplea retransmisiones broadcast basadas en contención. Este enfoque basado en contención proporciona robustez al proceso de retransmisión de mensajes. Las estimaciones de la conectividad multi-hop permiten quelas decisiones de enrutamiento se adapten dinámicamente a las variaciones deconectividad de la red vehicular. Además, el uso de estas estimaciones hace que la cargade comunicaciones se distribuya más uniformemente en el escenario, permitiendo de estamanera que se reduzca la probabilidad espacial de congestión del canal radio. Finalmente,la tesis propone un protocolo de diseminación híbrido que utiliza las ventajas de lascomunicaciones radio heterogéneas. En particular, el protocolo propuesto combinacomunicaciones celulares y comunicaciones V2V para diseminar información desde unproveedor centralizado hacia los vehículos situados en un área de relevancia. Enparticular, las estimaciones de la conectividad multi-hop se envían al proveedorcentralizado utilizando la red celular, y los datos se procesan y fusionan para obtener unaimagen global de la conectividad de la red vehicular. Este conocimiento contextual de laconectividad se emplea por el proceso de diseminación propuesto que combinainyecciones de la información mediante transmisiones celulares con una diseminacióncooperativa en la red de vehículos a través de comunicaciones V2V. La informacióncontextual permite realizar estrategias de inyección inteligentes que aumentan lafiabilidad del proceso de diseminación sin exigir una alta cantidad de recursos celulares.El conocimiento contextual de la conectividad basado en la información de conectividadmulti-hop se obtiene con bajos niveles de sobrecarga de comunicaciones tanto en la redcelular como en la vehicular. La eficacia y la eficiencia de todos los protocolospropuestos han sido validadas mediante simulaciones a gran escala con precisión, yconformes con los estándares de comunicación vehiculares. En este contexto, la tesispresenta una novedosa plataforma modular para la simulación de aplicaciones ITScooperativas que ofrece estas capacidades en una única solución., Resumen en español

The use of cooperative wireless communications can support driving through dynamic exchange of Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) messages. Traffic applications based on such systems will be able to generate a safer, faster, cheaper and cleaner way for people and goods to move. In this context, the iTERIS project aims at providing the framework to combine traffic mobility and wireless communication simulations for large scale testing of traffic management solutions based on cooperative systems. This paper addresses the description and explanation of the implementation choices taken to build a modular and interoperable architecture integrating heterogeneous traffic and wireless simulators, and application algorithms supporting traffic management strategies. The functions of an “in-between” control system for managing correct simulation executions over the platform are presented. The inter-block interaction procedures identified to ensure optimum data transfer for simulation efficiency are also introduced.