mobile systems applied to traffic management and safety a state of the art

Abstract Mobile systems applied to traffic management and control and traffic safety have the potential to shape the future of road transportation. The following innovations, that will be deployed on a large scale, could reshape road traffic management practices: – the implementation of connected vehicles with global navigation satellite (GNSS) system receivers; – the autonomous car revolution; – the spreading of smartphone-based systems and the development of Mobile Cooperative Web 2.0 which is laying the base for future development of systems that will also incorporate connected and autonomous vehicles; – an increasing need for sustainability of transportation in terms of energy efficiency, traffic safety and environmental issues. This paper intends to provide a state of the art on current systems and an anticipation of how mobile systems applied to traffic management and safety could lead to a completely new transportation system in which safety and congestion issues are finally properly addressed

A review of traffic signal control methods and experiments based on Floating Car Data (FCD)

Abstract This paper intends to give a short review of the state of the art on the use of floating car data concerning the management of traffic flow at signalized intersections. New technologies such as connected and autonomous vehicles and Co-operative Intelligent Transportation Systems (C-ITS) are going to change the future of traffic control and management. Traffic signal control systems can be reorganized by using Floating Car Data (FCD), yet the concept of floating car data (FCD) has been mainly studied to gain traffic information and/or signal information. Only recent works have been focalizing on the potential application of FCD for traffic signal real-time control. This paper aims to evidence the most important concepts that can be extracted from the literature on this important topic

Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in Multi-Agent RL

Most existing works consider direct perturbations of victim's state/action or the underlying transition dynamics to show vulnerability of reinforcement learning agents under adversarial attacks. However, such direct manipulation may not always be feasible in practice. In this paper, we consider another common and realistic attack setup: in a multi-agent RL setting with well-trained agents, during deployment time, the victim agent $\nu$ is exploited by an attacker who controls another agent $\alpha$ to act adversarially against the victim using an \textit{adversarial policy}. Prior attack models under such setup do not consider that the attacker can confront resistance and thus can only take partial control of the agent $\alpha$, as well as introducing perceivable ``abnormal'' behaviors that are easily detectable. A provable defense against these adversarial policies is also lacking. To resolve these issues, we introduce a more general attack formulation that models to what extent the adversary is able to control the agent to produce the adversarial policy. Based on such a generalized attack framework, the attacker can also regulate the state distribution shift caused by the attack through an attack budget, and thus produce stealthy adversarial policies that can exploit the victim agent. Furthermore, we provide the first provably robust defenses with convergence guarantee to the most robust victim policy via adversarial training with timescale separation, in sharp contrast to adversarial training in supervised learning which may only provide {\it empirical} defenses

Cyber Risk Assessment and Scoring Model for Small Unmanned Aerial Vehicles

The commercial-off-the-shelf small Unmanned Aerial Vehicle (UAV) market is expanding rapidly in response to interest from hobbyists, commercial businesses, and military operators. The core commercial mission set directly relates to many current military requirements and strategies, with a priority on short range, low cost, real time aerial imaging, and limited modular payloads. These small vehicles present small radar cross sections, low heat signatures, and carry a variety of sensors and payloads. As with many new technologies, security seems secondary to the goal of reaching the market as soon as innovation is viable. Research indicates a growth in exploits and vulnerabilities applicable to small UAV systems, from individual UAV guidance and autopilot controls to the mobile ground station devices that may be as simple as a cellphone application controlling several aircraft. Even if developers strive to improve the security of small UAVs, consumers are left without meaningful insight into the hardware and software protections installed when buying these systems. To date, there is no marketed or accredited risk index for small UAVs. Building from similar domains of aircraft operation, information technologies, cyber-physical systems, and cyber insurance, a cyber risk assessment methodology tailored for small UAVs is proposed and presented in this research. Through case studies of popular models and tailored mission-environment scenarios, the assessment is shown to meet the three objectives of ease-of-use, breadth, and readability. By allowing a cyber risk assessment at or before acquisition, organizations and individuals will be able to accurately compare and choose the best aircraft for their mission

Ubiqutious transport systems: Negotiating context through a mobile-stationary interface

Ubiquitous computing environments grant organizations a multitude of dynamic digital traces composed of context signals emanating from embedded and mobile components. However, previous research indicates that the utility of context data is frequently hampered by a priori interpretations of context embodied within the acquiring technologies themselves. This paper reports an 18 month action research study seeking to rearrange an industry wide assemblage of stationary, mobile, and embedded technologies and associated organizations for the purpose of facilitating cross-organizational access to reinterpretable digital traces of context data. This was done by embedding the notion of seamfulness in an open standardized interface as a means to shift the locus of interpretation of context data in ubiquitous transport systems. In environments such as these, open access to context data is of essential importance to create opportunities for flexible interpretations of mobile work for uses not anticipated by preconfigured representations. However, this requirement essentially clashed with the business strategies of actors providing context data acquiring technology. This clash resulted in a negotiated design compromise of limited access and a well defined expansion of additional uses of context data between the involved actor groups. Addressing the issue of how organizations can derive value from context data, the contribution of this paper is an analysis of the complexity of accomplishing links between socio-technical elements in ubiquitous computing environments

An Approach to Guide Users Towards Less Revealing Internet Browsers

When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Previous research has shown that there are numerous privacy and security risks result from exposing sensitive information in the User-Agent string. For example, it enables device and browser fingerprinting and user tracking and identification. Our large analysis of thousands of User-Agent strings shows that browsers differ tremendously in the amount of information they include in their User-Agent strings. As such, our work aims at guiding users towards using less exposing browsers. In doing so, we propose to assign an exposure score to browsers based on the information they expose and vulnerability records. Thus, our contribution in this work is as follows: first, provide a full implementation that is ready to be deployed and used by users. Second, conduct a user study to identify the effectiveness and limitations of our proposed approach. Our implementation is based on using more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available and the solution has been deployed

Stadtpilot: First Fully Autonomous Test Drives in Urban Traffic

The Stadtpilot project aims at autonomous driving on Braunschweig's inner city ring road. For this purpose, an autonomous vehicle called "Leonie" has been developed. In October 2010, after two years of research, "Leonie's" abilities were presented in a public demonstration. This vehicle is one of the first worldwide to show the ability of driving autonomously in real urban traffic scenarios. This paper describes the legal issues and the homologation process for driving autonomously in public traffic in Braunschweig, Germany. It also dwells on the Safety Concept, the system architecture and current research activities