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In this paper, a distributed consensus control approach for vehicular platooning systems is proposed. In formalizing the underlying consensus problem, a realistic vehicle dynamics model is considered and a velocity-dependent spacing policy between two consecutive vehicles is realized. As a particular case, the approach allows to consider bidirectional vehicle interaction, which improves the cohesion between vehicles in the platoon. Exponential stability of the platoon dynamics is evaluated, also in the challenging scenario in which a limitation on the velocity of one of the vehicles in the platoon is introduced. The theoretical results are experimentally validated using a three-vehicle platoon consisting of (longitudinally) automated vehicles equipped with wireless intervehicle communication and radar-based sensing.

Creating a driving cycle (DC) for the design and validation of new vehicles is an important step that will influence the efficiency, functionality and performance of the final systems. In this work, a DC synthesis method is introduced, based on multi-dimensional Markov Chain, where both the velocity and road slope are investigated. Particularly, improvements on the DC synthesis method are proposed, to reach a more realistic slope profile and more accurate fuel consumption and CO2 emission estimates. The effects of using synthesized DCs on fuel consumption are investigated considering three different vehicle models: conventional ICE, and full hybrid and mild hybrid electric vehicles. Results show that short but representative synthetic DCs will results in more realistic fuel consumption estimates (e.g. in the 5%-10% range) and in much faster simulations. Using the results of this proposed method also eliminates the need to use very simplified DCs, as the New European Driving Cycle(NEDC), or long, measured DCs.

We introduce a new way to look at the combined lateral and longitudinal control problem for platooning vehicles by studying these problems separately. The lateral control problem is approached as a path following problem in the spatial domain: based on the path of the preceding vehicle we determine a path for the following vehicle which converges to the given path of its predecessor. In particular if the following vehicle happens to be on the path of its predecessor, the generated path of the follower equals the path of its predecessor. This approach not only overcomes the problem of corner cutting, but also achieves appropriate following behavior in case of large initial errors. As a by-product of solving the lateral control problem, we obtain a mapping from the path of the follower to the path of its predecessor. Using this mapping we can consider the longitudinal control problem as controlling two points on the same path towards a required inter-vehicle distance, which is comparable to CACC, i.e., the problem of controlling two points on a straight line towards a required inter-vehicle distance. We illustrate our approach by means of simulation. We introduce a new way to look at the combined lateral and longitudinal control problem for platooning vehicles by studying these problems separately. The lateral control problem is approached as a path following problem in the spatial domain: based on the path of the preceding vehicle we determine a path for the following vehicle which converges to the given path of its predecessor. In particular if the following vehicle happens to be on the path of its predecessor, the generated path of the follower equals the path of its predecessor. This approach not only overcomes the problem of corner cutting, but also achieves appropriate following behavior in case of large initial errors. As a by-product of solving the lateral control problem, we obtain a mapping from the path of the follower to the path of its predecessor. Using this mapping we can consider the longitudinal control problem as controlling two points on the same path towards a required inter-vehicle distance, which is comparable to CACC, i.e., the problem of controlling two points on a straight line towards a required inter-vehicle distance. We illustrate our approach by means of simulation.

In this paper a Vehicle State Estimator is developed and validated on experimental data from a 2012 Toyota Prius. The estimator is capable of estimating both planar vehicle velocities and the tyre-road friction parameter. Emphasis is placed on the comparison of the commonly used Extended Kalman Filter and a novel application of the State Dependent Riccati Equation technique. The State Dependent Riccati based estimator relies on a factorization compared to linearization in the case of the Extended Kalman Filter. This factorization is non-unique, therefore the construction of this factorization, is also presented. A comparison is for both estimators is presented for experimental data. For estimation of the tyre-road friction parameter, simulations are used, due to absence of a reference value in the experimental set-up.

Nowadays, there is an increasing societal demand for smart mobility solutions which can increase the throughput, comfort, and safety of driving on a road. As one of these solutions, vehicle following technologies like cooperative adaptive cruise control (CACC) are introduced. with the help of vehicle-to-vehicle (V2V) communication, CACC can reduce the safe minimal inter-vehicular distance. Additionally, sharing the vehicle intentions through V2V, enables multi-vehicle maneuvers to be cooperatively executable. In this paper, using the concept of artificial potential fields, a longitudinal control scheme for performing a cooperative merging maneuver will be suggested. Artificial potential fields are powerful enough for modeling and solving such a complex problem, where in addition to vehicle following other objectives such as merging should be addressed. The designed algorithms for vehicle cooperative maneuvering are verified through simulations.

The optimal design of a hybrid electric vehicle (HEV) can be formulated as a multiobjective optimization problem that spreads over multiple levels (technology, topology, size, and control). In the last decade, studies have shown that by integrating these optimization levels, fuel benefits are obtained, which go beyond the results achieved with solely optimal control for a given topology. Due to the large number of variables for optimization, their diversity, and the nonlinear and multiobjective nature of the problem, a variety of methodologies have been developed. This paper presents a comprehensive analysis of the various methodologies developed and identifies challenges for future research. Starting from a general description of the problem, with examples found in the literature, we categorize the types of optimization problems and methods used. To offer a complete analysis, we broaden the scope of the search to several sectors of transport, such as naval or ground.

