Hanover Traffic Control Centre a combination of various technologies

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1 main menu VISUM-online traffic management for the EXPO 2000 based on a traffic model Martin Fellendorf, Klaus Nökel (PTV AG, Karlsruhe, Germany) Norbert Handke (move GmbH, Hannover, Germany) Hanover Traffic Control Centre a combination of various technologies This years World Exposition will be held in Hanover from June until the end of October During peak days visitors are expected. A number of measures are proposed to handle the expected surplus traffic. This article will describe the core system for traffic control and traffic information centre like it is being implemented in Hanover. The traffic control centre (TCC) is operated by the move GmbH in close cooperation with the police. The aims of the TCC include providing reliable prediction of travel times, alternative routing advice, mode choice information, parking guidance as well as reducing disruption caused by incidents. These objectives are tackled by linking various traffic data measurements techniques, a number of ITS traffic control measures and an online traffic simulation model. Fig.1: move traffic management centre central control room for the Hanover EXPO 2000 including workstations for VISUM-online and control units for park-guidance system, variable message signs, tidal flow, incident detection, video cameras etc VISUM-online, article for Traffic Technology International, Annual 2000 page 1

2 ITS applications to control traffic flow A number of ITS applications have been built in the Hanover region within the last couple years. Although the combination of applications is somewhat unique due to the special traffic patterns related to the EXPO 2000 being a single-point attraction, the whole ITS system follows the general EXPO-motto of sustained usability. This means that all components can also handle the general traffic situations after the end of the EXPO as well as traffic situations occuring during the numerous fairs and exhibitions (like the annual CeBIT, being the largest computer fair in the world). A number of typical urban as well as interurban ITS applications are embedded in a whole system. The system should provide reasonable travel times for the visitors without disturbing the necessary mobility needs of Hanover residents. In order to achieve these objectives the following systems to control traffic have been built Fig.2: Variable Message Signs for contraflow traffic on urban motorways around the EXPO 2000 fairground also suited for the tidal flow system (Source: Schnüll, Haller Ingenieurgesellschaft) 32 variable message signs as an additive route guidance system on the surrounding motorways 80 km of variable message signs for accident, roadwork and bad weather warning, lane closure measures as well as dynamic speed limits VISUM-online, article for Traffic Technology International, Annual 2000 page 2

3 A tidal flow system allowing contraflow traffic. Using a 12 km section of the innerurban motorway accessing the fair ground as a one way road, the capacity of this confluence of three motorways/directions can be raised from three to six lanes during peak hours. The oncoming traffic is guided on alternative parallel routes, and some of the on- and off-ramps on the motorway interchanges are also used in a contraflow manner. A number of technical solutions has been installed to minimize the manual work of marking, signalizing and controlling twice a day. Among the 380 individual devices are dynamic signs, traffic lights, automatic barriers, above-ground lane signing and in-road signalling as used on airports.these in-roadway signal heads supplement the above-ground lane signing to keep lane channelization and dynamic signing of directions in accordance. The tidal flow system is controled in the TCC by two persons and can switch to and from contraflow operation within 15 minutes. Fig.3: Tidal flow operation on the urban motorway including interchanges and switched twice a day Variable Park-and-Ride signs on the motorways for an alternative route guidance and parking lot assignment, based on data about traffic conditions and space availability. Dynamic parking guidance systems in the City Centre of Hanover and around the fair grounds combined with a lane signalisation on the four-lane exhibition ring road; the parking guidance system is linked with demand data provided by the EXPO ticketing and event system. Demand information is available since the visitor purchases with each ticket also the type of accepted modes and parking facilities. Roadwork information system for the City of Hanover and the surrounding motorways in Lower Saxony, based on a combination of planned and actual restraint data. VISUM-online, article for Traffic Technology International, Annual 2000 page 3

4 Urban traffic control system applying signal plans which react on the general or special traffic situation in the city and its adjacent motorways. Direct communication links to the local public transport operators (being located in the same building of the TCC), the German Railroad and the Hanover airport to get actual information about the passenger flow and capacity as well as about possible delays or incidents. Direct communication links to the mission guidance systems of the police and the fire brigade. Coordination of an incident management to minimize delays between incident occurance, its detection and its removal Comprehensive traffic information system: All information coming from the above systems is filtered, validated and if necessary completed and annoteted by trained traffic operators. The information is provided to a Call Center for individual and collective traffic information and guidance on a commercial basis different media like radio and television stations the RDS-TMC system providing digital traffic information via car radio bus traffic management, specially for EXPO visitors freight guidance, controling the in- and outgoing of goods during night time others like hotels, gas stations etc. VISUM-online a model based system approach Finding the most suitable strategy to control each of the ITS application requires profound knowledge of the current situation of traffic flow. Decisions on control measures should be made on forecasted traffic flows. VISUM-online takes all available historical and present traffic data of the Hanover region and uses traffic flow models to predict the current and future situation. VISUM-online includes multimode and multiclass assignment functionality known from standard transport models. Other models have been added to represent the dynamic nature of traffic. Besides prespecified input data like coded road networks of various detail and surveyed Origin-Destination matrices, incoming online traffic data is the primary input. Information on traffic flows is gained from different sources like trafficactuated signal control units and dedicated traffic monitoring devices. Each source of online traffic is defined as one external subsystem. Each subsystem delivers traffic data via a proprietory subsystem converter into a central database. Static data like the basic network and the O-D-matrices are stored in the database as well. VISUM-online, article for Traffic Technology International, Annual 2000 page 4

