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Integrated Model for the Analysis of Urban Route Optimization


The project's objective is to build a dynamic traffic test model for RTI applications in small urban areas. This will be used to test applications such as traffic information, delivery advice or ordering, route planning, route guidance systems, collision avoidance systems, incident detection, etc.
The main goal of the project was to prove the feasibility of certain methodologies in the arena of transportation research. As a result of the project, pilot versions of new modelling tools and measurement techniques have been developed and experimented.
The integrated model for the analysis of urban route optimisation (IMAURO) is an urban dynamical traffic assignment simulation model, sensitive to various road transport informatics (RTI) effects, able to predict and show the effects of broadcast information on travel times, traffic density and flow rates. IMAURO is conceived as an integrated tool with a modular structure: data acquisition, database and simulation model.
The IMAURO project introduced innovative techniques to realise its ambitious objective of integrating 3 submodels which are responsive to road transport informatics (RTI) and which operate on different levels of network detail, thus realising a dynamic traffic simulation tool. These innovative techniques include a rule language for describing driver behaviour in an integrated model for the analysis of urban route optimisation (IRTE), a representation for the information network of the IRTE, a representation for road networks at various levels of detail, a representation for perceived sections of a road network, a method for merging and splitting vehicle packets, improved devices for automatic road data collection, a method for integrating 3 simulation submodels per time slice, and a method for showing simulation results using a graphical user interface.
The resulting IMAURO implementation, which demonstrates these techniques, was shown to be adaptable to a realistic urban network, namely, the urban agglomeration of the Belgian city of Namur. Test runs, with a simple demand derived from the available data at FUNDP, have been executed with simulation of an event on a major road section alongside the river Meuse. These tests have shown that the evolution of flows and costs, for a same demand and an identical incident time and location, is different depending on the availability of RTI procuring information about the incident to the drivers. However, a real dynamical demand model for the city of Namur is not available at this time and should be used to be able to validate the models. In any case further development of the mesoscopic simulation model and of the cost model are necessary to produce a commercial product.
A prototype was made available on 25/08/92

A major innovation of the integrated model for the analysis of urban route optimisation (IMAURO) was the development of a rule language used to describe the behaviour of drivers in an integrated road transport environment (IRTE). The language has a friendly syntax and permits the behaviour of drivers in specific traffic scenarios to be described clearly, concisely and unambiguously. A set of such rules, constituting a behaviourial theory, may be accumulated incrementally by considering the behaviour of drivers in specific traffic scenarios.
The formality of the rule language not only ensures that driver behaviour can be specified and communicated clearly between the partners, but also permits rules to be machine readable. The IMAURO project fully pursued this opportunity with the development of a software mechanism which reads and compiles the rules into code which can be integrated with the simulation submodels and which executes the specified behaviour when the specified traffic scenarios are simulated.
A prototype was made available on 25/08/92

PACSIM simulates movements of packets of vehicles (groups of 1 to 30 vehicles with a coherent behaviour) over a network representing a small urban area. Such packets follow routes from their origin to their destination. These routes are updated, according to the combined impact of traffic events and information technology (RTI). Packets are not static entities but do merge and split all over the network. PACSIM plays a central role for computing a dynamic assignment over the entire network. The PACSIM model includes the following desirable features: a flexible network representation, a flexible and standardised behaviourial mechanism, a behaviourally coherent traffic metaphor, an explicit time reference, and an explicit model for information flow.
The PACSIM information model takes the form ofa network that features 3 main types of nodes: detectors, traffic information centres and information sockets. These 3 classes of information network nodes are themselves linked by communication lines whose reliability and delay can be parametrized. The detector's purpose is to monitor the status of the network and to detect any traffic event therein. Traffic information centres are nodes at which information on detected traffic events is centralized, screened and then distributed to other centres and information sockets. Information sockets model the various devices that are used to transmit information to network users (radio beacons and dedicated broadcastings, variable message signs, etc). They can be situated anywhere on the network.
A prototype was made available on 25/08/92

Within the context of the integrated model for the analysis of urban route organisation (IMAURO), MICSIM presents a moving window in the urban network with an animated graphical representation of vehicle flow. A file describing a perceived network is transferred from PACSIM to MICSIM at the point microscopic simulation should be initiated. This file effectively describes a snapshot of the PACSIM simulation on a small section of the road network which MICSIM proceeds to simulate for a short duration. A similar snapshot file is sent back to the now frozen PACSIM when the MICSIM simulation is complete.
The MICSIM software managing the kinematics of car following and gap acceptance at junctions provide the bedrock of the microscopic simulation submodel. To model the influence of broadcast road transport informatics (RTI) information on the vehicles being simulated, MICSIM makes use of an identical behaviourial rule mechanism to that of PACSIM. This layer of software of higher priority is used to model the major decisions drivers may take to reroute when informed of obstacles along their preplanned route. Thus 3 major components of MICSIM can be identified: MICSIM initialisation, MICSIM basic vehicle kinematic management and the MICSIM/PACSIM behaviourial rule mechanism.
The IMAURO solution is based on rapid execution of behaviourial rules which are used to specify complex behaviourial that might result for specific vehicle types in specific road situations. For sake of consistency within the IMAURO system, MICSIM uses the same rule set as PACSIM, which interprets in the same manner. However, for use within MICSIM, the rules are compiled to invoke MICSIM functions. The only difference in interpretation of the rule language for MICSIM, is that the USER denotes an individual vehicle whereas it denotes a packet within PACSIM.
A prototype was made available on 25/08/92

