Maria Luisa Tumminello’s research while affiliated with University of Palermo and other places

This paper presents a simulation-driven method for assessing the safety and efficiency of traffic at roundabouts incorporating connected and automated vehicle (CAV) technology. Utilizing the newly proposed CAV-based factors specified by the Highway Capacity Manual (HCM) provided a practical framework for analyzing capacity dynamics across various traffic scenarios. Using microscopic traffic simulation on a roundabout model replicating real-world geometry and traffic attributes facilitated the identification of crucial behavioral parameters. This simulation spanned from smooth traffic scenarios to operational saturation, aiding in the study of mixed traffic scenarios during the transition to increasing CAV presence. Additionally, the study assessed the safety and traffic impact of a dedicated CAV lane using surrogate safety metrics. Aimsun software aided in model parameter calibration, which, combined with the Surrogate Safety Assessment Model (SSAM), supported safety analysis. Despite observed enhancements in roundabout performance with CAV integration, the benefits of a designated CAV lane highlighted the potential to reduce conflicts among vehicles. In conclusion, the paper emphasizes the overall performance enhancement achieved with CAVs at roundabouts while also providing insights for evaluating the potential of CAV technologies in future mobility management strategies.

This paper explores the domain of intelligent transportation systems, specifically focusing on roundabouts as potential solutions in the context of smart mobility. Roundabouts offer a safer and more efficient driving environment compared to other intersections, thanks to their curvilinear trajectories promoting speed control and lower vehicular speeds for traffic calming. The synthesis review supported the authors in presenting current knowledge and emerging needs in roundabout design and evaluation. A focused examination of the models and methods used to assess safety and operational performance of roundabout systems was necessary. This is particularly relevant in light of new challenges posed by the automotive market and the influence of vehicle-to-vehicle communication on the conceptualization and design of this road infrastructure. Two case studies of roundabouts were analyzed in Aimsun to simulate the increasing market penetration rates of connected and autonomous vehicles (CAVs) and their traffic impacts. Through microscopic traffic simulation, the research evaluated safety and performance efficiency advancements in roundabouts. The paper concludes by outlining areas for further research and evolving perspectives on the role of roundabouts in the transition toward connected and autonomous vehicles and infrastructures.

Traffic-calming measures (TCMs) are non-invasive devices designed to improve road mobility and urban areas on a human scale. Despite their potential, they have been in use for a long time and now have to deal with the latest technological innovations in the automotive field, such as cooperative driving technologies (CDTs), to improve energy efficiency in cities. The goal of this study is to explore the safety and operational performances of TCMs featuring CDTs in urban areas. An urban-scale road network close to a seaside area in the City of Mazara del Vallo, Italy, was properly redesigned and simulated in AIMSUN to assess several design solutions, where connected and automated vehicles (CAVs) have been employed as a more energy-efficient public transportation system. Preliminarily, the fine-tuning process of model parameters included CAVs and human-operated vehicles (HOVs) flowing through the network up to saturation conditions. The safety of the planned solutions was tested by using surrogate measures. The micro-simulation approach allowed us to know in advance and compare the operational and safety performances of environmentally friendly solutions involving TCMs and CDTs. These results can also support urban road decision makers in pivoting urban-traffic-calming-based design solutions featuring cooperative driving technologies toward energy efficiency transitions for smart cities.

There is increasing interest in connected and automated vehicles (CAVs), since their implementation will transform the nature of transportation and promote social and economic change. Transition toward cooperative driving still requires the understanding of some key questions to assess the performances of CAVs and human-driven vehicles on roundabouts and to properly balance road safety and traffic efficiency requirements. In this view, this paper proposes a simulation-based methodological framework aiming to assess the presence of increasing proportions of CAVs on roundabouts operating at a high-capacity utilization level. A roundabout was identified in Palermo City, Italy, and built in Aimsun (version 20) to describe the stepwise methodology. The CAV-based curves of capacity by entry mechanism were developed and then used as target capacities. To calibrate the model parameters, the capacity curves were compared with the capacity data simulated by Aimsun. The impact on the safety and performance efficiency of a lane dedicated to CAVs was also examined using surrogate measures of safety. The paper ends with highlighting a general improvement with CAVs on roundabouts, and with providing some insights to assess the advantages of the automated and connected driving technologies in transitioning to smarter mobility.

Connectivity and automation are technologies applied in combination to achieve increases in road safety, traffic efficiency and energy savings. Despite their potential, there are still many open questions regarding how roadway capacitycapacity will be affected and what methods should be employed to assess the expected benefits in the transportation domain. In this paper “what-if” scenarios were modelled in Aimsun Next to analyse assumption-based behaviour of automated vehicles operating with a cooperative adaptive cruise control system on roundaboutsroundabout. The idea behind the study comes from the availability of the capacity adjustment factors for connected and automated vehiclesconnected and automated vehicles provided by the Highway Capacitycapacity Manual for varying market penetration rates. The case study of a single lane roundabout was examined to compare the CAV-adjusted capacity curves and simulated capacitiescapacity, and to endorse hypothesis on the model parameters of Aimsun Next which mostly affect the CAVsconnected and automated vehicles’ ability to increase roundaboutroundabout’ throughput.

