Editorial INSID E T HIS ISSU E: HAVEit at important conferences and congresses

Transcription

1 I SSUE 4 17 MARCH 2011 Editorial INSID E T HIS ISSU E: Welcome to the 4 th Newsletter of the HAVEit Consortium has been a very fruitful year as a key milestone has been successfully rolled up - the availability of first highly automated vehicle applications. The key achievements in HAVEit are summarized in this newsletter: The HAVEit Joint System is progressing with simulator study results and usability tests already becoming available and documented, as well as the first vehicle results. The safety architecture implementations are at the state of final testing. The highly automated vehicle applications are also progressing as planned and being finalized. Towards the Final Event demonstration, which will take place in Hällered, Sweden on June 21 st -22 nd, 2011, all systems, implementations and applications are integrated, tested and optimized. Information about the project, interesting news items and updates on the upcoming events can be found at the HAVEit website: Hoping to meet you all at the HAVEit Final Event in Sweden! HAVEit at important conferences and congresses Towards an intuitive Joint System: Simulator studies at DLR and WIVW and integration work in the FASCar Safety architecture implementation: Preliminary results Highly automated vehicle applications: Preliminary results Outlook to the HAVEit Final Event Imprint Project Coordinator Dr. Reiner Hoeger Continental Automotive GmbH (reiner.hoeger@continental-corporation.com) Project Managers Prof. Dr. Alfred Hoess Continental Automotive GmbH (alfred.hoess-ext@continental-corporation.com) Holger Zeng Continental Automotive GmbH (holger.zeng@continental-corporation.com) Dissemination Manager Dr. Angelos Amditis Institute of Communication and Computer Systems (ICCS) (a.amditis@iccs.gr) HAVEit Copyright

2 P AGE 2 I SSUE 4 HAVEit at important conferences and congresses 2010 has been a very productive year for the project allowing for a rich participation in various conferences and events through papers, special sessions, demonstration booths in order to properly disseminate the results of the project. ICT 2010, TRA 2010, the 2010 World ITS Congress in Busan, Korea, were excellent opportunities to showcase and promote our work. More precisely, the major disseminations events HAVEit had been present at were: TRA 2010: TRA 2010 was held at Brussels from June 7 th to June 10 th, 2010, focusing on "Sustaining Road Transport Mobility through innovation in Europe". HAVEit was present with a number of papers submitted and accepted depicting the advancements in highly automated driving and the work completed within the project for the HAVEit Joint System, the measures and countermeasures for impaired driver s state within highly automated driving, simulation results regarding optimal control strategy in hybrid vehicles. ICT 2010: The event ICT 2010: Digitally Driven took place at the Brussels EXPO from September 27 th to September 29 th, 2010 and attracted more than a thousand of people. The exhibition booth featuring HAVEit posters, videos and two demonstrators had been a huge success. More than 500 visitors had the chance to drive and get familiar with highly automated applications, trying out the Automated Queue Assistance application at a VOLVO truck simulator and the Joint System at a DLR car simulator, changing between highly and semi automated driving scenarios, while many others were introduced to HAVEit work. Many highly ranked members of the European Commission and the Industry passed by, had a ride at the simulators, watched the ICT 2010 Volvo simulator videos and got acquainted with our work, our goals and aspirations ITS World Congress: The annual ITS World Congress was carried out at Busan, Korea in late October HAVEit was present with a special session entitled Highly Automated Vehicles and applications for Intelligent Transport: Tools, Systems and Applications, where the main poles of HAVEit work were presented, starting from a speech about the envisioned HAVEit functionalities and the accomplishments. Then presentations followed by HAVEit members covering many aspects such as driving intelligence systems observing the environment and calculating optimal trajectories, assessing driver drowsiness and distraction, dynamic task repartition between the driver and the highly automated vehicle, integration and implementation issues. Papers coming from HAVEit partners concerning research carried within the Consortium were accepted and presented in a number of Conferences worldwide including AVEC 2010, AAET 2010, IV2010, Aachener Kolloquium as well as national conferences. HAVEit had made it to a number of magazines as well during the year: The Truck and Bus Builder, which is the International Newsletter of Commercial Vehicle Manufacturing Developments, through an article dedicated to the virtual co-driver system developments undergoing by Volvo Truck Corporation. The Volvo magazine On the Move : HAVEit appeared at the Volvo Customers Magazine "On the Move". Maria Bruce introduced the Active Green Driving concept developed in the HAVEit project. The TRAFFIC TECHNOLOGY INTERNATIONAL Magazine in January 2010: The article featured a detailed description of our project, its visions, goals and objectives, as well as an overview of the HAVEit technologies and applications.

