http://wpage.unina.it/valerio.persico/pubs/CloudIoT_FGCS.pdf

Integration of Cloud computing and Internet of Things

Intelligent vehicles have increased their capabilities for highly and, even fully, automated driving under controlled environments. Scene information is received using onboard sensors and communication network systems, i.e., infrastructure and other vehicles. Considering the available information, different motion planning and control techniques have been implemented to autonomously driving on complex environments. The main goal is focused on executing strategies to improve safety, comfort, and energy optimization. However, research challenges such as navigation in urban dynamic environments with obstacle avoidance capabilities, i.e., vulnerable road users (VRU) and vehicles, and cooperative maneuvers among automated and semi-automated vehicles still need further efforts for a real environment implementation. This paper presents a review of motion planning techniques implemented in the intelligent vehicles literature. A description of the technique used by research teams, their contributions in motion planning, and a comparison among these techniques is also presented. Relevant works in the overtaking and obstacle avoidance maneuvers are presented, allowing the understanding of the gaps and challenges to be addressed in the next years. Finally, an overview of future research direction and applications is given.

A Review of Motion Planning Techniques for Automated Vehicles

Safety critical systems involve the tight coupling between potentially conflicting control objectives and safety constraints. As a means of creating a formal framework for controlling systems of this form, and with a view toward automotive applications, this paper develops a methodology that allows safety conditions—expressed as control barrier functions —to be unified with performance objectives—expressed as control Lyapunov functions—in the context of real-time optimization-based controllers. Safety conditions are specified in terms of forward invariance of a set, and are verified via two novel generalizations of barrier functions; in each case, the existence of a barrier function satisfying Lyapunov-like conditions implies forward invariance of the set, and the relationship between these two classes of barrier functions is characterized. In addition, each of these formulations yields a notion of control barrier function (CBF), providing inequality constraints in the control input that, when satisfied, again imply forward invariance of the set. Through these constructions, CBFs can naturally be unified with control Lyapunov functions (CLFs) in the context of a quadratic program (QP); this allows for the achievement of control objectives (represented by CLFs) subject to conditions on the admissible states of the system (represented by CBFs). The mediation of safety and performance through a QP is demonstrated on adaptive cruise control and lane keeping, two automotive control problems that present both safety and performance considerations coupled with actuator bounds.

https://ieeexplore.ieee.org/ielaam/9/7993115/7782377-aam.pdf

Control Barrier Function Based Quadratic Programs for Safety Critical Systems

The introduction of connected and autonomous vehicles will bring changes to the highway driving environment. Connected vehicle technology provides real-time information about the surrounding traffic condition and the traffic management center’s decisions. Such information is expected to improve drivers’ efficiency, response, and comfort while enhancing safety and mobility. Connected vehicle technology can also further increase efficiency and reliability of autonomous vehicles, though these vehicles could be operated solely with their on-board sensors, without communication. While several studies have examined the possible effects of connected and autonomous vehicles on the driving environment, most of the modeling approaches in the literature do not distinguish between connectivity and automation, leaving many questions unanswered regarding the implications of different contemplated deployment scenarios. There is need for a comprehensive acceleration framework that distinguishes between these two technologies while modeling the new connected environment. This study presents a framework that utilizes different models with technology-appropriate assumptions to simulate different vehicle types with distinct communication capabilities. The stability analysis of the resulting traffic stream behavior using this framework is presented for different market penetration rates of connected and autonomous vehicles. The analysis reveals that connected and autonomous vehicles can improve string stability. Moreover, automation is found to be more effective in preventing shockwave formation and propagation under the model’s assumptions. In addition to stability, the effects of these technologies on throughput are explored, suggesting substantial potential throughput increases under certain penetration scenarios.

