Connected Vehicles

English summary:
An area of action analysis for 13 jointly selected application cases has been performed in order to evaluate the efficiency of simTD systems with direct influence on safety of road traffic concerning accident scenarios with injuries (Prioritisation of emergency vehicles, breakdown vehicles, slow vehicle warning, construction site warning, obstacle on road, traffic jam warning, road weather warning, emergency vehicle warning, ignoring traffic signs, ignoring "red light" warning, electronic brake light, cross traffic assistant and left turn assistant). The GIDAS accident data from the years 2001 to 2008 form the basis for the analysis. GIDAS (German In-Depth Accident Study) is a suitable basis, since the incorporated accident data (environment, vehicles, persons, injury data including accident scenario and photographs) are very detailed and comprehensive. The version used for the analysis comprises of 13821 accidents.
Weighting of the accidents collected in the areas of Hanover and Dresden is required for the estimation of all German road traffic accidents. Weighting is performed by means of four parameters used by GIDAS as well as the Federal Statistics. A description of the weighting process is given in chapter 1.2. Area of action analyses are the initial evaluation for the maximal achievable efficiency of systems. The actual efficiency of a system may be significantly less depending on the degree of efficiency. Detailed information on system specification, system limits and driver behaviour are required in order to evaluate the degree of efficiency.
In a simTD/GIDAS workshop on 09 March 2009 the areas of action have been discussed and determined by the persons responsible.
Since area of action analyses of the application cases often severely overlap, it is difficult to summarise the results. The effect of efficiency prediction overlap may be noticed for instance when combining application cases „intersection assistant“ resp. „left turning assistant“ and „Warning Disregarding Traffic Signs“. Approximately 8 % of all accidents in Germany could be influenced by both application cases simultaneously.
Would all application cases in road traffic be applied, an efficiency of 0 up to maximal 36 % depending on the degree of efficiency could be expected. The determination of a degree of efficiency is only completed by the end of the simTD project.

Zusammenfassung:
Zur Abschätzung der Effizienz von simTD - Systemen mit direktem Sicherheitseinfluss auf den Straßenverkehr hinsichtlich des Unfallgeschehens mit Personenschaden wurden Wirkfeldanalysen für 13 abgestimmte Anwendungsfälle durchgeführt (Priorisierung von Einsatzfahrzeugen, Liegengebliebene Fahrzeuge, Warnung vor langsamem Fahrzeug, Baustellenwarnung, Hindernis auf Fahrbahn, Stauendewarnung, Straßenwetterwarnung, Warnung vor Einsatzfahrzeug, Nichtbeachten Verkehrszeichen, Warnung Nichtbeachtung „Rot“, elektronisches Bremslicht, Querverkehrsassistent und Linksabbiegeassistent). Datengrundlage hierfür sind die von GIDAS erhobenen Unfalldaten aus den Jahren 2001 bis 2008. GIDAS (German In-Depth Accident Study) bildet dafür eine geeignete Grundlage, da die darin enthaltenen realen Unfalldaten (Umwelt-, Fahrzeug-, Personen-, Verletzungsdaten inkl. Unfallskizze und Bilddaten) sehr detailliert und umfangreich vorhanden sind. Die für die Auswertung verwendete Version enthält 13821 erfasste Unfälle.
Für eine Aussage bezüglich des gesamtdeutschen Unfallgeschehens ist eine Gewichtung dieser im Raum Hannover und Dresden erhobenen Unfälle erforderlich. Diese Gewichtung erfolgt mittels vier Variablen (Ortslage, Unfalltyp, Unfallkategorie1 und Unfallsjahr), die sowohl in GIDAS als auch in der amtlichen Bundesstatistik vorliegen. Eine Beschreibung der Gewichtung ist in Kapitel 1.2 zu finden.
Wirkfeldanalysen stellen eine erste Abschätzung für die maximal erreichbare Effizienz von Systemen dar. Die tatsächliche Effizienz eines Systems kann je nach Wirkungsgrad deutlich geringer sein. Aus diesem Grund ist die Wirkfeldanalyse zur Nutzen/Kostenanalyse nur bedingt verwendbar bzw. liefert den Nutzen eines idealen Systems ohne definierte Systemgrenzen. Um einer bessere Nutzenanalyse eines bestimmten Systems durchzuführen, muss deshalb der Wirkungsgrad bestimmt werden.
Für eine Ermittlung des Wirkungsgrads sind detaillierte Informationen über die Systemspezifikationen, Systemgrenzen und das Verhalten der Fahrer erforderlich.
Die Definitionen der Wirkfelder mittels GIDAS-Variablen und der simTD-relevanten Fahrzeuge wurden in einem simTD/GIDAS-Workshop am 09.03.2009 gemeinschaftlich mit den Funktionsverantwortlichen abgestimmt und festgelegt.
Da sich die Wirkfelder der Anwendungsfälle teilweise stark überschneiden, lassen sich die Ergebnisse nicht einfach aufsummieren. Der Effekt von Wirkfeldüberschneidungen ist beispielsweise bei der Kombination der Anwendungsfälle „Querverkehrsassistent“ bzw. „Linksabbiegeassistent“ und „Warnung Nichtbeachten Verkehrszeichen“ festzustellen. Ca. 8 % aller Unfälle in Deutschland könnten gleichzeitig von beiden Anwendungsfällen beeinflusst werden.
Würden alle Anwendungsfälle zum Einsatz kommen, so ist heute mit einer Effizienz, je nach Wirkungsgrad, von 0 bis maximal 36 % zu rechnen.
Eine genauere Eingrenzung des Wirkfeldes ist erst mit der Ermittlung von Wirkungsgraden möglich.
Daher werden im Projektverlauf mit den Funktionsentwicklungsteams, TP4 und TP5 Abstimmungen statt finden, um das weitere Vorgehen der Nutzenbewertung festzulegen. Die Methode der Wirkgradanalyse wird auf die besonderen Anforderungen von simTD angepasst werden. Da die Wirkungsgradanalysen auch auf Ergebnissen kommender Versuche basieren können, ist die Nutzenbewertung erst zum Projektende von simTD endgültig abgeschlossen.

