Generation of Cooperative Perception Messages for Connected and Automated Vehicles

Connected and Automated Vehicles (CAVs) utilize a variety of onboard sensors to sense their surrounding environment. CAVs can improve their perception capabilities if vehicles exchange information about what they sense using V2X communications. This is known as cooperative or collective perception (or sensing). A frequent transmission of collective perception messages could improve the perception capabilities of CAVs. However, this improvement can be compromised if vehicles generate too many messages and saturate the communications channel. An important aspect is then when vehicles should generate the perception messages. ETSI has proposed the first set of message generation rules for collective perception. These rules define when vehicles should generate collective perception messages and what should be their content. We show that the current rules generate a high number of collective perception messages with information about a small number of detected objects. This results in an inefficient use of the communication channel that reduces the effectiveness of collective perception. We address this challenge and propose an improved algorithm that modifies the generation of collective perception messages. We demonstrate that the proposed solution improves the reliability of V2X communication and the perception of CAVs

Cooperative Perception for Connected and Automated Vehicles: Evaluation and Impact of Congestion Control

Automated vehicles make use of multiple sensors to detect their surroundings. Sensors have significantly improved over the years but still face challenges due to the presence of obstacles or adverse weather conditions, among others. Cooperative or collective perception has been proposed to help mitigate these challenges through the exchange of sensor data among vehicles using V2X (Vehicle-to-Everything) communications. Recent studies have shown that cooperative perception can complement on-board sensors and increase the vehicle's awareness beyond its sensors field of view. However, cooperative perception significantly increases the amount of information exchanged by vehicles which can degrade the V2X communication performance and ultimately the effectiveness of cooperative perception. In this context, this study conducts first a dimensioning analysis to evaluate the impact of the sensors' characteristics and the market penetration rate on the operation and performance of cooperative perception. The study then investigates the impact of congestion control on cooperative perception using the Decentralized Congestion Control (DCC) framework defined by ETSI. The study demonstrates that congestion control can negatively impact the perception and latency of cooperative perception if not adequately configured. In this context, this study demonstrates for the first time that the combination of congestion control functions at the Access and Facilities layers can improve the perception achieved with cooperative perception and ensure a timely transmission of the information. The results obtained demonstrate the importance of an adequate configuration of DCC for the development of connected and automated vehicles

Context-based Broadcast Acknowledgement for Enhanced Reliability of Cooperative V2X Messages

Most V2X applications/services are supported by the continuous exchange of broadcast messages. One of the main challenges is to increase the reliability of broadcast transmissions that lack of mechanisms to assure the correct delivery of the messages. To address this issue, one option is the use of acknowledgments. However, this option has scalability issues when applied to broadcast transmissions because multiple vehicles can transmit acknowledgments simultaneously. To control scalability while addressing reliability of broadcast messages, this paper proposes and evaluates a context-based broadcast acknowledgement mechanism where the transmitting vehicles selectively request the acknowledgment of specific/critical broadcast messages, and performs retransmissions if they are not correctly received. In addition, the V2X applications/services identify the situations/conditions that trigger the execution of the broadcast acknowledgment mechanism, and the receiver(s) that should acknowledge the broadcast messages. The paper evaluates the performance of the context-based broadcast acknowledgment mechanism for a Collective Perception Service. The obtained results show the proposed mechanism can contribute to improve the awareness of crossing pedestrians at intersections by increasing the reliability in the exchange of CPM messages between vehicles approaching the intersection. This solution is being discussed under IEEE 802.11bd, and thus can be relevant for the standardization process.10.13039/501100000780-European Commission;10.13039/501100007170-Ministry of Econom

Benchmarking of Recommendation Trust Computation for Trust/Trustworthiness Estimation in HDNs

In the recent years, Heterogeneous Distributed Networks (HDNs) is a predominant technology implemented to enable various application in different fields like transportation, medicine, war zone, etc. Due to its arbitrary self-organizing nature and temporary topologies in the spatial-temporal region, distributed systems are vulnerable with a few security issues and demands high security countermeasures. Unlike other static networks, the unique characteristics of HDNs demands cutting edge security policies. Numerous cryptographic techniques have been proposed by different researchers to address the security issues in HDNs. These techniques utilize too many resources, resulting in higher network overheads. This being classified under light weight security scheme, the Trust Management System (TMS) tends to be one of the most promising technology, featured with more efficiency in terms of availability, scalability and simplicity. It advocates both the node level validation and data level verification enhancing trust between the attributes. Further, it thwarts a wide range of security attacks by incorporating various statistical techniques and integrated security services. In this paper, we present a literature survey on different TMS that highlights reliable techniques adapted across the entire HDNs. We then comprehensively study the existing distributed trust computations and benchmark them in accordance to their effectiveness. Further, performance analysis is applied on the existing computation techniques and the benchmarked outcome delivered by Recommendation Trust Computations (RTC) is discussed. A Receiver Operating Characteristics (ROC) curve illustrates better accuracy for Recommendation Trust Computations (RTC), in comparison with Direct Trust Computations (DTC) and Hybrid Trust Computations (HTC). Finally, we propose the future directions for research and highlight reliable techniques to build an efficient TMS in HDNs

