Reinhart Kühne

Calibration and Validation of Microscopic Traffic Flow Models

The aim of this paper is to present recent progress in calibrating ten microscopic traffic flow models. The models have been tested using data collected via DGPS-equipped cars (Differential Global Positioning System) on a test track in Japan. To calibrate the models, the data of a leading car are fed into the model under consideration and the model is used to compute the headway time series of the following car. The deviations between the measured and the simulated headways are then used to calibrate and validate the models. The calibration results agree with earlier studies as there are errors of 12 % to 17 % for all models and no model can be denoted to be the best. The differences between individual drivers are larger than the differences between different models. The validation process leads to errors from 17 % to 22 %. But for special data sets with validation errors up to 60 % the calibration process has reached what is known as “overfitting”: because of the adaptation to a particular situation, the models are not capable of generalizing to other situations.

Toward Benchmarking of Microscopic Traffic Flow Models

Several microscopic traffic flow models were tested with a publicly available data set. The task was to predict the travel times between several observers along a one-lane rural road, given as boundary conditions the flow into this road and the flow out of it. By using nonlinear optimization, the best matching set of parameters for each of the models was estimated. For this particular data set, the models that performed best were the ones with the smallest number of parameters. The average error rate of the best models is about 16%; however, this value is not very reliable: the error rate fluctuates between 2.5% and 25% for different parts of the data set.

Calibration and Validation of Microscopic Models of Traffic Flow

Because microscopic models are heavily used in applications, the appropriate calibration and validation of these models have been a recent concern. The contribution of this paper is to compare some of these models by calibrating and validating them with data from double loop detectors on a multilane freeway. To simplify this task, the models were tested by simplifying the multilane reality to a simulation of only a single lane. The results show that by simulating the multilane road with single-lane models, calibration errors (Theils U-value, or the root mean square error) of 14% to 16% were obtained. A validation of the models, which was done by taking the calibrated parameters of one data set to reproduce the other data sets, gives additional errors of about 0.5 to 2.5 percentage points. This is in good agreement with other calibration and validation approaches performed recently.

Probabilistic Description of Traffic Breakdowns

We analyze the characteristic features of traffic breakdown. To describe this phenomenon we apply the probabilistic model regarding the jam emergence as the formation of a large car cluster on a highway. In these terms, the breakdown occurs through the formation of a certain critical nucleus in the metastable vehicle flow, which enables us to confine ourselves to one cluster model. We assume that, first, the growth of the car cluster is governed by attachment of cars to the cluster whose rate is mainly determined by the mean headway distance between the car in the vehicle flow and, maybe, also by the headway distance in the cluster. Second, the cluster dissolution is determined by the car escape from the cluster whose rate depends on the cluster size directly. The latter is justified using the available experimental data for the correlation properties of the synchronized mode. We write the appropriate master equation converted then into the Fokker-Planck equation for the cluster distribution function and analyze the formation of the critical car cluster due to the climb over a certain potential barrier. The further cluster growth irreversibly causes jam formation. Numerical estimates of the obtained characteristics and the experimental data of the traffic breakdown are compared. In particular, we draw a conclusion that the characteristic intrinsic time scale of the breakdown phenomenon should be about 1 min and explain the case why the traffic volume interval inside which traffic breakdown is observed is sufficiently wide.

Evaluation of Compliance Rates and Travel Time Calculation for Automatic Alternative Route Guidance Systems on Freeways

This study outlines the concept of extending an available simulation model for evaluation of freeway route guidance systems using the compliance rates of drivers with alternative route recommendations based on measurements from the freeway subnetwork near Munich, Germany. The system works with variable direction signs that automatically display routing instructions to prevent congestion on the main road. The effectiveness of the system is assessed by calculating the travel times with and without an alternative route guidance system in operation. The result is a decrease in individual travel times on the main road and overall travel time savings for all traffic participants of the system. The simulation indicates a high sensitivity of diverting portions of traffic that allows an exact validation. The diverted traffic affects not only travel time and the congested area but also the destinations, which permits the use of the compliance rate as an accurate fit parameter for exact description of traffic patterns from measurement data.