Continuous and emerging advances in Information and Communication Technology 1 (ICT) have enabled IoT-to-Cloud applications to be induced by data pipelines coupled with 2 Edge Intelligence-based architectures. Advanced vehicular networks greatly benefit from these 3 architectures due to the implicit functionalities that are focused on realizing the Internet-of-4 Vehicle (IoV) vision. However, IoV is susceptible to attacks, where adversaries can easily exploit 5 existing vulnerabilities. Several attacks may succeed due to inadequate or weaker authentication 6 techniques. Hence, there is a timely need for hardening the authentication process through 7 cutting-edge access control mechanisms. This paper proposes a Blockchain-based Multi-Factor 8 authentication model that uses an embedded Digital Signature (MFBC_eDS) for vehicular clouds 9 and Cloud-enabled IoV. Our proposed MFBC_eDS model consists of a scheme that integrates 10 the Security Assertion Markup Language (SAML) to the Single Sign-On (SSO) capabilities for a 11 connected Edge-to Cloud ecosystem. MFBC_eDS draws an essential comparison with the baseline 12 authentication scheme suggested by Karla and Sood. Based on the foundations of Karla and Sood's 13 scheme, an embedded Probabilistic Polynomial-Time Algorithm (ePPTA) and an additional Hash 14 function for the P i generated during Karla and Sood's authentication are proposed and discussed. 15 The preliminary analysis of the proposition shows that the approach is more suitable to counter 16 major adversarial attacks in an IoV-centered environment based on Dolev-Yao adversarial model 17 while satisfying aspects of the CIA triad.

This paper addresses the intervehicular communication in Connected Vehicles (CV) by emphasizing V2V (vehicle-to-vehicle) and V2I (vehicle-to-infrastructure) communications in terms of evolution, current standards, state-of-the-art studies, embedded devices, simulation, trends, challenges, and relevant legislation. To accomplish the objective this review is based on studies conducted from 2003 to 2019, government reports about the sustainable deployment of these technologies and their adoption in the Brazilian automotive market according to experts. Moreover, WAVE (Wireless Access in Vehicular Environment) and DSRC (Dedicated Short-range Communication) standards, the performance analysis of communication parameters and intervehicular available at the market are also described. The current status of ITS (Intelligent Transportation System) development in Brazil is reviewed, as well as the research institutes and governmental actions focused on introducing the concept of connected vehicles into the society. The Brazilian outlook for technological adoption concerning CVs was also discussed. Besides those, challenges related to technical aspects, safety and environmental issues, and the standardization for vehicle communication are also described. Finally, this review highlights the challenges and proposals from available technologies devoted to the roads and vehicular infrastructure communication, their evolution and upcoming trends.

The latest technological innovations are creating the base for mobility solutions which, accompanied to cultural and socioeconomic changes taking place all over the World, opens the door to new mobility scenarios. The challenge of innovation in transport sector is represented by automation of vehicles, including all transport sectors (road, sea, rail and air) and particularly the automotive from the viewpoint of demonstration and validation. This chapter presents the state of the art of Connected and Automated Vehicles (CAVs) development outlining the conditions for sustainable mobility solutions and new business models for transport services.

Connected and autonomous vehicles (CAVs) have the potential to disrupt all industries tied to transport, including tourism. This conceptual paper breaks new ground by providing an in-depth imaginings approach to the potential future far-reaching implications of CAVs for urban tourism. Set against key debates in urban studies and urban tourism, we discuss the enchantments and apprehensions surrounding CAVs and how they may impact cities in terms of tourism transport mode use, spatial changes, tourism employment and the night-time visitor economy, leading to new socioeconomic opportunities and a range of threats and inequities. We provide a concluding agenda that sets the foundation for a new research sub-field on CAVs and tourism, of relevance to urban planners, policymakers and the tourism industry.