TransAID Deliverable 6.2/2 - Assessment of Traffic Management Procedures in Transition Areas

This Deliverable 6.2 of the TransAID project presents and evaluates the simulation results obtained for the scenarios considered during the project's first and second iterations. To this end, driver- and AV-models designed in WP3, traffic management procedures developed in WP4, and V2X communication protocols and models from WP5 were implemented within the iTETRIS simulation framework. Previous main results from Deliverable 4.2, where baseline and traffic management measures without V2X communication were compared, have been confirmed. While not all TransAID scenarios' traffic KPIs were affected, the realistic simulation of V2X communication has shown a discernible impact on some of them, which makes it an indispensable modelling aspect for a realistic performance evaluation of V2X traffic scenarios. Flaws of the first iteration's traffic management algorithms concerning wireless V2X communication and the accompanying possibility of packet loss were identified and have been addressed during the project's second iteration. Finally, lessons learned while working on these simulation results and assessments have additionally been described in the form of recommendations for the real-world prototype to be developed in WP7. We conclude that all results obtained for all scenarios when employing ideal communication confirmed the statistical trends of the results from the original TM scenarios as reported in Deliverable 4.2 where no V2X communication was considered. Furthermore, the performance evaluation of the considered scenarios and parameter combinations has shown the following, which held true in both the first and second iterations: (1) The realistic simulation of V2X communication has an impact on traffic scenarios, which makes them indispensable for a realistic performance evaluation of V2X traffic scenarios. (2) Traffic management algorithms need to account for sporadic packet loss of various message types in some way. (3) Although important, the realistic modelling and simulation of V2X communication also induces a significant computational overhead. Thus, from a general perspective, a trade-off between computation time and degree of realism should be considered

A Cost Effective Route Guidance Method for Urban Areas Using Histograms

Analysing shortest path for real time traffic environment is crucial with dynamic updating. VANET technology can be used for analysing traffic but generates a huge amount of data to be exchanged, which demands more processing power and resources. In this paper, a new histogram-based route guidance algorithm (HBA) has been proposed based on light weight processing. The proposed algorithm enables selecting the shortest path between any source and destination using the histogram models, which capture the higher order distribution function of the number vehicles in every lane. Furthermore, the histogram model is used to estimate the traffic delays at intersections and roundabouts. The data entity collection through sensors used for histogram modelling is presented in detail. The experimental results show that the proposed algorithm provides a good prediction of road traffic status and a better solution for the congestion problem in the urban areas

Scalable cooperative perception for connected and automated driving

Cooperative perception (a.k.a. Collective perception or cooperative sensing) will allow Connected and Automated Vehicles (CAVs) to share information about detected objects. Cooperative perception improves the sensing accuracy, confidence and range of CAVs, and extends their perception of the driving environment. First message generation rules based on the mobility and dynamics of detected objects have been proposed to decide when a cooperative perception message should be generated and what information it should include. Studies have shown that this type of generation rules can compromise the scalability of cooperative perception and vehicular networks, as they tend to transmit significant amounts of redundant information and generate small and frequent cooperative perception messages that increase the communications overhead. To combat these inefficiencies, this paper proposes and evaluates three techniques that combine, for the first time, baseline mobility-based generation rules for cooperative perception messages with mechanisms to control the redundancy and organize the information about detected objects in order to avoid the frequent transmission of small messages. This study demonstrates that the proposed techniques improve the perception of CAVs and reduce the information age. In addition, the techniques reduce the channel load and improve the scalability of cooperative perception services and vehicular networks. The study demonstrates that the most effective technique is based on: (1) first applying the generation rules to decide whether a cooperative perception message should be generated, (2) then applying redundancy control, and finally (3) organizing the information about all detected objects to avoid small and frequent message

Infrastructure-Supported Cooperative Automated Driving in Transition Areas

Automated driving is not possible everywhere. Limited by the Operational Design Domain (ODD) of vehicle automation functions, Transitions of Control (ToC) are required. If the ToCs fail, Minimum Risk Maneuvers (MRM) are executed, resulting in stopped vehicles on the road. As a result, traffic is negatively impacted, esp. when the number of automated vehicles (AVs) rises. To reduce such negative impacts, the EU-H2020 TransAID project has designed novel infrastructure-assisted traffic management measures using V2X communications, and evaluated them via simulations and field trials. This paper shows how prototypic real-world tests were performed to validate feasibility of the TransAID measures on public road and test track trials. The obtained results show that infrastructure support and V2X communication can contribute to drastically reduce the need to perform ToCs, MRMs, and hence the risk of blocked roads

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