Developing travel time estimation methods using sparse GPS data

Evaluating Environmental Impact of Traffic Congestion in Real Time ...

We estimate the traffic state, e.g., link average speed and traffic volume, using both sparse crowd-sourced mobile data and fixed location sensing and survey ...

DeepTravel: a Neural Network Based Travel Time Estimation Model ...

The advances in GPS-enabled mobile devices and pervasive computing techniques have generated massive trajectory data. The large amount of trajectory data ...

A data-driven travel mode share estimation framework based on ...

The proposed framework first identifies trip ends with a modified Spatiotemporal Density-based Spatial Clustering of Applications with Noise algorithm. Then ...

Travel Cost Inference from Sparse, Spatio-Temporally Correlated ...

Sparse: Travel-cost time series are built from GPS data obtained from probe vehicles that cannot cover every time interval. As a re- sult ...

Effective Travel Time Estimation: When Historical Trajectories over ...

Since vehicles can only travel on road networks, we match the GPS points onto road segments and then use road segment embeddings to represent the points. Its ...

A Study on Travel Time Estimation of Diverging Traffic Stream on ...

The use of Global Positional System (GPS) on the probe vehicles equipped with navigation devices or smartphones is another direct way of travel ...

Evaluation of roadway spatial-temporal travel speed estimation ...

accuracy and reliability of travel speed estimation using sparse low frequency GPS data ... This method calculates estimated link travel speed based on link ...

Spatiotemporal K-Nearest Neighbors Algorithm and Bayesian ...

Spatiotemporal K-Nearest Neighbors Algorithm and Bayesian Approach for Estimating Urban Link Travel Time Distribution From Sparse GPS ...

Learning Travel Time Distributions with Deep Generative Model

For travel time estimation, we compare DeepGTT with three baseline methods, namely, DeepTTE [38], WDR [41], and MU-. RAT [27]. For route recovery from sparse ...

Travel Time Estimation Using Sparsely Sampled Probe GPS Data in ...

... develop an implement a platform for sustainable mobility in order to evaluate it in the region, specifically Rouen, France. The result is a framework for ...

Estimating the Travel Time and the Most Likely Path ... - AMS Journals

Euclidean distance is often used as a measure of separability and isolation by distance (Becking et al. 2006; Ellingsen and Gray 2002) to find correlations with ...

Improved DTTE Method for Route-Level Travel Time Estimation on ...

To analyze their performance on route-level travel time estimation on freeways where congestion may occur, this study developed a framework ...

A data-driven travel mode share estimation framework based on ...

The GPS data in general has the highest spatial accuracy (e.g., 10 m) and the lowest LRI (usually 1 s), but it usually covers only a small ...

Estimation of Path Travel Time Distributions in Stochastic Time ...

Specifically, the goal is to develop methods to estimate path travel time distributions for any path in the networks by synthesizing available ...

Estimating arterial traffic conditions using sparse probe data

where Id,t,l is the set of travel time observations for day d, time interval t, and link l as provided by the travel time al- location method presented in ...

Citywide Estimation of Traffic Dynamics via Sparse GPS Traces

We take a holistic view of the map-matching and travel time allocation problems and propose a method to reconstruct the velocity field of a road network.

Estimating Arterial Traffic Conditions Using Sparse Probe Data

(i.e. travel time between GPS measurements). The observations are successive ... If the travel time allocation method is not used, then the resulting ...

driving directions based on taxi trajectories

Real-User Trajectories: We use a 2-month driving history of 30 real drivers recorded by GPS trajectories to evaluate travel time estimation. This data is a part ...

Travel time estimation for ambulances using Bayesian data ...

Due to sparseness and error in the GPS data, the exact ambulance paths and travel times on each road segment are unknown. We simultaneously ...

A review of travel and arrival-time prediction methods on road ...

Its main task is to extract key features from data to cope with complex problems and handle large collections of data. An ML approach in the ...