Information-aware connected and automated vehicles (CAVs) have drawn great attention in recent years due to their potentially significant positive impacts on roadway safety and operational efficiency. In this paper, we conduct an in-depth review of three basic and key interrelated aspects of a CAV: sensing and communication technologies; human factors; and information-aware controller design. First, the different vehicular sensing and communication technologies and their protocol stacks, to provide reliable information to the information-aware CAV controller, are thoroughly discussed. Diverse human factors, such as user comfort, preferences, and reliability, to design the CAV systems for mass adaptation are also discussed. Then, the different layers of a CAV controller (route planning, driving mode execution, and driving model selection) considering human factors and information through connectivity are reviewed. In addition, the critical challenges for the sensing and communication technologies, human factors, and information-aware controller are identified to support the design of a safe and efficient CAV system while considering user acceptance and comfort. Finally, the promising future research directions of these three aspects are discussed to overcome existing challenges to realize a safe and operationally efficient CAV.

The Congress headline was “Next generation integrated mobility: driving smart cities”. This wording aimed to reflect the remarkable range of ITS products that are being deployed now by cities and urban conurbations to support population increases, sustained growth in demand for mobility, and users’ appetites for services that build on 24/7 connectivity. At the same time ITS can deliver improvements to network
capacity, air quality and safety. The Congress was organized around seven key tracks: A. Connectivity and Autonomy; B. Infrastructure Challenges and Opportunities; C. Smart(er) Cities; D. Data, Security and Privacy; E. Integrated Approach: Planning, Operations and Safety; F. Disruption and New Business Models; and G. Innovation, What’s Next? The New Ideas. This Report summarizes the Congress proceedings. The first part focuses mostly on the Technical & Scientific papers and
the Special Interest Sessions; the second and third parts report on the Plenary and Executive Sessions.

The emergence of Intelligent Transportation Systems (ITS) has paved the way to new innovative prospects for improving the safety, operation, and environmental impact of transportation networks. Connected vehicle (CV), a groundbreaking initiative of " intelligent vehicles " , emerging as the next wave of technology to further empower travellers. Among other benefits, this technology will help provide for increased capacity of existing transportation networks in addition to increased roadside safety for motorists through the development of an overall Intelligent Transportation System. However, before we can even consider how to integrate the technology of CV into our transport system, professionals must understand and realize its environment and how future cities to be created. This paper outlines the various aspects of the CV concept and how it will affect the transport system and urban environments over the next decade with the aim of providing transport directors and practitioners with an insight into this innovative technology. Two main types of short-range wireless communication are discussed namely Vehicle-to-Vehicle (V2V), and Vehicle-to-Infrastructure (V2I) communication. An overview of the evolution of the CV and its operational aspects are presented together with its application. The impacts and potential operational benefits of the CV are discussed. The best practices of CV initiatives are reviewed, the broader public perception of CV applications are investigated, and the various challenges to the CV technology are identified.

In this paper, we present the design, implementation and evaluation of non-line-of-sight (NLOS) perception to achieve a virtual see-through functionality for road vehicles. In this system, a safety event, such as pedestrian crossing or traffic list status or vehicle merge, that are occluded to a driver due to another vehicle on the driving lane, are perceived and communicated by the occluding vehicle. Each vehicle is equipped with a camera, placed on the dashboard, that perceives the scene in a drivers view. This scene is analyzed and mapped into specific warning codes that are specific to a safety event, and communicated as short packets using visible light communication. The camera in the following vehicle captures this information and generates a recommendation for safety action to the driver by comparing the warning from the packet and from its own scene perception. Through experimental evaluations of a proof-of-concept implementation, we show that our system is able to achieve up to 90% accuracy in identifying nine occluded safety events, which correspond to traffic light statuses (red, green, yellow), other vehicles' lane change behaviors (merge/leave lane left/right), and pedestrian detection.

In the last couple of decades, there has been an unparalleled growth in number of people who can afford motorized vehicles. This is increasing the number of vehicles on roads at an alarming rate and existing infrastructure and conventional methods of traffic management are becoming inefficient both on highways and in urban areas. It is very important that our highways are up and running 24/7 as they not only provide a passage for human beings to move from one place to another, but also are the most important mode for intercity or international transfer of goods. There is an utter need of adapting the new world order, where daily processes are driven with the help of innovative technologies. It is highly likely that technological advancements like autonomous or connected vehicles, big data and the Internet of things can provide highway operators with a solution that might resolve unforeseeable challenges. This investigative exploratory research identifies and highlights the impact of new technological advancements in the automotive industry on highways and highway operators. The data for this research was collected on a Likert scale type online survey, from different organizations around the world (actively or passively involved in highway operations). The data was further tested for its empirical significance with non-parametric binomial and Wilcoxon signed rank tests, supported by a descriptive analysis. The results of this study are in line with theoretical and conceptual work done by several independent corporations and academic researchers. It is evident form the opinions of seasoned professionals that these technological advancements withhold the potential to resolve all potential challenges and revolutionize highway operations.

