Exploiting Traffic Light Coordination and Auctions for Intersection and Emergency Vehicle Management in a Smart City Mixed Scenario

Abstract

IoT (Internet-of-Things)-powered devices can be exploited to connect vehicles to smart city infrastructure, allowing vehicles to share their intentions while retrieving contextual information about diverse aspects of urban viability. In this paper, we place ourselves in a transient scenario in which next-generation vehicles that are able to communicate with the surrounding infrastructure coexist with traditional vehicles with limited or absent IoT capabilities. We focus on intersection management, in particular on reusing existing traffic lights empowered by a new management system. We propose an auction-based system in which traffic lights are able to exchange contextual information with vehicles and other nearby traffic lights with the aim of reducing average waiting times at intersections and consequently overall trip times. We use bid propagation to improve standard vehicle trip times while allowing emergency vehicles to free up the way ahead without needing ad hoc system for such vehicle, only an increase in their budget. The proposed system is then tested against two baselines: the classical Fixed Time Control system currently adopted for traffic lights, and an auction strategy that does not exploit traffic light coordination. We performed a large set of experiments using the well known MATSim transport simulator on both a synthetic Manhattan map and on a map we built of an urban area located in Modena, Northern Italy. Our results show that the proposed approach performs better than the classical fixed time control system and the auction strategy that does not exploit coordination among traffic lights.

Learning-Based Non-Intrusive Electric Load Monitoring for Smart Energy Management

“…The past decades have witnessed a booming of urban populations with ever-increased municipal facilities to serve all citizens. An effective solution to manage these facilities is smart city with Internet of Things (IoT), which is mostly benefitted from the recent development of Artificial Intelligence (AI) [1][2][3]. To support the smart city, an economic but efficient electric power management system is indispensable [4].…”

Learning-Based Non-Intrusive Electric Load Monitoring for Smart Energy Management

“…The past decades have witnessed a booming of urban populations with ever-increased municipal facilities to serve all citizens. An effective solution for managing these facilities is a smart city with an Internet of Things (IoT), which is mostly benefited from the recent development of Artificial Intelligence (AI) [1][2][3]. To support the smart city, an economic but efficient electric power management system is indispensable [4].…”