Modeling Intervehicle Spacing for Safe and Sustainable Operations on Two-Lane Roads

Andrea Pompigna, Giuseppe Cantisani (), Raffaele Mauro and Giulia Del Serrone
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Andrea Pompigna: Faculty of Technological & Innovation Sciences, Universitas Mercatorum, Piazza Mattei, 10, 00186 Rome, Italy
Giuseppe Cantisani: Department of Civil, Constructional and Environmental Engineering, University of Rome La Sapienza, Via Eudossiana 18, 00184 Rome, Italy
Raffaele Mauro: Department of Civil, Environmental and Mechanical Engineering, University of Trento, Via Mesiano 77, 38123 Trento, Italy
Giulia Del Serrone: Department of Civil, Constructional and Environmental Engineering, University of Rome La Sapienza, Via Eudossiana 18, 00184 Rome, Italy

Sustainability, 2025, vol. 17, issue 8, 1-21

Abstract: This paper examines the essential role of intervehicle spacing on two-lane rural roads, highlighting its significance for traffic safety and management. Recent technological advancements have enabled the precise positioning of vehicles on highways through video recordings and image processing techniques. However, these systems are less applicable to rural roads due to the absence of extensive sensor networks. This study bridges this gap by proposing a simulation-based model to evaluate the probability density of intervehicle spacing under varying traffic conditions. The simulation model integrates macroscopic traffic flow theories with microscopic car following models, simulating intervehicle spacings over a considerable highway segment. Calibration and validation were conducted using data from a two-lane road in Northern Italy. The simulation results identify key characteristics of spacing distribution, including positive skewness (i.e., a longer tail toward higher values), high kurtosis (a peaked distribution with frequent extreme values), non-zero minimum values, and autocorrelation at high traffic densities (indicative of platooning behavior). The Pearson type III distribution was determined to be the most suitable fit for the experimental data. Thus, future research should focus on parameter estimation for the Pearson type III distribution to further understand intervehicle spacing under varying traffic conditions and to expand applications to various road types and traffic scenarios.

Keywords: traffic management; vehicle spacing models; two-lane road safety; probabilistic traffic analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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