3 HAVEit e-newsletter P AGE 3 Towards an intuitive Joint System: Simulator studies at DLR and WIVW and integration work in the FASCar Transition study at DLR The subproject 3000 in the HAVEit project is the horizontal subproject for human automation integration influencing the vertical subprojects and demonstrator vehicles of HAVEit. Over the last three years, experts from different EU countries have developed the generic principles of such a Joint System of driver and automation, have explored different options for the Human-Machine-Interface (HMI) in simulator studies, have built a generic prototype, and have aligned the HMI design of the different HAVEit demonstrators developed in the vertical subprojects of HAVEit. In autumn 2010 we conducted a simulator study in the motion based driving simulator at DLR. The study was set up to test and compare the four different automation transition concepts of the demonstrator vehicles and to further align these concepts. Automation transitions are the changes between the HAVEit automation levels Driver Assisted, Semi Automated and Highly Automated that can either be initiated by the driver or the automation. The transition concepts of the four demonstrators differed especially in their reactions to drivers input via the accelerator and brake pedal or the steering wheel. In total, 32 drivers participated in the study and drove one of the four demonstrators. For the study driving data, videos, interview protocols, and questionnaire data were recorded and analysed. The results showed that most of the drivers were able to build up a correct understanding about the transitions of the demonstrator that they tested. All four concepts were positively evaluated by the drivers. The data also revealed some usability problems that give valuable hints for improving the demonstrators. In December 2010 the HAVEit partners from SP3000 and SP5000 Transition study in the driving simulator at DLR came together for a further HMI Workshop at DLR. The partners first tested the four transition concepts in the simulator and discussed the results of the transition study and further ideas for alignment. The result of the final alignment of principles will be demonstrated during the HAVEit Final Event. Drowsiness and distraction studies at WIVW One task of the HAVEit Joint System is to assure that in case of an inattentive driver (meaning either drowsy or distracted) everything is done to bring him/her back into the loop. At WIVW we conducted driving simulator studies to validate a general interaction strategy for these use cases. A stepwise escalation strategy starts first with some warning messages, and if this turns out to be not successful results in a switchoff of the Highly Automated mode and the request to the driver to take over the driving task. The interactions are based on the outputs of the Driver State Assessment (DSA) component which is able to detect online different levels Test driver detected as attentive by the DSA Warning message issued in case a drowsy driver is detected means of direct (camera-based) and indirect (driving performance based) measures. To test the interaction in case of drowsiness in the driving simulator, 12 drivers drove about 2.5 hours each in a night-time scenario on the motorway.