In the EU AUTOPILOT project, IoT is brought into the automotive world to transform connected vehicles — moving ‘things’ in the IoT ecosystem — into highly and fully automated vehicles. One of the considered use cases is the platooning use case, which is being tested at the Brainport pilot site in the Netherlands. The aim of this use case is to demonstrate the potential of IoT to improve vehicular platooning. To achieve this, several services and advanced vehicle-to-everything (V2X) connectivity technologies have been developed and tested. This paper describes theses services and technologies, as well as evaluation results of the pilot tests.

In the EU AUTOPILOT project, IoT is brought into the automotive world to transform connected vehicles — moving ‘things’ in the IoT ecosystem — into highly and fully automated vehicles. One of the considered use cases is the platooning use case, which is being tested at the Brainport pilot site in the Netherlands. The aim of this use case is to demonstrate the potential of IoT to improve vehicular platooning. To achieve this, several services and advanced vehicle-to-everything (V2X) connectivity technologies have been developed and tested. This paper describes theses services and technologies, as well as evaluation results of the pilot tests.

It’s hard to imagine life without smartphones. In many ways, they make our lives easier, more convenient and more productive. But when it comes to smartphone usage while driving, it is clear that sensible solutions are needed to make roads safer for us all.

It’s hard to imagine life without smartphones. In many ways, they make our lives easier, more convenient and more productive. But when it comes to smartphone usage while driving, it is clear that sensible solutions are needed to make roads safer for us all.

Cooperative Adaptive Cruise Control (CACC) employs wireless intervehicle communication to allow for automatic vehicle following at small intervehicle distances while guaranteeing string stability. Inherent to the CACC concept, however, is its vulnerability to communication impairments, among which latency of the wireless link, which compromise string stability and, hence, safety. To investigate the sensitivity of the string stability property with respect to communication latency, two controllers are developed by means of H8 controller synthesis, employing a one-vehicle look-ahead and a two-vehicle look-ahead communication topology, respectively. The string stability properties of the controlled vehicle platoon are investigated, based on which it is proposed to switch from one-to two-vehicle look-ahead when the latency exceeds a certain threshold, thereby creating robustness against increasing communication delay by retaining string stability at the lowest possible time gap.

Lateral vehicle control is an essential part for many automated and cooperative driving applications. Lane keeping and vehicle following are typical modes of such control system. The aim of this paper is to develop a generic lateral controller that can handle these different modes. Based on the available measurements, either path or single point preview information is used in the feedback loop of the controller, while controller parameters and adaptive gains are unaffected. The paper contains theoretical analysis and discusses the results of simulations and vehicle experiments.

This paper addresses safety indicators for truck platooning at short inter-vehicle distances (with a time gap of 0.5 s). The aim of a safety indicator is to determine the correct moment for initiating a Collision Avoidance brake action to prevent a collision with the preceding truck in threatening situations. Three safety indicators are selected for an evaluation: the intended acceleration of the preceding truck, which is shared via Vehicle-to-Vehicle (V2V) communication, the Brake Threat Number (BTN — based on simple vehicle models and an emergency brake assumption of the lead), and the Time-To-Collision (TTC — based on a constant velocity assumption). The latter two do not rely on V2V communication, but are obtained via on-board signals. Requirements for the amount of false negatives (missing a threatening situation) and the false positives (identifying a safe situation as threatening) are derived from a functional safety perspective. To find thresholds for the safety indicators that minimize the false negative rate, emergency brake tests are used. To evaluate the number of false positives, a set of data of two trucks driving in a platoon at 0.5 s at mixed-traffic highways in Belgium and the Netherlands, collected during 8 hours of automated driving in a platoon, is used. The results indicate that the communicated intended acceleration of the preceding truck might be able to distinguish safe and threatening situations in a vehicle platoon. Furthermore, for situations without V2V, both the BTN and the TTC are not capable to distinguish between threatening and safe situations. The amount of false positives found in the safe driving data-set does not fulfill the requirements derived from functional safety perspective.

This paper presents a multi-layer approach to Cooperative Adaptive Cruise Control (CACC) to improve the platoon cohesion subject to limited vehicle actuation capabilities. The objective of the design is to guarantee that the vehicles in the platoon keep their desired relative position, while maintaining desirable platoon properties in terms of disturbance attenuation. To this end, a multi-layered control architecture is proposed. On the lower layer, a unidirectional CACC is employed, involving information exchange in upstream direction. On the upper layer, a coordination variable is exchanged from each vehicle towards its direct preceding vehicle, thus yielding downstream information exchange. As a result, the leading vehicle is aware of the capabilities of the following vehicles, and therefore, is able to adapt its motion, if needed. Consequently, cohesion of a heterogeneous platoon is guaranteed, even in the case of physical limitations, like engine power limits. The developed technique is verified through simulations and experiments.

