Potential of Connected Fully Autonomous Vehicles in Reducing Congestion and Associated Carbon Emissions

Abstract

Congestion is an ongoing problem for many urban centres worldwide (such as London), leading to excessive delays, noise and air pollution, frustrated drivers, and high energy consumption. The carbon footprint of conventional transport systems can be high as a result and transport is among the highest contributors of greenhouse gas emissions. Therefore, with the growing interest in developing connected fully autonomous vehicles (ConFAVs), there is a pressing need to consider their effects within the congested urban setting. To address this, the current research study was designed to investigate the potential for ConFAVs in providing a sustainable transport solution. During this research, a simulation model was developed, calibrated, and validated using field data collected from several sites in East London, using the graphical user interface (GUI) simulation software PTV VISSIM to simulate the proposed driving and car following behaviour, which included the platooning of these ConFAVs, to assess how they could improve the level of service of the roads. Using the new model, this research addresses the shortcomings of two other adaptations of the Wiedemann 99 car-following models by changing the ConFAV’s behaviour to be more cautious when travelling behind a human driven vehicle, and less cautious when behind another ConFAV. As little is known about the transitional period from zero autonomy to full autonomy on the already congested road network, due to the fact that these vehicles are typically tested in small numbers (often one at a time in a controlled environment), the present research study introduced ConFAVs to the simulated network gradually and in large numbers at 20% intervals (namely 0% where there are no ConFAVs, 20%, 40%, 60%, 80%, and finally 100% where all vehicles within the network were ConFAVs). The average delays and subsequent level of service for the roads within the networks were then assessed against each ConFAV penetration level. This helped understand how the network’s efficiency changes when the number of ConFAVs increases, and the potential benefits for these self-driving vehicles on congestion and the ensuing greenhouse gas emissions. The model showed that a reduction in delay of up to 100% can be achieved by introducing ConFAVs, which translates to a significant reduction in greenhouse gas emissions. This, coupled with the fact that ConFAVs are predominantly electric, points to a future sustainable road transport system. The primary purpose of this research would be to investigate the potential of ConFAVs in reducing traffic congestion and, as a result, greenhouse gas emissions.

Influences of Autonomous Vehicles on Sustainability: A Systematic Literature Review

“…An important aspect of optimised driving patterns is so-called platooning. This involves the networked driving of several vehicles (Martin, 2019a(Martin, , 2019cNeufville et al, 2022). The greatest possible CO2 savings are achieved if not only route guidance is optimised by autonomous vehicles but also no pollutants are emitted locally by electric cars (Biloria, 2022;Prideaux & Yin, 2019).…”

Physical Activity and Ecological Means of Transport—Functional Assessment Methodology

“…Long-term exposure to traffic noise triggers a permanent stress response that results in the release of stress hormones, increased heart rate, increased blood pressure and vasoconstriction, ultimately leading to various chronic diseases [ 17 , 18 ]. In order to minimise the above negative effects, alternative, modern, environmentally friendly means of transport are being sought.…”

Load Effect of Automated Truck Platooning on Highway Bridges and Loading Strategy

“…Automated truck platooning (ATP) is a new intelligent and green transportation technology [ 3 ]. The technology enables multiple trucks spaced at a close distance to optimize their aerodynamic characteristics, thus reducing fuel consumption [ 4 ] and carbon emissions [ 5 ]. Promoted by the vehicle-to-vehicle (V2V) [ 6 ] and the 5G vehicle-to-everything (5G-V2X) technologies [ 7 ], the following gaps between trucks can be further shortened and maintained to reduce the aerodynamic drag.…”

“…Promoted by the vehicle-to-vehicle (V2V) [ 6 ] and the 5G vehicle-to-everything (5G-V2X) technologies [ 7 ], the following gaps between trucks can be further shortened and maintained to reduce the aerodynamic drag. In addition, ATP can also help improve road safety, save operating costs [ 4 ], reduce congestion [ 5 ], and indirectly solve many other traffic problems [ 8 ]. For these reasons, ATP has attracted increasing attention, and its commercial applications were recently tested in many countries [ 9 , 10 ], especially in China, as shown in Figure 1 .…”