Internet-connected Vehicles Research Articles

Abnormal communication internet-connected vehicle platoon dynamical modeling and characteristics study

With the advent of the vehicle interconnection era, all the internet-connected vehicles (i.e. ICVs) can communicate with each other through the whole platoon, and great changes of the dynamical motion characteristics in traffic flow system is happening. The wireless communication system plays more and more important roles to keep traffic flow system stable and safe. However, communication failure is a common and unevitable phenomenon, and an ICV in a platoon will inevitably lose its connection with other vehicles sometimes. So it is necessary and meaningful to study ICV’s dynamical characteristics under abnormal communication conditions. The study firstly analyzed the information exchange mechanism among ICVs and classify communication failure into three modes. Secondly, by considering normal and abnormal communication conditions, a car-following model for internet-connected vehicle flows with bidirectional mean expected velocity field was proposed. Thirdly, the ICV platoon system stable state condition was deduced based on linear stability theory. Finally, full simulation logical scenarios were set to support the theoretical analysis results considering the ICV system’s stability and communication states comprehensively. As for the abnormal communication state simulations, the leading vehicle, last vehicle, and middle vehicle communication failure scenarios were selected as typical examples. The study conclusions are (i) for bidirectional communication ICV platoon system, forward-looking and backward-looking mean expected velocity field terms show different influences on its stability, (ii) sudden abnormal communication failures can dramatically destroy the vehicle platoon stability, and (iii) different vehicle position communication failure has different effects on the system stability.

HARMONIC: Shapley values in market games for resource allocation in vehicular clouds

Real-time allocation of resources to fulfill service requests from road vehicles is becoming increasingly complex, for two main reasons: the continuous increase in the number of Internet-connected vehicles on roads all over the world, and the emergence of complex and resource-greedy applications that require fast execution, often under limited availability of computational resources. While many resource allocation solutions to this problem have been proposed recently, these solutions rely on unrealistic scenarios and constraints that limit their practical use.This paper presents HARMONIC, a Game Theory-based coalition game that aims to maximize resource utilization and dynamically balance resource usage across multiple Vehicular Clouds (VCs). HARMONIC employs a Shapley value-based strategy to determine the order of task allocation to available resources. It is built upon our proposed Market Game model, specifically designed to address resource allocation challenges in dynamic VCs. We conduct a comparative analysis with existing literature solutions under various scenarios and resource constraints to evaluate HARMONIC’s performance. Our simulation results demonstrate that HARMONIC achieves resource allocation in fewer rounds and with fewer failures. Furthermore, it effectively distributes tasks to more VCs, improving load balancing and overall system efficiency.

Developing Novel Performance Measures for Traffic Congestion Management and Operational Planning Based on Connected Vehicle Data

In this paper, the authors present their efforts in exploring a new type of traffic data, referred to as internet-connected vehicle (ICV) data, for traffic congestion management and operational planning. Most currently manufactured vehicles contain onboard GPS and cellular modules, and they constantly connect to automobile manufacturers’ clouds via cellular networks and upload their status. Some automobile manufacturers have recently redistributed the nonpersonal part of such data, such as geolocation, to third-party organizations for innovative applications. Compared with the traditional vehicle GPS data, the ICV data contain high-resolution GPS waypoints accompanied with the vehicles’ abnormal moving events (e.g., hard braking). The ICV data also have huge potential in congestion management and operational planning. They explore to identify and analyze traffic congestion on both freeways and arterials using the ICV data. The ICV data adopted for this research are redistributed by Wejo Data Service, representing 10%–15% of all moving vehicles in the Dallas–Fort Worth (DFW) area in Texas. Through one case study for a freeway segment and one for an arterial segment, new traffic performance metrics based on the characteristics of ICV data have been presented. The highlights of these efforts are as follows: (I) queue length and propagation at freeway bottlenecks can be directly measured based on where and when most internet-connected vehicles slow down and join the queue; (II) an internet-connected vehicle’s actual delay time on arterials can be directly measured according to its slow movement percentage, without assuming the nondelay travel speed; and (III) the ICV data set are also combined with the high-resolution traffic signal events to generate a ground-truth time-space diagram (TSD) on arterials—a common visualization of arterial signal performance for transportation planning and operations.

Intelligent vehicular maintenance system using IoT, Mobile application, internet-enabled vehicles and vehicular could

With the rapid increase of autonomous vehicles, safe and secure use and vehicle maintenance have become a concern for some vehicle owners. Safe and secure use of vehicles and maintenance is always essential, the current systems lack safety and security in autonomous vehicles. This paper is aimed at suggesting an autonomous maintenance system via IoT and mobile technology to indorse the safer and secure use and maintenance of autonomous vehicles. The development of cloud computing, internet-of-things, wireless sensor networks and so forth, has opened a new horizon for solving problems associated with the safer and secure use of the autonomous vehicles and their maintenance. This paper presents intelligent IoT enabled mobile application for the safer and secure use of autonomous vehicles along with the maintenance, the paper also discusses how the data from this system can be used in the vehicular cloud and support in autonomous internet-connected vehicles

Cyberphysical risks of hacked internet-connected vehicles.