Vehicle-to-Infrastructure (V2I) technology offers great potential in improving the safety and mobility in a transportation system. One mobility application is the travel time measurement in an urban road network. The presence of traffic control at intersections in an urban network makes it challenging for traditional traffic monitoring methods to provide accurate travel times. Several new technologies (e.g., Bluetooth) have been proposed to alleviate this problem. One of the features of V2I technology is probe vehicle data collection, where vehicles collect information such as their location and speed. The speed information can be used for travel time estimation. In this paper, one necessary and crucial aspect of travel time estimation using V2I technology is investigated. The paper proposes a methodology for determining the optimal placement of roadside equipment  (RSEs) for travel time estimation in a V2I environment. A connected vehicle simulation test-bed of Boise, Idaho, was developed in the VISSIM traffic simulation software following the SAE J2735 standard. A hybrid performance measure, network coverage index, which combines travel time error and the number of links for which travel times are available was proposed. A Genetic Algorithm-based solution method was implemented in conjunction with the simulation test-bed to determine the optimal placement of different RSE deployments. The results indicate that the proposed methodology is capable of optimizing RSE locations in a V2I environment. Sensitivity analysis was also conducted by varying the market penetration rate and travel time estimation interval. The results indicated that higher penetration rates and bigger estimation intervals produced better coverage index values.

With the auto industry moving to more and more computing units, connected infotainment, pairing of on-board equipment to mobile devices, cloud connectivity, V2V, V2X, and autonomous functions, architects and developers need all the help they can get to address security and safety concerns in the systems. In the past, the world of enterprise IT and mobile devices has seen its share of security failures and rebounds; however, the auto industry cannot afford to fall into the same pitfalls when greater things like safety are at stake. In this paper, we present a number of software protection technologies and their application to a trusted distributed environment. We show how layered robustness approaches like runtime application self-protection, white-box cryptography, program transforms, and a secure environment can be applied and orchestrated in a distributed network to establish trust in its leaf components. Furthermore, while on-board diagnostics like OBD2 and UDS are important, diagnostics over IP (DoIP) is becoming essential in a connected car. The natural extension to this is to enable security analytics through the telemetry connections, paving the way for analysis of the data to determine trends over the fleet. Finally, in this paper, we show a proof-of-concept network running on iMX6 and R-Car M2/3 boards demonstrating the main concepts being put forth, running on different OS’s, including Ubuntu, Android, and Automotive Grade Linux (AGL), which shows the flexibility of the approach.

A novel framework is developed in this paper, to increase the real-time roadway traffic condition assessment accuracy , which integrates connected vehicle technology (CVT) with artificial intelligence (AI) paradigm forming a CVT-AI method. Traffic density is a major indicator of traffic conditions. In this paper, the traffic operational condition is assessed based on traffic density. A simulated network of Interstate 26 in South Carolina is developed to investigate the effectiveness of the method. The assumption is that the vehicle onboard units will forward the CV generated data to the edge devices (e.g., roadside units) for further processing. CV generated distance headway and number of stops, and speed data are used to estimate traffic density. This paper reveals that, with 20% and greater CV penetration levels, the accuracy of the density information with the AI-aided CVT is a minimum of 85%. Moreover, this paper demonstrates that the integrated CVT-AI method yields a higher accuracy with the increase of CV penetration levels. Level of service (LOS) is the indicator of traffic congestion level on highways and is described with traffic density in terms of passenger car/mile/lane for a specific free flow speed. LOS estimated using the CVT-AI density estimation method is compared with the density estimation algorithm used by the Caltrans Performance Measurement System (PeMS), which relies on the occupancy and flow data collected by the freeway inductive loop detectors. With a 10% or more CV penetration, higher accuracy is achieved using the CVT-AI algorithm compared with the PeMS density estimation algorithm.

In the last couple of decades, there has been an unparalleled growth in number of people who can afford motorized vehicles. This is increasing the number of vehicles on roads at an alarming rate and existing infrastructure and conventional methods of traffic management are becoming inefficient both on highways and in urban areas. It is very important that our highways are up and running 24/7 as they not only provide a passage for human beings to move from one place to another, but also are the most important mode for intercity or international transfer of goods. There is an utter need of adapting the new world order, where daily processes are driven with the help of innovative technologies. It is highly likely that technological advancements like autonomous or connected vehicles, big data and the Internet of things can provide highway operators with a solution that might resolve unforeseeable challenges. This investigative exploratory research identifies and highlights the impact of...

C23 Resume With the spread of connected vehicles (CVs), a growth of novel information services exploiting data transmitted by CVs is expected. Wireless communication systems, in particular in vehicular applications, operate with a varying level of transmission reliability, which may affect the quality of V2X-data-driven intelligent transport systems (ITS). Therefore, the performance of ITS should be evaluated in a variety of conditions and the configuration of parameters should be fine-tuned in a safe testbed, using computer simulations. A simple framework is presented, which couples VISSIM traffic simulation and OMNeT++ communication networks simulation in real time, enabling an assessment of the relationship between a communication reliability and transport service quality. A functionality of the framework is demonstrated by applying it to a scheme controlling signalized intersections while estimating traffic flows from the V2I data. The proposed techniques rely heavily on an assumption of perfect communication (i.e. no latency and message loss), however, in the real world applications the reliability of communication networks might be affected by various factors [3-4]. Several studies investigate communication networks performance in connected vehicles environment [5-6] and while the effect of information transmission quality on vehicles' routing decisions in a signalized urban network has been investigated [7], the direct, real-time impact of imperfect communication on traffic control decisions at signalized intersections is less studied. As a field test validation of various traffic scenarios in connected vehicle environment might be too expensive and complex to set up, a common practice in traffic control research is to create simulation models. In this study, a simulation framework that integrates VISSIM traffic micro-simulation software and OMNET++ communication networks simulator was built in order to provide a testbed for realistic interaction scenarios. In the future work, the developed test bed/framework may provide some valuable insights into an impact of imperfect communication on, for example, signal traffic control performance in connected vehicles environment and possible ways to decrease the