4 P AGE 4 I SSUE 4 During the drive the drivers received warning messages or, in case of severe sleepiness, takeover requests by the HMI based on the real-time outputs of the DSA. Every 20 minutes and after each intervention the drivers rated their perceived drowsiness level and the adequateness of the messages. After the drive drivers judged their general acceptance of the interaction strategy as well as the used HMI. The analyses revealed that the interaction strategy was rated very positively. The drivers judged it as meaningful and useful, the HMI as very good to understand. Even the transition to Driver Assisted was perceived as meaningful and was not seen as domination by the system. The interventions turned out to have a slightly and shortly positive effect on driver s perceived drowsiness level although they were not Example of a test sequence during an integration week in Braunschweig able to make a sleepy driver awake again. However, the interventions were successful in preventing a drowsy driver from continuing driving and in persuading him to take a break. Integration weeks in Braunschweig For the technical implementation of the Joint System in the research vehicle FASCar and in the driving simulator the SP3000 partners from DRL, LCPC, INRIA, ICCS and WIVW met for several integration weeks in Braunschweig. During these weeks the software for the co-system was further developed, tuned and tested. The final Joint System will be presented during the HAVEit Final Event in June Safety architecture implementations: Preliminary results Subsequent to the first step in system validation by simulation (see previous article) the Joint system including the safe HAVEit architecture can be validated in vehicles. Three demonstrators have been built for this purpose. The following sections summarize the key developments and the achieved first highly automated functionalities. Extended Joint System demonstrator: Improved ergonomics based on steer-by-wire First system validation of this demonstrator focused on the use case emergency braking in highly automated mode during a Joint System Emergency braking use case integration meeting at DLR in Braunschweig. This use case is derived from the use case class Driving and detected obstacle that deals with an emergency situation triggered by a detected obstacle in front of the ego vehicle. The emergency interaction can be applied to all automation levels. During a validation scenario of this use case the reaction of the automation system in level highly automated has been tested. The demonstrator drives highly automated on the left lane of a twolane road at about 9 km/h (for safety reasons the speed was limited to 9 km/h). A team member suddenly holds an obstacle in front of the vehicle. In consequence, the automation level emergency is activated and an emergency brake is performed to avoid the collision. The validation procedure was carried out by verifying the reactions of the different system modules with respect to defined key parameters like response time, specific ranges and similar parameters. All modules have successfully passed the test. As illustrated in the figure on top of page 5, the ego vehicle is driving autonomously in automation level highly automated on the left lane (frame 1, 2). On the left road side there is an obstacle (frame 3) which suddenly moves into the lane directly in front of the vehicle (frame 4 at time 0.6s in the following figure). As shown in frame 5, the obstacle is detected and the automation level emergency is activated, because of the high criticality of the situation which could not be resolved by comfortable braking. Therefore, an automatic emergency brake procedure is performed and the vehicle comes to a complete stop (frame 6).

5 HAVEit e-newsletter P AGE 5 Driving and detected obstacle - emergency brake in highly automated mode x / m t / s 2 Object First Detection Track ID 304 Object first in lane of ego vehicle, Ego vehicle decelerates Ego vehicle standstill that the relative longitudinal velocity is decaying to zero, avoiding the collision with the obstacle. This is only one example of the use case validation experiments. Other use cases as described in the use case list were also validated with following a specified validation procedure. Some of these use cases will be presented during the HAVEit Final Event on the 21 st and 22 nd of June 2011 on Hällered proving ground in Sweden (near Gothenburg). Reduction of stopping distance: Brake-by-wire truck By replacing the existing brake system structure on heavy vehicles, which is based upon compressed air as energy source, with a fully Brake-by-Wire (BbW) system a significant improvement in braking performance and thereby vehicle safety will be achieved. v x / (m/s) t / s Driving and detected obstacle - emergency brake in highly automated mode: Relative distance and velocity of obstacle. The figure above shows the relative distance and velocity of the tracked obstacle that appears suddenly in front of the ego vehicle as determined by the data fusion module. It can be seen that the object is detected steadily while the ego vehicle decelerates (relative velocity is negative and finally it decreases to approximately zero). When an unexpected obstacle (a pedestrian for example) appears it usually comes from outside the road. The data fusion tracking component tracks the object even if this is outside of the road, but it doesn t report it to the other components. As soon as the object moves in the road it is included in the output of the data fusion and as consequence the Co-Pilot and control components can take proper action. As shown in Figure 2, immediately after the object has entered the lane, the automation level emergency is activated and an automatic braking is performed, which can be observed by the fact HAVEit Brake-by-Wire (BbW) truck demonstrator Brake-by-Wire wheel-end