5 Current traffic flows are computed continously and estimated volumes and travel times are displayed. Based on the current traffic flow short-term and long-term traffic flow forecasts are computed. Standardized protocols (ODBC) are implemented in VISUMonine to read and write data from the database. fig. 4: System architecture of the central traffic management system for the Hanover EXPO Digitized road networks in different layers All information of VISUM-online is based on a digitized road network. Some information ia already related towards the transit network being out of the scope of this article. The road network is based on data provided by Teleatlas in GDF 3.0 format. This network is called the navigation network. It includes every local street within the city of Hanover but it becomes very sparse when leaving the city boundaries. For transport planning purposes an integrated transit and road network has been developed for the region of Hanover. The planning network includes all major roads and some collector roads if needed to connect origins and destinations. Data completion and forecasting is only needed for roads with high volumes and a certain level of expected traffic delay. To minimize computational requirements and calibration needs the planning was reduced to a forecasting network. VISUM-online, article for Traffic Technology International, Annual 2000 page 5

6 Fig. 5: Increasing level of detail of network topology: A:forecasting network; B: planning network, C: navigation network type of network number of links number of zones navigation network about none planning network forecasting network Navigation network and planning network are updated continously by different bodies with different applications in mind. This has been of major concern within the traffic control centre. Therefore an updating mechanism had to be introduced by the administration of permanent link identification and cross-reference tables. The forecasting network is extracted from the planning network in a two-step process. First the built-in subnetwork generator of VISUM-online cuts the forecasting network, preserving the assigned traffic volumes by adding virtual zones wherever traffic flows from / to the cut-away portion enter or leave the subnetwork. This step reduces links at the expense of an increase in the number of zones from 545 to about 2100, thus defeating the reduction in computational complexity. Therefore in a second step the result- VISUM-online, article for Traffic Technology International, Annual 2000 page 6

7 ing zones are aggregated again by a clustering algorithm. Clustering introduces a discretization error (e.g. through the omission of intrazonal traffic from assignment), but the algorithm takes into account the detector locations, so that at least the assigned volumes of counted links are preserved and the data completion algorithm is unaffected. Each of the networks is supplemented by additional link or site attributes to model the relevant infrastructure such as traffic lights, measurement sites, variable message signs, parking lots etc. For input and editing of these data the graphical network editor of VI- SUM is used. Numerous functions for data management of the integrated road and transit transport network are provided. Treatment of incoming online measurement data Each of the above mentioned ITS applications has one or several sources to collect traffic data. In Hanover loop detectors, infrared-sensors, radar sensors, ground-hogs and video-detection is being implemented to collect locally traffic volumes, speeds and occupancy rates (NH: Detektorarten ggf. ändern). Additionally green times and the current states of the parking guidance and variable message signs systems have to be gathered. The data is transmitted via cable, channel-multiplexing-data-short-wavecommunication and fibre-optic link to the control centre. Interfaces had to be designed in order to sum up all incoming data in one universal data base system. VISUM-online evaluates data recorded via detectors from traffic flow. Technical standards of detectors, transmission protocols and the quality and level of aggregation of this data may differ. VISUM-online is able to prepare and process data from different sources. This data is classified by type and level of aggregation (counts or speed records, vehicle-based or interval-based), which is internally displayed in a unified format. The data of each subsystem has to be mapped to these formats. Data completion The current state of traffic flow (volumes, link speeds and travel times) is derived from the incoming traffic data being measured in 1-min and 5-min intervals. Data from temporarily faulty detectors is being estimated. Data completion in VISUM-online is based on algorithms developed to estimate origindestination matrices from traffic counts at cross-sections. The Path Flow Estimator designed at the University of Newcastle is incorporated within VISUM-online. An approximate (historical) O-D matrix and online traffic data (volumes and occupancy rates) are used to compute the most likely traffic situation. Basically the Path Flow Estimator modifies the assignment of a known O-D matrix in a way, that assigned traffic volumes at measurement sites are equal to counted data. Therefore the impedance of links is increased or reduced in an iterative process, as required by the deviations between assigned and counted volumes. The estimation may differ from the given O-D matrix within a scaleable range, in order to allow a better solu- VISUM-online, article for Traffic Technology International, Annual 2000 page 7