Influence of connected and autonomous vehicles on traffic flow stability and throughput

Intelligent vehicle cooperation based on reliable communication systems contributes not only to reducing traffic accidents but also to improving traffic flow. Adaptive cruise control (ACC) systems can gain enhanced performance by adding vehicle-vehicle wireless communication to provide additional information to augment range sensor data, leading to cooperative ACC (CACC). This paper presents the design, development, implementation, and testing of a CACC system. It consists of two controllers, one to manage the approaching maneuver to the leading vehicle and the other to regulate car-following once the vehicle joins the platoon. The system has been implemented on four production Infiniti M56s vehicles, and this paper details the results of experiments to validate the performance of the controller and its improvements with respect to the commercially available ACC system.

/pdf/cooperative-adaptive-cruise-control-in-real-traffic-35mggeon75.pdf

Cooperative Adaptive Cruise Control in Real Traffic Situations

The modern society's increasing mobility is placing a growing demand on traffic safety An important way to meet this demand will be offered by on-board driver assistance systems Introducing inter-vehicle communication allows these systems to use traffic data collected by other vehicles This opens up the possibility to implement co-operative driving behaviour thereby improving the overall traffic safety This idea is formalised in an advanced driver assistance concept called Mensor In this concept the actions of multiple drivers are measured and combined into a 'safety state' indicating the 'level of traffic safety' The safety state message is sent to other vehicles and communicated to their drivers allowing them to take preventive actions Initial experiments with a small scale demonstrator consisting of three passenger cars show considerable prospects to improve traffic safety

/pdf/mensor-utilisation-of-the-human-sensor-through-inter-vehicle-23slbqsjp8.pdf

Mensor: utilisation of the human sensor through inter-vehicle communication

In this paper, a collision warning method between the host vehicle and target object(s) is studied A probabilistic collision warning method is proposed, which is, in particular, useful for objects, eg vulnerable road users, which trajectories can rapidly change heading and/or velocity with respect to time A vehicle is equipped with the probabilistic collision warning system and its functionality is validated in experiments with a bicyclist as target object

/pdf/collision-warning-system-based-on-probability-density-24omn9dssr.pdf

Collision warning system based on probability density functions

In the past years TNO developed the SUMMITS Tool Suite to support the development and evaluation of cooperative vehicle-infrastructure systems. SUMMITS stands for: Sustainable Mobility Methodologies for Intelligent Transport Systems. Tool Suite consists of different modules that cover specific aspects of those systems varying from traffic flow analysis to assessment of human factors, and from dependable cooperative control architectures to fault tolerant hardware implementation. This memo describes the Tool Suite and how it matches with development process of cooperative road-vehicle systems and applications.

The SUMMITS Tool Suite: supporting the development and evaluation of cooperative vehicle-infrastructure systems in a multi-aspect assessment approach

Cooperative adaptive cruise control entails regulating the distance towards a preceding road vehicle, employing both on-board environmental sensors and wireless inter-vehicle communication, the latter necessary for acceleration information, which cannot be directly measured by on-board sensors. However, in case of communication impairments, such as high latency or significant packet loss, a degraded mode is required, to which end the acceleration of the preceding vehicle must be estimated using on-board sensors such as radar. Fast convergence towards the actual preceding vehicle acceleration is imperative for ensuring the cooperative driving safety. Consequently, we propose a sliding-mode based estimator ensuring the finite-time convergence of the acceleration estimation error, and hence, ensuring the functionality of the CACC in degraded situations.

Sliding Mode Acceleration Estimation For Safe Vehicular Cooperative Adaptive Cruise Control

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 Pade 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 Pade 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 Pade approximation in the given CACC system.

Jeroen Ploeg

Papers

Mensor: utilisation of the human sensor through inter-vehicle communication

Collision warning system based on probability density functions

The SUMMITS Tool Suite: supporting the development and evaluation of cooperative vehicle-infrastructure systems in a multi-aspect assessment approach

Sliding Mode Acceleration Estimation For Safe Vehicular Cooperative Adaptive Cruise Control

Padé approximation of delays in CACC-controlled string-stable platoons