There are many challenges currently faced by the humanoid robot' models to achieve the objective or target planned for them. One of these challenges is the trade-off between the ability to accurately mimic the human body and uptime. While some of these models like ASIMO has very accurate degree to mimic the bipedal walking gait used by human due to high actuations, it consumes high power. Through our proposed model we introduce a model-free deep Q-learning algorithm (DQN) that doesn't simulate the bipedal walking gait used by human based on predetermined sequence or modelling via supervised learning. On counter, our proposed model learns from interactions/interfacing with the surrounding environment by applying actions on the robot and observing the reward from that action to make an under-actuated robot able to balance and walk forward, backwards, sideways, and rotate in place using only 4 actuators. It takes quite long time at the start of the learning process where robot is learning by trial and error but once learned it becomes able to perform and reach the target goal without being fall down. Results achieved from the proposed simulated model show better performance in terms of ability to reach target without being fall and corresponding power consumption.

Stop and go movements on urban streets under traffic signals are sources of increased fuel consumptions, vehicle wear and tear, commuter anxiety and thus safety risks. One Connected Vehicle (CV) technology, Eco-approach and departure or called Green Light Optimal Speed Advisory (GLOSA), aims to alleviate all these side effects by assisting drivers or in-vehicle computers with traffic signal state and switching information. However, this CV technology must live on the key data feed of short-term predictive signal data instead of current signal states alone. An online system has been developed to generate such predictive data feeds for a horizon of up to one cycle length. By accessing signal controllers via common standard protocols, the system uses a proprietary algorithm to forecast control outputs for not only fixed time signals, but also traffic actuated controllers that allow for flexible phase sequences and variable durations. Lab experiments and field deployments were conducted in the US, China and Germany. Comparisons between prediction and actual signal switches and phase durations have shown consistent and high accuracies for signals at all test fields. This predictive data proved to be easily adaptable by both OEM infotainment centers for driving assistance and automatic engine starts/stop systems.

Advances in communication, sensing, and in-vehicle computing technology in the last two decades have enabled the development of self-driving vehicle (SDV) technology. This
technological development has a potential for revolutionizing traffic control technology. One of the questions for development of SDV technology is how these vehicles will interact in traffic, and especially at intersections, as critical points on the network. Alternatively to some previous research approaches, this research originates from the investigation of ethical dimension of the traffic control principles for SDVs. This approach is attempting to consider the development of SDV technology from a wider, sustainable perspective. Consequently, we will present the development of the traffic control framework that includes a perspective
of social justice, emphasizing delay distribution. First, the paper will present methodological approach and foundational deliberations from one of the leading social justice theories in
addition to human behavior considerations. This information will be used to establish a framework for the proposed traffic control mechanism. Furthermore, the paper will present
information collected about the proposed framework based on surveys and interviews. Finally, we will present the framework redesign and recommendations for further research
contemplation. The research presented here implies that there is a potential for development of traffic control principles which would enable end user responsibility in the control process.

Connected vehicle technologies, enabling communications between vehicles and between vehicles and roadside infrastructure, will improve traffic safety and mobility in future.

To test connected vehicle technologies in a real-life environment, the Safety Pilot Model Deployment (SPMD) project was initiated by University of Michigan Transportation Research Institute (UMTRI) and Ann Arbor. This model served as the first nationwide scaled-down testbed for connected vehicles and lasted from fall 2012 to Spring 2014.

Ann Arbor is ideal for test due to a good mix of high-volume multi-modal traffic, a variety of roadway characteristics (urban, suburban and rural roads), diverse weather conditions, and its proximity to vehicle manufacturers and suppliers.

In the SPMD program, more than 2,800 cars, commercial trucks, and transit vehicles were equipped with GPS antennas and DSRC devices. They broadcast basic safety message (BSM), such as their positions, velocities, and yaw rates, to neighboring vehicles and nearby roadside infrastructure at a frequency of 10 Hz. At the same time, they also receive BSM from neighboring vehicles. Inside cars, drivers’ verbal and physical reactions to a variety of traffic situations were recorded by cameras. Some cars were installed with advanced sensors which can detect obstacles and lane markings to alert drivers in case of emergency. These instrumented cars account for 3-4% of total trips in Ann Arbor and traffic data obtained from them provides rich information for time-series naturalistic driving studies from field operational tests under connected vehicle environment.