6 joint system P AGE 6 I SSUE 4 The brake torque on each wheelend can be individually monitored in a very accurate way which allows a better utilization of the existing tire/road friction conditions. In particular in emergency brake situations and during traction control on low friction conditions significant improvement can be achieved compared to a pneumatic brake system of today. Result of vehicle tests has shown a shortage of the braking distance in emergency brake situations by 15% in average on different road conditions. This result comes very close to what is physically possible to achieve from a brake system in terms of performance. During normal braking applications the quick response time of a Brake-by-Wire (BbW) system gives the driver a much better pedal feeling and a more precise control of the vehicle in general. In order to reduce the external power demand to perform a brake application the brake mechanism design is based upon the principle of self enforcement, using the rotational energy from the wheel to create clamp force between pad and disc. This enables to continue using a 24 V power supply system also for future BbW systems. One of the objectives of HAVEit is to show that the BbW system using Electro Mechanical Brakes respects all the appropriate performance requirements specified by the brake regulation (ECE-R13) under both normal and fault conditions. This work is performed together with TÜV Nord in Germany and will be finalized with a series of tests during the last quarter of the project proving the system compliance against the brake regulation. At the HAVEit Final Event the BbW Truck will be demonstrated both concerning its braking performance and its system safety in comparison with a standard truck of today. Architecture migration demonstrator: HAVEit implementation using automotive ECUs The Architecture Migration Demonstrator is intended to show a migration path of HAVEit technology towards mass production. Instead of realizing the HAVEit architecture Driver interface components Command layer Execution layer Driver Driver monitoring Driver states assessment Steering actuator HMI Mode selection unit automation level Braking actuator The 4 layers of the HAVEit architecture using prototyping equipment, the goal of this demonstrator was to build up the Joint System part of the vehicle with automotive standard embedded electronics: The Chassis and Safety Controller (CSC) by Continental. There were three major challenges: Bring the mostly PC developed HAVEit applications to run on the embedded CSC platform Adapt functionality, bus communication and network structure to cope with the relatively small bandwidth of a CAN bus Application Layer Software Component (SW-C) AUTOSAR Runtime Environment (RTE) Communication Services AUTOSAR COM (Com) PDU Router (PduR) CAN Transport Protocol (CanTp) Communication Hardware Abstraction CAN Interface (CanIf) Communication Drivers CAN Driver (Can) Environment sensors Command generation and plausiblization Diagnostic Communication Manager (Dcm) CSC communication stack Drivetrain control Sensor data fusion Co-Pilot motion control vector Engine actuator Vehicle sensors Gearbox actuator Perception layer Set up the communication network compliant with the AUTO- SAR methodology In addition, the common HAVEit architecture had to remain largely unchanged. The further development of the architecture has been a time consuming process, since thousands of signals had to be defined, checked and managed. Special software tools were developed to enable at least a partly automated processing of the extensive architectural data. The base vehicle, a Volkswagen Passat, has been equipped with actuators controlled through CAN bus interfaces. Longitudinal and lateral controllers were developed to accept the HAVEit Motion Control Vector and to actually drive the car. A radar and a mono camera by Continental allow lateral and longitudinal automation within one lane. The HAVEit Joint System has been deployed on six CSCs connected by four CAN buses, according to the HAVEit common architecture, which has been set up using the AUTOSAR methodology. HAVEit functions developed within the sub-project SP3000 such as the co-pilot and mode selection unit were adapted where needed and transferred to the embedded controller of the CSC. All of them are running successfully, showing that the Joint System can operate on a today s electronics platform compliant with automotive standards.

