Cooperative Intelligent Transport Systems Research Articles

Methodology of Functional and Technical Evaluation of Cooperative Intelligent Transport Systems and Its Practical Application

In the area of smart cities, great emphasis is placed on many different fields such as energetics, information systems, and transportation. All of these should lead to a simplification of life thanks to smart technologies. If we talk about the transportation field, the main issues related to this area are safety, traffic efficiency, or the environment. Another condition is the successful acceptance of any new technology by its users. Cooperative systems prove to be a suitable solution for these issues, especially in urban areas. Today, pilot implementations of cooperative systems in European countries are being carried out. However, before they are put into full operation, they need to be tested, evaluated, and assessed. This article focuses on the latter two points, i.e., evaluation and assessment of the cooperative systems. For this purpose, a methodology was created, which describes the procedure chosen in the evaluation and assessment of cooperative systems in the Czech Republic and a demonstration of its use by example. The methodology is focused on three main areas, which in this case are functional evaluation, user acceptance, and impact assessment. For the area of user acceptance, the main source was questionnaires, impact assessment relied on measured data while functional evaluation was based on discussions with the drivers, evaluating the cooperative systems, the measured data, and the expert observations. All collected and measured data were then processed and some of the results of the evaluation of the selected service are presented at the end of this article.

Traffic Control Scheme for Social Optimum Traffic Assignment with Dynamic Route Pricing for Automated Vehicles

In transportation modeling, after defining a road network and its origin-destination (OD) matrix, the next important question is how to assign traffic among OD-pairs. Nowadays, advanced traveler information systems (ATIS) make it possible to realize the user equilibrium solution. Simultaneously, with the advent of the Cooperative Intelligent Transport Systems (C-ITS), it is possible to solve the traffic assignment problem in a system optimum way. As a potential traffic assignment method in the future transportation system for automated cars, the deterministic system optimum (DSO) is modeled and simulated to investigate the potential changes it may bring to the existing traditional traffic system. In this paper, stochastic user equilibrium (SUE) is used to simulate the conventional traffic assignment method. This work concluded that DSO has considerable advantages in reducing trip duration, time loss, waiting time, and departure delay under the same travel demand. What is more, the SUE traffic assignment has a more dispersed vehicle density distribution. Moreover, DSO traffic assignment helps the maximum vehicle density of each alternative path arrive almost simultaneously. Furthermore, DSO can significantly reduce or avoid the occurrence of excessive congestion.

Machine learning-based radio access technology selection in the Internet of moving things

The Internet of Moving Things (IoMT) takes a step further with respect to traditional static IoT deployments. In this line, the integration of new eco-friendly mobility devices such as scooters or bicycles within the Cooperative-Intelligent Transportation Systems (C-ITS) and smart city ecosystems is crucial to provide novel services. To this end, a range of communication technologies is available, such as cellular, vehicular WiFi or Low-Power Wide-Area Network (LPWAN); however, none of them can fully cover energy consumption and Quality of Service (QoS) requirements. Thus, we propose a Decision Support System (DSS), based on supervised Machine Learning (ML) classification, for selecting the most adequate transmission interface to send a certain message in a multi-Radio Access Technology (RAT) set up. Different ML algorithms have been explored taking into account computing and energy constraints of IoMT enddevices and traffic type. Besides, a real implementation of a decision tree-based DSS for micro-controller units is presented and evaluated. The attained results demonstrate the validity of the proposal, saving energy in communication tasks as well as satisfying QoS requirements of certain urgent messages. The footprint of the real implementation on an Arduino Uno is 444 bytes and it can be executed in around 50 µs.