On infrastructure’s side, 73 lane-miles of roadway was instrumented with 29 roadside-equipment, including 3 speed warnings at curves, 5 freeway sites, and 21 signalized intersections, in order to capture all traffic operating environment with focus on local commuters. Among 21 intersection equipment, 12 of them were distributed along two signalized corridors. They broadcasted Signal Phase and Timing (SPaT) information to drivers who were approaching intersections. Such information was displayed to drivers and drivers’ reactions, such as acceleration/deceleration, braking, and turning status, were recorded accordingly by cameras and sensors.

Recent catastrophic bridge failures clearly indicate the urgent need for improving interval-based bridge inspection procedures that are qualitative and subjective in nature. Structural Health Monitoring (SHM) can mitigate the deficiencies of interval-based inspection techniques and provide real-time diagnostic information regarding the bridge structural health. SHM is not flawless however; the variability in the vehicle characteristics and traffic operational conditions makes it prone to false diagnosis. Recent advancements in the integration of SHM with intelligent transportation systems (ITS) demonstrate the successful use of ITS devices (e.g., traffic cameras, traffic detectors) in the analysis of bridge responses to multimodal traffic with varying loads or during the critical events that cause excess vibration beyond the normal limit. In an ITS-informed SHM system, the ITS device collected data can be integrated with SHM to increase the reliability and accuracy of the SHM system. This integration would reduce the possibility of false diagnosis of damages detected by the SHM system (e.g., vibrations caused by heavy vehicles on a bridge could be read by a SHM sensor as a structural health problem of the bridge), which would eventually decrease the bridge maintenance costs. Similarly, in SHM-informed ITS system, SHM sensors can provide data on bridge health condition for ITS applications, where ITS uses this bridge health condition information for real-time traffic management. In this paper, literature related to both ITS-informed SHM and SHM-informed ITS is reviewed. Based on the literature review, potential challenges and future research directions associated with ITS-SHM integration are also discussed.

—Vehicles today are becoming powerful sensor platforms capable to collect, store and share large amount of sensory data by constant monitoring of urban streets. It is quite challenging to upload such data from all vehicles to the infrastructure due to limited bandwidth resources and high cost. This invokes the need to identify the appropriate vehicles, important for different urban sensing tasks based on their natural mobility. This paper address this problem leveraging the self-decision making ability of a " Smart Vehicle " to measure its relative importance in the network. To do so, we present InfoRank as an Information-Centric algorithm for a vehicle to first autonomously rank different location-aware information. It then uses the information importance along its mobility pattern to find its importance in the network. We also present a selection algorithm to find the best ranked vehicles for urban sensing and vicinity monitoring to achieve a desired coverage within a limited budget. Our vehicle ranking system is the first step towards identifying the best information hubs to be used in the network for the efficient collection, storage and distribution of urban sensory information. We evaluate InfoRank under a scalable simulation environment using realistic vehicular mobility traces. Results show that the proposed ranking system efficiently identified socially important vehicles in comparison to other ranking schemes.

The Electric Vehicles (EVs) market has seen rapid growth recently despite the anxiety about driving range. Recent proposals have explored charging EVs on the move, using dynamic wireless charging that enables power exchange between the vehicle and the grid while the vehicle is moving. Specifically, part of the literature focuses on the intelligent routing of EVs in need of charging. Inter-Vehicle communications (IVC) play an integral role in intelligent routing of EVs around a static charging station or dynamic charging on the road network. However, IVC is vulnerable to a variety of cyber attacks such as spoofing. In this paper, a probabilistic cross-layer Intrusion Detection System (IDS), based on Machine Learning (ML) techniques, is introduced. The proposed IDS is capable of detecting spoofing attacks with more than 90% accuracy. The IDS uses a new metric, Position Verification using Relative Speed (PVRS), which seems to have a significant effect in classification results. PVRS compares the distance between two communicating nodes that is observed by On-Board Units (OBU) and their estimated distance using the relative speed value that is calculated using interchanged signals in the Physical (PHY) layer.

Drawing perspectives from science and technology
studies, philosophy of science, and literature from ethics and
social justice, this paper examines the promises and challenges in the development of self-driving vehicle (SDV) technology. We
start with the premise that the combination of different
computing technologies embedded in SDVs is a powerful tool for efficiency in communications, information gathering, processing, and storage. However, by focusing on efficiency, SDVs provide a new mode of industrialized transportation whose users can only choose between transportation services, but have little or no say about the broader social implications of the technology. We argue that perspectives from social justice and ethics show that SDVs have implications beyond transportation, with profound consequences for users and societies. In particular, values such as privacy, security, and responsibility may be changed for good or bad, in both the short and long-term. The examination of these
changes, while the technology is still under foundational
development, is as urgent as it is needed.