Introduction of automated driving increases complexity of automotive systems. As a result, architecture design becomes a major concern for ensuring non-functional requirements such as safety, and modifiability. In the ISO 26262 standard, architecture patterns are recommended for system development. However, the existing architecture patterns may not be able to answer requirements of automated driving completely. When applying these patterns in the automated driving context, modification and analysis of these patterns are needed. In this paper, we present a novel architecture pattern for safety criticalautomated driving functions. In addition, we propose a generic approach to compare our pattern with a number of existing ones. The comparison results can be used as a basis for project specific architectural decisions. Our Safety Channel pattern is validated by its implementation for a real-life truck platooning application.

Cooperative adaptive cruise control (CACC) allows for short-distance automatic vehicle following using intervehicle wireless communication in addition to onboard sensors, thereby potentially improving road throughput. In order to fulfill performance, safety, and comfort requirements, a CACC-equipped vehicle platoon should be string stable, attenuating the effect of disturbances along the vehicle string. Therefore, a controller design method is developed that allows for explicit inclusion of the string stability requirement in the controller synthesis specifications. To this end, the notion of string stability is introduced first, and conditions for cal L2 string stability of linear systems are presented that motivate the development of an H controller synthesis approach for string stability. The potential of this approach is illustrated by its application to the design of controllers for CACC for one-and two-vehicle look-ahead communication topologies. As a result, cal L2 string-stable platooning strategies are obtained in both cases, also revealing that the two-vehicle look-ahead topology is particularly effective at a larger communication delay. Finally, the results are experimentally validated using a platoon of three passenger vehicles, illustrating the practical feasibility of this approach. © 2013 IEEE.

In this paper, we consider a Cooperative Adaptive Cruise Control (CACC) system, which regulates intervehicle distances in a vehicle string, for achieving improved traffic flow stability and throughput. Improved performance can be achieved by utilizing information exchange between vehicles through wireless communication in addition to local sensor measurements. However, wireless communication introduces network-induced imperfections, such as transmission delays, due to the limited bandwidth of the network and the fact that multiple nodes are sharing the same medium. Therefore, we approach the design of a CACC system from a Networked Control System (NCS) perspective and present an NCS modeling framework that incorporates the effect of sampling, hold, and network delays that occur due to wireless communication and sampled-data implementation of the CACC controller over this wireless link. Based on this network-aware modeling approach, we develop a technique to study the so-called string stability property of the string, in which vehicles are interconnected by a vehicle following control law and a constant time headway spacing policy. This analysis technique can be used to investigate tradeoffs between CACC performance (string stability) and network specifications (such as delays), which are essential in the multidisciplinary design of CACC controllers. Finally, we demonstrate the validity of the presented framework in practice by experiments performed with CACC-equipped prototype vehicles. cop. 2014 IEEE.

This paper addresses safety indicators for truck platooning at short inter-vehicle distances (with a time gap of 0.5 s). The aim of a safety indicator is to determine the correct moment for initiating a Collision Avoidance brake action to prevent a collision with the preceding truck in threatening situations. Three safety indicators are selected for an evaluation: The intended acceleration of the preceding truck, which is shared via Vehicle-To-Vehicle (V2V) communication, the Brake Threat Number (BTN-based on simple vehicle models and an emergency brake assumption of the lead), and the Time-To-Collision (TTC-based on a constant velocity assumption). The latter two do not rely on V2V communication, but are obtained via on-board signals. Requirements for the amount of false negatives (missing a threatening situation) and the false positives (identifying a safe situation as threatening) are derived from a functional safety perspective. To find thresholds for the safety indicators that minimize the false negative rate, emergency brake tests are used. To evaluate the number of false positives, a set of data of two trucks driving in a platoon at 0.5 s at mixed-Traffic highways in Belgium and the Netherlands, collected during 8 hours of automated driving in a platoon, is used. The results indicate that the communicated intended acceleration of the preceding truck might be able to distinguish safe and threatening situations in a vehicle platoon. Furthermore, for situations without V2V, both the BTN and the TTC are not capable to distinguish between threatening and safe situations. The amount of false positives found in the safe driving data-set does not fulfill the requirements derived from functional safety perspective.

In this paper a Vehicle State Estimator is developed and validated on experimental data from a 2012 Toyota Prius. The estimator is capable of estimating both planar vehicle velocities and the tyre-road friction parameter. Emphasis is placed on the comparison of the commonly used Extended Kalman Filter and a novel application of the State Dependent Riccati Equation technique. The State Dependent Riccati based estimator relies on a factorization compared to linearization in the case of the Extended Kalman Filter. This factorization is non-unique, therefore the construction of this factorization, is also presented. A comparison is for both estimators is presented for experimental data. For estimation of the tyre-road friction parameter, simulations are used, due to absence of a reference value in the experimental set-up.

