Over the past decade, various players, including automotive OEMs, CCAM suppliers, SMEs, startups, as well as public and private research institutions, have made increased efforts to become active in this domain. Their endeavours include the development of driving assistance systems, entire CCAM vehicle prototypes, as well as autonomous driving laboratories aimed at creating realistic traffic situations for training intelligent vehicles, such as obstacle detection, autonomous braking and steering, and collision avoidance. All these developments have in common that they rely on PNT information and that significant efforts in research and development in this area are still required to drive this development forward, as the commercial implementation of CCAM solutions still remains a significant challenge.
Connected, Cooperative and Automated Vehicles (CCAV) can be defined as the next generation of vehicles equipped with advanced sensors, controllers, and actuators to provide intelligent driving, comfort, safety, and energy efficiency. In 2014, the Society of Automotive Engineers (SAE) published a standard for intelligent and autonomous vehicles that has been adopted by companies and research institutions around the world and classifies the level of driving intelligence and automation (see Table below for closer definition).
The degree of autonomy and the level of intelligent driving functions is complemented or even enabled by communication mechanisms between road users and their environment. The function of CCAM systems is thus mainly based on communication between vehicles (C2V or V2V) and communication between the vehicle and the environment (C2X or V2X). In this context, technological developments benefit in particular from the latest trends and advances in 5G technologies, machine learning and artificial intelligence, which have the ability to provide and share complementary PNT information. So, when it comes to the development and implementation of CCAM systems, the automotive industry is just as much in demand as the PNT community: Autonomous and connected vehicles need to be equipped with a multitude of sensors and actuators, generating a large amount of data in real-time that must be processed and analysed to make timely decisions.
There are different scenarios of how these types of vehicles will be integrated into the transportation sector, but the main ones are either fully autonomous, independent, self-driving vehicles that can work with existing infrastructure, or a simplified version, CCAVs, that are fully autonomous only where the road infrastructure allows, and switch between different levels of autonomy. The higher the level of automation and the more independent the execution of dynamic driving tasks, the more important PNT information becomes to enable real-time environmental awareness and decision making. This leads to a wide variety of technological possibilities for CCAM systems, depending on for example the degree of autonomy, the objective, the sensors used, or the capabilities required.
Different technical solutions entail very different requirements that have to be met in order to counter current and future challenges and enable the safe, accurate, and reliable use of CCAM systems. For autonomous and connected vehicle operation, the technical foundation must first be established, especially in urban situations with unpredictable traffic, including the collaboration of multiple real-time systems, such as environmental awareness, localization, planning, and control. In addition to these challenges, environmental factors, such as real-time traffic analysis and weather conditions, as well as road infrastructure, including traffic signs, road markings, accidents and road works, pavement, road structure, and available parking spaces, must be considered and integrated into the system. This must be combined with a robust vehicle platform with appropriate sensors, computer hardware, networks, and software infrastructures that are able to consider the volume, speed, quality, heterogeneity, and real-time nature of data.
Although many demonstration CCAVs have been developed to prove the concept of connected and autonomous driving and the possibility of improving traffic efficiency, there is still a large gap that needs to be closed before high-level mass production of CCAVs can be achieved. This gap reflects the discrepancy between the focus of the various actors involved. On the one hand, the automotive industry focus on the development of key technologies, mostly hardware, including high-value electronic components such as sensors, control units, and actuators. On the other hand, researchers focus on developing reliable algorithms to perform driving tasks such as perception, decision-making, and control. However, high-level interaction and cooperation between the two appear to be limited. The interaction between the automotive industry and research as well as the integration and complementation by the PNT Industry can provide confident solutions to the problem.
What are we looking for - Challenging PNT Use Cases
The provision of ubiquitous positioning, navigation, and timing information as well as the full situation awareness of vehicles in the system belong to the main challenges, that need to be countered in the future. Possible PNT solutions for CCAM are as diverse as their application areas and offer technological opportunities not only for passenger cars but also for buses, trucks, and entire infrastructures. This allows for more customized applications such as advanced traffic and parking management and traffic pricing systems. Thus, the integration of complementary and alternative PNT technologies in CCAM systems from tomorrow can reduce congestion, increase efficiency, minimize energy consumption, reduce emissions, avoid accidents, and thus provide more sustainable modes of transportation overall.
