scholarly journals An agent-based transportation impact sketch planning (TISP) model system

2021 ◽  
Vol 14 (1) ◽  
pp. 219-253
Author(s):  
Ayad Hammadi ◽  
Eric J Miller
Keyword(s):  
Land Use ◽  
Architectural Design ◽  
Travel Demand ◽  
Transportation Network ◽  
Geographic Location ◽  
Model System ◽  
Demand Model ◽  
Control Variables ◽  
Agent Based ◽  
Traffic Impact

A traffic impact sketch planning (TISP) model is presented for the estimation of the likely travel demand generated by a major land-use development or redevelopment project. The proposed approach overcomes the problems with the non-behavioral transportation-related studies used in practice for assessing the development design impacts on the local transportation system. The architectural design of the development, in terms of the number and type of dwellings, by number of bedrooms per unit, and the land-use categories of the non-residential floorspace, are reflected in the TISP model through an integrated population and employment synthesis approach. The population synthesis enables the feasible deployment of an agent-based microsimulation (ABM) model system of daily activity and travel demand for a quick, efficient, and detailed assessment of the transportation impacts of a proposed neighborhood or development. The approach is not restricted to a certain type of dataset of the control variables for the geographic location of the development. Datasets for different geographic dimensions of the study area, with some common control variables, are merged and cascaded into a synthesized, disaggregate population of resident persons, households and jobs. The prototype implementation of the TISP model is for Waterfront Toronto’s Bayside Development Phase 2, using the operational TASHA-based GTAModel V4.1 ABM travel demand model system. While the conventional transportation studies focus on the assessment of the local traffic impacts in the immediate surroundings of the development, the TISP model investigates and assesses many transportation related impacts in the district, city, and region, for both residents and non-residents of the development. TISP model analysis includes the overall spatiotemporal trips distribution generated by the residents and non-residents of the development for the auto and non-auto mobility systems and the simulated agents diurnal peaking travel times. The model results are compared with the trips estimates by a prior project traffic impact study and the Institute of Transportation Engineers (ITE) Trip Generation Manual (TGM) rates of weekday trips for the relevant land uses. Future extensions and improvements of the model including the generalization and full automation of the model, and the bi-level macro-micro representation of the transportation network are also discussed.

scholarly journals Creating an integrated agent-based travel demand model by combining mobiTopp and MATSim

2019 ◽  
Vol 151 ◽  
pp. 776-781 ◽  
Author(s):  
Lars Briem ◽  
Nicolai Mallig ◽  
Peter Vortisch
Keyword(s):  
Travel Demand ◽  
Demand Model ◽  
Agent Based ◽  
Travel Demand Model

scholarly journals Validation of an agent-based travel demand model with floating car data

2019 ◽  
Vol 37 ◽  
pp. 242-249
Author(s):  
Carlos Llorca ◽  
Sasan Amini ◽  
Ana Tsui Moreno ◽  
Rolf Moeckel
Keyword(s):  
Travel Demand ◽  
Demand Model ◽  
Agent Based ◽  
Floating Car Data ◽  
Travel Demand Model

scholarly journals Agent-Based Simulation to Improve Policy Sensitivity of Trip-Based Models

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Rolf Moeckel ◽  
Nico Kuehnel ◽  
Carlos Llorca ◽  
Ana Tsui Moreno ◽  
Hema Rayaprolu
Keyword(s):  
Travel Demand ◽  
Time Budget ◽  
Time Of Day ◽  
Destination Choice ◽  
Trip Generation ◽  
Demand Model ◽  
Agent Based ◽  
Travel Mode Choice ◽  
Travel Time Budget ◽  
Aggregate Nature

The most common travel demand model type is the trip-based model, despite major shortcomings due to its aggregate nature. Activity-based models overcome many of the limitations of the trip-based model, but implementing and calibrating an activity-based model is labor-intensive and running an activity-based model often takes long runtimes. This paper proposes a hybrid called MITO (Microsimulation Transport Orchestrator) that overcomes some of the limitations of trip-based models, yet is easier to implement than an activity-based model. MITO uses microsimulation to simulate each household and person individually. After trip generation, the travel time budget in minutes is calculated for every household. This budget influences destination choice; i.e., people who spent a lot of time commuting are less likely to do much other travel, while people who telecommute might compensate by additional discretionary travel. Mode choice uses a nested logit model, and time-of-day choice schedules trips in 1-minute intervals. Three case studies demonstrate how individuals may be traced through the entire model system from trip generation to the assignment.

