Search Results (25)

Red-light running at signalised intersections poses a significant safety risk, necessitating advanced predictive technologies to predict red-light violation behaviour, especially for advanced red-light warning (ARLW) systems. This research leverages Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models to forecast the red-light running and stopping behaviours of drivers in connected vehicles. We utilised data from the Ipswich Connected Vehicle Pilot (ICVP) in Queensland, Australia, which gathered naturalistic driving data from 355 connected vehicles at 29 signalised intersections. These vehicles broadcast Cooperative Awareness Messages (CAM) within the Cooperative Intelligent Transport Systems (C-ITS), providing kinematic inputs such as vehicle speed, speed limits, longitudinal and lateral accelerations, and yaw rate. These variables were monitored at 100-millisecond intervals for durations from 1 to 4 s before reaching various distances from the stop line. Our results indicate that the LSTM model outperforms the GRU in predicting both red-light running and stopping behaviours with high accuracy. However, the pre-trained GRU model performs better in predicting red-light running specifically, making it valuable in applications requiring early violation prediction. Implementing these models can enhance red-light violation countermeasures, such as dynamic all-red extension (DARE), decreasing the likelihood of severe collisions and enhancing road users’ safety. Full article

This paper examines the impact of Vehicle-to-Everything (V2X) communications on vehicle cooperation, focusing on increasing the robustness and feasibility of Cooperative, Connected, and Automated Vehicles (CCAVs). V2X communications enable CCAVs to obtain a holistic environmental perception, facilitating informed decision making regarding their trajectory. This technological innovation is essential to mitigate accidents resulting from inadequate or absent communication on the roads. As the importance of vehicle cooperation grows, the European Telecommunications Standards Institute (ETSI) has been standardizing messages and services for V2X communications, in order to improve the synchronization of CCAVs actions. In this context, this preliminary work explores the use of Maneuver Coordination Messages (MCMs), under standardization by ETSI, for cooperative path planning. This work presents a novel approach by implementing these messages as well as the associated Maneuver Coordination Service (MCS) with a Cooperative Driving System to process maneuver coordination. Additionally, a trajectory approach is introduced along with a message generation mechanism and a process to dynamically handle collisions. This was implemented in an Artery V2X simulation framework combining both network communications and SUMO traffic simulations. The obtained results demonstrate the effectiveness of using V2X communications to ensure the safety and efficiency of Cooperative Intelligent Transportation Systems (C-ITS). Full article

With the deployment of cooperative intelligent transportation systems (C-ITSs), the telecommunication systems and their performance occupy a key position in ensuring safe, robust, and resilient services to the end-users. Regardless of the adopted protocol, adequate road network coverage might affect the service performance, in terms of traffic and environmental efficiency. In this study, we analyze the traffic efficiency and emission pollutant sensitivity to the location of ad hoc network antennas when the C-ITS services disseminate dynamic messages to control the speed limit and ensure sustainable mobility. We design the experimentation with short-range communication resulting from an ad hoc network and requiring Roadside Units (RSUs) along the road to broadcast messages within their communication range to the end-user. The performance variability according to the RSUs’ location and effective road network coverage are highlighted through our microscopic simulation-based experimentations. This paper develops a sensitivity analysis to evaluate the impact of the network mesh according to the C-ITS service under consideration. Focus is placed on the variable speed limit (VSL) service, controlling upstream speed to restrict congestion and ensure more sustainable mobility. The results show that, while the traffic efficiency improves even at a low market penetration rate (MPR) of the connected vehicles, the environmental efficiency improves only at a high MPR. From the telecommunication perspective, an expansive broadcast strategy appears to be more effective than the conservative approach. Full article

Bluetooth Low Energy (BLE) is a prominent short-range wireless communication protocol widely extended for communications and sensor systems in consumer electronics and industrial applications, ranging from manufacturing to retail and healthcare. The BLE protocol provides four generic access profile (GAP) roles when it is used in its low-energy version, i.e., ver. 4 and beyond. GAP roles control connections and allow BLE devices to interoperate each other. They are defined by the Bluetooth special interest group (SIG) and are primarily oriented to connect peripherals wirelessly to smartphones, laptops, and desktops. Consequently, the existing GAP roles have characteristics that do not fit well with vehicular communications in cooperative intelligent transport systems (C-ITS), where low-latency communications in high-density environments with stringent security demands are required. This work addresses this gap by developing two new GAP roles, defined at the application layer to meet the specific requirements of vehicular communications, and by providing a service application programming interface (API) for developers of vehicle-to-everything (V2X) applications. We have named this new approach ITS-BLE. These GAP roles are intended to facilitate BLE-based solutions for real-world scenarios on roads, such as detecting road traffic signs or exchanging information at toll booths. We have developed a prototype able to work indistinctly as a unidirectional or bidirectional communication device, depending on the use case. To solve security risks in the exchange of personal data, BLE data packets, here called packet data units (PDU), are encrypted or signed to guarantee either privacy when sharing sensitive data or authenticity when avoiding spoofing, respectively. Measurements taken and their later evaluation demonstrated the feasibility of a V2X BLE network consisting of picocells with a radius of about 200 m. Full article