Accordingly, a variety of stakeholders is addressed, from private car users to car manufacturers and suppliers, to public authorities, municipalities and city planners. All will benefit from better connected, cleaner, and more automated traffic development. And although the development of fully automated vehicles (SAE Level 4-5) has still major challenges to overcome, the road ahead is described by innovative CCAM solutions, enabled by PNT data that, step by step, will enable the automotive sector of tomorrow.
The following section describes different potential application areas in form of five themes, all related to the integration of PNT information but all with different goals and addressing different challenges, to serve as illustration for what the market is currently looking for:
Theme 1: Ubiquitous and High-Performance PNT for CCAM
To ensure the reliability, accuracy, coverage, and safety of CCAM, continuous, trustworthy and real-time PNT information is critical. This is even more challenging when considering that highly automated vehicles require, depending on the application scenario, real-time accuracy of less than 10 cm, while also requiring a high level of integrity in any environment (in particular challenging in urban environments). GNSS alone is not able to meet all of these stringent requirements due to signal attenuation and potential interferences. To obtain accurate location information, various solutions need to be combined, including GNSS-based solutions that enable accurate outdoor location and 5G-based technologies such as angle-based solutions (Downlink Angle of Departure DL-AoD, Uplink Angle of Arrival UL-AoA), and time-based solutions (Downlink Time Difference of Arrival DL-TDOA, Uplink Time Difference of Arrival UL-TDOA, and Multi Round Time Trip Multi RTT). In addition to on-board sensors, concepts such as smart roads, Highway 4.0, and other intelligent transportation infrastructures that have recently gained momentum in the scientific community, can be used to increase the accuracy and reliability of PNT data. Unlike conventional roads, smart roads interact dynamically with drivers, using active perception and automatic differentiation to provide real-time information about traffic, accidents, and alternative routes in emergencies.
Theme 2: Perception 360 for CCAM
A key requirement for more automated traffic is the full situational awareness of the vehicles in the system. Connected, cooperative, and automated vehicles require information from a variety of sensors that perform tasks such as sensing, navigating, and communicating with other vehicles, and the environment. One important task is the detection of moving objects (MOD) in order to achieve robust autonomous driving. Thus, multiple sensors, including cameras, LIDAR sensors, and speed detection systems must cooperate for the perception of the surrounding environment. However, a challenge connected to this is the position of the respective vehicle itself. Cameras for example do not offer the capability to cover objects at all distances and speeds, in particular, if the ego-vehicle itself is moving. Moreover, cameras are informative systems, that are dependent on visibility conditions. Therefore, it is necessary to merge the information of cameras, as well as Radar or LIDAR sensors with PNT information in real-time, so the decision-making can be supported. However, combining this information and producing a meaningful, timely evaluation is difficult due to the latency of the transmitted data. Only if vehicles and objects that are in the same location have the same situational awareness at the same time within a very narrow time window, collision avoidance can be dramatically improved. Thus, if a vehicle is moving, solutions must be in place that can model the predicted position of the moving vehicle. Artificial intelligence and machine learning play an important role in evaluating the image and sensor data and correlating them with the actual or foreseeable position. Another perception issue concerns the development of suitable algorithms capable of detecting the environment with a high degree of reliability in all operational areas and distinguishing, for example, a stationary motorcycle from a cyclist riding on the side of the road.
Theme 3: Monitoring and over-the-air updates for CCAM
CCAM comprises all digital services and functions necessary to commercially realize automated driving to SAE Level 4 or higher in Europe, which includes a wide range of technologies and services. One of the most important components of connected, cooperative, and autonomous vehicles is the software and firmware. It is the foundation of every vehicle in the system and thus constant validation and update mechanisms need to be in place to ensure safe and reliable traffic behaviour. Instead of going to the garage, however, so-called over-the-air updates enable the remote management and update of the software and firmware in the car via various over-the-air (OTA) interfaces such as Cellular, Wi-Fi, and Bluetooth. This makes the rollout more convenient not only for the driver but also for the automotive OEM itself, as the introduction of OTA updates brought high-cost savings in the billions of dollars. OTA updates, especially of the software, are already common practice at many OEMs and include, for example, the regular updating of map material. However, with the transition to electric vehicles, these updates are becoming more regular, more complex and therefore more necessary. Some OEMs already offer OTAs to update the battery control module, or more generally to optimize the charging capability in all-electric vehicles. Still, there is much room for improvement as the adoption rate is still relatively low due to the complexity of the process and the need for high reliability of the update functionality. In addition, recent technical developments related to autonomous vehicles allow highly automated driving functions (HADF) to be updated over the air. This increases the need for highly secure development of these updates, as a threat in certain scenarios can lead to functional failures and thus greater damage.
