Simulation of connected driving in hazardous weather conditions: General and extensible multiagent architecture and models

Based on historical records, driving in hazardous weather conditions is one of the most serious causes that lead to fatal accidents on roads in general and in United Arab Emirates (UAE) highways in particular. One solution for improving road safety is to equip the vehicles and infrastructure with connected and smart devices. Before deploying a concrete solution to the field, it must be validated by simulation, and more specifically agent-based simulation. Several key features are expected for the simulation framework, such as the reproduction of different and detailed behaviors for the components of the road infrastructure and for the drivers, simulate specific weather conditions and forecast their impacts on the global system behavior. Additionally, several technological features are related to recent advancements in agent software engineering and simulation. This paper proposes an agent-based model for the modeling and simulation of traffic in foggy weather conditions that covers the above features and technological requirements. The architecture is used and validated on two scenarios of traffic on UAE highways in foggy weather conditions. The first scenario does not include an intelligent transport system, and the second considers smart speed limit panels. From the experiments, the proposed model supports the expected key features, i.e., microscopic simulation of intelligent transport systems, including infrastructure and connected cars, and of different driving behaviors (human or autonomous car). Even if the included weather condition model is basic, a proof of concept is provided regarding the connection of an agent model and a weather condition model

Comparison of Reaction Time-based Collaborative Velocity Control and Intelligent Driver Model for Agent-based Simulation of Autonomous Car

Based on historical records, driving in hazardous weather conditions is one of the most serious causes that lead to fatal accidents on roads in general and in United Arab Emirates (UAE) highways in particular. One solution to improve road safety is to equip vehicles and infrastructure with connected and smart devices and convert them into autonomous vehicles. Before deploying a concrete solution to the field, it must be validated by simulation, and more specifically by agent-based simulation. In this paper, we propose to implement the Reaction Time-Based Collaborative Velocity Control (RT-CVC) model that was implemented in autonomous cars into an agent-based simulator. This model is compared to the Intelligent Driver Model (IDM), which is one of the standard longitudinal driving behaviors in simulation environments. The experimental results show that RT-CVC generates traffic flows with fewer vehicle collisions and shorter travel times. This positive analysis is balanced by the fact that RT-CVC is designed for autonomous cars, and IDM is designed to model human-drive decisions. Using RT-CVC for modeling a human driver may be counter productive in simulation experiments

Curvature-Based Geometric Approach for the Lateral Control of Autonomous Cars

International audienc

Privacy Threat Analysis for connected and autonomous vehicles

International audienceConnected and autonomous vehicles produce, store and communicate a large amount of personal data (the route taken, the stop points, home and work addresses, etc.). The development of this type of vehicles brings the opportunity to offer new services to road users, with more software and hardware components on the vehicle. Many of these components suffer from weaknesses that can be exploited. The issue is that a single vulnerability in one element of the system will threaten the privacy of the vehicle's users (The weakest link principle of IT security). In this paper, we present a privacy threat analysis on the general architecture of connected and autonomous vehicles, to point out privacy risks according to formal privacy requirements. We present a use case modularization and its analysis that helps us to discern the privacy requirements of this use case, which can be enabled by manufacturers. To meet the previous objectives, we follow a LINDDUN methodology of privacy threat analysi

Utilisation de la conduite en convoi pour la conception de nouveau systèmes de transports innovants pour la livraison de marchandises dans les centres-villes

International audienc

Addressing hazardous weather conditions on Middle East highways with smart infrastructure and connected vehicles using agent-based simulation

The lack of visibility due to foggy conditions is known to cause of a lot of accidents every year in the United Arab Emirates, eventually leading to fatal injuries. Yet, today’s technology can help to overcome these visibility issues by providing dynamic information to the driver about the current weather and an appropriate speed limit. This paper explores four strategies, ranging from static road signs to advanced inter-vehicular communication, to better warn the drivers and make them adapt their speed depending on the weather. To evaluate the impact of each policy, agent-based simulations are designed and performed. The results show that a dynamic communication about the weather conditions, supported by either an infrastructure-to-vehicle or a vehicle-to-vehicle protocol, can reduce the probability of occurrence of accidents