Despite the potential of connected and automated vehicles (CAVs), there are still many open questions on how road capacity can be influenced and what methods can be used to assess its expected benefits in the progressive transition towards fully cooperative driving. This paper contributes to a better understanding of the benefits of CAV technologies by investigating mobility-related issues of automated vehicles operating with a cooperative adaptive cruise control system on roundabout efficiency using microscopic traffic simulation. The availability of the adjustment factors for CAVs provided by the 2022 Highway Capacity Manual allowed to adjust the entry capacity equations to reflect the presence of CAVs on roundabouts. Two mechanisms of entry maneuver based on the entry lane type were examined to compare the capacity target values with the simulated capacities. The microscopic traffic simulator Aimsun Next has been of great help in building the “what-if” traffic scenarios that we analysed to endorse hypothesis on the model parameters which affect the CAVs’ capabilities to increase roundabouts’ throughput. The results highlighted that the increasing penetration rates of CAVs have greater impacts on the operational performances of roundabouts, and provided a synthetic insight to assess the potential benefits of CAVs from an efficiency perspective.

The paper describes the pilot study conducted to assess the feasibility of the empirical approach utilizing vehicle trajectory data from a smartphone app and the Vehicle-Specific Power methodology to estimate pollutant emissions at urban roundabouts. The goal of this research phase is to acquire instantaneous speed data from a sample of six roundabouts located in the road network of the City of Palermo, Italy, and quantify emissions generated by the test vehicle through the examined roundabouts. For the case studies of roundabouts acceleration events in the circulating and exiting areas contributed to about 25% of the emissions for a given speed profile. More in general, the results from this research shed lights for further opportunities to examine infrastructural scenarios when decision makers require to assess changes in the design or operation of urban transportation systems.

Passenger Car Equivalents (PCEs in the following) are used to transform a mixed fleet of vehicles into a fleet of equivalent passenger cars and to analyze capacity and level-of-service of roads and intersections. Most roundabouts guidelines propose constant values for PCEs but a single PCE value can result improper under heterogeneous traffic conditions. PCEs should be vary with traffic and road conditions and consequently PCEs applied to undersaturated traffic conditions can overestimate the heavy vehicle effect or be not sensitive to the traffic level or characteristics of heavy vehicles. Compared to other at-grade intersections, the interaction between the operational performances of the heavy vehicles and the geometric features at roundabouts can produce significant impacts on the heavy vehicle paths and traffic operations due to the curvilinear nature of the roundabout design. Literature presents various methods of estimation to obtain PCE values for heavy vehicles. The focus of this paper is to review statistical methods and traffic simulation studies based on microscopic approaches used to calculate PCEs for heavy vehicles driving roundabouts. Effects on capacity and estimates of PCEs based on models currently employed in roundabout analysis are also compared. The results obtained in this study aim at providing an overview of the existing knowledge concerning the estimation of PCEs at roundabouts and can represent a guideline for transportation engineers in planning, design and capacity analysis of roundabouts that operate under conditions of mixed traffic.

This paper addresses issues on road safety analysis through microscopic traffic simulation models. The Surrogate Safety Assessment Model (SSAM) was applied to read vehicle trajectory files generated by two micro-simulators and then calculate surrogate measures of safety. Since safety assessment of any road entity can provide different results based on the micro-simulator which is used, the main objective of this research was to estimate the safety performance of three roundabout layouts and compare the conflict events simulated by AIMSUN and VISSIM. The two micro-simulators were used to build the calibrated models of the roundabouts, each fitting the corresponding empirical capacity function. The results provided insights on how to set the SSAM filters in order to have a comparable frequency of conflicts by simulation and examine conditions under which a safety analysis could be independent of the software used.

The paper presents a microsimulation-based approach for roundabout safety performance evaluation. Based on a sample of Slovenian roundabouts, the vehicle trajectories exported from AIMSUN and VISSIM were used to estimate traffic conflicts using the Surrogate Safety Assessment Model (SSAM). AIMSUN and VISSIM were calibrated for single-lane, double-lane and turbo roundabouts using the corresponding empirical capacity function which included critical and follow-up headways estimated through meta-analysis. Based on calibration of the microsimulation models, a crash prediction model from simulated peak hour conflicts for a sample of Slovenian roundabouts was developed. A generalized linear model framework was used to estimate the prediction model based on field collected crash data for 26 existing roundabouts across the country. Peak hour traffic distribution was simulated with AIMSUN, and peak hour conflicts were then estimated with the SSAM applying the filters identified by calibrating AIMSUN and VISSIM. The crash prediction model was based on the assumption that the crashes per year are a function of peak hour conflicts, the ratio of peak hour traffic volume to average daily traffic volume and the roundabout outer diameter. Goodness-of-fit criteria highlighted how well the model fitted the set of observations also better than the SSAM predictive model. The results highlighted that the safety assessment of any road unit may rely on surrogate safety measures, but it strongly depends on microscopic traffic simulation model used.