Path planning of an autonomous vehicle as a non-holonomic system is an essential part for many automated driving applications. Parking a car into a parking lot and maneuvering it through a narrow corridor would be a common driving scenarios in an urban environment. In this study a hybrid approach for dynamic path planning is presented which deals with the limited degrees of freedom of a non-holonomic system, as well as the real-time constraints and limited computational power. Furthermore, it takes into account ride comfort of the passenger by generating smooth path. The proposed method has been evaluated in simulation environment and is implemented and tested on a Toyota Prius test vehicle with an active steering system.

Lateral vehicle control is an essential part for many automated and cooperative driving applications. Lane keeping and vehicle following are typical modes of such control system. The aim of this paper is to develop a generic lateral controller that can handle these different modes. Based on the available measurements, either path or single point preview information is used in the feedback loop of the controller, while controller parameters and adaptive gains are unaffected. The paper contains theoretical analysis and discusses the results of simulations and vehicle experiments.

Introduction of automated driving increases complexity of automotive systems. As a result, architecture design becomes a major concern for ensuring non-functional requirements such as safety, and modifiability. In the ISO 26262 standard, architecture patterns are recommended for system development. However, the existing architecture patterns may not be able to answer requirements of automated driving completely. When applying these patterns in the automated driving context, modification and analysis of these patterns are needed. In this paper, we present a novel architecture pattern for safety critical automated driving functions. In addition, we propose a generic approach to compare our pattern with a number of existing ones. The comparison results can be used as a basis for project specific architectural decisions. Our Safety Channel pattern is validated by its implementation for a real-life truck platooning application.

More and more Advanced Driver Assistance Systems (ADAS) are entering the market for improving both safety and comfort by assisting the driver with their driving task. An important aspect in developing future ADAS and Automated Driving Systems (ADS) is testing and validation. Validating the failure rate of an ADS requires so many operational hours that testing in real time is almost impossible. One way to reduce this test load is virtual testing or hardware in-The-loop testing. The major challenge is to create realistic test cases that closely resemble the situation on the road. We present a way to use data of naturalistic driving to generate test cases for Monte-Carlo simulations of ADS. Because real-life data is used, the assessment allows to draw conclusions on how the ADS would perform in real traffic. The method, developed in EU AdaptIVe, is demonstrated by testing an Adaptive Cruise Control (ACC) system in scenarios where the predecessor of the ego vehicle is braking. We show that the probability of the occurrence of unsafe situations with the ACC system can be accurately and efficiently determined.

Cooperative Adaptive Cruise Control (CACC) improves road throughput by employing intervehicle wireless communications. The inherent communication time delay significantly limits the minimum inter-vehicle distance in view of string stability. Applying a Padé approximation leads to a model with a rational transfer function, which allows many control methods to compensate for this delay to a certain extent. Our objective is to find the lowest possible order of Padé approximations, which is sufficiently accurate in view of string stability. To this end, the minimum string-stable time gaps are chosen as the main criterion against which the quality of the Pad´e approximations is measured. The results indicate that it is feasible to apply a 2nd-order Padé approximation in the given CACC system.

More and more Advanced Driver Assistance Systems (ADAS) are entering the market for improving both safety and comfort by assisting the driver with their driving task. An important aspect in developing future ADAS and Automated Driving Systems (ADS) is testing and validation. Validating the failure rate of an ADS requires so many operational hours that testing in real time is almost impossible. One way to reduce this test load is virtual testing or hardware in-The-loop testing. The major challenge is to create realistic test cases that closely resemble the situation on the road. We present a way to use data of naturalistic driving to generate test cases for Monte-Carlo simulations of ADS. Because real-life data is used, the assessment allows to draw conclusions on how the ADS would perform in real traffic. The method, developed in EU AdaptIVe, is demonstrated by testing an Adaptive Cruise Control (ACC) system in scenarios where the predecessor of the ego vehicle is braking. We show that the probability of the occurrence of unsafe situations with the ACC system can be accurately and efficiently determined.

This paper presents a multi-layer approach to Cooperative Adaptive Cruise Control (CACC) to improve the platoon cohesion subject to limited vehicle actuation capabilities. The objective of the design is to guarantee that the vehicles in the platoon keep their desired relative position, while maintaining desirable platoon properties in terms of disturbance attenuation. To this end, a multi-layered control architecture is proposed. On the lower layer, a unidirectional CACC is employed, involving information exchange in upstream direction. On the upper layer, a coordination variable is exchanged from each vehicle towards its direct preceding vehicle, thus yielding downstream information exchange. As a result, the leading vehicle is aware of the capabilities of the following vehicles, and therefore, is able to adapt its motion, if needed. Consequently, cohesion of a heterogeneous platoon is guaranteed, even in the case of physical limitations, like engine power limits. The developed technique is verified through simulations and experiments.