The function of TOPCOST is to compute speed flow concentration relationships, to produce the cost results, and to transfer them to other submodels by adequate interfaces. TOPCOST is constructed as a number of components, each component managing a travel cost of a particular type.
TOPCOST uses a continuous traffic stream model. The maximum capacity flow is based on the principles of the American highway capacity manual (HCM) adapted for Belgian urban conditions. For roundabouts a British model is used.
The fuel consumption component is a variant of one of the Australian ARFCOM models. It computes the total fuel consumption of a vehicle, as it cruises towards an intersection, decelerates to the stopline, idles, accelerates, and cruises away from the intersection.
The travel time component is directly computed as the sum of cruise time and all kinds of delay. Cruise time is defined by the quotient of link length and cruise speed, which itself is obtained from the SFC model.
The junction queuing component is based on a British unified Transport and Road Research Laboratory (TRRL) approach derived from probabilistic queuing theory.
The discrete events component are treated by the kinematic wave approach originally conceived for traffic applications by Lighthill and Whitham.
The accidents component provides a macroscopic measure of the main categories of accident costs, as far as the necessary calibration data are available.
The noise component involves only the noise emission. TOPCOST estimates a weighted noise index for each link, in the middle of the link.
The exhaust pollution component deals with 6 different pollutants, carbon monoxide, oxides of nitrogen, hydrocarbons, sulphur dioxide, lead components and various particles.
The information cost component where road transport informatics (RTI) costs are to be payed for a service or equipment provided by a private or public company. There is room for testing the impact of 5 basic RTI techniques on cost functi ons used for route choice. The fares component simulates a cost charged by the public authorities, independently of some information service to the road user.
The factors proposed to identify the value the route selection determinants of the individual's travel behaviour and of society optimum behaviour are described. TOPCOST uses 28 elementary costs on link level, which have been grouped, using a common aggregation method, into 5 impedance or objective oriented subsets, to construct 5 aggregate link functions.
A prototype was made available on 25/08/92

The data necessary for the integrated model for the analysis of urban route optimisation (IMAURO) simulation models are topological and geometric data for the description of the urban road network of the selected city and real traffic data in different traffic situations for calibration purposes. Topological and geometrical data could be taken from existing maps and plans. A second part is based upon the observation of the road characteristics on site. This data includes the geometrical characteristics of the junctions and links of the network such as length, width, number of lanes, parking zones, priorities, bus stops, etc. Another part is the road equipment for traffic regulation, such as speed limits that apply, cycle time of traffic lights, possible movements at a junction, etc.
The traffic data needed to calibrate a dynamic model are the flow, the classification of the vehicles, the distribution of speeds and the concentration or occupancy. The data collection methodology must be able to give figures characterising the traffic situation in a given zone of the network. Therefore different types of sensors were needed, some of them being capable of being moved and installed rapidly. 2 major types of equipment were tested, inductive loops and video based traffic sensors. A comparison of the measurements with video camera and inductive loops was completed, using as a reference some visual observations, executed by BRRC people on the same sites. The camera and loop equipment are now capable of delivering traffic data with good precision. The database representing the traffic observed at a main entry node of the central part La Corbeille in Namur, during different periods of the year and in different traffic conditions, is available for further use.
A prototype was made available on 25/08/92
The output of IMAURO will be an integrated tool with a modular structure consisting of:
- a data acquisition module,
- a model construction module,
- a data base system module.
The project's data acquisition phase will collect essential `real world' data from a specific test network containing 500 km of urban roads by using modern techniques such as video camera observations & automatic image analysis, mobile measuring stations as well as other more classical data collection techniques. The data will be used in simulation testing.
In the model construction phase, a tool will be constructed which will integrate :
- a dynamic macroscopic traffic assignment using a `node environment' and limited driver knowledge of the network status (TOPSORT),
- a microscopic traffic simulation based on gap acceptance (MICSIM),
- an advanced network oriented numerical optimization technique (PSN LNO).
The techniques to be used in the macroscopic model will enable the simulation of RTI effects such as driver information systems, incident detection systems, route guidance techniques, road pricing and green waves.
The structure of the microscopic model will allow simulation of the effects of RTI, such as distance warning, overtaking aids, urban variants of convoy driving involving synchronized acceleration/deceleration phases in relation to traffic lights and other effects.
The above described dynamic traffic simulation model will not include dynamic demand forecasting or modal split models but will provide a mechanism for integration with such models, if they are developed by other DRIVE projects.
Finally the database system will be provided (including a database management subsystem) and will be used to store and retrieve data used in the models and in the interaction with the measurement work in the field. A user interface and a software interface to demand modelling tools will also be developed.
Main Deliverables:
Report on survey and data collection, Report on data base system.
Reports on final models TOPSORT, PSNLNO, MICSIM.



Participants (5)

United Kingdom