7 HAVEit e-newsletter P AGE 7 Highly automated vehicle applications for use on public roads: Preliminary results The development and validation of HAVEit applications aims at improved traffic safety and efficiency as well as for fuel and pollution reduction. For each of the demonstrators at least a basic version of the Joint System has been implemented, depending on the ADAS configuration. Additionally, the HMI of the demonstrators needed to be adapted to the needs of the Joint System. Assisting in Roadworks and Congestion in Highly Automated Mode The Automated Assistance in Roadworks and Congestion (ARC) application is safety and comfort oriented. It is fundamentally intended to support the driver in challenging scenarios (so-called overload situations) like driving in narrow lanes of roadwork areas with lots of vehicles driving closely beside. In such complex scenarios a high quality in information about all relevant surrounding objects is needed to give the driver a comprehensive assistance. Continental equipped its demonstrator with several radar sensors and a multifunctional camera. The sensors are all mass production systems just enhanced with additional computing power and improved algorithms. Gathered measurements are fused on different levels from object based fusion down to grid fusion for the reliable recognition of standing obstacles like beacons and guide walls. Based on all recognized objects, a save guidance through roadworks and congestions is possible. Several assistance functions are running on the demonstrator at the same time. Their activation state is handled by the Mode Selection and Arbitration Unit, which s development is one of the main focuses of the HAVEit project. The complete system is already running and under intense testing for the HAVEit Final Event in June For the assistance in roadwork areas, existing functions had to be enhanced and new ones had to be developed. One example of those function is the virtual wall algorithm. It provides a loose guidance in the centre of the lane and a high counter torque close to the guide walls. In combination with Lane Keeping Assistance, an assistance system helping the driver to center the car in the lane by low torque support in the steering, the lateral control mode for Highly Automated is reached. Resulting from the possibility of hands-off driving in highly automated mode, Combination of virtual Wall (vwall) and lane keeping assistance system (LKAS) the system was enhanced to handle additional use cases, e.g. curve overspeed prevention and automated deceleration if the driver is inattentive. With Lane Departure Warning, Heading Control, virtual Wall and Lane Keeping Assistance four lateral control modes are available. With the three longitudinal control modes Full Speed Range ACC, Forward Collision Warning and Emergency Brake Assistance 12 (4*3) different control modes are possible. With this high amount of existing functions it gets clear that a Mode Selection and Arbitration Unit is needed to gain any usability for the Sensor field of view (red: Far and medium distance radar sensor, green: Front camera, blue: Radar based blind spot and lane change assistance sensors) Automated Assistence in Roadworks and Congestion (ARC) instrument cluster driver. For further enhancement of the usability, the modes can be switched by the existing ACC (Adaptive Cruise Control) stroke. Only for demonstrations, an additional touch screen is integrated in the vehicle.

8 P AGE 8 I SSUE 4 ARC example scenario: Vehicle enters the roadwork area and has to slow down due to a preceding vehicle. Lateral assistance is provided continuously despite the dummy vehicle to the right. Automated Queue Assistance The main goal of Automated Queue Assistance (AQuA) is to relieve the driver of the monotonous task of driving in low-speed congested traffic. Using data from a number of environment sensors the system can create a view of the equipped vehicle s surrounding. Based on this information the vehicle can be controlled to follow its lane and to adapt the speed to the preceding vehicle. In close cooperation with other work packages there has also been a big focus on creating a common and intuitive Human-Machine-Interface (HMI) to interact with the driver in an optimal way. There are a number of preconditions that have to be met before it is possible to activate AQuA. The vehicle has to be travelling on a motorway, the speed has to be below 30 km/h, there needs to be a target vehicle in front and the road has to have detectable lane markings. Fulfilling all those conditions strongly indicates that the vehicle is on a driveable path with good infrastructure and all data needed for the control algorithm is available. To be able to drive autonomously it is of great importance that the algorithm has a correct and unambiguous view of the surrounding environment. To achieve this several sensors are used including laser scanners, radars, camera, e- horizon and V2V communication. The sensors all provide data which needs to be combined in an optimal way. This is done in the sensor data fusion algorithm which weights the different measurements together and sends the output to the control algorithm. As mentioned above the algorithm controls the vehicle both in the longitudinal and lateral direction. Longitudinally the vehicle is controlled to keep a desired distance to the vehicle in front. This is achieved by measuring the distance and speed of the target; this input is then used by the algorithm to calculate a suitable engine torque or brake demand. Laterally the aim is to keep the vehicle in the centre of its driving lane. A sensor measures the offset from lane centre, heading deviation between vehicle and lane as well as lane curvature. Based on the measured data the control algorithm can calculate appropriate steering commands. When supporting the driver by autonomously handling driving tasks or parts of tasks it is fundamental to interact with the driver in a clear way. The drivers always need to know what input is ex- AQuA demonstrator truck pected from their side. Failing in communication with the driver can lead to critical situations. A big part of the HAVEit project has therefore focused on the Human-Machine- Interface and how to interact with the driver in an optimal way. This work has resulted in an application which always informs the driver of the systems current state and sends commands when interaction from the driver is necessary. The critical situation when a driver does not respond in the expected way to a command has been the focus of many discussions and is now handled by braking down the vehicle to a full stop. As the latest achievement the AQuA demonstrator vehicle has been equipped with all components and a test of the first functionality has been performed. The results are in general according to plan. All sensors are mounted and working. The sensor data fusion algorithm performs quite well, but the software is continuously improved and updated. The control algorithms work well with correct input data but will be tuned further. The performance of the sensors, sensor data fusion and control is tightly linked together and further evaluation and improvement will be done during the upcoming test periods. The HMI application has been finalized and only minor updates if any should be needed. The application will be further evaluated during last phase of the project.

