Vehicular Fog Computing Enabled Real-time Collision Warning via Trajectory Calibration

Vehicular fog computing (VFC) has been envisioned as a promising paradigm for enabling a variety of emerging intelligent transportation systems (ITS). However, due to inevitable as well as non-negligible issues in wireless communication, including transmission latency and packet loss, it is still challenging in implementing safety-critical applications, such as real-time collision warning in vehicular networks. In this paper, we present a vehicular fog computing architecture, aiming at supporting effective and real-time collision warning by offloading computation and communication overheads to distributed fog nodes. With the system architecture, we further propose a trajectory calibration based collision warning (TCCW) algorithm along with tailored communication protocols. Specifically, an application-layer vehicular-to-infrastructure (V2I) communication delay is fitted by the Stable distribution with real-world field testing data. Then, a packet loss detection mechanism is designed. Finally, TCCW calibrates real-time vehicle trajectories based on received vehicle status including GPS coordinates, velocity, acceleration, heading direction, as well as the estimation of communication delay and the detection of packet loss. For performance evaluation, we build the simulation model and implement conventional solutions including cloud-based warning and fog-based warning without calibration for comparison. Real-vehicle trajectories are extracted as the input, and the simulation results demonstrate that the effectiveness of TCCW in terms of the highest precision and recall in a wide range of scenarios

Models and Performance of VANET based Emergency Braking

The network research community is working in the field of automotive to provide VANET based safety applications to reduce the number of accidents, deaths, injuries and loss of money. Several approaches are proposed and investigated in VANET literature, but in a completely network-oriented fashion. Most of them do not take into account application requirements and no one considers the dynamics of the vehicles. Moreover, message repropagation schemes are widely proposed without investigating their benefits and using very complicated approaches. This technical report, which is derived from the Master Thesis of Michele Segata, focuses on the Emergency Electronic Brake Lights (EEBL) safety application, meant to send warning messages in the case of an emergency brake, in particular performing a joint analysis of network requirements and provided application level benefits. The EEBL application is integrated within a Collaborative Adaptive Cruise Control (CACC) which uses network-provided information to automatically brake the car if the driver does not react to the warning. Moreover, an information aggregation scheme is proposed to analyze the benefits of repropagation together with the consequent increase of network load. This protocol is compared to a protocol without repropagation and to a rebroadcast protocol found in the literature (namely the weighted p-persistent rebroadcast). The scenario is a highway stretch in which a platoon of vehicles brake down to a complete stop. Simulations are performed using the NS_3 network simulation in which two mobility models have been embedded. The first one, which is called Intelligent Driver Model (IDM) emulates the behavior of a driver trying to reach a desired speed and braking when approaching vehicles in front. The second one (Minimizing Overall Braking Induced by Lane change (MOBIL)), instead, decides when a vehicle has to change lane in order to perform an overtake or optimize its path. The original simulator has been modified by - introducing real physical limits to naturally reproduce real crashes; - implementing a CACC; - implementing the driver reaction when a warning is received; - implementing different network protocols. The tests are performed in different situations, such as different number of lanes (one to five), different average speeds, different network protocols and different market penetration rates and they show that: - the adoption of this technology considerably decreases car accidents since the overall average maximum deceleration is reduced; - network load depends on application-level details, such as the implementation of the CACC; - VANET safety application can improve safety even with a partial market penetration rate; - message repropagation is important to reduce the risk of accidents when not all vehicles are equipped; - benefits are gained not only by equipped vehicles but also by unequipped ones

Managed information gathering and fusion for transient transport problems

This paper deals with vehicular traffic management by communication technologies from Traffic Control Center point of view in road networks. The global goal is to manage the urban traffic by road traffic operations, controlling and interventional possibilities in order to minimize the traffic delays and stops and to improve traffic safety on the roads. This paper focuses on transient transport, when the controlling management is crucial. The aim was to detect the beginning time of the transient traffic on the roads, to gather the most appropriate data and to get reliable information for interventional suggestions. More reliable information can be created by information fusion, several fusion techniques are expounded in this paper. A half-automatic solution with Decision Support System has been developed to help with engineers in suggestions of interventions based on real time traffic data. The information fusion has benefits for Decision Support System: the complementary sensors may fill the gaps of one another, the system is able to detect the changing of the percentage of different vehicle types in traffic. An example of detection and interventional suggestion about transient traffic on transport networks of a little town is presented at the end of the paper. The novelty of this paper is the gathering of information - triggered by the state changing from stationer to transient - from ad hoc channels and combining them with information from developed regular channels. --information gathering,information fusion,Kalman filter,transient traffic,Decision Support System

An Overview of Vehicular Communications

The transport sector is commonly subordinate to several issues, such as traffic congestion and accidents. Despite this, in recent years, it is also evolving with regard to cooperation between vehicles. The fundamental objective of this trend is to increase road safety, attempting to anticipate the circumstances of potential danger. Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) technologies strive to give communication models that can be employed by vehicles in different application contexts. The resulting infrastructure is an ad-hoc mesh network whose nodes are not only vehicles but also all mobile devices equipped with wireless modules. The interaction between the multiple connected entities consists of information exchange through the adoption of suitable communication protocols. The main aim of the review carried out in this paper is to examine and assess the most relevant systems, applications, and communication protocols that will distinguish the future road infrastructures used by vehicles. The results of the investigation reveal the real benefits that technological cooperation can involve in road safety. Document type: Articl

Implicit Cooperative Positioning in Vehicular Networks

Absolute positioning of vehicles is based on Global Navigation Satellite Systems (GNSS) combined with on-board sensors and high-resolution maps. In Cooperative Intelligent Transportation Systems (C-ITS), the positioning performance can be augmented by means of vehicular networks that enable vehicles to share location-related information. This paper presents an Implicit Cooperative Positioning (ICP) algorithm that exploits the Vehicle-to-Vehicle (V2V) connectivity in an innovative manner, avoiding the use of explicit V2V measurements such as ranging. In the ICP approach, vehicles jointly localize non-cooperative physical features (such as people, traffic lights or inactive cars) in the surrounding areas, and use them as common noisy reference points to refine their location estimates. Information on sensed features are fused through V2V links by a consensus procedure, nested within a message passing algorithm, to enhance the vehicle localization accuracy. As positioning does not rely on explicit ranging information between vehicles, the proposed ICP method is amenable to implementation with off-the-shelf vehicular communication hardware. The localization algorithm is validated in different traffic scenarios, including a crossroad area with heterogeneous conditions in terms of feature density and V2V connectivity, as well as a real urban area by using Simulation of Urban MObility (SUMO) for traffic data generation. Performance results show that the proposed ICP method can significantly improve the vehicle location accuracy compared to the stand-alone GNSS, especially in harsh environments, such as in urban canyons, where the GNSS signal is highly degraded or denied.Comment: 15 pages, 10 figures, in review, 201