Effects of Autonomous Vehicle Behavior on Arterial and Freeway Networks

Abstract

Autonomous vehicles offer new traffic behaviors that could revolutionize transportation. Examples include reservation-based intersection control and reduced reaction times that result in greater road capacity. Most studies have used microsimulation models of those new technologies to study their impacts more realistically. However, microsimulation is not tractable for larger networks. Recent developments in simulating reservation-based controls and multiclass cell transmission models for autonomous vehicles in dynamic traffic assignment have allowed studies of larger networks. This paper presents analyses of several highly congested arterial and freeway networks to quantify how reservations and reduced reaction times affect travel times and congestion. Reservations were observed to improve over signals in most situations. However, signals outperformed reservations in a congested network with several close local road and arterial intersections because the capacity allocations of signals were more optimized for the network. Reservations also were less efficient than were traditional merges and diverges for on- and off-ramps. However, the increased capacity from reduced following headways resulted in significant improvements for both freeway and arterial networks. Finally, the authors studied a downtown network, including freeway, arterial, and local roads, and found that the combination of reservations and reduced following headways resulted in a 78% reduction in travel time.

Empirical Study on the Properties of Adaptive Cruise Control Systems and Their Impact on Traffic Flow and String Stability

“…The campaign took place at the proving ground of AstaZero in Sweden within a controlled environment to ensure safety and avoid interactions with other vehicles that could distort the conclusions. The results show that under normal driving car-following conditions the response time for the controllers of the four following vehicles was significantly higher than values that have been reported in the literature ( 10 , 14 , 26 , 30 – 32 ). Additionally, the minimum time headway was found to be close to those reported by Nowakowski et al ( 29 ).…”

Microscopic Modeling of the Effects of Autonomous Vehicles on Motorway Performance

“…Conversely, many researchers have assembled their own vehicle controllers from in situ measurements of human drivers made possible by the miniaturization of dGPS and sensor suites (7,8). Lastly, with V2X communication now available and its operational properties becoming well known, detailed examination can be undertaken of aspects of cooperative systems, such as operational policies (9)(10)(11), latency and the effect of message corruption on overall efficiency (12) and interaction with traffic signals (13,14). This wave of technical enthusiasm has also been adopted by road authorities and governments who, seeing that such systems may now be reaching a high TRL level, are eager to future-proof their roads and adjust their expenditure accordingly.…”

A bi‐level model to optimize road networks for a mixture of manual and automated driving: An evolutionary local search algorithm

“…Another approach for incorporating capacity changes as well as several other changes in traffic flow characteristics (e.g., traffic flow stability and throughput) in presence of AVs with more accuracy is via dynamic traffic assignment (DTA) models and adjusted fundamental diagrams. In order to model the differences in backwards wave speed and lane capacity in shared roads for AVs and CVs, Levin and Boyles () proposed a multiclass cell transmission model (CTM) that was utilized later in Patel, Levin, and Boyles () to evaluate the impacts of improved capacity due to AD efficiency and reservation controls on arterial and motorway networks. Other researchers have developed and used DTA models to study possible changes in traffic flow dynamics caused by AVs as well.…”