12TH World Congress on ITS, 6-10 November 2005, San Francisco
Paper 1840
A Web-Based Traffic Simulation Framework For ITS Education And Training Chen-Fu Liao*, Ted Morris, Max Donath Center For Transportation Studies Intelligent Transportation System Institute University of Minnesota 200 Transportation and Safety Building 511 Washington Ave SE, Minneapolis, MN 55455 Phone: 612-626-1697 Fax: 612-625-6381 Email:
[email protected] [email protected] [email protected]
ABSTRACT Many traffic simulation software packages are available to help traffic engineers and researchers study and evaluate the potential impact of proposed traffic management strategy and policy. However, existing tools require a significant investment in time for learning how to create models, perform calibrations and finally analyze the results. This substantial learning curve severely restricts their application and makes it difficult for engineering students, the general public and policy makers to take advantage of these tools. An Internet-based traffic simulation framework was developed to enhance the learning experience for transportation students and engineers. Pre-generated traffic scenarios were first implemented as part of a Civil Engineering undergraduate class. Based on feedback, an interactive simulation tool was developed to allow users to make changes to the model and examine the traffic impacts. This now allows students to for example, minimize the queue length by changing the cycle length or splits. This interactive traffic simulation tool was deployed and tested in an undergraduate class of 73 students and feedback was collected from instructors and students that will facilitate additional enhancements of the lab module.
KEYWORDS Traffic Simulation, Distance Learning, Transportation Visualization
INTRODUCTION Traffic simulation tools have been widely used by transportation engineers and consultants to assist traffic managers and operators with the evaluation and analysis of the potential impact of design or control strategy changes. As an early example, Hourdakis and Michalopoulos [1] created a framework that allowed traffic operations personnel to try various strategies for managing a 'virtual' freeway incident. This was achieved by real time integration of traffic 1
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microsimulation software with a GUI (Graphical User Interface) front end. Their GUI displayed a 2D traffic map of the modeled freeway network (traffic volume is mapped to a color), variable message sign (VMS) I/O, and an interface to remote cameras (for live video feeds). The GUI and the traffic management strategies were formulated from rules written with a 'natural language' expert system programming language (http://www.gensym.com). Thus, they were able to evaluate how traffic operations personnel managed incidents while varying the content and UI (User Interface) presentation of the 'sensed' traffic data. The framework could also be 'switched' to use 'live' traffic instead of the simulated traffic (i.e., by collecting freeway loop detector data in real-time). These tools are rather complex and have been developed for and used by researchers, and trained traffic engineers. Existing tools require a significant investment in time for learning how to create models, perform calibrations and finally analyze the results. This substantial learning curve severely restricts their application and makes it difficult for engineering students, the general public and policy makers to take advantage of these tools. The benefit of using simulation to train people who deal with matters of life and death (e.g. pilots) is clear. However, many do not see the benefit of using simulation to teach material that has been taught using traditional methods in the classroom [2]. Yet, it is well understood that conveying complex concepts can be achieved by exploring them through simulation. Accordingly, in order to enhance the learning experience and understanding of intelligent transportation systems (ITS) by students and traffic engineers, we created a web-based traffic simulation module for an undergraduate transportation engineering course at the University of Minnesota. This web-based traffic simulation lab module was developed based on a microscopic traffic simulation package, AIMSUN (Advanced Interactive Microscopic Simulator for Urban and Non-urban Networks, http://www.aimsun.com) [3]. AIMSUN is embedded in GETRAM (Generic Environment for TRaffic Analysis and Modeling), a simulation environment inspired by modern trends in the design of graphical user interfaces adapted to traffic modeling requirements [3]. AIMSUN has been used successfully for numerous large-scale traffic modeling research projects within the lab [4, 5] and provides a well documented Application Programming Interface (API) to access and modify all elements of the simulation state (signal control, sensing, vehicle characteristics and state) while the simulation is running. Of course, other simulation packages with similar capabilities can be integrated into our web-based traffic simulation framework. These include, CORSIM [6] (Corridor Simulation, a comprehensive microscopic traffic simulation, applicable to surface streets, freeways, and integrated networks, http://ops.fhwa.dot.gov/trafficanalysistools/corsim.htm) operated under TSIS (Traffic Software Integrated System) environment and VISSIM (a microscopic, behavior-based multi-purpose traffic simulation program, http://www.ptvamerica.com/vissim.html). Our goal was to help students and engineers understand issues related to traffic management and operations. Using this new simulation tool accessed in real time over the Internet, students were able to analyze existing traffic situations and provide potential solutions to improve traffic operational efficiency.