Cooperation between Roads and Vehicles: Field Validation of a Novel Infrastructure-Based Solution for All Road Users’ Safety

Cooperative intelligent transport systems (C-ITS) are expected to considerably influence road safety, traffic efficiency and comfort. Nevertheless, their market penetration is still limited, on the one hand due to the high costs of installation and maintenance of the infrastructures and, on the other hand, due to the price of support automated driving functions. A breakthrough C-ITS technological solution was studied, designed, built and tested that is based on the implementation of custom low-cost on-road platforms (named “strips”) that embed micro/nano sensors, communication technologies and energy harvesting to shift intelligence from the vehicle to the road infrastructure. The strips, through a V2X and LTE communication gateway, transmit real-time, reliable and accurate information at lane level about the environmental and road condition, the traffic and the other road users’ position and speed. The exchanged information supports a series of C-ITS functions and services extending equipped vehicles capabilities and providing similar functions to non-equipped ones (including powered two wheelers). The general framework and the technological solution proposed is presented and the results of the field trials, conducted in three pilot sites around Europe, quantify the promising system performance as well as the positive effects of the C-ITS applications developed and tested on driver/rider’s behavior.

Impact of Safety Message Generation Rules on the Awareness of Vulnerable Road Users.

In the face of cooperative intelligent transportation systems (C-ITS) advancements, the inclusion of vulnerable road users (VRU), i.e., pedestrians, cyclists, and motorcyclists, has just recently become a part of the discussion. Including VRU in C-ITS presents new challenges, most notably the trade-off between the increase in VRU safety and the aggravation in channel congestion resulting from VRU-generated messages. However, previous studies mainly focus on network-related metrics without giving much consideration to VRU safety-related metrics. In this context, we evaluated such a trade-off with a study of motion-based message generation rules for VRU transmissions. The rules were analyzed using theoretical and simulation-based evaluations. In addition to studying the message generation rules using channel load metrics, such as channel busy ratio (CBR) and packet delivery ratio (PDR), we introduced a new metric: the VRU Awareness Probability (VAP). VAP uses the exchange of messages from active VRU to measure the probability of VRU detection by nearby vehicles. Results show that fixed message-filtering mechanisms reduce the overall channel load, but they could negatively impact VRU detection. We established the importance of quantifying the VRU awareness and its inclusion in C-ITS analysis because of its direct impact on VRU safety. We also discussed approaches that include VRU context and dynamism to improve the definition of message generation rules.

C‐ITS road‐side unit deployment on highways with ITS road‐side systems: A techno‐economic approach

Connectivity and cooperation are considered important prerequisites to automated driving, as they are crucial elements in increasing the safety of future automated vehicles and their full integration in the overall transport system. Although many European Member States, as part of the C-Roads Platform, have implemented and are still implementing Road-side Units (RSUs) for Cooperative Intelligent Transportation Systems (C-ITS) within pilot deployment projects, the platform aspires a wide extension of deployments in the coming years. Therefore, this paper investigates techno-economic aspects of C-ITS RSU deployments from a road authority viewpoint. A two-phased approach is used, in which firstly the optimal RSU locations are determined, taking into account existing road-side infrastructure. Secondly, a cost model translates the amount of RSUs into financial results. It was found that traffic density has a significant impact on required RSU density, hence impacting costs. Furthermore, major cost saving can be obtained by leveraging existing road-side infrastructure. The proposed methodology is valuable for other member states, and in general, to any other country aspiring to roll out C-ITS road infrastructure. Results can be used to estimate required investment costs based on legacy infrastructure, as well as to benchmark with the envisioned benefits from the deployed C-ITS services.

Performance analysis of vehicle-to-vehicle communications based on organic light emitting diodes and discrete multitone modulation

We provide a numerical model to investigate the performance of a visible light communication-based vehicle-to-vehicle (V2V) communication system that incorporates organic light emitting diode (OLED) transmitters and discrete multitone modulation to overcome the bandwidth limitations of the organic devices. Different application scenarios using vehicle’s headlights and taillights as optical transmitters are considered. The results indicate the potential of using OLEDs for cooperative intelligent transportation system applications to achieve transmission of low-to-moderate data rates, providing evidence that the proposed OLED-based V2V system can achieve data communication of several Mbps. In the scenario that involves transmitting data to the leading car using the OLED headlights as transmitters, we show that the data rate can exceed 5 Mbps, despite the low modulation bandwidth of the OLED. When transmitting data to the trailing car using the taillights, we show that the transmission rate can reach 2 Mbps. We also discuss the trade-off between vehicle distance and communication performance and show that, even for distances up to 40 m, data rates on the order of several hundred kbps can be supported.

