Modeling Automated Driving in Microscopic Traffic Simulations for Traffic Performance Evaluations: Aspects to Consider and State of the Practice

Abstract

The gradual deployment of automated vehicles on the existing road network will lead to a long transition period in which vehicles at different driving automation levels and capabilities will share the road with human driven vehicles, resulting into what is known as mixed traffic. Whether our road infrastructure is ready to safely and efficiently accommodate this mixed traffic remains a knowledge gap. Microscopic traffic simulation provides a proactive approach for assessing these implications. However, differences in assumptions regarding modeling automated driving in current simulation studies, and the use of different terminology make it difficult to compare the results of these studies. Therefore, the aim of this study is to specify the aspects to consider for modeling automated driving in microscopic traffic simulations using harmonized concepts, to investigate how both empirical studies and microscopic traffic simulation studies on automated driving have considered the proposed aspects, and to identify the state of the practice and the research needs to further improve the modeling of automated driving. Six important aspects were identified: the role of authorities, the role of users, the vehicle system, the perception of surroundings based on the vehicle's sensors, the vehicle connectivity features, and the role of the infrastructure both physical and digital. The research gaps and research directions in relation to these aspects are identified and proposed, these might bring great benefits for the development of more accurate and realistic modeling of automated driving in microscopic traffic simulations.

Review of driving-behaviour simulation: VISSIM and artificial intelligence approach

“…AVs are generally understood to possess varying degrees of connectivity, encompassing basic navigation capabilities as well as sophisticated functionalities for cooperative driving. The term “automated vehicle” refers to a vehicle with the capability for autonomous operation at any level of automation, often referred to as self-driving cars or robotic cars, thereby classifying them as a type of mobile robot [ 55 ].…”

“…Moreover, when implemented in public transportation, AVs can reduce labour expenses [ 56 ]. Microscopic traffic simulations, also known as traffic simulation, such as VISSIM, offer a proactive methodology for evaluating the consequences of automated traffic on different aspects, including transportation efficiency, safety, equity, and the environment [ 26 , 55 ] ( Table 3 ).…”

Social Interaction‐Aware Dynamical Models and Decision‐Making for Autonomous Vehicles

“…[57] Pedestrian willingness to cross was unaffected by eHMIs when vehicles did not yield or decelerated aggressively. [35,50] Other concepts, e.g., installing eHMIs on road infrastructures instead of vehicles [58] and combining eHMIs with vehicle motion cues, [59,60] could outperform pure eHMIs.…”