Cooperative Intelligent Transport Systems (C-ITS) address contemporary transportation challenges, as Connected Vehicles (CVs) can play a pivotal role in enhancing efficiency and safety. The role of central governing authorities in shaping traffic management policies for CVs influences decision-making processes and system performance. In this work, the role of central governing authorities in the traffic management of a mixed traffic network is examined, integrating System Optimum principles with game theory. More specifically, we introduce and develop a framework that models and analyses the strategic interactions between different stakeholders in a mixed traffic environment, considering central governing authorities with varying levels of control. The results indicate how the various levels of control of a central governing authority may have an impact on the network in terms of traffic measures. Through a strategic games analysis, the trade-offs associated with centralized control mechanisms are demonstrated and recommendations are offered for policymakers and practitioners to optimize traffic management strategies. Full article

Cooperative communications advancements in Vehicular-to-Everything (V2X) are bolstering the autonomous driving paradigm. V2X nodes are connected through communication technology, such as a short-range communication mode (Dedicated Short Range Communication (DSRC) and Cellular-V2X) or a long-range communication mode (Uu). Conventional vehicular networks employ static wireless vehicular communication technology without considering the traffic load on any individual V2X communication technology and the traffic dynamics in the vicinity of the V2X node, and are hence inefficient. In this study, we investigate hybrid V2X communication and propose an autonomous and intelligent technology selection algorithm using a decision tree. The algorithm uses the information from the received Cooperative Intelligent Transport Systems (C-ITS) Cooperative Awareness Messages (CAMs) to collect statistics such as inter vehicular distance, one-way end-to-end latency and CAM density. These statistics are then used as input for the decision tree for selecting the appropriate technology (DSRC, C-V2X PC5 or 5G) for the subsequent scheduled C-ITS message transmission. The assessment of the intelligent hybrid V2X algorithm’s performance in our V2X test setup demonstrates enhancements in one-way end-to-end latency, reliability, and packet delivery rate when contrasted with the conventional utilization of static technology. Full article

A connected vehicle (CV) enables vehicles to communicate not only with other vehicles but also the road infrastructure based on wireless communication technologies. A road system with CVs, which is often referred to as a cooperative intelligent transportation system (C-ITS), provides drivers with road and traffic condition information using an in-vehicle warning system. Road environments with CVs induce drivers to reduce their speed while increasing the spacing or changing lanes to avoid potential risks downstream. Such avoidance maneuvers can be considered to improve driving behavior from a traffic safety point of view. This study seeks to quantitatively evaluate the effect of in-vehicle warning information using per-vehicle data (PVD) collected from freeway C-ITSs. The PVD are reproduced to extract the speed–spacing relationship and are evaluated to determine whether the warning information induces drivers to drive in a conservative way. This study reveals that the in-vehicle warning prompts drivers to increase the spacing while decreasing their speed in the majority of samples. The rate of conservative driving behavior tends to increase during the initial operation period, but no significant changes were observed after this period; that is, the reliability of in-vehicle warning information is not constant in the CV environment. Full article

Cooperative intelligent transport systems (C-ITS) continue to be developed to enhance transportation safety and sustainability. However, the communication of vehicle-to-everything (V2X) systems is inherently open, leading to vulnerabilities that attackers can exploit. This represents a threat to all road users, as security failures can lead to privacy violations or even fatalities. Moreover, a high fatality rate is correlated with soft-mobility road users. Therefore, when developing C-ITS systems, it is important to broaden the focus beyond connected vehicles to include soft-mobility users and legacy vehicles. This work presents a new approach developed in the context of emerging hybrid networks, combining intelligent transport systems operating in 5.9 GHz (ITS-G5) and radio-mobile cellular technologies. Two protocols were implemented and evaluated to introduce security guarantees (such as privacy and integrity) in communications within the developed C-ITS hybrid environment. As a result, this work securely integrates G5-connected ITS stations and soft-mobility users through a smartphone application via cellular networks. Commercial equipment was used for this goal, including on-board and roadside units. Computational, transmission and end-to-end latency were used to assess the system’s performance. Implemented protocols introduce an additional 11% end-to-end latency in hybrid communications. Moreover, workflows employing hybrid communications impose, on average, an extra 28.29 ms of end-to-end latency. The proposal shows promise, as it reaches end-to-end times below the latency requirements imposed in most C-ITS use cases. Full article