Travel Demand Modeling and Conformity Determination: Atlanta Regional Commission Case Study

2002 ◽  
Vol 1817 (1) ◽  
pp. 172-176 ◽  
Author(s):  
Guy Rousseau ◽  
Tracy Clymer
Keyword(s):  
Land Use ◽  
Travel Demand ◽  
Mode Choice ◽  
Time Of Day ◽  
Traffic Model ◽  
Demand Model ◽  
Primary Input ◽  
Land Use Model ◽  
Home Based ◽  
Travel Demand Model

The Atlanta Regional Commission (ARC) regional travel demand model is described as it relates to its link-based emissions postprocessor. In addition to conformity determination, an overview of other elements is given. The transit networks include the walk and highway access links. Trip generation addresses trip production, trip attraction, reconciliation of productions and attractions, and special adjustments made for Hartsfield Atlanta International Airport. Trip distribution includes the application of the composite impedance variable. In the mode choice model, home-based work uses a logit function, whereas nonwork uses information from the home-based work to estimate modal shares. Traffic assignment includes preparation of time-of-day assignments. The model assigns single-occupancy vehicles, high-occupancy vehicles, and trucks by using separate trip tables. The procedures can accept or prohibit each of the three types of vehicles from each highway lane. Feedback between the land use model and the traffic model is accounted for via composite impedances generated by the traffic model and is a primary input to the land use model DRAM/EMPAL. The land use model is based on census tract geography, whereas the travel demand model is based on traffic analysis zones that are subareas within census tracts. The ARC model has extended the state of the practice by using the log sum variable from mode choice as the impedance measure rather than the standard highway time. This change means that the model is sensitive not only to highway travel time but also to highway and transit costs.

Method of Successive Averages Versus Evans Algorithm: Iterating a Regional Travel Simulation Model to the User Equilibrium Solution

1998 ◽  
Vol 1645 (1) ◽  
pp. 32-40 ◽  
Author(s):  
W. Thomas Walker ◽  
Thomas F. Rossi ◽  
Nazrul Islam
Keyword(s):  
Performance Monitoring ◽  
Travel Demand ◽  
User Equilibrium ◽  
Model System ◽  
Demand Model ◽  
Initial Model ◽  
Vehicle Miles Traveled ◽  
Convergence Error ◽  
Iteration Methods ◽  
Method Of Successive Averages

The results of comparative tests of two methods for iterating a regional travel demand model system are presented. Model iteration is necessary to ensure consistency between model input and output speeds, as required by current federal legislation. Two methods were tested: the Evans algorithm and the method of successive averages. A series of tests using alternative assignment techniques was conducted for each method. Criteria for evaluating the iteration methods included convergence error, average highway speeds compared with observations, highway vehicle miles traveled compared with Highway Performance Monitoring System estimates, transit boardings compared with observations, and computer running time. It was concluded that the Evans algorithm performed the best, primarily on the basis of superior computational efficiency, although good results were obtained by using the method of successive averages. Use of the Evans algorithm is recommended, embedded within a formal assignment restart, for iterating the model system. Multiple iterations of highway assignment should be used in the initial model loop and all-or-nothing assignments in subsequent iterations of the modeling chain.

Using Indicators to Assess Sustainable Transportation and Related Concepts

2018 ◽  
Vol 2672 (3) ◽  
pp. 92-103 ◽  
Author(s):  
Tara Ramani
Keyword(s):  
Land Use ◽  
Travel Demand ◽  
El Paso ◽  
Planning Horizon ◽  
The United States ◽  
Traffic Analysis ◽  
Sustainable Transportation ◽  
Demand Model ◽  
Health Indices ◽  
Over Time

The overall goal of this study is to assess the concept of sustainability in relation to the related concepts of “health” and “livability” that have emerged in transportation planning discourse. This study achieves the goal using an indicator-based case study, conducted for the El Paso metropolitan area in the United States. Data from the regional travel demand model and other sources were used to quantify a sustainability index, livability index, and health index for individual traffic analysis zones in the region, for four analysis years over a 30-year planning horizon. Each index was comprised of representative indicators, which were normalized and aggregated in accordance with common multi-criteria decision-making methods. The analysis results demonstrated little correlation between the quantified livability, sustainability, and health indices developed for the El Paso region. The indices also showed relatively low levels of change over time for a location. That is, the relative performance of a traffic analysis zone tended to stay the same, despite the modeled changes to the transportation system, demographics, and land use. The main implication of the research findings is that despite overlaps at a theoretical level, concepts such as livability and health cannot necessarily serve as proxies for sustainability when implemented in practice. The study also provides insight into the challenges of making meaningful change in the area of sustainability over time and highlights the influence of factors beyond transportation, such as land use and socio-economic issues.

scholarly journals Development of an urban travel demand model of the Town of Oakville

2021 ◽  
Author(s):  
Lukasz Pawlowski
Keyword(s):  
Data Management ◽  
Travel Demand ◽  
Transportation Network ◽  
Demand Model ◽  
Traffic Demand ◽  
University Of Toronto ◽  
Transportation Modelling ◽  
Microcomputer Software ◽  
The Town ◽  
Travel Demand Model

This dissertation documents the development of a travel demand model of the Town of Oakville. The purpose of the model was to predict traffic demand on study area roadways during the morning peak hour. The model focused on the prediction of auto driver trips. The model was developed based on the 1996 Transportation Tomorrow Survey data, available from the Data Management Group at the University of Toronto. The model was developed in accordance with the Urban Transportation Modelling System (UTMS) of models. Activities included: Trip Generation, Trip Distribution, and Trip Assignment. Accounting for Mode Split was unnecessary as the model focused only on auto driver trips. The final product of the model is a set of traffic flows over links in the transportation network. The model was developed using TransCAD transportation GIS (Geographic Information System) software. TransCAD is a microcomputer software specifically designed for transportation planning and data management.

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