Theme 4: PNT for Clean Mobility
In order to comply with the Paris Agreement and reach the net zero goal by 2050, sooner or later petrol vehicles will be replaced by electric vehicles. The adoption of electric vehicles (EVs) has the potential to reduce pollutant and greenhouse gas emissions currently cause by road transport (approximately 25% of global CO2 emissions. The development of electric vehicles and associated infrastructures is closely linked to the adoption of CCAM technologies, which can help accelerate the transition to more sustainable modes of transport.
The deployment of EVs still struggles with various challenges such as long charging times and limited range. Moreover, the nationwide or regional introduction of electric vehicles depends not only on the public acceptance of the vehicles themselves but also on the development and expansion of the corresponding supportive infrastructure. Charging vehicles at home is obviously more convenient for owners in rural areas, but the majority of people live in cities, and the trend is growing. Here, access to the user’s own garages is limited and public charging stations are needed. While home charging takes about 6 hours, public fast-charging stations take about 30 minutes, which has a greater impact on power grids. If the energy is purchased on the wholesale electricity market, the prices for charging at public charging stations can be even lower due to the corresponding lower tariffs. Given the huge investment effort required for these infrastructures, this is a challenge for many countries and regions. Thus, in addition to the provision of charging stations, the integrated provision of information for vehicles but also for the energy provider must be taken into account. Route planning and optimization, including the integration of the consideration of charging points and times, are important cornerstones when it comes to the wider use of electric vehicles.
Theme 5: Testing for CCAM-related PNT technologies
All the technological opportunities described above, such as digitalization, 5G and IOT (Internet of Things), and their combination with common or new PNT technologies, open up new ways to improve road safety, develop sustainable infrastructure and increase mobility. However, in order to fully exploit the potential of these technological opportunities, various CCAM innovations need to be tested and, if necessary, improved and further developed. Testing new technologies is particularly important, as errors or inaccuracies can lead to the damage of vehicles, infrastructures, or even to the loss of life of road users. Therefore, the standardization of technologies in road traffic is indispensable to make the public space safer, avoid possible errors, but also to create legal certainty in case of unexpected problems. The validation of alternative or complementary PNT technologies and their impact, or linkage with other elements in the system, be it the environment or the ego-vehicle itself, plays an important role in supporting the certification process. Testing and validation also build trust in society, which affects adoption rates, and is an important component of each country's national strategy to fully implement CCAM. To this end, there are several initiatives, such as testbeds, developed by the academic community, research institutions and public authorities but also private companies that, while not widely promoted or advertised, are proving to be noteworthy and particularly relevant for moving forward in connected, cooperative and automated driving tasks.
The Navigation Innovation and Support Programme (NAVISP)
ESA’s Navigation Innovation and Support Programme is a key enabler for innovation and competitiveness and a strategic tool of ESA to support and develop the overall European POSITIONING, NAVIGATION and TIMING landscape. The main NAVISP objective is to facilitate and support the generation of innovative propositions that go beyond the exclusive use of satellite navigation signals and data and include the development of competitive industrial capabilities and the development of new, innovative technologies to complement, upgrade or replace current PNT technologies The NAVISP programme is structured according to three Elements:
- (Element 1: Innovation)
- Objectives: Perform feasibility studies, viability analysis, proof-of concept
- Element 2: Competitiveness
- Aims to maintain and improve the capabilities and competitiveness of the industry in the global PNT market
- Objectives: maintain and improve the competitiveness of the industry, facilitate the emergence of new actors in the PNT sector
- Funding: Activities are co-funded (50% for large companies, up to 80% for SMEs, 100%, up to 100% for research institutions)
- Element 3: Support Member States
- Aims to support national PNT strategies by providing support per country and possibly per domain for the development and promotion of products and services based on PNT systems to foster national and international cooperation
- Objectives: Identify and federate institutional demands, foster cooperation
- Funding: Activities under Element 3 are fully funded by ESA
This campaign addresses ideas submitted to Element2 and Element 3
For more information on the NAVISP programme please visit our website.
Reference Documents
RD1 Thematic Window PNT4CCAM
RD2 NAVISP Overview