Connected and automated vehicles (CAVs) will be a key component of future cooperative intelligent transportation systems (C-ITS). Since the adoption of C-ITS is not foreseen to happen instantly, not all of its elements are going to be connected at the early deployment stages. We consider a scenario where vehicles approaching a traffic light are connected to each other, but the traffic light itself is not cooperative. Information about indented trajectories such as decisions on how and when to accelerate, decelerate and stop, is communicated among the vehicles involved. We provide an optimization-based procedure for efficient and safe passing of traffic lights (or other temporary road blockage) using vehicle-to-vehicle communication (V2V). We locally optimize objectives that promote efficiency such as less deceleration and larger minimum velocity, while maintaining safety in terms of no collisions. The procedure is computationally efficient as it mainly involves a gradient decent algorithm for one single parameter. Full article

Cooperative intelligent transport systems (C-ITSs) are being deployed all around the world. Shortly, in addition to vehicles, bicycles, pedestrians, buses, and all moving equipment will be compatible with C-ITS. These systems are connected through wireless local area networks based on WIFI IEEE 802.11p. The large number of C-ITSs and services will lead to a glut in the bandwidth of wireless networks. To overcome this limitation, we propose in this paper a new approach using the information-centric networking (ICN) paradigm which allows vehicles to communicate with the cloud environment. This scheme is denoted by vehicular central data networking (GeoVCDN). Our approach aims to reduce bandwidth consumption and improve data freshness by taking benefit from the existing application beacons and the geographical routing used by C-ITS actors. We have compared the performances (in terms of the network overhead and data freshness) of our solution to two other well-known ICN-based solutions. Each of them represents one of ICN categories, in particular, rendez-vous network (RENE) and named data networking (NDN). To do so, we have proposed a probabilistic model that allows us to evaluate the freshness and the load of the network. Furthermore, we have implemented these methods in a simulator. Our proposal outperforms the other methods in terms of network overhead and data freshness. Full article

Road infrastructure plays a critical role in the support and development of the Cooperative Intelligent Transport Systems (C-ITS) paradigm. Roadside Units (RSUs), equipped with vehicular communication capabilities, traffic radars, cameras, and other sensors, can provide a multitude of vehicular services and enhance the cooperative perception of vehicles on the road, leading to increased road safety and traffic efficiency. Moreover, the central C-ITS system responsible for overseeing the road traffic and infrastructure, such as the RSUs, needs an efficient way of collecting and disseminating important information to road users. Warnings of accidents or other dangers, and other types of vehicular services such as Electronic Toll Collection (ETC), are examples of the types of information that the central C-ITS system is responsible for disseminating. To remedy these issues, we present the design of an implemented roadside and cloud architecture for the support of C-ITS services. With the main objectives of managing Vehicle-to-Everything (V2X) communication units and network messages of a public authority or motorway operator acting as a central C-ITS system, the proposed architecture was developed for different mobility testbeds in Portugal, under the scope of the STEROID research project and the pan-European Connected Roads (C-Roads) initiative. RSUs, equipped with ETSI ITS-G5 communications, are deployed with a cellular link or fiber optics connection for remote control and configuration. These are connected to a cloud Message Queuing Telemetry Transport (MQTT) broker where communication is based on a geographical tiling scheme, which allows the selection of the appropriate coverage areas for the dissemination of C-ITS messages. The architecture is deployed in the field, on several Portuguese motorways, where road traffic and infrastructure are monitored through a C-ITS platform with visualization and event reporting capabilities. The provided architecture is independent of the underlying communication technology and can be easily adapted in the future to support Cellular-V2X (PC5 interface) or 5G RSUs. Performance results of the deployed architecture are provided. Full article

The growth of the automobile industry in recent decades and the overuse of personal vehicles have amplified problems directly related to road safety, such as the increase in traffic congestion and number of accidents, as well as the degradation of the quality of roads. At the same time, and with the contribution of climate change effects, dangerous weather events have become more common on road infrastructure. In this context, Cooperative Intelligent Transport Systems (C-ITS) and Internet of Things (IoT) solutions emerge to overcome the limitations of human and local sensory systems, through the collection and distribution of relevant data to Connected and Automated Vehicles (CAVs). In this paper, an intra- and inter-vehicle sensory data collection system is presented, starting with the acquisition of relevant data present on the Controller Area Network (CAN) bus, collected through the vehicle’s On-Board-Diagnostics II (OBD-II) port, as well as on an on-board smartphone device and possibly other additional sensors. Short-range communication technologies, such as Bluetooth Low Energy (BLE), Wi-Fi, and ITS-G5, are employed in conjunction with long-range cellular networks for data dissemination and remote cloud monitoring. The results of the experimental tests allow the analysis of the road environment, as well as the notification in near real-time of adverse road conditions to drivers. The developed data collection system reveals itself as a potentially valuable tool for improving road safety and to iterate on the current Road Weather Models (RWMs). Full article

