Network of automated vehicles: the AutoNet 2030 vision

electronic proceedingsInternational audienceAutoNet2030 - Co-operative Systems in Support of Networked Automated Driving by 2030 - is a European project connecting two domains of intensive research: cooperative systems for Intelligent Transportation Systems and Automated Driving. Given the latest developments in the standardization of vehicular communications, vehicles will soon be wirelessly connected, enabling cooperation among them and with the infrastructure. At the same time, some vehicles will offer very advanced driving assistance systems, ranging from Cooperative Adaptive Cruise Control (C-ACC) to full automation. The research issues addressed in AutoNet2030 are as follows: how can all these vehicles with different capabilities most efficiently cooperate to increase safety and fluidity of the traffic system? What kind of information should be exchanged? Which organization (e.g. centralized or distributed) is the best? The purpose of this paper is to introduce the vision and concepts underlying the AutoNet2030 project and the direction of this ongoing research work

Analytical Models for Vehicle/Gap Distribution on Automated Highway Systems

Highway congestion has in recent years become a pervasive problem for urban and suburban areas alike. The concept of Automated Highway Systems is based on the belief that integration of sensing, communication, and control technologies into vehicles and highways can lead to a large improvement in capacity and safety without requiring a significant amount of additional highway right-of-way. A fundamental determinant of Automated Highway Systems capacity is the vehicle-following rule, the rule that governs the behavior of vehicles traveling along a common lane (e.g., the spacing between any two longitudinally adjacent vehicles). Vehicle following affects the longitudinal capacity (achievable flow within a lane), the lateral capacity (achievable flow between lanes) and the conflicting relationship between the longitudinal flow and lateral capacity. The issues are investigated by developing probabilistic models for vehicle/platoon and gap distributions, for vehicles that travel in platoons, in slots, or as free-agents. Mathematical models are also developed to estimate the completion time of a lane change, which can be used as a surrogate for the lateral capacity. Numerical results for the three major vehicle-following rules and their comparison are also provided

Argumentation among self-driving vehicles

In this day and age where the number of vehicles that are being used on highways and roads has been increasing considerably, there is a need for a global driving technique, or a driving phenomenon, where the vehicles can communicate with each other and maintain efficient driving positions by automating the process without the help of a human driver. With the available technology, self-driving cars are already under the spotlight, but these vehicles only offer limited support to the driver and they require human input in the process of driving. Argumentation techniques can be used to develop an efficient algorithm to resolve the conflicts between Agents i.e vehicles to allow safer travel, reduced emissions and better traffic distribution over road networks. Considering the importance of cooperative driving. platoon transition that has been overlooked in the existing research, our implementation tests the use of an Argumentation technique, on top of the platoons, providing an edge over the existing work related to self-driving vehicles. Utilizing the Argumentation allowed an effective way in resolving the conflicts among platoon leaders allowing a smoother transition of platoon groups. The conducted experiment compared the traffic flow of vehicles between two scenarios namely cooperative driving and non-cooperative driving, deriving the results that showcase the advantages of cooperative driving and also the role of argumentation in conflict resolution among vehicle agents

On Constant Distance Spacing Policies for Cooperative Adaptive Cruise Control

Cooperative Adaptive Cruise Control (CACC) systems are considered as key potential enablers to improve driving safety and traffic efficiency. They allow for automated vehicle following using wireless communication in addition to onboard sensors. To achieve string stability in CACC platoons, constant time headway (CTH) spacing policies have prevailed in research; namely, vehicle interspacing grows with the speed. While constant distance headway (CDH) spacing policies provide superior potential to increase traffic capacity than CTH, a major drawback is a smaller safety margin at high velocities and string stability cannot be achieved using a one-vehicle look-ahead communication. The hypothesis of this work is to apply CDH only in few driving situations, when traffic throughput is of highest importance and safety requirements can be met due to comparably low velocities. As the most relevant situations where CDH could be applied, we identify starting platoons at signalized intersections. In this paper, we illustrate this idea. Specifically, we compare CTH with CDH regarding its potential to increase the capacity of traffic lights. Starting with the elementary situation of single traffic lights we expand our scope to whole traffic networks including several thousand vehicles in simulation. Using real world data to calibrate and validate vehicle dynamics simulation and traffic simulation, the study discusses the most relevant working parameters of CDH, CTH, and the traffic system in which both are applied.Comment: In preparation for submission to IEEE Transactions on Intelligent Transportation System

