On the Potential of V2X Message Compression for Vehicular Networks

The emergence of connected automated vehicles and advanced V2X applications and services can challenge the scalability of vehicular networks in the future. This challenge requires solutions to reduce and control the communication channel load beyond the traditional congestion control protocols proposed to date. In this paper, we propose and evaluate the use of V2X message compression to reduce the channel load and improve the scalability and reliability of future vehicular networks. Data compression has the potential to reduce the channel load consumed by each vehicle without reducing the amount of information transmitted. To analyze its potential, this paper evaluates the compression gain of three compression algorithms using standardized V2X messages for basic awareness (CAMs), cooperative perception (CPMs) and maneuver coordination (MCMs) extracted from standard-compliant prototypes. We demonstrate through network simulations that V2X message compression can reduce the channel load. In particular, the tested compression algorithms can reduce the channel load by up to 27% without reducing the amount of information transmitted. Reducing the channel load and the consequent interferences significantly improves the reliability of V2X communications. However, this study also emphasizes the need for high-speed compression and decompression modules capable to compress and decompress V2X messages in real time, especially under highly loaded scenarios

Infrastructure Support for Cooperative Maneuvers in Connected and Automated Driving

Connected and automated vehicles can exploit V2X communications to coordinate their maneuvers and improve the traffic safety and efficiency. To support such coordination, ETSI is currently defining the Maneuver Coordination Service (MCS). The current approach is based on a distributed solution where vehicles coordinate their maneuvers using V2V (Vehicle-to-Vehicle) communications. This paper proposes to extend this concept by adding the possibility for the infrastructure to support cooperative maneuvers using V2I (Vehicle-to-Infrastructure) communications. To this aim, we propose a Maneuver Coordination Message (MCM) that can be used in cooperative maneuvers with or without road infrastructure support. First results show the gains that cooperative maneuvers can achieve thanks to the infrastructure support. This paper also analyses and discusses the need to define MCM generation rules that decide when MCM messages should be exchanged. These rules have an impact on the effectiveness of cooperative maneuvers and on the operation and scalability of the V2X network

TransAID Deliverable 7.2: System Prototype Demonstration (Iteration 1)

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

TransAID Deliverable 7.2: System prototype demonstration (iteration 2)

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

TransAID Deliverable 8.2: Meta-analysis of the results

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

ITETRIS: a modular simulation platform for the large scale evaluation of cooperative ITS applications

Cooperative ITS systems are expected to improve road traffic safety and efficiency, and provide infotainment services on the move, through the dynamic exchange of messages between vehicles, and between vehicles and infrastructure nodes. The complexity of cooperative ITS systems and the interrelation between its components requires their extensive testing before deployment. The lack of simulation platforms capable to test, with high modelling accuracy, cooperative ITS systems and applications in large scale scenarios triggered the implementation of the EU-funded iTETRIS simulation platform. iTETRIS is a unique open source simulation platform characterized by a modular architecture that allows integrating two widely adopted traffic and wireless simulators, while supporting the implementation of cooperative ITS applications in a language-agnostic fashion. This paper presents in detail the iTETRIS simulation platform, and describes its architecture, standard compliant implementation, operation and new functionalities. Finally, the paper demonstrates iTETRIS large scale cooperative ITS evaluation capabilities through the implementation and evaluation of cooperative traffic congestion detection and bus lane management applications. The detailed description and implemented examples provide valuable information on how to use and exploit iTETRIS simulation potential