(1) Background: Cooperative Intelligent Transportation Systems (C-ITS) will soon operate using 5G New-Radio (NR) wireless communication, overcoming the limitations of the current V2X (Vehicle-to-Everything) wireless communication technologies and increasing road-safety and driving efficiency. These innovations will also change the RF exposure levels of pedestrians and road-users in general. These people, in fact, will be exposed to additional RF sources coming from nearby cars and from the infrastructure. Therefore, an exposure assessment of people in the proximity of a connected car is necessary and urgent. (2) Methods: Two array antennas for 5G-V2X communication at 3.5 GHz were modelled and mounted on a realistic 3D car model for evaluating the exposure levels of a human model representing people on the road near the car. Computational simulations were conducted using the FDTD solver implemented in the Sim4Life platform; different positions and orientations between the car and the human model were assessed. The analyzed quantities were the Specific Absorption Rate on the whole body (SAR_wb), averaged over 10 g (SAR_10g) in specific tissues, as indicated in the ICNIRP guidelines. (3) Results: the data showed that the highest exposure levels were obtained mostly in the head area of the human model, with the highest peak obtained in the configuration where the main beam of the 5G-V2X antennas was more direct towards the human model. Moreover, in all configurations, the dose absorbed by a pedestrian was well below the ICNIRP guidelines to avoid harmful effects. (4) Conclusions: This work is the first study on human exposure assessment in a 5G-V2X scenario, and it expands the knowledge about the exposure levels for the forthcoming use of 5G in connected vehicles. Full article

The adoption of cooperative intelligent transportation systems (cITSs) improves road safety and traffic efficiency. Vehicles connected to cITS form vehicular ad hoc networks (VANET) to exchange messages. Like other networks and systems, cITSs are targeted by attackers intent on compromising and disrupting system integrity and availability. They can repeatedly spoof false information causing bottlenecks, traffic jams and even road accidents. The existing security infrastructure assumes that the network topology and/or attack behavior is static. However, the cITS is inherently dynamic in nature. Moreover, attackers may have the ability and resources to change their behavior continuously. Assuming a static IDS security model for VANETs is not suitable and can lead to low detection accuracy and high false alarms. Therefore, this paper proposes an adaptive security solution based on deep learning and contextual references that can cope with the dynamic nature of the cITS topologies and increasingly common attack behaviors. In this study, deep belief networks (DBN) modeling was used to train the detection model. Binary cross entropy was used as a loss function to measure the prediction error. Two activation functions were used, Relu and Softmax, for input–output mapping. The Relu was used in the hidden layers, while the Sigmoid was used in the last layer to map the real vector to output between 0 and 1. The adaptation mechanism was incorporated into the detection model using a moving average that monitors predicted values within a time window. In this way, the model can readjust the classification thresholds on-the-fly as appropriate. The proposed model was evaluated using the Next Generation Simulation (NGSIM) dataset, which is commonly used in such related works. The result is improved accuracy, demonstrating that the adaptation mechanism used in this study was effective. Full article

The safety of urban transportation systems is considered a public health issue worldwide, and many researchers have contributed to improving it. Connected automated vehicles (CAVs) and cooperative intelligent transportation systems (C-ITSs) are considered solutions to ensure the safety of urban transportation systems using various sensors and communication devices. However, realizing a data flow framework, including data collection, data transmission, and data processing, in South Korea is challenging, as CAVs produce a massive amount of data every minute, which cannot be transmitted via existing communication networks. Thus, raw data must be sampled and transmitted to the server for further processing. The data acquired must be highly accurate to ensure the safety of the different agents in C-ITS. On the other hand, raw data must be reduced through sampling to ensure transmission using existing communication systems. Thus, in this study, C-ITS architecture and data flow are designed, including messages and protocols for the safety monitoring system of CAVs, and the optimal sampling interval determined for data transmission while considering the trade-off between communication efficiency and accuracy of the safety performance indicators. Three safety performance indicators were introduced: severe deceleration, lateral position variance, and inverse time to collision. A field test was conducted to collect data from various sensors installed in the CAV, determining the optimal sampling interval. In addition, the Kolmogorov–Smirnov test was conducted to ensure statistical consistency between the sampled and raw datasets. The effects of the sampling interval on message delay, data accuracy, and communication efficiency in terms of the data compression ratio were analyzed. Consequently, a sampling interval of 0.2 s is recommended for optimizing the system’s overall efficiency. Full article