Implementation and Evaluation of a Cooperative Vehicle-to-Pedestrian Safety Application

While the development of Vehicle-to-Vehicle (V2V) safety applications based on Dedicated Short-Range Communications (DSRC) has been extensively undergoing standardization for more than a decade, such applications are extremely missing for Vulnerable Road Users (VRUs). Nonexistence of collaborative systems between VRUs and vehicles was the main reason for this lack of attention. Recent developments in Wi-Fi Direct and DSRC-enabled smartphones are changing this perspective. Leveraging the existing V2V platforms, we propose a new framework using a DSRC-enabled smartphone to extend safety benefits to VRUs. The interoperability of applications between vehicles and portable DSRC enabled devices is achieved through the SAE J2735 Personal Safety Message (PSM). However, considering the fact that VRU movement dynamics, response times, and crash scenarios are fundamentally different from vehicles, a specific framework should be designed for VRU safety applications to study their performance. In this article, we first propose an end-to-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection based on the most common and injury-prone crash scenarios. The details of our VRU safety module, including target classification and collision detection algorithms, are explained next. Furthermore, we propose and evaluate a mitigating solution for congestion and power consumption issues in such systems. Finally, the whole system is implemented and analyzed for realistic crash scenarios

Towards Full Automated Drive in Urban Environments: A Demonstration in GoMentum Station, California

Each year, millions of motor vehicle traffic accidents all over the world cause a large number of fatalities, injuries and significant material loss. Automated Driving (AD) has potential to drastically reduce such accidents. In this work, we focus on the technical challenges that arise from AD in urban environments. We present the overall architecture of an AD system and describe in detail the perception and planning modules. The AD system, built on a modified Acura RLX, was demonstrated in a course in GoMentum Station in California. We demonstrated autonomous handling of 4 scenarios: traffic lights, cross-traffic at intersections, construction zones and pedestrians. The AD vehicle displayed safe behavior and performed consistently in repeated demonstrations with slight variations in conditions. Overall, we completed 44 runs, encompassing 110km of automated driving with only 3 cases where the driver intervened the control of the vehicle, mostly due to error in GPS positioning. Our demonstration showed that robust and consistent behavior in urban scenarios is possible, yet more investigation is necessary for full scale roll-out on public roads.Comment: Accepted to Intelligent Vehicles Conference (IV 2017

Requirement analysis for building practical accident warning systems based on vehicular ad-hoc networks

An Accident Warning System (AWS) is a safety application that provides collision avoidance notifications for next generation vehicles whilst Vehicular Ad-hoc Networks (VANETs) provide the communication functionality to exchange these notifi- cations. Despite much previous research, there is little agreement on the requirements for accident warning systems. In order to build a practical warning system, it is important to ascertain the system requirements, information to be exchanged, and protocols needed for communication between vehicles. This paper presents a practical model of an accident warning system by stipulating the requirements in a realistic manner and thoroughly reviewing previous proposals with a view to identify gaps in this area

A survey on pseudonym changing strategies for Vehicular Ad-Hoc Networks

The initial phase of the deployment of Vehicular Ad-Hoc Networks (VANETs) has begun and many research challenges still need to be addressed. Location privacy continues to be in the top of these challenges. Indeed, both of academia and industry agreed to apply the pseudonym changing approach as a solution to protect the location privacy of VANETs'users. However, due to the pseudonyms linking attack, a simple changing of pseudonym shown to be inefficient to provide the required protection. For this reason, many pseudonym changing strategies have been suggested to provide an effective pseudonym changing. Unfortunately, the development of an effective pseudonym changing strategy for VANETs is still an open issue. In this paper, we present a comprehensive survey and classification of pseudonym changing strategies. We then discuss and compare them with respect to some relevant criteria. Finally, we highlight some current researches, and open issues and give some future directions

Context-based Pseudonym Changing Scheme for Vehicular Adhoc Networks

Vehicular adhoc networks allow vehicles to share their information for safety and traffic efficiency. However, sharing information may threaten the driver privacy because it includes spatiotemporal information and is broadcast publicly and periodically. In this paper, we propose a context-adaptive pseudonym changing scheme which lets a vehicle decide autonomously when to change its pseudonym and how long it should remain silent to ensure unlinkability. This scheme adapts dynamically based on the density of the surrounding traffic and the user privacy preferences. We employ a multi-target tracking algorithm to measure privacy in terms of traceability in realistic vehicle traces. We use Monte Carlo analysis to estimate the quality of service (QoS) of a forward collision warning application when vehicles apply this scheme. According to the experimental results, the proposed scheme provides a better compromise between traceability and QoS than a random silent period scheme.Comment: Extended version of a previous paper "K. Emara, W. Woerndl, and J. Schlichter, "Poster: Context-Adaptive User-Centric Privacy Scheme for VANET," in Proceedings of the 11th EAI International Conference on Security and Privacy in Communication Networks, SecureComm'15. Dallas, TX, USA: Springer, June 2015.