9 HAVEit e-newsletter P AGE 9 Temporary Auto-Pilot The Temporary Auto Pilot (TAP) is fundamentally intended to support the driver in monotonous traffic situations like traffic jams or monotonous long distance driving from A to B where the driver can experience work underload which can lead to a lack of focus and increased accident risk. The TAP is a passenger car application which will support the driver on motorways and motorway similar roads with different driving context-dependent levels of automation in longitudinal and lateral control of the vehicle at speeds between 0 and 130 km/h. The automation spectrum is as follows: Highly-Automated: hands-off driving, automated longitudinal and lateral control (lane keeping at the center of the driving lane) Semi-Automated: hands-on driving, automated longitudinal control (ACC) Assisted driving: hands-on driving, assisted lateral control (LKAS) Safety function: emergency braking This guarantees that the driver gets the best possible support available. This can contribute to traffic safety. The TAP demonstrator has been equipped with the following environmental sensors: series front camera for the detection of lane markings series front long range radar for the detection of vehicles series ultrasonic sensors for the near free area and pedestrians detection prototype electronic Horizon for the additional lane data and traffic road signs 3 prototype front laser scanners for the detection of obstacles like guardrails driver monitoring sensors: prototype camera for driver state monitoring, mounted in the central instrumental panel and prototype capacitive sensor in the steering wheel for hands on/off detection ultrasonic sensors 77 GHz radar laser scanners Temporary Auto-Pilot (TAP) demonstrator 77GHz radar mono camera E-horizon traffic signs mono camera lane markings All sensor data are fused together in an adequate way in the Sensor Data Fusion Module, which contains 5 components as Ego Fusion, Object Fusion, Lane Fusion, Occupancy Grid and Map Matching. The Sensor Data Fusion delivers a robust and unambiguous view of the surrounding environment to the applications (here, the longitudinal and lateral controller) like relevant driver monitoring camera laser scanners vehicles, pedestrians Temporary Auto-Pilot (TAP) sensor coverage TAP instrument cluster with integrated driver monitoring system E-Horizon ultrasonic sensors vehicles, pedestrians object data, lane data and the TAP vehicle s dynamics. The interaction between the driver and the system is successfully performed via an intuitive Human Machine Interface from operating components through dedicated warning strategies until the central display concept. A transparent functional integration of the Pilot function is harmonized together with established driver assistance systems. While the hardware components are implemented as serial or prototype devices, the software components are for the most part developed at Volkswagen Group Research and run in different operating systems like embedded Windows and RT-Linux. All developed software have been carefully tested by Hardware- and Software-In-the-Loop methods.