Enhanced Protective System For Children In School Transportation

The higher number of vehicles on the roads increase in the number of road accidents worldwide. And these problems are considered as major public safety problem. A major part of providing a quality education to every children is ensuring their safety during transportation from their home to school. Thus, we have developed a smart and effective school bus system for the safety of children while transportation. This paper discusses about the hardware-based smart and effective school bus system for ensuring and monitoring the safety of school-going children through school bus. In this project, vehicles are considered as the main key enabling technology to improve children safety and the emergence of next-generation cooperative intelligent transport systems (ITS). In ITS, network services and applications (e.g., safety messages) will require event location information. Faster and efficient routing protocols could play a vital role in the applications of ITS, safe guarding both the driver and the children and thus maintaining a safe on-road environment. In this project, an intelligent transportation system (ITS) is designed to monitor real evacuation tests where an emergency event has been simulated and experimented and a general methodology is reported with the description of the main models and procedures. Models are calibrated and validated employing observed data obtained from ITS.

Synthetic Data generation using DCGAN for improved traffic sign recognition

Traffic sign detection and recognition perform a vital function in real-world driver guidance applications, including driver assistance systems. Research into vision-based traffic sign detection (TSD) and traffic sign recognition (TSR) has gained considerable attention in the scientific community, led mainly by three variables: identification, monitoring, and classification. In addition, TSR provides valuable details and alerts for smart cars including advanced driving assistance (ADAS) and cooperative intelligent transport systems (CITS). Our work will generate high-quality synthetic prohibitory sign images using deep convolutional generative adversarial networks (DCGAN). This paper analyzes and discusses CNN models incorporating different backbone architectures and feature extractors, focusing on Resnet 50 and Densenet for object detection. Assessment of the models provides important information, including mean average accuracy (mAP), workspace capacity, detection period, and the amount of billion floating-point operations (BFLOPS). The maximum average accuracy is 92% (Densenet DCGAN), led by 91% (Resnet 50 DCGAN), 88% (Densenet), and 63% (Resnet 50). We find when using the original image and a synthetic image, accuracy increases, while detection time falls. Our findings show that combining original images and synthetic images in the dataset for training can improve intersection over union (IoU) and traffic sign recognition performance.

Road Design Criteria and Capacity Estimation Based on Autonomous Vehicles Performances. First Results from the European C-Roads Platform and A22 Motorway

Abstract Several European road operators and authorities joined the C-Roads Platform with the aim of harmonising the deployment activities of cooperative intelligent transport systems (C-ITS). C-ITS research is preliminary to future automated-driving vehicles. The current conventional highways were designed on traditional criteria and models specifically developed for traffic flows of manually guided vehicles. Thus, this article describes some new criteria for designing and monitoring road infrastructures on the basis of performance features of autonomous (or self-driving) vehicles. The new criteria have been adopted to perform an accurate conformity control of the A22 Brenner motorway, included in the C-Roads Platform, and also to ascertain whether in future it may be travelled by automated vehicles in safety conditions. Always in accordance with the technical and scientific insights required by the C-Roads Platform, a traffic model has been implemented to estimate how the A22 capacity increases compared to current values, by taking various percentages of automated or manual vehicles into consideration. The results given by theoretical models indicate that the highway will be able to be travelled by automated vehicles in safety conditions. On the other hand, the lane capacity is due to increase up to 2.5 times more than the current capacities, experimentally determined through traffic data collected from 4 highway sections by means of Drake’s flow model.

C-V2X Communications for the Support of a Green Light Optimized Speed Advisory (GLOSA) Use Case

Rapid expansion of 5G affects a number of sectors, including vehicular communications relying on cooperative intelligent transportation systems (C-ITS). More specifically, in the context of the Internet of Vehicles (IoV), a particular emphasis is placed on modern cellular V2X (C-V2X) technologies aiming to further improve road safety. This work originates from the detailed scope of the ongoing 5G-DRIVE research project promoting cooperation between the EU and China, with the aim of demonstrating IoV services that rely on vehicle-to-infrastructure (V2I) communications. With the C-V2X approach serving as a point of departure, we analyze and describe a specific green light-optimized speed advisory (GLOSA) use case, for which we provide a detailed descriptive framework, a proposed architectural framework for trials, as well as specific KPIs for the joint assessment of trials between the EU and China. We also discuss the context for performance test procedures to be conducted as part of the intended trials. GLOSA provides end-users with short-term information on upcoming traffic light status to optimize traffic flows, help prevent speed limit violations, improve fuel efficiency, and reduce pollution