We introduce a new way to look at the combined lateral and longitudinal control problem for platooning vehicles by studying these problems separately. The lateral control problem is approached as a path following problem in the spatial domain: based on the path of the preceding vehicle we determine a path for the following vehicle which converges to the given path of its predecessor. In particular if the following vehicle happens to be on the path of its predecessor, the generated path of the follower equals the path of its predecessor. This approach not only overcomes the problem of corner cutting, but also achieves appropriate following behavior in case of large initial errors. As a by-product of solving the lateral control problem, we obtain a mapping from the path of the follower to the path of its predecessor. Using this mapping we can consider the longitudinal control problem as controlling two points on the same path towards a required inter-vehicle distance, which is comparable to CACC, i.e., the problem of controlling two points on a straight line towards a required inter-vehicle distance. We illustrate our approach by means of simulation.

Nowadays, there is an increasing societal demand for smart mobility solutions which can increase the throughput, comfort, and safety of driving on a road. As one of these solutions, vehicle following technologies like cooperative adaptive cruise control (CACC) are introduced. with the help of vehicle-to-vehicle (V2V) communication, CACC can reduce the safe minimal inter-vehicular distance. Additionally, sharing the vehicle intentions through V2V, enables multi-vehicle maneuvers to be cooperatively executable. In this paper, using the concept of artificial potential fields, a longitudinal control scheme for performing a cooperative merging maneuver will be suggested. Artificial potential fields are powerful enough for modeling and solving such a complex problem, where in addition to vehicle following other objectives such as merging should be addressed. The designed algorithms for vehicle cooperative maneuvering are verified through simulations.

In this paper, non-linear estimators and feedforward actions are designed to solve a vehicular platoon control problem. In particular, these estimators are useful in implementation of a Multi-Layer Consensus Seeking approach to the platooning problem. In the Multi-Layer approach the feed-forward part is built separately from the feedback part, based on desired trajectories. This opens the way to study different methods to compute this information. In this work, sliding mode algorithms are employed to generate the desired trajectories and also to compute the feed-forward control input of each vehicle. In this way, a velocity-dependent inter-vehicle spacing policy can be realized without using derivatives of the vehicular acceleration to compute the feed-forward input. Furthermore, a full-state feedback implementation scheme is discussed. The vehicles are modeled with heterogeneous linear longitudinal dynamics. The proposed algorithms are validated through experiments on automated cars.

This paper presents a method for trajectory control, based on feedback linearization to guide an Automatic Guided Vehicle (AGV). The novelty of this work, is the adaptation of a reference trajectory with respect to a desired velocity in real-time to avoid collisions using a time-scaling mechanism. Employing this mechanism, collision avoidance by braking is implemented. Implementation and experimental evaluation of the integrated design of trajectory control, time-scaling and collision avoidance is performed on a real AGV platform.

In this paper, non-linear estimators and feed-forward actions are designed to solve a vehicular platoon control problem. In particular, these estimators are useful in implementation of a Multi-Layer Consensus Seeking approach to the platooning problem. In the Multi-Layer approach the feed-forward part is built separately from the feedback part, based on desired trajectories. This opens the way to study different methods to compute this information. In this work, sliding mode algorithms are employed to generate the desired trajectories and also to compute the feed-forward control input of each vehicle. In this way, a velocity-dependent inter-vehicle spacing policy can be realized without using derivatives of the vehicular acceleration to compute the feed-forward input. Furthermore, a full-state feedback implementation scheme is discussed. The vehicles are modeled with heterogeneous linear longitudinal dynamics. The proposed algorithms are validated through experiments on automated cars.

Context. In safety-critical domains, safety cases are widely used to demonstrate the safety of systems. A safety case is an argumentation for showing confidence in the claimed safety assurance of a system, which should be comprehensible and well-structured. Typically, safety cases can be represented in plain text or graphic way, such as Goal Structuring Notation (GSN). After safety cases are developed, assessment of safety cases needs to be performed to check the quality of them. Besides, different roles are involved during this process: safety case developers and safety case assessors. Objective. During the safety case assessment process, safety case assessors are required to evaluate the validity of a safety case and discuss their judgement with safety case developers. Currently, the outcome of a safety case assessment and the way of providing judgement are not systematically supported, which may cause inconsistent outcomes and wrong judgements. Therefore a systematic process of safety case assessment is required. Moreover, to support safety case assessment in an efficient and effective way, tool support is needed. Recently, a number of safety case editors are developed to support safety case development with the GSN. These editors support the development and management of safety cases. However, only a few editors offer limited functionalities for safety case assessment which is one of the crucial phases of the safety assurance process. This motivates us to develop a tool to support safety case assessment. Method. In this paper, we first identify two research questions. Resulting in two directions for further study have been identified: formalising the safety case assessment process and developing safety case tooling. First, we carried out a study on the state of art on safety case assessment and safety case tooling. Based on our findings, we formalize the safety assessment process by identifying the typical steps in safety case assessment. This assessment process can guide assessors to assess a safety case from a general level to a detailed level and provide reliable and understandable feedback to developers. Finally two industrial case studies are carried out to validate the proposed assessment process. Results. To support the proposed process, a prototype tool for safety case assessment was developed. A number of required features are implemented in the prototype tooling, among other it provides a complete and self-contained evaluation system to measure the quality of the safety case. Moreover, the case study validations show potential for facilitating safety assessment in practice. Conclusions. In this paper, two research questions are identified and the solutions of them are discussed. Then we propose a systematic approach for safety case assessment. For demonstration, a tool support is also developed. For validation two industrial case studies have been carried out to show the effectiveness of the proposed process.

