Traffic state estimation on highway: A comprehensive survey
Traffic state estimation (TSE) refers to the process of the inference of traffic state variables
(ie, flow, density, speed and other equivalent variables) on road segments using partially …
(ie, flow, density, speed and other equivalent variables) on road segments using partially …
A survey of methods and technologies for congestion estimation based on multisource data fusion
Traffic congestion occurs when traffic demand is greater than the available network capacity.
It is characterized by lower vehicle speeds, increased travel times, arrival unreliability, and …
It is characterized by lower vehicle speeds, increased travel times, arrival unreliability, and …
Edge-computing video analytics for real-time traffic monitoring in a smart city
The increasing development of urban centers brings serious challenges for traffic
management. In this paper, we introduce a smart visual sensor, developed for a pilot project …
management. In this paper, we introduce a smart visual sensor, developed for a pilot project …
[HTML][HTML] Near-real-time dynamic noise mapping and exposure assessment using calibrated microscopic traffic simulations
With prospective applications ranging from improving the understanding of the daily and
seasonal dynamics of noise exposure to raising public awareness of the associated health …
seasonal dynamics of noise exposure to raising public awareness of the associated health …
Towards data-driven car-following models
V Papathanasopoulou, C Antoniou - Transportation Research Part C …, 2015 - Elsevier
Car following models have been studied with many diverse approaches for decades.
Nowadays, technological advances have significantly improved our traffic data collection …
Nowadays, technological advances have significantly improved our traffic data collection …
Non-parametric estimation of route travel time distributions from low-frequency floating car data
The paper develops a non-parametric method for route travel time distribution estimation
using low-frequency floating car data (FCD). While most previous work has focused on link …
using low-frequency floating car data (FCD). While most previous work has focused on link …
Dynamic data-driven local traffic state estimation and prediction
Traffic state prediction is a key problem with considerable implications in modern traffic
management. Traffic flow theory has provided significant resources, including models based …
management. Traffic flow theory has provided significant resources, including models based …
An enhanced SPSA algorithm for the calibration of Dynamic Traffic Assignment models
Simultaneous perturbation stochastic approximation (SPSA) is an efficient and well
established optimization method that approximates gradients from successive objective …
established optimization method that approximates gradients from successive objective …
A comparison of machine learning methods for the prediction of traffic speed in urban places
C Bratsas, K Koupidis, JM Salanova… - Sustainability, 2019 - mdpi.com
Rising interest in the field of Intelligent Transportation Systems combined with the increased
availability of collected data allows the study of different methods for prevention of traffic …
availability of collected data allows the study of different methods for prevention of traffic …
A data fusion approach with mobile phone data for updating travel survey-based mode split estimates
Up-to-date information on different modes of travel to monitor transport traffic and evaluate
rapid urban transport planning interventions is often lacking. Transport systems typically rely …
rapid urban transport planning interventions is often lacking. Transport systems typically rely …