—Content distribution in vehicular networks is greatly impaired by high mobility and intermittent connectivity. Social-aware content distribution schemes based on typical centrality metrics address the challenge, however they suffer due to their network-centric nature instead of information centric. We suggest to exploit the recently proposed information-centric networking architecture which cater the issue by decoupling host-user and support in-network caching at intermediate nodes. In this paper, we propose a novel information-centric social-aware content distribution protocol, STRIVE confining the broadcast nature of interest/content by routing it selectively towards high centrality information facilitator vehicles. We use a three-tier forwarding strategy to discover potential local and global information facil-itators in an urban environment for efficient content delivery. The performance evaluation implements a scalable simulation environment deploying up to 2986 vehicles using realistic vehicular mobility traces. Simulation results show that our proposed novel vehicle centrality based content distribution protocol, STRIVE outperforms existing social content distribution metrics used in the literature.

There is an ongoing debate in research and industry communities whether IEEE 802.11p or 3GPP LTE should be used for vehicular communications. In this work, we argue that a hybrid vehicular network combining both technologies can increase the performance of the system. We first propose a mechanism to improve location- based routing in a hybrid vehicular networks architecture, by data and signalling traffic separation on independent wireless networks. We then develop analytical models for calculating the stochastic upper bound of the end-to- end delay for location-based routing in three different networking architecture alternatives based on: (a) short range ad-hoc only, (b) cellular only, and (c) the proposed hybrid ad-hoc/cellular network. The analytical approach in this paper is based on Stochastic Network Calculus theory, which provides a solid and uniform framework for analysis of the upper bound of the end-to-end delay in communication networks. It is demonstrated that the proposed hybrid network provides a lower end-to-end delay compared to the other two alternatives. Comparisons of realistic simulation results, carried out in NS3, and analytical results show that the proposed delay bounds provide relatively tight approximations for the end-to-end delay in the three alternative architectures for vehicular networks investigated in this paper.

Statistics show that about 23% of all vehicle crashes
per year are rear-end collisions. In most cases, these accidents are
due to the sudden decrease in the speed of the front vehicle and
insufficient time for the rear vehicles to decrease their speed.
This is usually the consequence of limited view span of the driver
and thus failure to react at the proper time. The issue exacerbates
in today’s high-speed highways in which several fast-moving
vehicles move consecutively in one line. In such situations sudden
decrease in the speed of one vehicle may result in a chain
collision. Due to limited coverage and functionality, current
vehicle safety systems like sensor and radars fail to extend the
view span of the drivers as desired. Therefore, recently taking
advantage of vehicular short communications is attracting lots of
interest among car manufactures and academic bodies. In this
paper, we use the test-bed of the CVT-Project (Connected
Vehicle Technology Project) to investigate the amount of success
of inter-vehicle communications (based on IEEE 1609/WAVE
standard) in chain collision avoidance. We first implement a
multi-hop safety message dissemination algorithm through which
approaching vehicles can be informed about sudden speed
reductions (e.g., collisions) in a timely manner. In comparison to
drivers’ perception which is simply based on brake-light of the
front vehicle, the above-mentioned message dissemination buys
some time for the drivers to react timely. Our results suggest that
inter-vehicle communication technology contributes significantly
in decreasing the probability of chain collision occurrence.
Furthermore the number of vehicles involved in the accident is
decreased noticeably. We also show that the severity of accident
is reduced significantly by even 50% technology penetration.

ACECR (Academic Center for Education, Culture and Research) -Sharif Branch in cooperation with IDRO (Industrial Development and Renovation Organization of Iran) has devoted extensive efforts in Design and Implementation of Vehicular Intelligent Transportation System Project aiming to improve driving safety, traffic management improvement and reducing vehicles fuel consumption in I.R.IRAN. Following the primary researches, producing software applications and conducting experimental and field tests, the project is now in its pilot phase. By successful implementation of defined applications in the pilot, stakeholders’ cooperation has been obtained in order to prepare a road map for vehicular communication technology development in the country

To facilitate a sustainable transformation that aligns with economic, political, and ideological elements of our societies, this is an auspicious idea to have a deliberated planning for our automated fleets. A crucial item in such vehicles is providing a significant efficiency for users such that it competes with the status quo efficiency of internal combustion engine vehicles (ICEVs) with petroleum fuels. The charging time for fully hydrogen fuel cell vehicles (HFCVs) is a hindrance for the market penetration of those cars. Moreover, planning for refueling and charging stations should be prioritized in this matter due to the fact that those topics are intertwined with one another. The main hindrance for market penetration of hydrogen fuel cell vehicles at the right moment is range anxiety. In other words, the drivers are not sure if they can make it to the next refueling/recharging station with the ongoing number of charging lots. This study investigates the opportunities and challenges associated with different automated vehicles’ refueling/recharging systems and the provided efficiency of each system. Furthermore, the authors provide some insights on allocating the refueling and charging stations according to each system.

—Autonomous vehicles can construct a more accurate perception of their surrounding environment by exchanging rich sensor data with nearby vehicles. Such exchange can require larger bandwidths than currently provided by ITS-G5/DSRC and Cellular V2X. Millimeter wave (mmWave) communications can provide higher bandwidth and could complement current V2X standards. Recent studies have started investigating the potential of IEEE 802.11ad to support high bandwidth vehicular communications. This paper introduces the first performance evaluation of the IEEE 802.11ad MAC (Medium Access Control) and beamforming mechanism for mmWave V2V communications. The study highlights existing opportunities and shortcomings that should guide the development of mmWave communications for V2V communications.

