Investigation of Automated Vehicle Effects on Drivers Behavior and Traffic Performance

Abstract

Advanced Driver Assistance Systems (ADAS) offer the possibility of helping drivers to fulfill their driving tasks. Automated vehicles (AV) are capable of communicating with surrounding vehicles (V2V) and infrastructure (V2I) in order to collect and provide essential information about the driving environment. Studies have proved that automated driving have the potential to decrease traffic congestion by reducing the time headway (THW), enhancing the traffic capacity and improving the safety margins in car following. Despite different encouraging factors, automated driving raise some concerns such as possible loss of situation awareness, overreliance on automation and system failure. This paper aims to investigate the effects of AV on driver’s behavior and traffic performance. A literature review was conducted to examine the AV effects on driver’s behavior. Findings from the literature survey reveal that conventional vehicles (CV), i.e. human driven, which are driving close to a platoon of AV with short THW, tend to reduce their THW and spend more time under their critical THW. Additionally, driving highly AV reduce situation awareness and can intensify driver drowsiness, exclusively in light traffic. In order to investigate the influences of AV on traffic performance, a simulation case study consisting of a 100% AV scenario and a 100% CV scenario was performed using microscopic traffic simulation. Outputs of this simulation study reveal that the positive effects of AV on roads are especially highlighted when the network is crowded (e.g. peak hours). This can definitely count as a constructive point for the future of road networks with higher demands. In details, average density of autobahn segment remarkably improved by 8.09% during p.m. peak hours in the AV scenario, while the average travel speed enhanced relatively by 8.48%. As a consequent, the average travel time improved by 9.00% in the AV scenario. The outcome of this study jointly with the previous driving simulator studies illustrates a successful practice of microscopic traffic simulation to investigate the effects of AV. However, further development of the microscopic traffic simulation models are required and further investigations of mixed traffic situation with AV and CV need to be conducted.

Keywords

Automated driving ; Automated vehicles ; Microscopic traffic simulation ; Driver behavior ; Traffic performance ; capacity

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