Nowadays traffic flow and congestion is one of the main societal and economical problems related to transportation in industrialized countries. In this respect, managing traffic in congeste...

State-of-the-art of vehicular traffic flow modelling

We address the controversial issue of traffic flow modeling, whether first-order, second-order, or other traffic models are best supported by empirical facts and theoretical considerations. This is done by a critical discussion of the pros and cons of the different theoretical approaches and by the analysis of a large set of empirical data with new evaluation techniques. Specifically, we investigate characteristic properties of the congested traffic states on a 30-km-long stretch of the German freeway A5 near Frankfurt/Main. Among the approximately 245 breakdowns of traffic flow at several different bottlenecks in 165 days, we have identified five different kinds of spatiotemporal congestion patterns and their combinations. Based on an “adaptive smoothing method” for the visualization of detector data, we also discuss particular features of breakdowns, such as signs of unstable traffic flow and the “boomerang effect,” which often seems to be caused by overtaking maneuvers of trucks. Controversial issues such as “synchronized flow” or stop-and-go waves are addressed as well. Our empirical results are compared with the implications of different theoretical concepts such as first-order traffic models and the phase diagram of congested traffic states predicted by some second-order models and the nonlocal, gas-kinetic based traffic model (GKT model). For a correct understanding of empirical observations such as the “general pattern,” it is important to consider particularities such as the fact that off-ramps can act as bottlenecks, when activated by downstream on-ramp bottlenecks. As sequences of off-and on-ramps generate different congestion patterns than single on-ramps, they must be treated as interconnected bottlenecks. Furthermore, our empirical results question Kerner's three-phase theory.

Empirical Features of Congested Traffic States and Their Implications for Traffic Modeling

We investigate characteristic properties of the congested traffic states on a 30 km long stretch of the German freeway A5 north of Frankfurt/Main. Among the approximately 245 breakdowns of traffic flow in 165 days, we have identified five different kinds of spatio-temporal congestion patterns and their combinations. Based on an "adaptive smoothing method" for the visualization of detector data, we also discuss particular features of breakdowns such as the "boomerang effect" which is a sign of linearly unstable traffic flow. Controversial issues such as "synchronized flow" or stop-and-go waves are addressed as well. Finally, our empirical results are compared with different theoretical concepts and interpretations of congestion patterns, in particular first- and second-order macroscopic traffic models.

Information is a key commodity in many socio-economic systems like stock markets or traffic systems. In this paper the influence of dynamic information on the stability of traffic patterns is investigated using a very simple route choice scenario. The basis of the route decisions is dynamic information generated by traffic flow simulations. A correlation analysis yields that the system can be destabilized by introducing information. It is found that the overall performance of the system is reduced, although the information should help to distribute traffic more efficiently.

Decision dynamics in a traffic scenario

Different methods of traffic forecast based on real data

A dynamic route guidance system based on real traffic data

Simulation of traffic in large road networks

Recently, an on-line simulation for traffic flow in urban areas has been presented [1,2]. In this contribution, a framework for on-line simulations of freeways is proposed. It is based on cellular automaton models which are supplemented by real world traffic data stemming from about 2,500 inductive loops distributed over the freeway network of North Rhine-Westphalia (NRW). We propose and analyse different methods to tune the simulation with regard to the real world measurements. The possibility of a short-term traffic forecast is discussed.

On-Line Simulation of the Freeway Network of North Rhine-Westphalia

In this paper a concept for online simulations of urban road networks is developed, with real-time traffic data from induction loops serving as input for microscopic simulations From the simulations, estimates of traffic conditions for regions which are not adequately covered by measurements are determined The quality of the reproduced traffic states with regard to vehicle densities and link travel times is investigated The dynamic data are processed by a route guidance system based on a fuzzy logic approach As an example of dynamic traffic management, different strategies for individual en-route guidance systems and their efficiencies are studied The study area is the road network of Duisburg

Microscopic online simulations of urban traffic

The development of dynamic traffic information systems is one of the most important challenges in the field of Intelligent Transportation Systems ITS. A promising way is to couple simulations of the actual traffic state together with online counting data stemming from detection devices, e.g. induction loops. The aim is to generate a one-to-one image of the individual on-road car motion in the computer and to derive the relevant information from the simulation results. In addition, the simulation serves as an “interpolation” for regions which are not adequately covered by measurements. In this contribution the method of online simulations is discussed and some results are reported.

L. Neubert

Papers

A dynamic route guidance system based on real traffic data

Simulation of traffic in large road networks

On-Line Simulation of the Freeway Network of North Rhine-Westphalia

Microscopic online simulations of urban traffic

Online Traffic Simulation with Cellular Automata