Transportation Modeling: Difference between revisions
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=Agenda= | |||
'''Developing the ActivitySim Open Platform for Travel Demand Modeling | <div style="color:#000000;">'''Title: '''Developing the ActivitySim Open Platform for Travel Demand Modeling</div> | ||
<span style="color:#000000;">'''Speaker: '''</span><span style="color:#000000;">Ben Stabler, Director, RSG (</span>[mailto:Ben.Stabler@rsginc.com Ben.Stabler@rsginc.com]<span style="color:#000000;">)</span> | |||
ActivitySim is an open platform for activity-based (AB) travel demand modeling. It emerged from a consortium of Metropolitan Planning Organizations (SANDAG, MTC, ARC, PSRC) and other transportation planning agencies (SFCTA) that wanted to build a shared, open, platform that could be easily adapted to their individual needs, but would share a robust, efficient, and well-maintained common core. It is unlike previous AB model development efforts since it is principally an open software engineering project. The goal is a new community supported framework for advanced travel demand models that will eventually replace the AB modeling tools developed to date. The first generation of AB modeling tools are now mature and in use at various transportation planning agencies around the world. These modeling tools succeeded in establishing AB modeling. However, it can be argued that these tools are more prototype than platform. Prototypes typically lack usability, transparency, stability, extensibility, and optimization. Platforms excel at these requirements. The purpose of this presentation is to share the impetus for this collaborative effort, the proposed solution, and provide an update on progress and next steps. | ActivitySim is an open platform for activity-based (AB) travel demand modeling. It emerged from a consortium of Metropolitan Planning Organizations (SANDAG, MTC, ARC, PSRC) and other transportation planning agencies (SFCTA) that wanted to build a shared, open, platform that could be easily adapted to their individual needs, but would share a robust, efficient, and well-maintained common core. It is unlike previous AB model development efforts since it is principally an open software engineering project. The goal is a new community supported framework for advanced travel demand models that will eventually replace the AB modeling tools developed to date. The first generation of AB modeling tools are now mature and in use at various transportation planning agencies around the world. These modeling tools succeeded in establishing AB modeling. However, it can be argued that these tools are more prototype than platform. Prototypes typically lack usability, transparency, stability, extensibility, and optimization. Platforms excel at these requirements. The purpose of this presentation is to share the impetus for this collaborative effort, the proposed solution, and provide an update on progress and next steps. | ||
'''Current Trends and Challenges in Traffic Simulation | <div style="color:#000000;">'''Title: '''Current Trends and Challenges in Traffic Simulation</div> | ||
<span style="color:#000000;">'''Speaker: '''</span><span style="color:#000000;">Munehiro Fukuda, Division of Computing & Software Systems, University of Washington Bothell (Munehiro Fukuda <</span>[mailto:mfukuda@u.washington.edu mfukuda@u.washington.edu]<span style="color:#000000;">)</span> | |||
Traditional transport simulators such as EMME/3 have compared highway traffic to fluid dynamics and thus have modeled it mathematically (in most common cases using finite difference methods.) However, this approach encounters a difficulty in modeling microscopic traffic events including traffic lights, constructions, different types of vehicles, and pedestrians. Therefore, recent traffic simulators including TRNASIMS and MATSim focus on micro-simulation that views traffic as a flow of individual entities or agents, (i.e., vehicles and pedestrians, each with a different itinerary). Such micro-simulation has been highlighted as agent-based modes. Agent-based transport simulation describes traffic network as a graph of small links, each with its own attributes such as a different speed limit. The recent research handles dynamic trip plans, signals, and lanes, parking, public transport, freight traffic, etc. On the other hand, simulation of emergent collective group behavior of agents results in two challenges: (1) simulation models must be calibrated with real-world data since the results are no longer verified mathematically and (2) they need substantial computing resources to simulate realistic problems such as metropolitan transport with millions of vehicles. As focusing on MATSim, this talk will discuss what agent-based transport simulation can do and what solutions are considered to address the challenges. | Traditional transport simulators such as EMME/3 have compared highway traffic to fluid dynamics and thus have modeled it mathematically (in most common cases using finite difference methods.) However, this approach encounters a difficulty in modeling microscopic traffic events including traffic lights, constructions, different types of vehicles, and pedestrians. Therefore, recent traffic simulators including TRNASIMS and MATSim focus on micro-simulation that views traffic as a flow of individual entities or agents, (i.e., vehicles and pedestrians, each with a different itinerary). Such micro-simulation has been highlighted as agent-based modes. Agent-based transport simulation describes traffic network as a graph of small links, each with its own attributes such as a different speed limit. The recent research handles dynamic trip plans, signals, and lanes, parking, public transport, freight traffic, etc. On the other hand, simulation of emergent collective group behavior of agents results in two challenges: (1) simulation models must be calibrated with real-world data since the results are no longer verified mathematically and (2) they need substantial computing resources to simulate realistic problems such as metropolitan transport with millions of vehicles. As focusing on MATSim, this talk will discuss what agent-based transport simulation can do and what solutions are considered to address the challenges. | ||
