Both the industrial and the scientific communities are working on problems related to vehicular traffic congestion, intelligent transportation systems, and mobility patterns using information collected from a variety of sources. Usually, a vehicular traffic simulator, with an appropriate scenario for the problem at hand, is used to reproduce realistic mobility patterns. Many mobility simulators are available, and the choice is made based on the type of simulation required, but a common problem is finding a realistic traffic scenario. The aim of this work is to provide and evaluate a scenario able to meet all the basic requirements in terms of size, realism, and duration, in order to have a common basis for evaluations. In the interest of building a realistic scenario, we used information from a real city with a typical topology common in mid-size European cities, and realistic traffic demand and mobility patterns. In this paper, we show the process used to build the Luxembourg SUMO Traffic (LuST) Scenario, and present a summary of its characteristics together with our evaluation and validation of the traffic demand and mobility patterns.

Luxembourg SUMO Traffic (LuST) Scenario: Traffic Demand Evaluation

Elyes Ben Hamida *, Hassan Noura and Wassim ZnaidiQatar Mobility Innovations Center (QMIC), Qatar Science and Technology Park (QSTP), Doha,P.O. Box 210531, Qatar; E-Mails: hnouran@gmail.com (H.N.); wassimz@qmic.com (W.Z.)* Author to whom correspondence should be addressed; E-Mail: elyesb@qmic.com;Tel.: +974-4459-5082.Academic Editor: Felipe JimenezReceived: 31 May 2015 / Accepted: 24 June 2015 / Published: 6 July 2015Abstract: Due to the growing number of vehicles on the roads worldwide, road trafﬁcaccidents are currently recognized as a major public safety problem. In this context,connected vehicles are considered as the key enabling technology to improve road safetyand to foster the emergence of next generation cooperative intelligent transport systems(ITS). Through the use of wireless communication technologies, the deployment of ITSwill enable vehicles to autonomously communicate with other nearby vehicles and roadsideinfrastructures and will open the door for a wide range of novel road safety and driverassistive applications. However, connecting wireless-enabled vehicles to external entitiescan make ITS applications vulnerable to various security threats, thus impacting the safetyof drivers. This article reviews the current research challenges and opportunities relatedto the development of secure and safe ITS applications. It ﬁrst explores the architectureand main characteristics of ITS systems and surveys the key enabling standards and projects.Then, various ITS security threats are analyzed and classiﬁed, along with their correspondingcryptographic countermeasures. Finally, a detailed ITS safety application case study isanalyzed and evaluated in light of the European ETSI TC ITS standard. An experimentaltest-bed is presented, and several elliptic curve digital signature algorithms (ECDSA) arebenchmarked for signing and verifying ITS safety messages. To conclude, lessons learned,open research challenges and opportunities are discussed.

Security of Cooperative Intelligent Transport Systems: Standards, Threats Analysis and

Connected autonomous vehicles are considered as mitigators
of issues such as traffic congestion, road safety, inefficient fuel
consumption and pollutant emissions that current road transportation
system suffers from. Connected autonomous vehicles
utilise communication systems to enhance the performance of
autonomous vehicles and consequently improve transportation by
enabling cooperative functionalities, namely, cooperative sensing
and cooperative manoeuvring. The former refers to the ability to
share and fuse information gathered from vehicle sensors and road
infrastructures to create a better understanding of the surrounding
environment while the latter enables groups of vehicles to drive in
a co-ordinated way which ultimately results in a safer and more efficient
driving environment. However, there is a gap in understanding
howand to what extent connectivity can contribute to improving the
efficiency, safety and performance of autonomous vehicles. Therefore,
the aim of this paper is to investigate the potential benefits
that can be achieved from connected autonomous vehicles through
analysing five use-cases: (i) vehicle platooning, (ii) lane changing,
(iii) intersection management, (iv) energy management and (v) road
friction estimation. The current paper highlights that although connectivity
can enhance the performance of autonomous vehicles and
contribute to the improvement of current transportation system performance,
the level of achievable benefits depends on factors such
as the penetration rate of connected vehicles, traffic scenarios and
the way of augmenting off-board information into vehicle control
systems.

