Failure of classical traffic flow theories: Stochastic highway capacity and automatic driving

Abstract

In a mini-review [Physica A 392 (2013) it has been shown that classical traffic flow theories and models failed to explain empirical traffic breakdown -a phase transition from metastable free flow to synchronized flow at highway bottlenecks. The main objective of this mini-review is to study the consequence of this failure of classical traffic-flow theories for an analysis of empirical stochastic highway capacity as well as for the effect of automatic driving vehicles and cooperative driving on traffic flow. To reach this goal, we show a deep connection between the understanding of empirical stochastic highway capacity and a reliable analysis of automatic driving vehicles in traffic flow. With the use of simulations in the framework of three-phase traffic theory, a probabilistic analysis of the effect of automatic driving vehicles on a mixture traffic flow consisting of a random distribution of automatic driving and manual driving vehicles has been made. We have found that the parameters of automatic driving vehicles can either decrease or increase the probability of traffic breakdown. The increase in the probability of traffic breakdown, i.e., the deterioration of the performance of the traffic system can occur already at a small percentage (about 5%) of automatic driving vehicles. The increase in the probability of traffic breakdown through automatic driving vehicles can be realized, even if any platoon of automatic driving vehicles satisfies condition for string stability.

The impact of autonomous vehicles on urban traffic network capacity: an experimental analysis by microscopic traffic simulation

“…There exist two basic macroscopic traffic flow modeling approaches in the literature: three-phase traffic flow theory and Macroscopic Fundamental Diagram (MFD), to choose from to analyze the data. In the three-phase traffic flow theory the capacity of road is not a constant value but infinite numbers within a range of the flow rate between a minimum and maximum capacity (Kerner 2016). It would add unnecessary complexity to the estimation of AVs' impacts on the road capacity.…”

Resource allocation with population dynamics

“…Notice that much of the research on exogenous uncertainty in travel costs, as well as the research on choice models such as MNL and MNP, focuses on the conditions for the existence and computations of equilibria. In theory, the restriction to the existence of equilibria is rather unfortunate [11,14], as it obscures the complexity of the possible behaviour of the non-linear dynamics. In practice, it may be very hard for the transportation authorities to steer the system to-ward the equilibrium, while maintaining the trust of the users, which may be require the information provided to be truthful, in some sense.…”

A Universal Trajectory Planning Method for Automated Lane-Changing and Overtaking Maneuvers

“…Automated driving system can significantly alleviate traffic congestion, ensure traffic safety, and improve road capacity [1][2][3][4]. In order to realize the intelligent vehicle as soon as possible, some automated driving technologies are being tested on roads.…”