This paper presents a method for trajectory control, based on feedback linearization to guide an Automatic Guided Vehicle (AGV). The novelty of this work, is the adaptation of a reference trajectory with respect to a desired velocity in real-time to avoid collisions using a time-scaling mechanism. Employing this mechanism, collision avoidance by braking is implemented. Implementation and experimental evaluation of the integrated design of trajectory control, time-scaling and collision avoidance is performed on a real AGV platform.

In this paper, a distributed consensus control approach for vehicular platooning systems is proposed. In formalizing the underlying consensus problem, a realistic vehicle dynamics model is considered and a velocity-dependent spacing policy between two consecutive vehicles is realized. As a particular case, the approach allows to consider bidirectional vehicle interaction, which improves the cohesion between vehicles in the platoon. Exponential stability of the platoon dynamics is evaluated, also in the challenging scenario in which a limitation on the velocity of one of the vehicles in the platoon is introduced. The theoretical results are experimentally validated using a threevehicle platoon consisting of (longitudinally) automated vehicles equipped with wireless intervehicle communication and radarbased sensing.

Cooperative adaptive cruise control and platooning are well-known applications in the field of cooperative automated driving. However, extension toward maneuvering is desired to accommodate common highway maneuvers, such as merging, and to enable urban applications. To this end, a layered control architecture is adopted. In this architecture, the tactical layer hosts the interaction protocols, describing the wireless information exchange to initiate the vehicle maneuvers, supported by a novel wireless message set, whereas the operational layer involves the vehicle controllers to realize the desired maneuvers. This hierarchical approach was the basis for the Grand Cooperative Driving Challenge (GCDC), which was held in May 2016 in The Netherlands. The GCDC provided the opportunity for participating teams to cooperatively execute a highway lanereduction scenario and an urban intersection-crossing scenario. The GCDC was set up as a competition and, hence, also involving assessment of the teams’ individual performance in a cooperative setting. As a result, the hierarchical architecture proved to be a viable approach, whereas the GCDC appeared to be an effective instrument to advance the field of cooperative automated driving.

A method of neighborhood data fusion in decentralized anomaly detection is proposed.The effects of neighborhood size and spatio-temporal correlation are explored.Performance increases when the system is deployed in a correlated environment.Fusing small neighborhoods is preferred over larger neighborhoods. The field of wireless sensor networks (WSNs), embedded systems with sensing and networking capability, has now matured after a decade-long research effort and technological advances in electronics and networked systems. An important remaining challenge now is to extract meaningful information from the ever-increasing amount of sensor data collected by WSNs. In particular, there is strong interest in algorithms capable of automatic detection of patterns, events or other out-of-the order, anomalous system behavior. Data anomalies may indicate states of the system that require further analysis or prompt actions. Traditionally, anomaly detection techniques are executed in a central processing facility, which requires the collection of all measurement data at a central location, an obvious limitation for WSNs due to the high data communication costs involved. In this paper we explore the extent by which one may depart from this classical centralized paradigm, looking at decentralized anomaly detection based on unsupervised machine learning. Our aim is to detect anomalies at the sensor nodes, as opposed to centrally, to reduce energy and spectrum consumption. We study the information gain coming from aggregate neighborhood data, in comparison to performing simple, in-node anomaly detection. We evaluate the effects of neighborhood size and spatio-temporal correlation on the performance of our new neighborhood-based approach using a range of real-world network deployments and datasets. We find the conditions that make neighborhood data fusion advantageous, identifying also the cases in which this approach does not lead to detectable improvements. Improvements are linked to the diffusive properties of data (spatio-temporal correlations) but also to the type of sensors, anomalies and network topological features. Overall, when a dataset stems from a similar mixture of diffusive processes precision tends to benefit, particularly in terms of recall. Our work paves the way towards understanding how distributed data fusion methods may help managing the complexity of wireless sensor networks, for instance in massive Internet of Things scenarios.

