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

Abstract

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 endto-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.

The Use of Meta-Surfaces in Vehicular Networks

“…Hence, in addition to the safety measures to protect vehicle occupants, determined efforts have to be done to implement specific measures to prevent fatalities and injuries of VRUs, such as cyclists and pedestrians, is needed to protect users outside of the vehicle [59]. Current pedestrian detection is based on advanced driver assistance systems (ADAS) with onboard sensors, such as cameras, radar and LIDAR, to detect the presence of VRUs [60,61]. All of these sensors require line of sight (LOS) to properly work and they cannot detect VRUs in case of obstacles partially or totally occluding the visibility, such as trees, trucks or buildings.…”

Cooperative Automated Vehicles: A Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking

“…13 Human-vehicle interaction mediated by v2x communication (e.g., vehicle to wearable device) can provide a greater level of communication between human and vehicle, complementary to, or as an alternative to, visual physical gestures or signaling. A Vehicleto-Pedestrian framework is provided in [63] using a DSRCenabled smartphone.…”

A Learning-Based Stochastic MPC Design for Cooperative Adaptive Cruise Control to Handle Interfering Vehicles

“…To show that Ω is invariant over the infinite horizon of the second mode of (15), constraint satisfaction should be checked over a long enough finite horizon (N c ). Here, N c is the smallest number which satisfies the following equations…”

“…The state variables of system (13), x[k], asymptotically converge to zero, i.e. the system is asymptotically stable, under the control law(15) if predicted cost J[k] is an infinite cost, (A, Q 12 ) is observable, and the tailũ[k] is feasible for all k > 0 wherẽu[k + 1] = u * [k + 1|k], . .…”