Potential of remote sensing for traffic applications

The paper deals about the potential of remote sensing for traffic applications. Taxis equipped with digital trunk radio and with satellite positioning transmit their position via the trunk radio network to the taxi despatch centre. The taxi despatch centre uses the information for the disposition of the vehicles. The positioning information of the taxis can be transmitted to generate the traffic position to a server in a traffic management center. The principle of floating car data, helps to generate the traffic data from the consecutive position of taxis. Knowing the position of public transportation modes and operating information enables arrival times to be calculated in advance and thus form the basis of passenger information system.

Air- and space borne remote sensing systems for traffic data collection -European contributions

The increasing volume of traffic and transport rates in Europe and in other continents require new methods of traffic data recording as well as an intelligent traffic management, which fits the intermodal and cross-boarder traffic. Simultaneously it has to take in account that the EU enlargement in particular into Eastern European economic areas corresponds with an expandability of trans-national traffic management in Europe. The air and space borne remote sensing technologies have the highest potential to solve the sustainable traffic problems. With this it is merely possible to open up potentials of traffic route infrastructure identified by scientific research and to transfer the results of present rural approaches to European scale. It will result in a standardization of traffic data in terms of quality and quantity which is the key point for an integrated and sustainable traffic management in Europe for the future. A special session for the European contributions on this new ITS-topic gives the possibility for a better cooperation in international research.

Sustainable Mobility and Sustainable Transport for Medium-Size Cities in China

The project METRASYS (Mega Region Transport Systems for China) funded by the Federal Ministry of Education and Research of Germany in the program of research for sustainability and co-funded by the Chinese Ministry of Science and Technology follows an interdisciplinary approach integrating spatial planning (new urbanism), transport science, engineering and political science in order to contribute to the mitigation of climate change. An important part of METRASYS is to assess the environmental impacts of the traffic management system and planned urban traffic developments on the basis of a Business-As-Usual (BAU) scenario. Linking technological developments with urban and transport-planning policies is one of the foci of this project activity: The identification of suitable strategies and policies is a prerequisite to ensure permanent and effective implementation of technological approaches.How the results of the analysis as well as alternative measures and instruments for the development of a climate and energy efficient transport system are discussed with local decision makers is reported. A geo information system (GIS) model is presented for spatial visualization to assist decision makers and stakeholders in their comprehension and evaluation of the effects of policy measures. The BAU scenario is also the basis for the analysis of the suitability of transport management as a Clean Development Mechanism (CDM). It will show how to this extent the collected vehicle probe data can be used.The development of the technical system for traffic management and its installation in Hefei will be reported. All information and results of the traffic management system are open for the public. The dissemination activities aim at a broader audience within China and worldwide. It is aimed at transferring the results of the project to different cultural and institutional contexts. Main written products are more comprehensive discussion papers presenting the state of research, new findings from the project and recommendations. An important task

The future of traffic control

Vehicle probes as data collectors, satellites as traffic spies and area wide traffic signal control will shape the future traffic system. In order to apply these technologies, new methods for data mining are necessary. Aerial photogrammetry covers a wide range of edges and nodes that have to be linked with digital maps, containing static and dynamic attributes in real time. The dynamic attributes are generated from ground-based vehicle probes and from air borne platforms using extraction techniques with different kinds of imagery. New methods of data fusion are necessary to generate reliable and up to date traffic data. Finally, fast algorithms for dynamic routing have to be developed. These will contribute to new control principles covering extended areas instead of arterials and corridors. The methods are exemplified for several metropolitan areas such as Berlin, Vienna and Hamburg, where comprehensive data are collected. A series of big events such as the visit of President Bush to Berlin, an extended thunderstorm in Vienna and a big freeway tunnel shut-down in Hamburg are used to describe the above mentioned functions of data mining and data fusion as well as the consequences for event adaptive traffic control. The presentation ends with an online demonstration of area wide traffic assessment and comparison of the traffic status and level of service quality of different metropolitan areas.

Traffic monitoring and traffic flow measurement by remote sensing systems

Prediction of traffic, dynamical routing, off board navigation and a standardisation of traffic flow parameters are the cornerstones of modern intelligent transport systems. Development of such systems requires intelligent data acquisition from different sensors and platforms.