Context. In safety-critical domains, safety cases are widely used to demonstrate the safety of systems. A safety case is an argumentation for showing confidence in the claimed safety assurance of a system, which should be comprehensible and well-structured. Typically, safety cases can be represented in plain text or graphic way, such as Goal Structuring Notation (GSN). After safety cases are developed, assessment of safety cases needs to be performed to check the quality of them. Besides, different roles are involved during this process: safety case developers and safety case assessors. Objective. During the safety case assessment process, safety case assessors are required to evaluate the validity of a safety case and discuss their judgement with safety case developers. Currently, the outcome of a safety case assessment and the way of providing judgement are not systematically supported, which may cause inconsistent outcomes and wrong judgements. Therefore a systematic process of safety case assessment is required. Moreover, to support safety case assessment in an efficient and effective way, tool support is needed. Recently, a number of safety case editors are developed to support safety case development with the GSN. These editors support the development and management of safety cases. However, only a few editors offer limited functionalities for safety case assessment which is one of the crucial phases of the safety assurance process. This motivates us to develop a tool to support safety case assessment. Method. In this paper, we first identify two research questions. Resulting in two directions for further study have been identified: formalising the safety case assessment process and developing safety case tooling. First, we carried out a study on the state of art on safety case assessment and safety case tooling. Based on our findings, we formalize the safety assessment process by identifying the typical steps in safety case assessment. This assessment process can guide assessors to assess a safety case from a general level to a detailed level and provide reliable and understandable feedback to developers. Finally two industrial case studies are carried out to validate the proposed assessment process. Results. To support the proposed process, a prototype tool for safety case assessment was developed. A number of required features are implemented in the prototype tooling, among other it provides a complete and self-contained evaluation system to measure the quality of the safety case. Moreover, the case study validations show potential for facilitating safety assessment in practice. Conclusions. In this paper, two research questions are identified and the solutions of them are discussed. Then we propose a systematic approach for safety case assessment. For demonstration, a tool support is also developed. For validation two industrial case studies have been carried out to show the effectiveness of the proposed process.

The optimal design of a hybrid electric vehicle (HEV) can be formulated as a multiobjective optimization problem that spreads over multiple levels (technology, topology, size, and control). In the last decade, studies have shown that by integrating these optimization levels, fuel benefits are obtained, which go beyond the results achieved with solely optimal control for a given topology. Due to the large number of variables for optimization, their diversity, and the nonlinear and multiobjective nature of the problem, a variety of methodologies have been developed. This paper presents a comprehensive analysis of the various methodologies developed and identifies challenges for future research. Starting from a general description of the problem, with examples found in the literature, we categorize the types of optimization problems and methods used. To offer a complete analysis, we broaden the scope of the search to several sectors of transport, such as naval or ground.

Creating a driving cycle (DC) for the design and validation of new vehicles is an important step that will influence the efficiency, functionality and performance of the final systems. In this work, a DC synthesis method is introduced, based on multi-dimensional Markov Chain, where both the velocity and road slope are investigated. Particularly, improvements on the DC synthesis method are proposed, to reach a more realistic slope profile and more accurate fuel consumption and CO2 emission estimates. The effects of using synthesized DCs on fuel consumption are investigated considering three different vehicle models: conventional ICE, and full hybrid and mild hybrid electric vehicles. Results show that short but representative synthetic DCs will results in more realistic fuel consumption estimates (e.g. in the 5%-10% range) and in much faster simulations. Using the results of this proposed method also eliminates the need to use very simplified DCs, as the New European Driving Cycle(NEDC), or long, measured DCs.

Path planning of an autonomous vehicle as a non-holonomic system is an essential part for many automated driving applications. Parking a car into a parking lot and maneuvering it through a narrow corridor would be a common driving scenarios in an urban environment. In this study a hybrid approach for dynamic path planning is presented which deals with the limited degrees of freedom of a non-holonomic system, as well as the real-time constraints and limited computational power. Furthermore, it takes into account ride comfort of the passenger by generating smooth path. The proposed method has been evaluated in simulation environment and is implemented and tested on a Toyota Prius test vehicle with an active steering system.

Cooperative Adaptive Cruise Control (CACC) improves road throughput by employing intervehicle wireless communications. The inherent communication time delay significantly limits the minimum inter-vehicle distance in view of string stability. Applying a Padé approximation leads to a model with a rational transfer function, which allows many control methods to compensate for this delay to a certain extent. Our objective is to find the lowest possible order of Padé approximations, which is sufficiently accurate in view of string stability. To this end, the minimum string-stable time gaps are chosen as the main criterion against which the quality of the Pad´e approximations is measured. The results indicate that it is feasible to apply a 2nd-order Padé approximation in the given CACC system.

In this paper, in addition to the main functionality of vehicle following, cooperative adaptive cruise control (CACC) is enabled with additional features of gap closing and collision avoidance. Due to its nonlinear nature, a control objective such as collision avoidance, cannot be addressed using a linear controller such as a PD controller. However, the artificial potential functions can be adopted to design controllers which accommodate multiple (nonlinear) control objectives in a single design. By defining an appropriate control law, the system state is always driven to the minima of the designed potential function which guarantees the required performance of the system.