Vehicular Communication Management Framework: A Flexible Hybrid Connectivity Platform for CCAM Services

In the upcoming decade and beyond, the Cooperative, Connected and Automated Mobility (CCAM) initiative will play a huge role in increasing road safety, traffic efficiency and comfort of driving in Europe. While several individual vehicular wireless communication technologies exist, there is still a lack of real flexible and modular platforms that can support the need for hybrid communication. In this paper, we propose a novel vehicular communication management framework (CAMINO), which incorporates flexible support for both short-range direct and long-range cellular technologies and offers built-in Cooperative Intelligent Transport Systems’ (C-ITS) services for experimental validation in real-life settings. Moreover, integration with vehicle and infrastructure sensors/actuators and external services is enabled using a Distributed Uniform Streaming (DUST) framework. The framework is implemented and evaluated in the Smart Highway test site for two targeted use cases, proofing the functional operation in realistic environments. The flexibility and the modular architecture of the hybrid CAMINO framework offers valuable research potential in the field of vehicular communications and CCAM services and can enable cross-technology vehicular connectivity.

Standards-Compliant Multi-Protocol On-Board Unit for the Evaluation of Connected and Automated Mobility Services in Multi-Vendor Environments.

Vehicle-to-everything (V2X) communications enable real-time information exchange between vehicles and infrastructure, which extends the perception range of vehicles beyond the limits of on-board sensors and, thus, facilitating the realisation of cooperative, connected, and automated mobility (CCAM) services that will improve road safety and traffic efficiency. In the context of CCAM, the successful deployments of cooperative intelligent transport system (C-ITS) use cases, with the integration of advanced wireless communication technologies, are effectively leading to make transport safer and more efficient. However, the evaluation of multi-vendor and multi-protocol based CCAM service architectures can become challenging and complex. Additionally, conducting on-demand field trials of such architectures with real vehicles involved is prohibitively expensive and time-consuming. In order to overcome these obstacles, in this paper, we present the development of a standards-compliant experimental vehicular on-board unit (OBU) that supports the integration of multiple V2X protocols from different vendors to communicate with heterogeneous cloud-based services that are offered by several original equipment manufacturers (OEMs). We experimentally demonstrate the functionalities of the OBU in a real-world deployment of a cooperative collision avoidance service infrastructure that is based on edge and cloud servers. In addition, we measure end-to-end application-level latencies of multi-protocol supported V2X information flows to show the effectiveness of interoperability in V2X communications between different vehicle OEMs.

Hybrid short-term traffic forecasting architecture and mechanisms for reservation-based Cooperative ITS

Traffic forecasting is a critical challenge for Intelligent Transportation Systems (ITS), increasingly enabled by the deepening interconnectedness of intelligent vehicles and traffic infrastructures. In this study, we propose a hybrid short-term forecasting architecture based on the careful consideration and analysis of reservation-based behavior cooperation and the characteristics of Cooperative ITS (C-ITS), especially its future application mode of Service-oriented C-ITS (SoC-ITS). We design several novel models and mechanisms to forecast the behavioral parameters of road vehicles in this architecture, combining a developed artificial neural network method and a statistical technique. Considering the lack of large-scale deployment of C-ITS at present, a new simulator (SoC-ITSS v2.1) is independently designed with two main aims. The first is to establish a massive dataset that is unavailable for current transportation systems, but necessary for back propagation neural network-based forecasting and statistics models. Our second aim is to provide an effective visual verification environment for this proposed mechanism. Using our newly developed simulator, these proposed models and methods are verified under two typical authorization policies (First-Arrival-First-Pass-Multi-Queue for ordinary C-ITS and Highest-Weight-First-Pass-Multi-Queue for SoC-ITS). The experimental results show that this forecasting mechanism can adaptively model traffic situations of both ordinary C-ITS and SoC-ITS, and provide good performance. • A new hybrid short-term forecasting architecture is proposed for Cooperative ITS. • Forecasting models and mechanisms are established on the basis of BPNN and statistics. • A new simulator SoC-ITSS v2.1 is designed where all mechanisms have been implemented. • Via SoC-ITSS v2.1, all proposed mechanisms are verified with a simulated dataset.

