Given a set of moving objects as well as their friend relationships, a time-aware road network, and a time threshold per friend pair, the proximity detection problem in time-aware road networks is to find each pair of moving objects such that the time distance (defined as the shortest time needed for two moving objects to meet each other) between them is within the given threshold. The problem of proximity detection is often encountered in autonomous driving and traffic safety related applications, which require low-latency, real time proximity detection with relatively low communication cost. However, (i) most existing proximity detection solutions focus on the Euclidean space which cannot be used in road network space, (ii) the solutions for road networks focus on static road networks and do not consider time distance and thus cannot be applied in time-aware road networks, and (iii) there are no works aiming to simultaneously reduce the communication cost, the communication latency, and computational cost. Motivated by these, we first design a low-latency proximity detection architecture based on Mobile Edge Computing (MEC) with the purpose of achieving low communication latency, then propose a proximity detection method including a client-side algorithm and a server-side algorithm, aiming at reducing the communication cost, and subsequently propose server-side computational cost optimization techniques to reduce the computational cost. Experimental results show that our MEC enhanced proximity detection architecture, our proximity detection method, and the server-side computational cost optimization techniques can reduce the communication latency, the communication cost, and the computational cost effectively.

Introduction

In a road network, how to effectively detect whether the moving users are within proximity or not, is referred to as the problem of proximity detection in road networks. In a dynamically changing road network, proximity detection among a large number of moving users plays an important role in ensuring traffic safety, guaranteeing assisted driving, and realizing the future large-scale autonomous driving. With the spreading of modern mobile devices like smart phones, PDAs or car navigation systems and the development of positioning technologies such as GPS, WiFi, cellular base station positioning or A-GPS, users can conveniently obtain their positions and send their location information to control center servers or other users’ mobile devices. Mobile users communicate with servers or other users frequently, leading to a large number of communication messages referred to as communication cost, consuming a lot of network bandwidth. Given a large number of mobile users and time distance T , time-aware proximity detection problem in road networks is to find a solution which not only can continuously detect which pairs of users among all users are within proximity based on time distance, but also can achieve the objectives of reducing communication cost, communication latency, and computational cost, so as to save the network bandwidth and improve the reliability and efficiency of proximity detection. Here, time distance refers to the shortest time needed for two users to meet each other.