Traffic jams induced by fluctuation of a leading car

Minimum memory for generating rare events

We classify the rare events of structured, memoryful stochastic processes and use this to analyze sequential and parallel generators for these events. Given a stochastic process, we introduce a method to construct a process whose typical realizations are a given process' rare events. This leads to an expression for the minimum memory required to generate rare events. We then show that the recently discovered classical-quantum ambiguity of simplicity also occurs when comparing the structure of process fluctuations.

Resonance, criticality, and emergence in city traffic investigated in cellular automaton models

The complex behavior that occurs when traffic lights are synchronized is studied for a row of interacting cars. The system is modeled through a cellular automaton. Two strategies are considered: all lights in phase and a "green wave" with a propagating green signal. It is found that the mean velocity near the resonant condition follows a critical scaling law. For the green wave, it is shown that the mean velocity scaling law holds even for random separation between traffic lights and is not dependent on the density. This independence on car density is broken when random perturbations are considered in the car velocity. Random velocity perturbations also have the effect of leading the system to an emergent state, where cars move in clusters, but with an average velocity which is independent of traffic light switching for large injection rates.

Intron delays and transcriptional timing during development

The time taken to transcribe most metazoan genes is significant because of the substantial length of introns. Developmentally regulated gene networks, where timing and dynamic patterns of expression are critical, may be particularly sensitive to intron delays. We revisit and comment on a perspective last presented by Thummel 16 years ago: transcriptional delays may contribute to timing mechanisms during development. We discuss the presence of intron delays in genetic networks. We consider how delays can impact particular moments during development, which mechanistic attributes of transcription can influence them, how they can be modeled, and how they can be studied using recent technological advances as well as classical genetics.

Hysteresis phenomena of the intelligent driver model for traffic flow

We present hysteresis phenomena of the intelligent driver model for traffic flow in a circular one-lane roadway. We show that the microscopic structure of traffic flow is dependent on its initial state by plotting the fraction of congested vehicles over the density, which shows a typical hysteresis loop, and by investigating the trajectories of vehicles on the velocity-over-headway plane. We find that the trajectories of vehicles on the velocity-over-headway plane, which usually show a hysteresis loop, include multiple loops. We also point out the relations between these hysteresis loops and the congested jams or high-density clusters in traffic flow.

Modeling traffic through a sequence of traffic lights

We introduce a microscopic traffic model, based on kinematic behavior, which consists of a single vehicle traveling through a sequence of traffic lights that turn on and off with a specific frequency. The reconstructed function that maps the state of the vehicle from light to light displays complex behavior for certain conditions. This chaotic behavior, which arises by the discontinuous nature of the map, displays an essential ingredient in traffic patterns and could be of relevance in studying traffic situations.

Effect of adaptive cruise control systems on traffic flow

The flow of traffic composed of vehicles that are equipped with adaptive cruise control (ACC) is studied using simulations. The ACC vehicles are modeled by a linear dynamical equation that has string stability. In platoons of all ACC vehicles, perturbations due to changes in the lead vehicle's velocity do not cause jams. Simulations of merging flows near an onramp show that if the total incoming rate does not exceed the capacity of the single outgoing lane, free flow is maintained. With larger incoming flows, a state closely related to the synchronized flow phase found in manually driven vehicular traffic has been observed. This state, however, should not be considered congested because the flow is maximal for the density. Traffic composed of random sequences of ACC vehicles and manual vehicles has also been studied. At high speeds (approximately 30 m/s ) jamming occurs for concentrations of ACC vehicles of 10% or less. At 20% no jams are formed. The formation of jams is sensitive to the sequence of vehicles (ACC or manual). At lower speeds (approximately 15 m/s ), no critical concentration for complete jam suppression is found. Rather, the average velocity in the pseudojam region increases with increasing ACC concentration. Mixing 50% ACC vehicles randomly with manually driven vehicles on the primary lane in onramp simulations shows only modestly reduced travel times and larger flow rates.

Multilane simulations of traffic phases

The optimal velocity model, as modified by the author, is used in simulations of traffic on a dual-lane highway and a single-lane highway with an on-ramp. The equilibrium solutions of the modified model cover a two-dimensional region of flow-density space beneath the fundamental-diagram curve, rather than just lying on the curve as in the original model. Thus it satisfies a requirement of the three-phase model of Kerner [Phys. Rev. Lett. 81, 3797 (2002)]. Synchronization of velocity across dual lanes due to frequent lane changes is observed in free flow. True synchronized flow, as determined by the region of density-flow space it occupies, is obtained in on-ramp simulations with typical driver reaction times. A gradual change to the formation of a jam is observed for increasing delay times.

Towards a variational principle for motivated vehicle motion

We deal with the problem of deriving the microscopic equations governing individual car motion based on assumptions about the strategy of driver behavior. We presume the driver behavior to be a result of a certain compromise between the will to move at a speed that is comfortable for him under the surrounding external conditions, comprising the physical state of the road, the weather conditions, etc., and the necessity to keep a safe headway distance between the cars in front of him. Such a strategy implies that a driver can compare the possible ways of further motion and so choose the best one. To describe the driver preferences, we introduce the priority functional whose extremals specify the driver choice. For simplicity we consider a single-lane road. In this case solving the corresponding equations for the extremals we find the relationship between the current acceleration, velocity, and position of the car. As a special case we get a certain generalization of the optimal velocity model similar to the "intelligent driver model" proposed by Treiber and Helbing.

Enhancement and stabilization of traffic flow by moving in groups

We study the traffic behavior of vehicles moving in groups analytically and numerically. A car-following model of traffic is extended to take into account a binary mixture of vehicles. It is shown that the movement in groups stabilizes the traffic flow. The jamming transition among the free traffic, the inhomogeneous traffic, and the homogeneous congested traffic occurs at a higher density than the threshold of the original model. The traffic current is highly enhanced at a high-density region by keeping a short headway without jam. The jamming transition is analyzed by using the linear stability method. It is found that the theoretical neutral stability curve agrees with the transition line obtained by the simulation.