Fuzzy-Based Variable Speed Limits System Under Connected Vehicle Environment: A Simulation-Based Case Study in the City of Naples

Abstract

This paper handles the problem of controlling speed limits on freeways in a connected traffic environment to reduce traffic congestion and improve both the operational and environmental performance of the road network. In order to achieve this objective, we present a Variable Speed Limit (VSL) system that utilizes fuzzy logic, which adjusts the speed limits that connected vehicles must comply with by leveraging traffic data such as vehicle flow, occupancy, and speed obtained from loop detectors installed along the road. To evaluate the effectiveness of the proposed Fuzzy-based VSL system and its potential benefits compared to the conventional rule-based VSL system in terms of traffic congestion and environmental impact, we conducted a simulation analysis using the microscopic traffic simulator, VISSIM. Specifically, three simulation scenarios are taken into account: i) no VSL, where the VSL system is not enabled; ii) Rule-based VSL system, where a typical a decision tree-based system is considered; iii) Fuzzy-based VSL system, where the herein proposed approach is appraised. The results demonstrate that the proposed approach enhances road efficiency by decreasing speed variation, increasing average speed and vehicle volume, and reducing fuel consumption.

Statistical and Clustering-Based Assessment of Variable Speed Limits Effects on Motorway Performance from Real-World Observations

“…Development of robust and responsive models' specifications, together with accurate calibration, are needed to achieve a good grade of representativity of the modeled system. Simulation models are frequently applied to the behavior of traffic flow with the primary objective to assess the effectiveness of different control strategies with low expenses [6][7][8][9][10][11][12][13].…”

“…Table 1 covers the main methods and synthetic results obtained for both simulation evaluation and field evaluation of VSL systems. While simulation studies have widely reported benefits both in safety conditions [7,9,[11][12][13]36] and traffic flow performance in the case of VSL application [6,8,9,11], according to the several experimental applications of the VSL system, the effectiveness of this control strategy remains uncertain. Despite most of the field studies concerning safety having proved VSL as an effective control strategy [27,32], the studies related to road traffic performances report controversial results.…”

Reinforcement Learning-Based Dynamic Zone Positions for Mixed Traffic Flow Variable Speed Limit Control with Congestion Detection

“…Previously analyzed VSL control approaches applied in mixed traffic flow environments considered the state space based on the occupancy rates reported by the loop detectors mounted on fixed positions [19], with the loop detectors placed on four measured mainstream lanes [20], while in [21], traffic data collected using loop detectors included local speed, occupancy, and traffic flow data, which were used to transmit the environment state to the fuzzy controller that computes speed limits. In [12], traffic states were obtained at the initial position of each cell by collecting traffic information such as the number of vehicles, vehicle speed, and density of the cell, and the inflow of vehicles was calculated.…”

Variable Speed Limit Control for the Motorway–Urban Merging Bottlenecks Using Multi-Agent Reinforcement Learning

“…As a part of the intelligent transportation system (ITS), variable speed limit (VSL) control has been widely used as one of the traffic control measures to improve traffic efficiency [11][12][13], benefit the environment [14,15], and enhance traffic safety [16,17] in bottleneck areas. By adjusting the speed limit of the main line upstream of the bottlenecks, the number of vehicles entering the motorway bottleneck area during the congestion period is controlled within a certain range to keep the traffic state more uniform and stable.…”