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Showing 1 to 11 of 11 for “"Travel Time Estimation"”.

  1. Travel Time Estimation on Arterial Streets

    Estimation of real-time travel times on arterial streets has been a challenging task due to the intersection control delay as well as bottleneck delay from the downstream link. Therefore, few transportation professionals have conducted research at utilizing the dynamic flow methods to estimate …

    vt Repository record for Travel Time Estimation on Arterial Streets (opens in a new tab)

  2. Crowdsourcing traffic data for travel time estimation

    Travel time estimation is a fundamental measure used in routing and navigation applications, in particular in emerging intelligent transportation systems (ITS). For example, many users may prefer the fastest route to their destination and would rely on real-time predicted travel times. It also …

    wvu Repository record for Crowdsourcing traffic data for travel time estimation (opens in a new tab)

  3. A System for Travel Time Estimation on Urban Freeways

    Travel time information is important for Advanced Traveler Information Systems (ATIS) applications. People traveling on urban freeways are interested in knowing how long it will take them to reach their destinations, particularly under congested conditions. Though many advances have been made in …

    vt Repository record for A System for Travel Time Estimation on Urban Freeways (opens in a new tab)

  4. Freeway Travel Time Estimation Based on Spot Speed Measurements

    … one of the kernel components of ITS technology, Travel Time Estimation (TTE) has been a high-interest topic in highway operation and management for years. Out of numerous vehicle detection technologies being applied in this project, intrusive loop detector, as the representative of spot …

    vt Repository record for Freeway Travel Time Estimation Based on Spot Speed Measurements (opens in a new tab)

  5. Link travel time estimation based on connected vehicle probe data

    … vehicle probe data (CVPD) model to estimate travel time on urban arterials. This research applies VISSIM to simulate probe vehicles that can generate and assemble snapshots via installed On-Board Unit (OBU). Each snapshot, which can include link identification, instantaneous speed, location …

    missouri Repository record for Link travel time estimation based on connected vehicle probe data (opens in a new tab)

  6. Incident-Related Travel Time Estimation Using a Cellular Automata Model

    … of this study was to estimate the drivers' travel time with the occurrence of an incident on freeway. Three approaches, which were shock wave analysis, queuing theory and cellular automata models, were initially considered, however, the first two macroscopic models were indicated to …

    vt Repository record for Incident-Related Travel Time Estimation Using a Cellular Automata Model (opens in a new tab)

  7. Mantis: A Predictive Driving Directions Recommendation System

    … the optimal route based on current and predicted travel conditions. The system uses the Bing Maps REST service to obtain a set of routes. Traffic data from the California Department of Transportation’s Performance Measurement System (PeMS) is then used to estimate travel times for these routes. In …

    calpoly Repository record for Mantis: A Predictive Driving Directions Recommendation System (opens in a new tab)

  8. Deep learning-based framework for traffic estimation for the MLK Smart Corridor in downtown Chattanooga, TN

    … movement direction identification, and speed estimation. We chose YOLOv7 for objects detection given its ability to run up to 160 fps. We trained YOLOv7 to detect and classify vehicles into four classes with a reported mean average precision of 0.69. For re-identification, we refined the …

    utc Repository record for Deep learning-based framework for traffic estimation for the MLK Smart Corridor in downtown Chattanooga, TN (opens in a new tab)

  9. Design and evaluation of a novel convolutional neural network for short-term vehicle multi-traffic prediction

    … for all 5-minute intervals from the initial time up to one hour into the future. Our proposed method was compared with the state of the art Stacked Long Short-Term Memory (S-LSTM) model, and showed 20% proportionally smaller percentage error and about 2% better recall. Our model also showed …

    uoit Repository record for Design and evaluation of a novel convolutional neural network for short-term vehicle multi-traffic prediction (opens in a new tab)

  10. Adapting Seismic Processing Techniques for Data Preconditioning in Radar Imaging of Highly Dissipative and Dispersive Media

    … on first-breaks to detect the pulse arrival time in the presence of severe waveform distortion. Second, we adapt Gabor nonstationary deconvolution to accurately estimate the subsurface reflectivity in the presence of severe attenuation and dispersion due to EM wave propagation in highly lossy …

    calgary Repository record for Adapting Seismic Processing Techniques for Data Preconditioning in Radar Imaging of Highly Dissipative and Dispersive Media (opens in a new tab)

  11. Methodologies for integrating traffic flow theory, ITS and evolving surveillance technologies

    … areas, in general; and - a methodology for real-time link and incident specific freeway diversion in conjunction with freeway incident management, in particular. The first methodology includes the development of a dynamic flow model based on stochastic queuing theory and the principle of …

    vt Repository record for Methodologies for integrating traffic flow theory, ITS and evolving surveillance technologies (opens in a new tab)