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WHY TRAFFIC SIMULATION ON THE INTERNET There are many commercial traffic simulation software packages available to help traffic engineers and researchers study and evaluate the potential impact of proposed traffic management strategy and policy. Creating a traffic model and calibrating the model is a fairly complicated process which often discourages students or engineers from learning and understanding the importance and impact of traffic control. From an educational point of view, this interactive web-based tool allows people to try their own design/control approach in the simulated network without disrupting the real traffic. From an operation and management point of view, traffic simulation helps test and verify different control strategies (ramp metering, signal timing control, etc.) for different traffic conditions. Clearly this approach could be integrated – with other distance learning approaches already in place for teaching ITS technologies (Web Research Modules, http://www.its.umn.edu/education/modules.html#webmodule, for high school students). Helbing and Treiber [7] developed multilane freeway traffic with microscopic continuous-time models to help people better understand on-ramp vehicle merging, lanechanging, car following, lane-closing, and signal control through online traffic simulation and visualization (http://www.mtreiber.de/MicroApplet/index.html). Lastly, new traffic control strategies that are proposed often meet considerable resistance from the general public. We believe that by providing traffic simulations which incorporate visualization tools available on the Internet along with the ability to investigate and analyze different cause and effect scenarios, various stakeholders will better understand the impacts of changes in traffic operations or proposed ITS technologies.
OUR APPROACH An initial study site of Washington Avenue SE on the Minneapolis campus of the University of Minnesota was chosen. The Public Works Department of the City of Minneapolis provided intersection signal timing and traffic flow data. Regional aerial images were acquired for network geometry layout. Scaling factors of the aerial images were calculated to reflect the corresponding scales in the simulation model. Network geometry was created using the graphical traffic editor (TEDI) that is integrated into the GETRAM environment [8] with the aerial images placed in the background. In addition to traffic network geometry modeling, a software interface was developed to access traffic simulation data through the GETRAM extension API (Application Program Interface) and store data to a MySQL (http://www.mysql.com) database server while the simulation is running. Java client/server applications were developed to handle data communication between the client computer, traffic simulators, web server and database server. Traffic simulation The vehicle data on a user’s PC is updated and graphically displayed during every simulation step by sending queries to the web server. The web server processes and forwards the request to the database server and returns the requested data. Intersection signal timing information and time-space diagrams can also be displayed, as shown in Figure 1, with the selected vehicle(s)
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traced in real time. Vehicle information (such as vehicle ID, type, length, width, location and heading data) can be logged and saved from the graphical user interface. Interactive simulation model In the initial phase, our web-based 2D traffic simulation module limited users to choosing only from a fixed set of pre-generated scenarios for their analysis. The student could not design new signal control strategies or traffic demand models for the network. We have since developed an “interactive” traffic simulation lab module that will allow on campus or distance-learning students to configure their own signal control strategies and traffic demand patterns—and see the results either in ‘real-time’ or in ‘accelerated time’ using the microsimulation software (AIMSUN). As before, users can select, for example, a bus and watch it run its route through the network while monitoring the distance traveled on time-space plots overlaid with the signal phases along its route (Figure 1). Simulation results are saved in a traffic simulation database. Measures of Effectiveness (MOEs), including traffic flow, travel time, delay time, speed, density, stop time, number of stops, total travel distance and total travel time, for the simulation can be accessed for each simulation run for further analysis. The ability to run the simulator in ‘real-time’ can be used to test the efficacy of various operational management strategies. For example, students can create ‘incidents’ or lane blockages and monitor how well their incident management strategies work.
Figure 1 - Java-Based Users Interface 4
12TH World Congress on ITS, 6-10 November 2005, San Francisco
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The new module design consists of an interactive web-based application, a database server, web server, and several custom developed JAVA back-end services as shown in Figure 2. The web application displays the vehicle movements and signal states either ‘as they happen’ in real-time or by scrolling through post-processed simulation data. The servers act as a communication ‘bridge’ between the web application and the microsimulation software running within the ITS Laboratory network. The backend services also manage the run-time execution of the microsimulation software and other user authentication functions to restrict access. The prototype was recently used in an undergraduate transportation engineering class of 73 students.