10 P AGE 10 I SSUE 4 Active Green Driving The main goal of Active Green Driving is to reduce the fuel consumption in a heavy hybrid demonstrator vehicle by using an e-horizon system enhanced with environment sensors (laser scanners and colour camera). This is accomplished by two quite different strategies, both relying on the continuous prediction of the vehicle speed. The first strategy is a fuel optimal powertrain strategy, where the overall control objectives are, for any moment in time, to decide the power split between the electrical machine and the internal combustion engine, the switching on and off of the internal combustion engine, and the selection of gear by considering powertrain efficiency at selected revolution speeds and torques. To accelerate the hybrid vehicle, the driver effectively requests a torque to the wheels. The requested torque has to be realized by the powertrain actuators. In a hybrid vehicle, there is more flexibility, compared to a conventional vehicle, to realize this torque. The demonstrator vehicle has a parallel powertrain which means the power to the wheels can at any moment be a mix of power from the combustion engine and power from the electrical machine. When the driver brakes, kinetic energy is recuperated by operating the electrical machine as a generator and store the electrical energy in the high voltage battery. The second strategy is a driver support interface to give driving recommendations, in certain defined situations, using both graphical and textual information as well as haptic feedback in the accelerator pedal. The strategy also helps the driver to plan the driving by showing relevant information about the future driving environment. The e-horizon system provides both strategies with information about future driving conditions several minutes ahead of the vehicle. The information from this system is of static nature, which means that it does not change from time to time during the same route. Typical information provided is speed limits of the road and the location of, for AGD hybrid bus Driver Coaching HMI instance, traffic lights, roundabouts and altitude. The other two sensor systems, the laser scanner and the colour camera, give environmental information about future driving conditions a few seconds ahead of the vehicle, like distance, velocity and acceleration of a preceding vehicle and current status of traffic lights. All sensors combined will provide the demonstration vehicle, a Volvo city bus, with information on the long term static road conditions as well as short term dynamic traffic environment in front of the bus. The driver is in charge of acceleration and deceleration. The first strategy simply accepts the driver s behaviour and adjusts the powertrain accordingly, and the second strategy tries to influence the driver by giving fuel saving advice. The two strategies work independent of each other. So far, both strategies as well as the e-horizon and sensor systems have been implemented in the demonstration vehicle and are currently undergoing further testing and trimming to improve the functionality. First tests have shown some promising results which will be quantified in more depth in the upcoming period. Active Green Driving also cooperates with AQuA in the effort to use vehicle-to-vehicle (V2V) communications devices, developed by EFKON, to transmit CAN data between both demonstration vehicles. The V2V modules use infrared light as a transmission medium. This requires direct line of sight and optical alignment of the units before communication can occur.

11 HAVEit e-newsletter P AGE 11 Outlook to the HAVEit Final Event Date and location The HAVEit Final Event will take place in Sweden on June 21st and 22nd, 2011 Both days will be organised almost identical: The registration and presentation part will take place in First Hotel Grand in Borås. The exhibition and vehicle demonstration part will be organised at the Volvo Proving Ground Hällered. Simultaneously to live demonstrations of the HAVEit vehicles in relevant scenarios, instructive exhibits will be shown, e.g. simulators, videos, posters. A bus shuttle service will care for the transfer of guests between hotel and proving ground. Expression of interest The final programme and further information will be provided via a dedicated website. To receive your personal invitation to the HAVEit Final Event and your individual login to this site, please express your interest and send your contact details to Ms Silvia Hilpert, registration@haveit-eu.net Online registration for the event using your individual access code is mandatory to get access to conference rooms, shuttle buses, exhibition and demonstration vehicles. HAVEit systems interact with the driver by visual, acoustic and haptic feedback. Here, a recommendation to initiate a highly automated lane change is displayed. First Hotel Grand Borås Volvo Proving Ground Hällered Preliminary Programme Registration in First Hotel Grand Opening Session: Views on highly automated driving Break HAVEit Session HAVEit - from the idea over the Joint System to highly automated vehicle applications to improve safety and environmental friendliness Lunch break Transfer to Volvo Proving Ground Hällered Exhibition and live demonstrations Feel Highly Automated Driving! Transfer to First Hotel Grand

12 Consortium (alphabetical order; beneficiaries only, 5 Third Parties in addition): Duration: February 01, July 31, 2011 Total cost: 28 M, 17 M EC contribution Programme: 7th FW, ICT European Commission Scientific Officer: Francisco Ferreira DG Information Society and Media Unit G4 - ICT for Transport Francisco.Ferreira@ec.europa.eu