Network of automated vehicles: The AutoNet2030 vision

AutoNet2030 – Co-operative Systems in Support of Networked Automated Driving by 2030 – is a European project connecting two domains of intensive research: cooperative systems for Intelligent Transportation Systems and Automated Driving. Given the latest developments in the standardization of vehicular communications, vehicles will soon be wirelessly connected, enabling cooperation among them and with the infrastructure. At the same time, some vehicles will offer very advanced driving assistance systems, ranging from Cooperative Adaptive Cruise Control (C-ACC) to full automation. The research issues addressed in AutoNet2030 are as follows: how can all these vehicles with different capabilities most efficiently cooperate to increase safety and fluidity of the traffic system? What kind of information should be exchanged? Which organization (e.g. centralized or distributed) is the best? The purpose of this paper is to introduce the vision and concepts underlying the AutoNet2030 project and the direction of this ongoing research work

Platooning of connected automated vehicles on freeways: a bird’s eye view

A platoon of connected automated vehicles (CAVs) is defined as a group of CAVs that exchange information, so that they can drive in a coordinated way, allowing very small spacings and, still, travelling safely at relatively high speeds. The concept of vehicle platooning is not new. Scientific articles on platooning have been published since the 1970s, and the first large-scale pilot test on vehicle platooning was carried out in the mid 1990s in California. By 1992, the first vehicle platooning experiments were successfully concluded, and the four-vehicle platoon capability was demonstrated for visitors on the I-15 HOV lanes in San Diego in 1994. The main purpose of these early research works was to improve traffic efficiency and reduce vehicle consumption, as well as to develop the existing technology, which represented a strong limitation at the time. Precisely, the development of new technologies and communications in the last decade has given a new impetus to the research on vehicle platooning on freeways, as one of the most promising forms of cooperation among CAVs. These recent studies have extended the analysis beyond traffic efficiency, including safety, sustainability, business productivity, among other objectives. In this context, today, there are many scientific publications on vehicle platooning with different purposes, scopes, scenarios, and based on a wide diversity of vehicles and technologies (i.e. regular or segregated lanes, cars or trucks, vehicles with different SAE levels, etc.). In order to organize and consolidate the existing knowledge on the field, a comprehensive and systematic review must be performed. The present work represents a first approach to this ambitious objective. First, platooning is conceptualized in order to facilitate its analysis and comparison among studies. Second, key publications on platooning are analyzed to determine the most significant impacts that can be expected from its implementation. Finally, some important research gaps and disparate findings on the topic are identified.This research has been partially funded by the Spanish Ministry of Economy, Industry and Competitiveness, within the National Program for Research Aimed at the Challenges of Society (grant ref. PID2019-105331RB-I00).Peer ReviewedPostprint (published version