HTTP Application
LDAP Authenticate
LDAP Authorize
Application check validation of session key
Web Server
Traffic demand and signal control settings, authentication and trigger execution
Generate & return session key
User ID, Application ID, Magic Number, Timestamp & Duration
Return session key validation and user application ID
Traffic simulation nodes PC 2 GETRAM EXT uid.dll
TRAFFIC SIMULATION DATABASE SERVER
OpenLDAP DATABASE
PC 3 GETRAM EXT uid.dll
Figure 2 - Web-Based Simulation Framework
Single intersection example In a single intersection example, as shown in Figure 3, the web interface allows users to specify traffic demands from each approach and design desired signal cycle time and green splits. Before the simulation starts, the web interface first communicates with the web server and scans through the available simulation nodes (up to 10 licenses simultaneously) and determines the least loaded simulator available to execute the simulation in batch mode. User inputs (such as traffic demands, signal timing, simulation period) are formatted into corresponding data files and sent to the remote simulation engine prior to the simulation. Resulting statistics (MOEs, such as traffic flow, travel time, delay time, speed, density, stop time, number of stops, total travel distance and total travel time) are stored in a centralized database during the simulation at minute intervals. The graphical interface on the user’s computer will start rendering the real-time simulation as soon as data is available. When the simulator finishes the batch mode execution (a 5
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batch execution could take about one minute for an hour of simulation for the single intersection example), a simulation time slider on the screen becomes enabled which allows users to jump to any simulation time stamp forward or backward within the simulation period. Users can use this feature to examine traffic condition such as queue length or delay more efficiently.
Figure 3 - Interactive Traffic Simulation Interface
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12TH World Congress on ITS, 6-10 November 2005, San Francisco
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Simulation statistics, as shown in Figure 4, can also be saved to the user’s PC and transformed into a Microsoft Excel for later analysis.
Figure 4 - Traffic Simulation Statistics
In the lab module designed by the course teaching assistants, existing intersection traffic demand and turning movements were provided. Students were asked to develop a new signal timing plan. They needed to evaluate three alternative plans, each with different objectives: I. Minimize the intersection delay II. Minimize the number of stops per vehicle III. Based on a combination of the above two, consider alternatives for the optimization using the performance index (PI), PI = 1*delay (sec)/vehicle + 10*number of stops/vehicle. Students needed to find the timing plan with the lowest PI. Students were also asked to develop a signal timing plan based on the traffic demand forecast (e.g. 5% increase for NB and SB directions, and 2% increase for the EB and WB directions over the next 5 years while the turning proportions remain the same) using the same PI as described above. Students were to investigate timing plan changes if the cycle length remained the same.
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Previously, students relied mainly on the formula suggested in the Highway Capacity Manual [9] to calculate estimated cycle time, green splits, lost time, delays and make the necessary adjustments for left-turn movement. The design of an implementable signal timing plan is a complex and iterative process that is generally carried out with the assistance of computer software (for example, Highway Capacity Software, http://mctrans.ce.ufl.edu/hcs/). However, there was no verification or feedback on how well the design of the signal timing performs. The traffic simulation tool helped students visualize traffic parameters, such as lost time, gap acceptance, queue length and delay, and make adjustments to the signal timing plan as needed.
TRAFFIC SIMULATION IN 3D In order to further enhance the user’s ability to understand the traffic effects within the context of the infrastructure, we added a 3D component to the simulation. We first developed a 3D webbased traffic simulation for the Washington Ave corridor in Minneapolis, as shown in Figure 5, using VRML (Virtual Reality Modeling Language) EAI (External Authoring Interface). The VRML EAI interface allowed users to control the content of a VRML browser window embedded in a web page from a Java applet interface. It enabled embedded objects on a web page to communicate with each other through a browser plug-in. For example, user inputs, such as traffic demand, green splits and cycle length, from the web page could be sent to the 3D world environment interactively. Unfortunately, we found that the VRML EAI interface scales poorly (memory and 3D rendering performance) as more vehicles were added to the network.
