Abstract

In the face of cooperative intelligent transportation systems (C-ITS) advancements, the inclusion of vulnerable road users (VRU), i.e., pedestrians, cyclists, and motorcyclists, has just recently become a part of the discussion. Including VRU in C-ITS presents new challenges, most notably the trade-off between the increase in VRU safety and the aggravation in channel congestion resulting from VRU-generated messages. However, previous studies mainly focus on network-related metrics without giving much consideration to VRU safety-related metrics. In this context, we evaluated such a trade-off with a study of motion-based message generation rules for VRU transmissions. The rules were analyzed using theoretical and simulation-based evaluations. In addition to studying the message generation rules using channel load metrics, such as channel busy ratio (CBR) and packet delivery ratio (PDR), we introduced a new metric: the VRU Awareness Probability (VAP). VAP uses the exchange of messages from active VRU to measure the probability of VRU detection by nearby vehicles. Results show that fixed message-filtering mechanisms reduce the overall channel load, but they could negatively impact VRU detection. We established the importance of quantifying the VRU awareness and its inclusion in C-ITS analysis because of its direct impact on VRU safety. We also discussed approaches that include VRU context and dynamism to improve the definition of message generation rules.

Highlights

  • We conducted a trade-off study based on channel busy ratio (CBR), packet delivery ratio (PDR), and VRU Awareness Probability (VAP) to analyze vulnerable road users (VRU) message generation rules proposed in the literature [4]

  • Such a metric is complemented with the channel busy ratio (CBR) and the packet delivery ratio (PDR) to account for the channel load and successful delivery of packets, respectively

  • We introduced a novel VRU awareness metric—VRU awareness probability (VAP)—and studied existing message generation rules on channel load and VRU awareness

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Vehicular networking represents one of the critical elements to enable a diverse set of applications related to intelligent transportation systems (ITS). Such applications range from safety to convenience services bringing benefits to accident prevention, accident mitigation, traffic optimization, comfort, and many others [1]. The most common approach is passive detection, in which vehicles use different sensor technologies, such as video analysis and object detection based on nonvisible light, to characterize the surroundings (e.g., signalization elements and presence of pedestrians) and to identify possible traffic threats involving other road users. Despite the benefits that C-ITS brings to traffic safety, existing systems still fail to include all possible road users as active participants in the communication processes [8]. The lack of inclusion of these actors in the planning, design, and management of road operations explains a significant percentage of these fatalities [11]

Motivation
Contributions
Related Work
System Model
VRU Message Generation Rules
Evaluation Metrics
Simulation Analysis
Evaluating the Impact of VRU Message Generation Rules
Analysis of Baseline VRU Transmissions
Comparison of Baseline and Message Generation Rules
Node Behavior Variation
Variation for MultiTx Rule
Summary of Results
Conclusions
Full Text
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