Hubert Rehborn

Traffic state detection with floating car data in road networks

A method for a reporting behavior at optimal costs of single vehicles (FCD: floating car data) in road networks with the aim of a high quality of traffic state recognition is presented. It is shown that based on minimum two FCD messages the substantial information of a typical traffic incident in a traffic center can be recognized. The two relevant periods of such an obstruction of traffic in road networks are the periods, in which either a travel time increase takes place due to congestion emergence or a travel time decrease because of congestion dissolution. A statistic analysis already shows the high quality of the reconstruction of the actual travel times in the net with 1.5% equipped FCD vehicles and a reduction of the FCD message sending of the vehicles by suppression of redundant incident information. Incidents with at least 20 min duration can be recognized with a probability of 65% with an penetration rate of 1.5% FCD vehicles within the whole amount of vehicles, whereby the FCD vehicles send only in each incident case two messages per event.

Traffic prediction systems in vehicles

A goal of the contribution is the presentation of both autonomous and center-based traffic prediction conceptions in vehicles. Components of software that have been developed based on these conceptions are conceived thereby system-oriented flexibly between vehicle and service center. Additionally requirements at system components are considered such as travel time curves, digital map, and routing software to traffic prediction. Systems for traffic prediction developed in a vehicle are demonstrated including a visualisation design.

Forecasting of Traffic Congestion

Results of investigations of a recent method for the automatic tracing of moving traffic jams and of the prediction of time-dependent vehicle trip times are presented using different levels of data inputs. The method is based on the previous findings that moving jams possess some characteristic parameters, i e., the parameters are unique, coherent, predictable and reproducible. Based on available data it is found that the method, which performs without any validation of the parameters of a model under different infrastructures of a highway, weather, etc., can be applied for a reliable forecasting of traffic congestions on a highway.

Automatic Tracing and Forecasting of Moving Traffic Jams Using Predictable Features of Congested Traffic Flow

Abstract The results of investigations of a recent model (Kerner, et al ., 1997) for the automatic tracing of moving traffic jams and of the prediction of the jam propagation and time-dependent vehicle trip times are presented. It is found that the model which performs without any validation of the parameters of a model under different infrastructures of a highway, weather, etc. and which is based on the previous findings that moving traffic jams possess some characteristic parameters (i.e., the parameters of moving jams are unique, reproducible and predictable) can be applied for a reliable traffic forecasting on a highway.

Microscopic Simulation of Synchronized Flow in Oversaturated City Traffic: Effect of Driver’s Speed Adaptation

Synchronized flow has been found recently in studies of empirical GPS probe-vehicle data collected in oversaturated city traffic. In this paper, results of simulations with a three-phase microscopic model from Kerner and Klenov are presented. These results show features of synchronized flow. The effect of the drivers speed adaptation was found to play the key role in understanding the emergence of synchronized flow in over-saturated city traffic. The physical meaning of the speed adaptation effect in oversaturated city traffic was explained, and the influence of the speed adaptation effect on the average speed and travel time in oversaturated city traffic was investigated.

Common traffic congestion features studied in USA, UK, and Germany based on kerner's three-phase traffic theory

Based on real traffic data measured on American, UK and German freeways, we study Kerners common features of traffic congestion phases (synchronized flow and wide moving jam) relevant for many transportation engineering applications. General features of traffic congestion, i.e., features of traffic breakdown and of the further development of congested regions, are shown on freeways in the USA and UK beyond the previously known data examples. For the testing of Kerners “line J”, representing the propagation of the wide moving jams downstream front, four different methods are studied and compared for each congested traffic situation occurring in the three countries.

ASDA/FOTO based on Kerner’s three-phase traffic theory in North Rhine-Westphalia and its integration into vehicles

Traffic data measured with stationary loop detectors on freeways in North-Rhine Westphalia are used at a major German radio broadcasting station (WDR) for the detection and reconstruction of spatial-temporal congested traffic patterns. This is done with models ASDA (automatic jam recognition) and FOTO (forecasting of traffic objects) based on Kernerpsila three-phase traffic theory. The detected congested traffic patterns can be suitable as a basis for production and control of RDS/TMC traffic messages which are broadcasted to radio listeners and RDS/TMC receivers in vehicle navigation systems. The article briefly discusses the theoretical background of the models ASDA and FOTO as well as the results achieved until now in the on-line operation in North Rhine-Westphalia without any calibration of model parameters. A quality index developed for ASDA and FOTO relevant for RDS/TMC messages as well as architectural aspects of the modelpsilas integration into vehicles are presented.

Game-Theoretic Context and Interpretation of Kerner’s Three-Phase Traffic Theory

We present four classical developments in traffic theory and Kerner’s (Phys A 392:5261–5282, 2013, [36]) critique that these are not consistent with fundamental empirical features of traffic breakdown at a highway bottleneck (transition from free flow (F) to congested traffic at the bottleneck) that is the basic empiric of traffic theory. Kerner argued that traffic breakdown is probabilistic, can be spontaneous (emerging internally at the bottleneck) or induced (emerging from a downstream bottleneck), and is a transition from free flow to synchronized flow (S) (synchronized flow is one of the two traffic phases of congested traffic) called as a F → S transition, after which wide moving jam (J) (J is another from two phases of congested traffic) may arise. Return to free flow occurs through hysteresis and usually at smaller flow rates. Common games in traffic theory are presented and exemplified, i.e. the chicken game, battle of the sexes, prisoner’s dilemma, and coordination game. The four developments and Kerner’s theory are linked to game theory, and especially to the chicken game. For the first F → S transition the density increases at a constant flow rate. Increasing density increases the prevalence of the chicken strategy due to drivers in a congested environment becoming apprehensive, fearful, and wary of accidents. For the second S → J the chicken strategy is equally likely while the flow rate decreases at constant density. For the third J → F transition the density decreases which decreases the prevalence of the chicken strategy. Finally, within free flow F where the flow rate and density again increase, the chicken strategy is played with higher probability.

Increased Consumption in Oversaturated City Traffic Based on Empirical Vehicle Data

Congestion of urban roads causes extra travel time as well as additional fuel consumption. We present an approach to determine this additional fuel consumption on the basis of empirical vehicle data. We study probe vehicle data provided by TomTom to find the various traffic patterns of urban congestion. We use simulations of these urban traffic patterns based on a stochastic Kerner- Klenov model as input for an empirical fuel consumption matrix compiled from empirical CAN bus signals from vehicles. Our results confirm that in certain congested city traffic patterns vehicles consume more than twice as much fuel as in free city traffic.

Traffic Jam Warning Messages from Measured Vehicle Data with the Use of Three-Phase Traffic Theory

Based on Kerner’s three-phase theory, we study an algorithm for the generation of traffic jam warming messages from measured GPS and GSM probe vehicle data that have been collected in TomTom’s HD-traffic service both from nomadic devices and vehicle’s embedded systems. We find that the data allows us to reconstruct the structure of congested traffic patterns with a much greater quality of spatiotemporal resolution than has been possible before. It occurs that congested traffic in measured traffic patterns consists of the two traffic phases of Kerner’s three-phase theory, synchronized flow and wide moving jams. The application method distinguishes between the fronts of the congested traffic phases, wide moving jam and synchronized flow. It will be shown that a penetration of about 2% of the total traffic flow is enough to implement a precise traffic jam warning message for navigation systems.