Towards connected autonomous driving: review of use-cases

Vehicular cloud computing (VCC) is an improvement from conventional cloud computing to new revolutionized computing services including intelligent transportation, autonomous driving and vehicle control, Internet browsing, online documentation, and infotainment. It enables vehicles to autonomously share heterogeneous computational resources while solving unanticipated critical problems dynamically. However, in a world of black hats, technology often has a dark side as well. Therefore, the VCC is limited by considerable security and privacy challenges. The special characteristics of VCC, including the multitenancy nature of clouds, intermittent wireless communications, high mobility of vehicles, and rapid resource elasticity with decentralized operations, have promoted security solutions used in vehicular ad hoc networks and conventional cloud computing to be revised. This paper first presents a state-of-the-art study of VCC that focuses on VCC architecture, its features analysis, and extensive VCC applications. Second, the proposed threats identification taxonomy and an exhaustive survey on security and privacy issues in VCC are presented under a layered approach: physical resource layer, vehicle-to-anything (V2X) network layer, and vehicular cloud layer, as well as at a complete system level. Finally, we highlight and discuss challenges and open research issues that can be considered as future research directions.

Security and Privacy Challenges in Connected Vehicular Cloud Computing

The Internet of Things (IoT) envisions to connect billions of sensors to the Internet, in order to provide new applications and services for smart cities. IoT will allow the evolution of the Internet of Vehicles (IoV) from existing Vehicular Ad hoc Networks (VANETs), in which the delivery of various services will be offered to drivers by integrating vehicles, sensors, and mobile devices into a global network. To serve VANET with computational resources, Vehicular Cloud Computing (VCC) is recently envisioned with the objective of providing traffic solutions to improve our daily driving. These solutions involve applications and services for the benefit of Intelligent Transportation Systems (ITS), which represent an important part of IoV. Data collection is an important aspect in ITS, which can effectively serve online travel systems with the aid of Vehicular Cloud (VC). In this paper, we involve the new paradigm of VCC to propose a data collection model for the benefit of ITS. We show via simulation results that the participation of low percentage of vehicles in a dynamic VC is sufficient to provide meaningful data collection.

Vehicular Cloud data collection for Intelligent Transportation Systems

Vehicular networks reflect user mobility behavior and present complex microscopic and macroscopic mobility patterns. Microscopic mobility is often simplified in macroscopic systems and we argue that its impact is too largely neglected. Notwithstanding improvements in realistically modeling and predicting mobility, few vehicular traces - especially complex microscopic ones - are available to validate such models. In this paper, we present a realistic synthetic dataset of vehicular mobility over two daily traffic peaks in a small area: the Europarc roundabout in the town of Creteil, France. We outline how the description and comprehensive representation of local mobility at an intersection, such as the roundabout chosen here, is important for any interpretation made of it.

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On the importance of real data for microscopic urban vehicular mobility trace

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving.

https://hal.inria.fr/hal-01024271/document

VANET Applications: Hot Use Cases

Cooperative ITS is enabling vehicles to communicate with the infrastructure to provide improvements in traffic control. A promising approach consists in anticipating the road profile and the upcoming dynamic events like traffic lights. This topic has been addressed in the French public project Co-Drive through functions developed by Valeo named Green Light Optimal Speed Advisor (GLOSA). The system advises the optimal speed to pass the next traffic light without stopping. This paper presents results of its performance in different scenarios through simulations and real driving measurements. A scaling is done in an urban area, with different penetration rates in vehicle and infrastructure equipment for vehicular communication. Our simulation results indicate that GLOSA can reduce CO2 emissions, waiting time and travel time, both in experimental conditions and in real traffic conditions.

https://hal.inria.fr/hal-01159866/document

Real scenario and simulations on GLOSA traffic light system for reduced CO2 emissions, waiting time and travel time

Road intersections are considered to be bottlenecks for urban transportation whose impacts are longer travel times and wasted human resources. In this paper we focus on vehicle to vehicle communications (V2V) that allow exchanging data between vehicles. Considering that vehicles are controlled by drivers (not autonomous), we do not pretend to take control of them, nor is the goal to avoid collision or improve safety, as is often done elsewhere. By eliminating the potential overlaps of vehicular trajectories coming from all opposing directions at an intersection, our aim is to demonstrate the potential of communication between vehicles in a complex roundabout and test the connexion strength of that network. We test it on a synthetic trace that reproduces a real traffic flow at a roundabout in Creteil (France).

https://hal.inria.fr/hal-01346423/document

Marie-Ange Lebre

Papers

On the importance of real data for microscopic urban vehicular mobility trace

VANET Applications: Hot Use Cases

Real scenario and simulations on GLOSA traffic light system for reduced CO2 emissions, waiting time and travel time

Resilient, Decentralized V2V Online Stop-Free Strategy in a Complex Roundabout

Real scenario and simulations on GLOSA traffic light system for reduced CO2 emissions, waiting time and travel time