Bicycle Data-Driven Application Framework: A Dutch Case Study on Machine Learning-Based Bicycle Delay Estimation at Signalized Intersections Using Nationwide Sparse GPS Data

Data-driven approaches are helpful for quantitative justification and performance evaluation. The Netherlands has made notable strides in establishing a national protocol for bicycle traffic counting and collecting GPS cycling data through initiatives such as the Talking Bikes program. This article addresses the need for a generic framework to...

Exploring the Influence of Signal Countdown Timers on Driver Behavior: An Analysis of Pedestrian–Vehicle Conflicts at Signalized Intersections

Although signal countdown timers (SCTs) are likely to enhance efficiency at signalized intersections, there is little research on how they affect road users’ behavior. The present study explores factors associated with driver behavior through two approaches to examine how SCTs influence drivers’ actions toward pedestrians violating red lights....

Prioritizing Cyclists at Signalized Intersections Using Observations from Connected Autonomous Vehicles

When making trips in urban environments, cyclists lose time as they stop and idle at signalized intersections. The main objective of this study was to show how augmenting the situational awareness of traffic signal controllers, using observations from moving sensor platforms, can enable prioritization of cyclists and reduce lost time within...

Controlling Spillback Effects In Multimodal Real-time Controlled Traffic Systems

When traffic demand is high and the intersection lacks throughput, oversaturated traffic phenomena occur, such as the oversaturation of a turning bay or intersection link. When such unsafe situations emerge, control strategies can be applied to handle or avoid these spillback effects. In this paper, a spillback component is designed that detects...

Turning Maneuver Prediction of Connected Vehicles at Signalized Intersections: A Dictionary Learning-Based Approach

Vehicle-to-Infrastructure (V2I) communication has provided a solution for the improvement of the traffic efficiency of smart city intersections. For example, turning maneuvers prediction at signalized intersections in a connected environment helps traffic command centers time traffic lights and dynamically predict traffic flow. However, the...

Reliability of Intergreen Interval Based on Combined Dilemma and Option Zones

Currently, the dilemma and option zones’ failures are independently used to analyze the intergreen interval at signalized intersections. Therefore, the present research work is initiated to integrate these failures. First, the dilemma and option zones are modelled using the first-order second-moment method. Then, game theory is used to model the...

Exploring the Potential of Neural Networks for Bicycle Travel Time Estimation

A tool for travel time estimation of cyclists approaching a traffic light can monitor level of service of intersections in bike crowded cities. This work represents a first step in developing such a tool. Neural Network models are evaluated on how they perform in estimating individual travel time of cyclists approaching a signalized...

Improvement of road traffic sustainability by implementation of priority weights for trucks in predictive signalized intersection control

In the European Union Road freight transport volume is expected to grow 78% between 2000 and 2030, which results in more trucks on the road network. The worldwide estimated trend shows an increase of 150 million freight vehicles and an increase of 240 million passenger vehicles. The growth of both vehicle classes will have a major impact on the...

An extensive investigation of an eco-approach controller under a partially connected and automated vehicle environment

This study evaluated the performance of an eco-approach control system at signalized intersections under a partially connected and automated vehicle (CAV) environment. This system has the first eco-approach controller able to function with the existence of surrounding human-driven traffic. A previous evaluation only confirmed its benefits....

DIRECTOR: Enabling advanced driver assistance systems with predictive signalized intersection control using LSTM networks: An AI approach to signalized intersection control

Traffic congestion at signalized intersections is a big economical and ecological problem. Handcrafted traffic light controllers (TLCs) are currently used to minimize the impact, but they are expensive to design and maintain and their performance degrades over time. Predictive TLCs and advanced driver assistance systems (ADAS) form a potential...

Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection

This master thesis aims to gain new empirical insights into longitudinal driving behavior by means of the enumeration of a new hybrid car-following (CF) model which combines parametric and non parametric formulation. On one hand, the model, which predicts the drivers acceleration given a set of variables, benefits from innovative machine...

Loop detector data error diagnosing and interpolating with probe vehicle data

Traffic volume and queue length are two important variables to identify traffic states in urban areas. Loop detectors are often used for monitoring traffic. A prominent weakness of loop detector data is the limited reliability due to equipment malfunctions and communication faults. This paper presents a method to identify the validity of loop...