Three-phase traffic theory and two-phase models with a fundamental diagram in the light of empirical stylized facts

Despite the availability of large empirical data sets and the long history of traffic modeling, the theory of traffic congestion on freeways is still highly controversial. In this contribution, we compare Kerner's three-phase traffic theory with the phase diagram approach for traffic models with a fundamental diagram. We discuss the inconsistent use of the term "traffic phase" and show that patterns demanded by three-phase traffic theory can be reproduced with simple two-phase models, if the model parameters are suitably specified and factors characteristic for real traffic flows are considered, such as effects of noise or heterogeneity or the actual freeway design (e.g. combinations of off- and on-ramps). Conversely, we demonstrate that models created to reproduce three-phase traffic theory create similar spatiotemporal traffic states and associated phase diagrams, no matter whether the parameters imply a fundamental diagram in equilibrium or non-unique flow- density relationships. In conclusion, there are different ways of reproducing the empirical stylized facts of spatiotemporal congestion patterns summarized in this contribution, and it appears possible to overcome the controversy by a more precise definition of the scientific terms and a more careful comparison of models and data, considering effects of the measurement process and the right level of detail in the traffic model used.Comment: 18 pages in the published article, 13 figures, 2 table

Probabilistic Traffic Flow Breakdown in Stochastic Car Following Models

There is discussion if traffic displays spontaneous breakdown. This paper presents computational evidence that stochastic car following models can have a control parameter that moves the model between displaying and not displaying spontaneous phase separation for some densities. Those phases can be called “laminar” and “jammed”. Models with spontaneous phase separation show three states as a function of density: a first state at low density, where those models are homogeneously laminar; a second state at high density, where they are homogeneously jammed; and a third state at intermediate density, where they consist of a mix between the two phases (phase coexistence). This is the same picture as for a gas-liquid transition when volume of the gas is the control parameter. Although the gas-liquid analogy to traffic models has been widely discussed, no traffic-related model so far displayed a completely understood stochastic version of that transition. Having a stochastic model is important to understand the potentially probabilistic nature of the transition. Most importantly, if indeed models with spontaneous phase separation describe certain aspects correctly, then this leads to an understanding of spontaneous breakdown. Alternatively, if models without spontaneous phase separation describe these aspects better, then there is no spontaneous breakdown (= no breakdown without a reason). Interestingly, even models without spontaneous phase separation can still allow for jam formation on small scales, which may give the impression of having a model with spontaneous phase separation

Autonomous detection and anticipation of jam fronts from messages propagated by inter-vehicle communication

In this paper, a minimalist, completely distributed freeway traffic information system is introduced. It involves an autonomous, vehicle-based jam front detection, the information transmission via inter-vehicle communication, and the forecast of the spatial position of jam fronts by reconstructing the spatiotemporal traffic situation based on the transmitted information. The whole system is simulated with an integrated traffic simulator, that is based on a realistic microscopic traffic model for longitudinal movements and lane changes. The function of its communication module has been explicitly validated by comparing the simulation results with analytical calculations. By means of simulations, we show that the algorithms for a congestion-front recognition, message transmission, and processing predict reliably the existence and position of jam fronts for vehicle equipment rates as low as 3%. A reliable mode of operation already for small market penetrations is crucial for the successful introduction of inter-vehicle communication. The short-term prediction of jam fronts is not only useful for the driver, but is essential for enhancing road safety and road capacity by intelligent adaptive cruise control systems.Comment: Published in the Proceedings of the Annual Meeting of the Transportation Research Board 200

Traffic Operations Analysis of Merging Strategies for Vehicles in an Automated Electric Transportation System

Automated Electric Transportation (AET) is a concept of an emerging cooperative transportation system that combines recent advances in vehicle automation and electric power transfer. It is a network of vehicles that control themselves as they traverse from an origin to a destination while being electrically powered in motion – all without the use of connected wires. AET\u27s realization may provide unparalleled returns in the form of dramatic reductions in traffic-related air pollution, our nation’s dependence on foreign oil, traffic congestion, and roadway inefficiency. More importantly, it may also significantly improve transportation safety by dramatically reducing the number of transportation-related deaths and injuries each year as it directly addresses major current issues such as human error and adverse environmental conditions related to vehicle emissions. In this thesis, a logical strategy in transitioning from today’s current transportation system to a future automated and electric transportation system is identified. However, the chief purpose of this research is to evaluate the operational parameters where AET will be feasible from a transportation operations perspective. This evaluation was accomplished by performing lane capacity analyses for the mainline, as well as focusing on the merging logic employed at freeway interchange locations. In the past, merging operations have been known to degrade traffic flow due to the interruptions that merging vehicles introduce to the system. However, by analyzing gaps in the mainline traffic flow and coordinating vehicle movements through the use of the logic described in this thesis, mainline traffic operations can remain uninterrupted while still allowing acceptable volumes of merging vehicles to enter the freeway. A release-to-gap merging algorithm was developed and utilized in order to maximize the automated flow of traffic at or directly downstream of a freeway merge point by maximizing ramp flows without causing delay to mainline vehicles. Through these tasks, it is the hope of this research to aid in identifying the requirements and impending impacts of the implementation of this potentially life-altering technology