Figure 5 - Snap shot of VRML model of Washington Ave. SE in Minneapolis
We therefore developed a standalone 3D application based on OSG (OpenSceneGraph, http://www.OpenSceneGraph.org) and CommonC++ (http://www.cplusplus.org) that can interface with the web-based traffic simulation framework previously discussed. It allows users to experience traffic simulation in a virtual reality environment. Users can interactively view the
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simulation from any perspective—including from within or above a moving vehicle. The user can gain additional insights into the nature of the simulated traffic flow, such as shockwave propagation [10, 11], driver-roadside traffic information infrastructure, and context design and urban planning issues [TRB visualization in transportation, http://www.trbvis.org]. Initially, we developed conversion software in order to import road networks created in the AIMSUN environment into the 3D application. However, road geometry information such as grade, curvature, over/underpass grade and height changes, terrain models, and other vital infrastructure are either insufficient or difficult to model within the microsimulation environment. For this reason, we re-create geospecific (NAD83- State Plane) models using commercial 3D/GIS software to extract geometry from stereo epipolar aerial photos [12,13].
FUTURE WORK We collected feedback from students on the interactive web-based traffic simulation model. One of the comments was that we display the statistics graphically on the web interface without the need for post analysis of data using a spreadsheet. This will help users visualize the impacts of the applied control strategy and make adjustment more efficiently. We will continue to enhance the design to include larger road and highway networks that allow the consideration of a multiplicity of control strategies, for example, adding a bus signal priority module or a rampmetering module. We currently continue to integrate the web-based traffic simulation with a 3D visualization interface. The visualization interface can render the simulation results in a virtual reality environment and provide real-time interactivity. Future enhancements for the 3D software will allow the user to program signal timing plans and select vehicle probes similar to the 2D applications. Finally, we wish to integrate actual state-of-the-art sensing and signal control hardware into our framework. Other facilities and laboratories have done this [14, 15], although our framework will allow individuals to learn and ‘experience’ these technologies from any location having Internet access.
ACKNOWLEDGEMENT We would like to thank the Intelligent Transportation Systems Institute, University of Minnesota, for supporting this development work, and the Institute for New Media Studies, University of Minnesota, for their partial support. We would also like to thank Scott Tacheny, traffic engineer in the City of Minneapolis, for providing the traffic and signal timing data. We would like to thank the faculty and students of the Civil Engineering Department for providing us with their invaluable feedback on the prototype lab modules. We thank Professor David Levinson for his providing access to the students and to his teaching assistants, Nebiyou Tilahun and Lei Zhang for their assistance.
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[3]
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[4]
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[5]
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[8]
“GETRAM Extensions Version 4.1 User’s Manual”, TSS, Barcelona, Spain, Mar. 2002.
[9]
Highway Capacity Manual – “Chapter 16: Signalized Intersections”, Transportation Research Board, National Research Council, Washington DC, 2000
[10] Franklin, R.E. (1961), The Structure of a Traffic Shock Wave. Civil Engineering Pulb. Wks. Rev. 56, 1186-1188. [11] Del Castillo, J.M. (1996). A Car-Following Model based on the Lighthill-Whitham Theory. In: Lesort, J.B. (ed), Proceedings of the 13th International Symposium of Transportation and Traffic Theory, Lyon, 517-538. [12] Hearne, L. P., and Matthews, D., “Improving the Geospatial Data Extraction and Analysis Process Using Stereo Imagery Datasets,” American Congress on Surveying and Mapping (ACSM), Nashville TN, April 16-21, 2004. http://www.acsm.net/HearnePhotogrammetry42004.pdf [13] Jones, Ted, Hamilton-Smith, G., and Matthews, N.D., “Integrating Remotely Sensed Imagery And Information For Transportation Infrastructure Management,”, American Society for Photogrammetry & Remote Sensing, ISPRS-Pecora, Denver Colorado, November 10-15, 2002. [14] Engelbrecht, R., C. Poe, and K. Balke, “Development of a Distributed Hardware-in-theLoop Simulation System for Transportation Networks,” in Proceedings of the 78th Annual Conference of the Transportation Research Board, 1999, Washington, D.C. [15] Bullock, D. and A. Catarella, “Real-Time Simulation Environment for Evaluating Traffic Signal Systems,” Transportation Research Record 1634, 1998: pp. 130-135.
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