Implications of the Emergence of Autonomous Vehicles and Shared Autonomous Vehicles: A Budapest Perspective

Abstract

The introduction of autonomous vehicles (AVs) and shared autonomous vehicles (SAVs) is projected to enhance network performance and accessibility. The future share distribution of AV and SAV is not yet apparent, nor is which of these two future transport modes will become dominant. Therefore, this research deploys a simulation-based dynamic traffic assignment using Visum software to investigate the impact of varying the share distribution of AVs and SAVs on Budapest’s network performance and consumer surplus in three projected future traffic scenarios for the years 2030 and 2050 compared to the Base scenario for 2020. The three future scenarios are presented and characterized by different penetration rates of AVs and SAVs to reflect the uncertainty in the market share of these future cars as follows: Mix-Traffic scenario for 2030, and AV-Focused and SAV-Focused scenarios for 2050. The results revealed that the emergence of AVs and SAVs would improve the overall network performance, and better performance was observed with increasing the share distribution of SAVs. Similarly, the consumer surplus increased in all future scenarios, especially with increasing the share distribution of AVs. Consequently, the advent of AVs and SAVs will improve traffic performance and increase consumer surplus, benefiting road users and authorities.

On-Demand Autonomous Vehicles in Berlin: A Cost–Benefit Analysis

“…These results contradict some of the findings in literature ( 7 , 10 , 73 ) in which an important gain can be found at the vehicle scale. The difference can be found in the parameters used to value the opportunity cost of time.…”

“…Kockelman et al reduced VoT by 50%, which counterbalanced the increase in VMT (+10%), congestion, and travel time ( 7 ). Shatanawi and Mészáros chose to reduce VoT from 25% to 50%, found a reduction of 45% in the traffic volume (in VKT), an average speed increase, and an increase in CS ( 73 ). Conversely, Xue found that AV traffic flow improvement resulted in an overall positive consumer gain, despite an assumed 2% yearly traffic growth and no VoT reduction for AV passengers ( 34 ).…”

“…To conclude the results section, the CS and financial results were mostly inconsistent with the literature, which may be summarized as follows. The CS losses were a result of the reduced values of time considered within certain studies ( 7 , 10 , 73 ). There were differences in the items considered in other financial evaluations of AVs, for example, they did not include infrastructure- or supervision costs ( 9 ).…”

Analysis of the Emergence of Autonomous Vehicles Using Simulation-based Dynamic Traffic Assignment – The Case of Budapest

“…(Simoni et al, 2019) used a 1.5 capacity increment factor when modeling fully automated vehicles, in SBA, this can be interpreted into a reaction time factor using the SBA capacity equation (PTV Group, 2021), as shown in Eq. ( 4 (2001) and Shatanawi and Mészáros (2022). The process of deploying SBA can be divided into three main parts: network, demand, and SBA parameters.…”

Examining the Impact of Hysteresis on the Projected Adoption of Autonomous Vehicles

“…Some researchers tend to create several scenarios to cover the possible cases of integrating AVs into road networks as this new technology is not yet entirely developed (see e.g. [10][11][12][13]), which consumes time and effort.…”