Development of the Cooperative Intelligent Transport System in Thailand: A Prospective Approach

Smart mobility is becoming an alternative technology of transportation development for today and the future. Thailand has applied the intelligent transport system (ITS) to improve traffic and transport services. The success of the project is generally dependent on collaboration between private, public, and governmental agencies in policymaking and planning, coupled with an inclusive agreement and technological knowledge in the field. This study argues that Thailand’s automatic transportation has been successful because of cooperative-ITS (C-ITS). This study explores the evidence-based cases of ITS development from six areas, Singapore, South Korea, Japan, China, the European Union, and the United States of America, to explain how the C-ITS conditions support the success of ITS. The study uses the SWOT (Strength, Weakness, Opportunity, Threat) and TOWS (Threat, Opportunity, Weakness, Strength) analysis matrix to identify influential factors from the six-area cases and compare them to Thailand. The authors identified seven components that relate to the success of Thailand’s C-ITS. These include: (1) Pragmatic policy for pilot project implementation; (2) close cooperation among stakeholders; (3) working criteria for C-ITS development; (4) architecture of standard and framework; (5) share of lessons learned about current technology; (6) capability of C-ITS deployment; and (7) a clear statement of data exchange and sharing. These findings represent both the threat and opportunity for traffic and transport improvement in Thailand through the C-ITS approach.

The convergence of Internet of Things, Blockchain and Connected Vehicles: Conceptual Advantages and Disadvantages of a new Cooperative Intelligent Transportation System

This paper intends to explore the convergence of some technological innovations that could lead to new cooperative Intelligent Transportation Systems (ITS). The technologies that might soon converge and lead to some new developments are: the Blockchain Technology (BT) concept, Internet of Things (IoT) and Connected and Automated Vehicles (CAV). Advantages and disadvantages of the new concepts founding a new ITS system are discussed in this conceptual paper. Blockchain technology has been recently introduced and many research ideas have been presented for application in the transportation sector. In this paper, we discuss a system that is based on a dedicated blockchain, able to involve both drivers and city administrations in the adoption of promising and innovative technologies that will create cooperation among connected vehicles. The proposed blockchain-based system can allow city administrators to reward drivers when they are willing to share travel data. The system manages in a special way the creation of rewards which are assigned to drivers and institutions participating actively in the system. Moreover, the system allows keeping a complete track of all transactions and interactions between drivers and city management on a completely open and shared platform. The main idea is to combine connected vehicles with BT to promote Cooperative ITS use, a better use of infrastructures and a more sustainable eco-system of cryptocurrencies. A short description of BT is introduced to evidence energy problems of sustainability in the implementation of Proof of Work (PoW) that is adopted by many blockchains.

Cooperative Intelligent Transport Systems: Choreography-Based Urban Traffic Coordination

With the emerging connected automated vehicles, 5G and Internet of Things (IoT), vehicles and road infrastructure become connected and cooperative, enabling Cooperative Intelligent Transport Systems (C-ITS). C-ITS are transport system of systems that involves many stakeholders from different sectors. While running their own systems and providing services independently, stakeholders cooperate with each other for improving the overall transport performance such as safety, efficiency and sustainability. Massive information on road and traffic is already available and provided through standard services with different protocols. By reusing and composing the available heterogeneous services, novel value-added applications can be developed. This paper introduces a choreography-based service composition platform, i.e. the CHOReVOLUTION Integrated Development and Runtime Environment (IDRE), and it reports on how the IDRE has been successfully exploited to accelerate the reuse-based development of a choreography-based Urban Traffic Coordination (UTC) application. The UTC application takes the shape of eco-driving services that through real-time eco-route evaluation assist the drivers for the most eco-friendly and comfortable driving experience. The eco-driving services are realized through choreography and they are exploited through a mobile app for online navigation. From specification to deployment to execution, the CHOReVOLUTION IDRE has been exploited to support the realization of the UTC application by automatizing the generation of the distributed logic to properly bind, coordinate and adapt the interactions of the involved parties. The benefits brought by CHOReVOLUTION IDRE have been assessed through the evaluation of a set of Key Performance Indicators (KPIs).

