Congestion Effects of Autonomous Taxi Fleets

Abstract

Fleets of shared Autonomous Vehicles (AVs) could replace private cars by providing a taxi-like service but at a cost similar to driving a private car. On the one hand, large Autonomous Taxi (AT) fleets may result in increased road capacity and lower demand for parking spaces. On the other hand, an increase in vehicle trips is very likely, as travelling becomes more convenient and affordable, and additionally, ATs need to drive unoccupied between requests. This study evaluates the impact of a city-wide introduction of ATs on traffic congestion. The analysis is based on a multi-agent transport simulation (MATSim) of Berlin (Germany) and the neighbouring Brandenburg area. The central focus is on precise simulation of both real-time AT operation and mixed autonomous/conventional vehicle traffic flow. Different ratios of replacing private car trips with AT trips are used to estimate the possible effects at different stages of introducing such services. The obtained results suggest that large fleets operating in cities may have a positive effect on traffic if road capacity increases according to current predictions. ATs will practically eliminate traffic congestion, even in the city centre, despite the increase in traffic volume. However, given no flow capacity improvement, such services cannot be introduced on a large scale, since the induced additional traffic volume will intensify today’s congestion.

Autonomous Vehicles and their Impact on Parking Search

“…In order to model parking search, as well as other processes that cannot be planned ahead for the whole day, MATSim has been extended with several implementations that allow agents to change their behavior within an iteration. This feature is often referred to as withinday replanning [22], [23] and has extended application of MATSim to a wide range of different use cases, from evaluating evacuation scenarios [24] through modeling congestion effects of city-wide SAV fleets [25] to benchmarking dynamic vehicle routing algorithms [26].…”

Enhanced Mobility With Connectivity and Automation: A Review of Shared Autonomous Vehicle Systems

“…Considering 100% penetration of SAVs, the authors found that under certain scenarios (e.g., with the option of dynamic ridesharing), a smaller fleet of SAVs performed better than a larger fleet due to lower congestion in the network. Maciejewski and Bischoff [156] evaluated the impacts of a city-wide introduction of SAVs on traffic congestion through an agent-based simulation model, focusing on the analysis of traffic congestion under different SAV penetration rates. With an assumption of increased road capacity due to AV operations, their work showed that despite increased traffic volume, a fleet of SAV could have a positive effect on traffic at a penetration rate as low as 20%.…”

Comparison of exhaust emission on the basis of Real Driving Emissions measurements and simulations

“…The computer simulations of the passage through the analyzed road infrastructure were made using PTV Vissim software [18], which is a tool for traffic simulation in the microscopic scale [19][20][21]. The advantage of this system is the ability to accurately design the geometry and parameters of the modeled road section and traffic [22].…”