Cognitive Vehicle Platooning in the Era of Automated Electric Transportation

Vehicle platooning is an important innovation in the automotive industry that aims at improving safety, mileage, efficiency, and the time needed to travel. This research focuses on the various aspects of vehicle platooning, one of the important aspects being analysis of different control strategies that lead to a stable and robust platoon. Safety of passengers being a very important consideration, the control design should be such that the controller remains robust under uncertain environments. As a part of the Department of Energy (DOE) project, this research also tries to show a demonstration of vehicle platooning using robots. In an automated highway scenario, a vehicle platoon can be thought of as a string of vehicles, following one another as a platoon. Being equipped by wireless communication capabilities, these vehicles communicate with one another to maintain their formation as a platoon, hence are cognitive. Autonomous capable vehicles in tightly spaced, computer-controlled platoons will lead to savings in energy due to reduced aerodynamic forces, as well as increased passenger comfort since there will be no sudden accelerations or decelerations. Impacts in the occurrence of collisions, if any, will be very low. The greatest benefit obtained is, however, an increase in highway capacity, along with reduction in traffic congestion, pollution, and energy consumption. Another aspect of this project is the automated electric transportation (AET). This aims at providing energy directly to vehicles from electric highways, thus reducing their energy consumption and CO2 emission. By eliminating the use of overhead wires, infrastructure can be upgraded by electrifying highways and providing energy on demand and in real time to moving vehicles via a wireless energy transfer phenomenon known as wireless inductive coupling. The work done in this research will help to gain an insight into vehicle platooning and the control system related to maintaining the vehicles in this formation

Cooperative Collision Avoidance in a Connected Vehicle Environment

Connected vehicle (CV) technology is among the most heavily researched areas in both the academia and industry. The vehicle to vehicle (V2V), vehicle to infrastructure (V2I) and vehicle to pedestrian (V2P) communication capabilities enable critical situational awareness. In some cases, these vehicle communication safety capabilities can overcome the shortcomings of other sensor safety capabilities because of external conditions such as 'No Line of Sight' (NLOS) or very harsh weather conditions. Connected vehicles will help cities and states reduce traffic congestion, improve fuel efficiency and improve the safety of the vehicles and pedestrians. On the road, cars will be able to communicate with one another, automatically transmitting data such as speed, position, and direction, and send alerts to each other if a crash seems imminent. The main focus of this paper is the implementation of Cooperative Collision Avoidance (CCA) for connected vehicles. It leverages the Vehicle to Everything (V2X) communication technology to create a real-time implementable collision avoidance algorithm along with decision-making for a vehicle that communicates with other vehicles. Four distinct collision risk environments are simulated on a cost effective Connected Autonomous Vehicle (CAV) Hardware in the Loop (HIL) simulator to test the overall algorithm in real-time with real electronic control and communication hardware

A Rule Based Control Algorithm for on-Ramp Merge With Connected and Automated Vehicles

One of the designs for future highways with the flow of Connected Automated Vehicles (CAVs) cars will be a dedicated lane for the CAVs to form platoons and travel with higher speeds and lower headways. The connectivity will enable the formation of platoons of CAVs traveling beside non-platoon lanes. The advent of connectivity between vehicles and the infrastructure will enable advanced control strategies ̶ improving the performance of the traffic ̶ to be incorporated in the traffic system. The merge area in a multilane highway with CAVs is one of the sections which can be enhanced by the operation of a control system. In this research, a model is developed for investigating the effects of a Rule Based control strategy yielding a more efficient and systematic method for the vehicles joining the highway mainlines comprised of platoon and non-platoon lanes. The actions tested for assisting the merge process included deceleration in the mainlines and lane change to join a platoon in the platoon lane. The model directs every CAV entering a multi-lane highway from an on-ramp, to the rightmost lane of the highway based on the appropriate action which is selected according to the traffic demand conditions and location of the on-ramp vehicle. To account for car following behavior, the vehicles in the platoon lanes are assumed to have a simplified CACC (cooperative adaptive cruise control) and those in the non-platoon lanes the IDM+ car-following model. The IDM+ car following model is modified with additional controls to incorporate the current technologies of Advanced Driver Assistant Systems (ADAS). The results of this study showed that the proposed car following model can increase the throughput of the non-platoon lane from approximately 2000 vehicle per hour (vph) to 3400 vph while the platoon lanes each had an average throughput of 3500 vph. The merge model enabled higher merging throughput for the merge area compared to current day conditions and displayed the potential for improved traffic performance in a connected environment comprised of platoon and non-platoon lanes. The results of this research will help in the design and development of advanced systems for controlling on-ramp merge sections in the future with CAVs