This paper presents the controller design for combined lateral and longitudinal Cooperative Adaptive Cruise Control (CACC) for a unicycle-type platoon with emphasis on the cornering maneuvers. A decentralized controller for lateral and longitudinal behavior is designed using input-output linearization by static feedback. A preceding vehicle look-ahead approach is adapted in the controller to maintain desired inter-vehicle distance. However, due to the position control of the look-ahead point, the follower vehicle may cut corners on turns. In this paper, the extension of a look-ahead point that is able to compensate the cutting-corner behavior is then proposed. To validate the theoretical analysis, the full nonlinear system together with the developed controller is simulated for two scenarios, a circular path and a particular path scenario, and a comparison is made between the system with the preceding vehicle look-ahead and the extended look-ahead. The simulation shows that the proposed lateral and longitudinal controller using the extended look-ahead eliminates the cutting corner behavior.

In May 2011, the Grand Cooperative Driving Challenge (GCDC) was held, providing the possibility for teams to develop and compare their cooperative driving solutions in a competitive setting. The challenge was organized to further accelerate developments in the area of cooperative driving. Nine international teams challenged each other to handle both an urban and a highway scenario. These scenarios have been chosen such that the performance of the implementation of cooperative adaptive cruise control of each participant can be judged. Evaluation of the vehicle behavior has been performed by means of video-based roadside units, installed at the test site in The Netherlands, that is capable of tracking the individual vehicles, in addition to the information obtained through wireless communication. Judgement criteria include both macroscale criteria, such as platoon length and traffic light throughput, and individual criterion, like string stability. Most teams performed well, although clear differences in performance and reliability could be observed. The GCDC showed that it is possible to cooperatively drive with heterogeneous systems. It is envisioned to make the GCDC a regular event and to further extend the active role of roadside communication units, as well as include automated lateral vehicle control.

The challenge of designing stability control functions for trucks is to guarantee robustness for all variations in truck and trailer combinations. The method proposed in this study can be used to quickly narrow down the number of truck and trailer combinations to a critical set to be evaluated with complex nonlinear simulation software or full-scale tests. To reach this goal, equations of motion are derived for single track linear vehicle models to understand the fundamental differences between the dynamic yaw performance of the truck and trailer combinations. The Hurwitz criterion is used to determine approximate analytical stability boundaries. It is shown that stability does not provide discrimination between combinations as most combinations are stable during normal driving conditions. In contrast, rearward amplification is a discriminatory performance measure. A frequency domain approach is used to study the fundamental differences between vehicle combinations. A comparison with complex nonlinear simulation model results indicates that the proposed method can be used to select critical vehicle combinations and to study the effect of parameter changes. © 2012 Copyright Taylor and Francis Group, LLC.

Recent development in wireless technology enables communication between vehicles. The concept of co-operative adaptive cruise control (CACC)--which uses wireless communication between vehicles--aims at string stable behavior in a platoon of vehicles. "String stability" means any non-zero position, speed, and acceleration errors of an individual vehicle in a string do not amplify when they propagate upstream. In this article, we will discuss the string stability of CACC and evaluate its performance under varying packet loss ratios, beacon sending frequencies, and time headway settings in simulation experiments. The simulation framework is built up with a controller prototype, a traffic simulator, and a network simulator.

This report summarizes the work conducted within work package (WP) 5 "Verification of test matrix and protocol" of the Cyclist AEB testing system (CATS) project. It describes the verification process of the draft CATS test matrix resulting from WP1 and WP2, and the feasibility of meeting requirements set by CATS consortium based on requirements in Euro NCAP AEB protocols regarding accuracy, repeatability and reproducibility using the developed test hardware. For the cases where verification tests or additional information indicated that the protocol needed adaptation, proposed changes were discussed and upon agreement amongst the partners provided to the matrix including supporting argumentation. In WP1 the relevant accident scenarios have been determined, where in WP2 the most relevant accident parameters were extracted from accidentology and an additional observation study. Using these sources of information, a draft CATS test matrix has been developed. This draft CATS test matrix was used as a basis for the verification process. The process included workshops where all partners of the CATS consortium have been given the possibility to test the scenarios, a full spec test series was performed with a vehicle including a Cyclist-AEB system. Furthermore simulation studies were done and a robustness test series was performed to check the accuracies of the test protocol and the practical usability of the test equipment. Verification tests and simulations revealed that both the near-side CVNBU crossing scenario with 0% overlap and the far-side CVFB with 50% overlap crossing scenario were approximately equally difficult in terms of feasibility. It was therefore decided to change the collision point in the CVNBU test to 50% instead of 0% and the collision point in the CVFB scenario from 50% to 25%. Both changes still correspond to the parameters found in accidentology. This creates a two-step approach in terms of difficulty where the CVNBU is now less challenging and the CVFB more challenging. Furthermore it was found in the tests that the lateral accuracy of the target remains a challenge, especially for the longitudinal scenario with a long single belt. As a result, the collision point in the longitudinal scenario is changed from 20% to 25% since it is important that cyclist remains inside the width of the vehicle in terms of trigger an AEB activation. This still corresponds to the parameters found in accidentology.