Stability and safety evaluation of mixed traffic flow with connected automated vehicles on expressways.

Neuroadaptive quantized PID sliding‐mode control for heterogeneous vehicular platoon with unknown actuator deadzone

A major goal of advanced driver-assistance systems (ADAS) deployment is higher road safety. However, these systems are only as safe as users handle them. This article presents a study evaluating the links between the use of ADAS and road risk perception. 101 drivers were invited to evaluate accident probability and risk controllability and to indicate whether they were using ADAS or not. Results show that the use of ADAS decreases perceived accident probability and increases perceived controllability for risky driving situations. Since the degree of automation in ADAS is still low nowadays, it is important to discuss the importance of human factors for the purpose of a safer implementation.

Safe on the road – Does Advanced Driver-Assistance Systems Use affect Road Risk Perception?

Vehicle platooning has gained attention for its potential to increase road capacity and safety, and higher fuel efficiency. Platoon controls are implemented over Vehicle-to-Vehicle (V2V) wireless communication, in-vehicle networks and Electronic Control Units (ECUs). V2V communication has a low message rate imposed by the V2V standard compared to the rate of modern in-vehicle networks and ECUs. The platoon control strategy should take into account such multi-rate nature of the implementation architecture for higher performance. Current literature does not explicitly consider such real-life constraints. We propose a two-layered control framework for vehicle platoons wirelessly communicating complying with the industrial standard IEEE 802.11p. In the upper-layer, vehicles receive state information from the immediate preceding vehicle over a control channel at 10 Hz under the IEEE 802.11p standard with occasional packet drops. Using such information and the vehicle state information, the engine control system, i.e. the lower-layer, realizes the desired vehicle state (e.g., acceleration) over the fast and reliable in-vehicle networks (e.g., FlexRay, Ethernet). In this work, a distributed model predictive control framework is proposed for the upper-layer targeting a Predecessor-Follower (PF) topology. A state-feedback control scheme is proposed for realizing the desired vehicle states for the lower-layer. Our framework minimizes the inter-vehicle distance and the tracking error enforcing collision avoidance and robustness against packet drops at the upper-layer. We validate our algorithm in simulation using our co-simulation framework CReTS and on an embedded platform, developed by Cohda Wireless and NXP, running in real time and communicating through the IEEE 802.11p standard. With extensive simulations and experiments, we evaluate the performance and feasibility of the proposed framework under a number of practical constraints. Our approach is a step towards the implementation of platoon control in reality.

Multi-layer multi-rate model predictive control for vehicle platooning under IEEE 802.11p

With the advance of automation in the field of transportation, the number of emerging systems that are going to be deployed on the European roads is growing fast The aim of C-Roads Italy, part of the Europe-wide C-Roads Project, is to evaluate the impacts on public roads and the feasible operational modes of Truck Platooning, when jointly implemented with Day 1 C-ITS This paper, first, reports an extended summary of the available bibliography on Truck Platooning focused on the assessment of the implementation scenario presented as an example in Section IV The literature review is necessary to investigate the more promising implementation schemes in the short term on the European area and the system expected impacts when deployed as a stand-alone service Then, the evaluation methodology that is currently being drafted in the activity of C-Roads Italy is described, aimed to assess the jointed impact of Day 1 C-ITS services and Truck Platooning Finally, a meaningful example of the approach for the evaluation of the jointed implementation of Truck Platooning and C-ITS services is presented, considering one of the use cases of the Road Works Warning Service, as defined in the current version of the C-Roads documents

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Evaluation Approach for a Combined Implementation of Day 1 C-ITS and Truck Platooning

In this paper, a novel Multi-Layer Consensus Seeking (MLCS) framework is proposed, focusing on the vehicular platooning problem. The vehicles are described by linear heterogeneous dynamics. For example, we consider third-order systems, however the algorithms discussed are suitable for any higher-order. A velocity-dependent inter-vehicle spacing policy is rigorously addressed. The approach used is both multi-layered and consensus-based. The multi-layer approach allows to separate the problem of estimating the desired trajectories from the problem of controlling the vehicles towards those trajectories while keeping a safety distance. Consensus algorithms will be employed on each layer to solve these two problems.

Vehicular platooning: Multi-Layer Consensus Seeking

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.

A multi-layer control approach to truck platooning: Platoon cohesion subject to dynamical limitations

Safety analysis of a vehicle equipped with Cooperative Adaptive Cruise Control

Decision making for autonomous vehicles: Combining safety and optimality

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.

Mauro Fusco

Papers

Vehicular platooning: Multi-Layer Consensus Seeking

A multi-layer control approach to truck platooning: Platoon cohesion subject to dynamical limitations

Safety analysis of a vehicle equipped with Cooperative Adaptive Cruise Control

Decision making for autonomous vehicles: Combining safety and optimality

Nonlinear multi-layer consensus seeking of vehicular platoons