8 tion for the overall network. Thus the matrix is being used as constraint to estimate traffic flows and at the same time it is continuously updated due to measured data. Fig. 6: Data completion via Path Flow Estimator The procedures applied for data completion in VISUM-online generate traffic volumes per link, routes for each O-D pair and the volumes on these routes. Because of the routes Floating Car Data will be a valuable source if this data becomes available in the future. Measured and computed data is being stored for follow-up computations since the general method includes a self-learning process. For instance one may start without historical flow patterns and will gain a more and more reliable and extensive database during operation. Forecasting methods based on origin-destination information Two forecasting methods are being implemented in Hanover. Song-term forecasts are generated for the next hour and long-term forecasts provide information for the. next coming days The first forecast is based on traffic flow simulation, the second one on dynamic assignment. Based on the current traffic conditions gained by data completion traffic states are forecasted every 15 minutes for the next one hour. The information will help to find the most suitable traffic control scheme by assisting a human operator in the evaluation of alternative options. There is no optimization of the control strategy considering the compli- VISUM-online, article for Traffic Technology International, Annual 2000 page 8

9 ance rates of various driver types. The mesoscopic traffic flow simulation model DYNEMO is applied for short-term forecasting of urban and rural road networks. It is able to deal with networks with about 100,000 vehicles moving simultaneously, and has been used to simulate a large part of the German motorway network. Regarding movement of vehicles, DYNEMO is a mesoscopic model in the sense that the unit of traffic flow is the individual vehicle rather than the temporal and spatial aggregates used in static assignment models. Their movement is governed by the average traffic density on the link they traverse rather than the behaviour of other driver-vehicle units in the immediate neighbourhood as in microscopic traffic flow models. Fig. 7: Traffic flow simulation DYNEMO for shortterm forecasting Unlike static assignment where all trips are assumed to happen instantaneously and simultaneously, dynamic assignment takes into account the travel time on the loaded network (up to one hour in the Hanover forecasting network) and the daily profile of the trips. Volumes and volume-dependent link travel times are computed and recorded separately for each of 96 quarter-hour time-slices. Route choice is governed by the expected loaded trip time, summing over the expected future link travel times at the time when the vehicle will reach the particular link. Chosen routes and link travel times are adjusted simultaneously in an iterative procedure. The demand side in dynamic assignment is given in the form of hourly (or shorter) o-d matrices rather than the daily matrices typically used in strategic transportation planning. For the Hannover case the hourly ma- VISUM-online, article for Traffic Technology International, Annual 2000 page 9

10 trices are computed as the sum of historically known non-expo traffic and a forecast of EXPO visitor traffic (based on ticketing information). Visualisation and Assessment A number of visualisation measures are set up in the control room of the TCC. A large central visualisation screen is used to display the images of the video-cameras, the states of the various traffic control techniques (VMS, tidal flow, parking guidance) and the current traffic flow situation. Each operator has three standard PC monitors. Usually opens up various windows to display current and forecasted traffic flow at different levels of detail. Incoming online measurement data and traffic flow data derived from data completion and forecast are displayed graphically on the navigation network. Minor links without any traffic information can be omitted for clarity. The traffic flow data displayed graphically or as table may vary between volume per vehicle type, speed and density per measurement site, link or turning movement. The predicted evolution of flows resulting from forecast calculations is presented as an animated display. Travel times are estimated using data completion and the general knowledge of routes within the network. Emissions can be estimated based on the traffic flows and speeds but emissions are not of major concern in Hanover. Implausible data from detectors (e.g. as detector is faulty or has not been positioned correctly in the network) is marked; data plausibility is checked during data completion. The graphical user interface provides numerous functions for display of various types of data on the road network. Displays are configured by the user and stored as defined visualisation profiles. Particular information is selected using comprehensive filter functions. Additionally the graphical display of the network includes to visualize the current state of each subsystem as a separate layer. This facility helps that all information concerning traffic flow and control measures can be displayed in one uniform system although the data has been provided by various sources. In that respect the core system within the Hanover TCC is probably the most comprehensive system in Germany as it unifies data collection, traffic control techniques and traffic simulation within one GIS-based visualisation framework. The various traffic control systems can be managed with a smaller staff than usually required if each system is set up individually and all decisions are based on the same level of information. VISUM-online, article for Traffic Technology International, Annual 2000 page 10