Recent advancements in vehicle-to-vehicle communications have paved the way for testing new solutions to reduce congestion and prevent traffic incidents. The main objective of multiple transport agencies is to improve road safety by providing reliable and flexible solutions to all drivers on the roads. While significant effort has been made in the development of regulations and operating standards, many questions regarding the practical performance and accuracy of such technologies are yet to be answered. This paper presents the results obtained from an ongoing investigation focusing on testing the capabilities of Dedicated Short Range Communications (DSRC) to meet critical levels of road safety in terms of positioning accuracy. After previous analysis of positioning accuracy of heavy vehicles on a test-bed in the Illawarra, New South Wales, Australia, this paper focuses on testing the accuracy of positioning transmitted by two light vehicles while engaged in five different experime...

This report summarises key findings and recommendations arising from narrative analysis of policy and industry proposals in the field of connected and automated vehicles, based on a hybrid methodology of ‘discourse analysis’ and a number of in-depth interviews conducted bythe JRC concerning the future of mobility and in particular the issue of connected and self-driving vehicles. This hybrid methodology was a step towards critically reviewing those futures by making visible their underpinning political and social narratives.This work was carried out under the framing of the NewHorrizon project (newhorrizon.eu), funded by the Horizon 2020, which explores Responsible Research and Innovation (RRI) inspired governance modalities through a number of Social Lab experiments. The project iscoordinated by the Institute for Advanced Studies in Vienna (IHS). In September 2018, the JRC became part of the Social Lab experiments as a follow-up of a RRI Social Lab co-organised with IHS. As a concrete outcome of this partnership, the JRC conducted a pilot project on thetopic of the future of mobility and the place of Connected and Automated Vehicles (CAVs) in those visions. The pilot on ‘CAVs and the Future of Mobility’ assesses the potential implications and societal expectations of CAVs and explores various mobility narratives, ethical considerations, expectations and matters of concern toward this new type of mobility. The pilot has been providing the JRC with the opportunity to investigate whether a more persistent and broader RRI approach (Engagement, Ethics and Governance) could deliver morecomprehensive knowledge to sustain policy design. This report illustrates the application of narrative analysis, as well as in depth interviews with stakeholders, to address the social and ethical issues of CAVs. The document reports how various stakeholders and professionals inthe field are questioning the mobility imaginary involving CAVs that the industries are promoting and investing in. These challenges to the industry’s imaginations of mobility have led us to investigate alternative imaginaries of mobility and cities with citizens through anumber of participatory events, focusing on their matters of concern (see Van Wynsberghe & Guimarães Pereira, 2021). The CAVs technology has been an opportunity and prompt to re-imagine plausibility and desirability of different futures.

In recent years the interest in urban mobility has grown considerably, not only due to the local increase in negative externalities generated by transport, but also because recent technological innovations are offering effective solutions especially in urban context. In particular, the introduction of Connected and Automated Vehicles (CAVs) could radically change the mobility scenario allowing, on the one hand, a widespread diffusion of shared vehicles that could feed the stations of the mass rapid transit network, improving the attractiveness of Public Transportation (PT), and on the other, the implementation of Travel Demand Management (TDM) measures on large areas of the most densely urbanized (and congested) territory of a city, without reducing accessibility and creating social exclusion. The present study aims at evaluating, through a system of Land-Use Transportation Interaction (LUTI) models, the impacts on transport demand and on population and activities location, of transportation policies oriented to both enhancing PT and restricting the individual use of the car. The case study analyzed is represented by the urban area of Rome. Several scenarios have been simulated and compared by means of sustainability indicators. Preliminary results show that the improvement of PT services, combined with the introduction of car use restriction and car free areas, do induce not only a significant modal shift towards more sustainable transportation modes, but also a limitation of urban sprawl. Abstract In recent years the interest in urban mobility has grown considerably, not only due to the local increase in negative externalities generated by transport, but also because recent technological innovations are offering effective solutions especially in urban context. In particular, the introduction of Connected and Automated Vehicles (CAVs) could radically change the mobility scenario allowing, on the one hand, a widespread diffusion of shared vehicles that could feed the stations of the mass rapid transit network, improving the attractiveness of Public Transportation (PT), and on the other, the implementation of Travel Demand Management (TDM) measures on large areas of the most densely urbanized (and congested) territory of a city, without reducing accessibility and creating social exclusion. The present study aims at evaluating, through a system of Land-Use Transportation Interaction (LUTI) models, the impacts on transport demand and on population and activities location, of transportation policies oriented to both enhancing PT and restricting the individual use of the car. The case study analyzed is represented by the urban area of Rome. Several scenarios have been simulated and compared by means of sustainability indicators. Preliminary results show that the improvement of PT services, combined with the introduction of car use restriction and car free areas, do induce not only a significant modal shift towards more sustainable transportation modes, but also a limitation of urban sprawl.