Cross-Border Interoperability for Cooperative, Connected, and Automated Driving

The implementation on a massive scale of safe, highly automated driving is very difficult using only information from ego vehicles, which are subject to visual horizon limitations. For automated driving systems to become a reality, it is essential to provide them with two fundamental elements, among others: connectivity and cooperative services. Both elements are still at a very early stage of development in communications technology and in the organization and generation of support information. In addition, extra difficulties are presented, such as transnational barriers to accessing services and exchanging information with other vehicles and infrastructure. This article presents the implementation of a novel architecture to support the integration of cooperative intelligent transportation systems in automated driving, including the results of cross-border interoperability tests carried out in three cooperative, connected, and automated driving (CCAD) pilots that were deployed in three cities belonging to the Trans-European Atlantic Corridor—Madrid, Spain; Lisbon, Portugal; and Paris, France—under the framework of the European Regulation Study for Interoperability in the Adoption of Autonomous Driving in European Urban Nodes. These results show the performance of the CCAD architecture and have been analyzed to include a set of recommendations to ensure the successful deployment of CCAD driving at the European level.

Sensors on the Move: Onboard Camera-Based Real-Time Traffic Alerts Paving the Way for Cooperative Roads.

European road safety has improved greatly in recent decades. However, the current numbers are still far away to reach the European Commission’s road safety targets. In this context, Cooperative Intelligent Transport Systems (C-ITS) are expected to significantly improve road safety, traffic efficiency and comfort of driving, by helping the driver to make better decisions and adapt to the traffic situation. This paper puts forward two vision-based applications for traffic sign recognition (TSR) and real-time weather alerts, such as for fog-banks. These modules will support operators in road infrastructure maintenance tasks as well as drivers, giving them valuable information via C-ITS messages. Different state-of-the-art methods are analysed using both publicly available datasets (GTSB) as well as our own image databases (Ceit-TSR and Ceit-Foggy). The selected models for TSR implementation are based on Aggregated Chanel Features (ACF) and Convolutional Neural Networks (CNN) that reach more than 90% accuracy in real time. Regarding fog detection, an image feature extraction method on different colour spaces is proposed to differentiate sunny, cloudy and foggy scenes, as well as its visibility level. Both applications are already running in an onboard probe vehicle system.

Connected vehicle-based road safety information system (CROSS): Framework and evaluation

Valuable high-resolution data representing the maneuvering of both individual subject vehicles and adjacent vehicles are available in the era of the connected vehicle systems, which is also referred to as cooperative intelligent transportation systems (C-ITS). C-ITS can share useful traffic information between connected vehicles (CV) and between vehicles and infrastructure in support of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications. An excellent feature of a C-ITS pre-deployment project in Korean freeways that CVs are equipped with an in-vehicle forward collision warning system. This technical support provides a useful opportunity to evaluate crash risks more objectively and scientifically based on the analysis of vehicle interactions, which motivates our study. The purpose of this study is to develop a road safety information system based on the analysis of CV data. The proposed system estimates individual vehicle crash risks based on the crash potential index (CPI) and further utilizes them to develop a methodology for assessing road safety risks on freeways. High CPIs were observed in toll plaza area, recurrent congestion sections, and on and off-ramp areas. An encouraging result showed that the relationship between the estimated CPI and the actual crash frequencies was statistically meaningful. In addition, the impact of the CV market penetration rate (MPR) on the feasibility of the proposed road risk monitoring method was explored by microscopic traffic simulation experiments using VISSIM. A safety evaluation equivalent to 100 % MPR was obtainable with 30 % MPR. The outcomes of this study are expected to be utilized as fundamental to support the development of novel road risk monitoring systems in C-ITS environments.