The integration of automotive technology with internet connectivity promises to both dramatically improve transportation while simultaneously introducing the potential for new unknown risks. Internet-connected vehicles are like digital data because they can be targeted for malicious hacking. Unlike digital data, however, internet-connected vehicles are cyberphysical systems that physically interact with each other and their environment. As such, the extension of cybersecurity concerns into the cyberphysical domain introduces new possibilities for self-organized phenomena in traffic flow. Here we study a scenario envisioned by cybersecurity experts leading to a large number of internet-connected vehicles being suddenly and simultaneously disabled. We investigate posthack traffic using agent-based simulations and discover the critical relevance of percolation for probabilistically predicting the outcomes on a multilane road in the immediate aftermath of a vehicle-targeted cyberattack. We develop an analytic percolation-based model to rapidly assess road conditions given the density of disabled vehicles and apply it to study the street network of Manhattan (New York City, New York, USA) revealing the city's vulnerability to this particular cyberphysical attack. While a comprehensive investigation of city-scale traffic around hacked vehicles is an extremely complicated problem, we find that the statistical physics of percolation can provide an estimate of the number of vehicles that critically disrupts citywide traffic flow. Our upper-bound estimate represents a quantification of citywide traffic disruptions when multiple vehicles are hacked.

Toward an Efficient Deployment of Open Source Software in the Internet of Vehicles Field

Recent developments in communication technologies, hardware and software are facilitating the implementation of different types of intelligent networks in various environments. One such network is the Internet-connected vehicles network. Internet of Vehicles (IoV) has recently become an active area of standardization, development and research, because it has shown to improve vehicle usage, traffic efficiency, road safety, as well as drivers’ and passengers’ comfort. As vehicles are becoming more connected and smarter, they are also becoming more reliant on software built with open source software (OSS). The deployment of OSS in the IoV field is, however, erratic and does not follow a clear approach. This study overviews the different applications in IoV as well as the existing and available open source software, in order to represent the current state of how this software paradigm is being used in IoV. This study also outlines challenges that remain to be addressed if we are to facilitate the widespread deployment and prevalent implementation of open source in IoV. Finally, this study explores some potential opportunities within IoV open source software for developing different IoV applications.

Efficiency is Easy to Hack

This article focuses on the possible cyberattacks as the current generation go Internet-connected way. Connecting an appliance to the Internet provides not only the opportunity for added functions and efficiency, but also the potential for hackers to exploit security lapses. As the attack plain begins to expand and digital attacks spread and become individual, physical, or even kinetic in nature, the calculus will change. Cybersecurity experts have demonstrated that Internet-connected vehicles are vulnerable to attack by hackers. As more physical systems undergo a wave of artificial intelligence (AI)-driven automation with the driving factor being efficiency, those systems become increasingly vulnerable to attack. The article concludes that traditional engineering has long optimized for things like cost, efficiency, or simplicity. Internet-connected machines and IoT-enabled devices will allow systems to do amazing things, but they also create opportunities for bad actors to turn these systems against us.

Internet of Vehicles: From intelligent grid to autonomous cars and vehicular fogs

Recent advances in communications, controls, and embedded systems have changed the perception of a car. A vehicle has been the extension of the man’s ambulatory system, docile to the driver’s commands. It is now a formidable sensor platform, absorbing information from the environment (and from other cars) and feeding it to drivers and infrastructure to assist in safe navigation, pollution control, and traffic management. The next step in this evolution is just around the corner: the Internet of Autonomous Vehicles. Pioneered by the Google car, the Internet of Vehicles will be a distributed transport fabric capable of making its own decisions about driving customers to their destinations. Like other important instantiations of the Internet of Things (e.g. the smart building), the Internet of Vehicles will have communications, storage, intelligence, and learning capabilities to anticipate the customers’ intentions. The concept that will help transition to the Internet of Vehicles is the vehicular fog, the equivalent of instantaneous Internet cloud for vehicles, providing all the services required by the autonomous vehicles. In this article, we discuss the evolution from intelligent vehicle grid to autonomous, Internet-connected vehicles, and vehicular fog.

Nonlinear Analysis of a New Car-Following Model Based on Internet-Connected Vehicles

Nonlinear Analysis of a New Car-Following Model Based on Internet-Connected Vehicles

Automated on‐ramp merging control algorithm based on Internet‐connected vehicles

With the rapid development of Information and Communication Technologies, vehicular networks that communicate with each other will have an innovative application in traffic safety and congestion. This study describes a preliminary study on an automated on-ramp merging control algorithm for vehicles on freeways under condition of Internet-connected vehicles. On the basis of vehicular operation characteristics during the merging process analysis, a cooperative driving algorithm based on Internet of vehicles was designed to achieve ramp merging without collision. Then two on-ramp merging cases, including one vehicle and two vehicles merging into the platoon on main lane, were discussed in detail. Simulation works were carried out and the results proved that the on-ramp merging algorithm was effective, but the vehicle following the leading vehicle on ramp lane is disturbed seriously by the leading vehicle. At the same time, the simulation results also showed the scenario that merging a platoon into the two vehicles on main lane affects the traffic flow more seriously than letting each individual vehicle on ramp lane consecutively to merge in between the two vehicles in the main lane under the same initial condition.