'''Title: '''Thoughts from a Regional Forecaster on Cities’ Forecasting and Smart Data Needs | |||
'''Speaker: '''Jeff Frkonja, Research Center Director, Oregon Metro, ([mailto:Jeff.Frkonja@oregonmetro.gov Jeff.Frkonja@oregonmetro.gov]) | |||
Public-sector transportation and land use policy-making and programming face a broad and deep array of challenges and opportunities. On the one hand decision-makers desire information at ever greater levels of detail while on the other hand they ask analysts to cover a broader array of specialized topics. Citizens appropriately demand that their elected officials pay due attention to all such factors while simultaneously balking at the idea of providing their personal information to government to help inform such discussions. This presentation will briefly describe the breadth and detail requirements of city-level decision support analytics, enumerate the tool developments (proven and prospective) that could meet those requirements, and speculate on the opportunities that truly smart cities have to bring in the data that will make all the above possible. | |||
The Transportation Modeling web page shows the two talks above, but not the third talk. Please add the following information to the web page… | |||
Latest revision as of 07:31, February 1, 2017
Agenda
Speaker: Ben Stabler, Director, RSG (Ben.Stabler@rsginc.com)
ActivitySim is an open platform for activity-based (AB) travel demand modeling. It emerged from a consortium of Metropolitan Planning Organizations (SANDAG, MTC, ARC, PSRC) and other transportation planning agencies (SFCTA) that wanted to build a shared, open, platform that could be easily adapted to their individual needs, but would share a robust, efficient, and well-maintained common core. It is unlike previous AB model development efforts since it is principally an open software engineering project. The goal is a new community supported framework for advanced travel demand models that will eventually replace the AB modeling tools developed to date. The first generation of AB modeling tools are now mature and in use at various transportation planning agencies around the world. These modeling tools succeeded in establishing AB modeling. However, it can be argued that these tools are more prototype than platform. Prototypes typically lack usability, transparency, stability, extensibility, and optimization. Platforms excel at these requirements. The purpose of this presentation is to share the impetus for this collaborative effort, the proposed solution, and provide an update on progress and next steps.
Speaker: Munehiro Fukuda, Division of Computing & Software Systems, University of Washington Bothell (Munehiro Fukuda <mfukuda@u.washington.edu)
Traditional transport simulators such as EMME/3 have compared highway traffic to fluid dynamics and thus have modeled it mathematically (in most common cases using finite difference methods.) However, this approach encounters a difficulty in modeling microscopic traffic events including traffic lights, constructions, different types of vehicles, and pedestrians. Therefore, recent traffic simulators including TRNASIMS and MATSim focus on micro-simulation that views traffic as a flow of individual entities or agents, (i.e., vehicles and pedestrians, each with a different itinerary). Such micro-simulation has been highlighted as agent-based modes. Agent-based transport simulation describes traffic network as a graph of small links, each with its own attributes such as a different speed limit. The recent research handles dynamic trip plans, signals, and lanes, parking, public transport, freight traffic, etc. On the other hand, simulation of emergent collective group behavior of agents results in two challenges: (1) simulation models must be calibrated with real-world data since the results are no longer verified mathematically and (2) they need substantial computing resources to simulate realistic problems such as metropolitan transport with millions of vehicles. As focusing on MATSim, this talk will discuss what agent-based transport simulation can do and what solutions are considered to address the challenges.
Title: Thoughts from a Regional Forecaster on Cities’ Forecasting and Smart Data Needs
Speaker: Jeff Frkonja, Research Center Director, Oregon Metro, (Jeff.Frkonja@oregonmetro.gov)
Public-sector transportation and land use policy-making and programming face a broad and deep array of challenges and opportunities. On the one hand decision-makers desire information at ever greater levels of detail while on the other hand they ask analysts to cover a broader array of specialized topics. Citizens appropriately demand that their elected officials pay due attention to all such factors while simultaneously balking at the idea of providing their personal information to government to help inform such discussions. This presentation will briefly describe the breadth and detail requirements of city-level decision support analytics, enumerate the tool developments (proven and prospective) that could meet those requirements, and speculate on the opportunities that truly smart cities have to bring in the data that will make all the above possible. The Transportation Modeling web page shows the two talks above, but not the third talk. Please add the following information to the web page…