3D driving simulator with VANET capabilities to assess cooperative systems: 3DSimVanet

Michaeler, Florian; Olaverri-Monreal, Cristina

doi:10.1109/ivs.2017.7995845

Cited by 21 publications

(8 citation statements)

References 9 publications

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“…Akhtar et al [32] presented simulation model of microscopic mobility VANET segment by using SUMO [33] traffic simulation package and Freeway Performance Measurement System database. Michaeler et al [34] presented 3-dimensional driving simulator based on Open-StreetMap data, which integrates VANET communication capabilities. Buse et al [35] proposed event-driven simulator with a city-scale VANET simulation for the advanced driver assistance system development.…”

Section: Related Workmentioning

confidence: 99%

Message Authentication and Network Anomalies Detection in Vehicular Ad Hoc Networks

Legashev

Bolodurina

Zabrodina

et al. 2022

Security and Communication Networks

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Intelligent transport systems are the future in matters of safe roads and comfortable driving. Integration of vehicles into a unified intelligent network leads to all kinds of security issues and cyber threats common to conventional networks. Rapid development of mobile ad hoc networks and machine learning methods allows us to ensure security of intelligent transport systems. In this paper, we design an authentication scheme that can be used to ensure message integrity and preserve conditional privacy for the vehicle user. The proposed authentication scheme is designed with lightweight cryptography methods, so that it only brings little computational and communication overhead. We also conduct experiments on vehicular ad hoc network segment traffic generation in OMNeT++ tool and apply up-to-date machine learning methods to detect malicious behavior in a given simulated environment. The results of the study show high accuracy in distributed denial-of-service attack detection.

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Section: Related Workmentioning

confidence: 99%

Message Authentication and Network Anomalies Detection in Vehicular Ad Hoc Networks

Legashev

Bolodurina

Zabrodina

et al. 2022

Security and Communication Networks

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“…The 3DCoAutoSim simulation platform was originally implemented to mimic Vehicle-to-Vehicle (V2V) [6] communication from a driver-centric perspective [7] and has been continuously extended to include automated capabilities and reproduce cooperative Advanced Driving Assistance Systems (ADAS). It uses vehicular data connection among multiple simulators and makes it possible to test applications that are additionally based on Vehicle-to-Infrastructure (V2I) or/and Vehicle-to-Pedestrian (V2P) communication [8]- [11].…”

Section: Introductionmentioning

confidence: 99%

Simulation-Based Impact of Connected Vehicles in Platooning Mode on Travel Time, Emissions and Fuel Consumption

Validi,

Olaverri-Monreal

2021

Preprint

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Several approaches have been presented during the last decades to reduce carbon pollution from transportation. One example is the use of platooning mode. This paper considers data obtained from daily trips to investigate the impact of platooning on travel time, emissions of CO2, CO, NOx and HC and fuel consumption on a road network in Upper Austria. For this purpose, we studied fuel combustion-based engines relying on the extension of the 3DCoAutoSim simulation platform. The obtained results showed that the platooning mode not only increased driving efficiency but also decreased the total emissions by reducing fuel consumption.

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“…There has been a drastic increase in the number of vehicular systems on the market that rely on some degree of automation. These advanced driving assistance systems (ADAS) enhance driver perception and augment the drivers awareness of the surrounding environment, thereby helping to increase road safety [1]. However, they are not necessarily accepted and utilized by all users, reflecting the perceived trustworthiness of the automation and the skepticism of drivers.…”

Section: Introductionmentioning

confidence: 99%

Vehicle Automation Field Test: Impact on Driver Behavior and Trust

Morales-Alvarez

Smirnov

Matthes

et al. 2020

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)

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With the growing technological advances in autonomous driving, the transport industry and research community seek to determine the impact that autonomous vehicles (AV) will have on consumers, as well as identify the different factors that will influence their use. Most of the research performed so far relies on laboratory-controlled conditions using driving simulators, as they offer a safe environment for testing advanced driving assistance systems (ADAS). In this study we analyze the behavior of drivers that are placed in control of an automated vehicle in a real life driving environment. The vehicle is equipped with advanced autonomy, making driver control of the vehicle unnecessary in many scenarios, although a driver take over is possible and sometimes required. In doing so, we aim to determine the impact of such a system on the driver and their driving performance. To this end road users' behavior from naturalistic driving data is analyzed focusing on awareness and diagnosis of the road situation. Results showed that the road features determined the level of visual attention and trust in the automation. They also showed that the activities performed during the automation affected the reaction time to take over the control of the vehicle.

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3D driving simulator with VANET capabilities to assess cooperative systems: 3DSimVanet

Cited by 21 publications

References 9 publications

Message Authentication and Network Anomalies Detection in Vehicular Ad Hoc Networks

Message Authentication and Network Anomalies Detection in Vehicular Ad Hoc Networks

Simulation-Based Impact of Connected Vehicles in Platooning Mode on Travel Time, Emissions and Fuel Consumption

Vehicle Automation Field Test: Impact on Driver Behavior and Trust

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