banner image
image of Volume 12, Issue 6
Online ISSN 1751-9578 Print ISSN 1751-956X

IET Intelligent Transport Systems

Volume 12, Issue 6, August 2018

Volume 12, Issue 6

August 2018

Show / Hide details
    • Driver distraction and inattention in the realm of automated driving
      How many times do young drivers actually touch their smartphone screens while driving?
      Driven to discussion: engaging drivers in conversation with a digital assistant as a countermeasure to passive task-related fatigue
      Simulating the effect of cognitive load on braking responses in lead vehicle braking scenarios
      Understanding the effects of peripheral vision and muscle memory on in-vehicle touchscreen interactions
    • Multi-level thinking cellular automata using granular computing title
      Potential safety effects of a frontal brake light for motor vehicles
      Influence of haptic guidance on driving behaviour under degraded visual feedback conditions
      Wavelet-based short-term forecasting with improved threshold recognition for urban expressway traffic conditions
      Feature selection-based approach for urban short-term travel speed prediction
      Longitudinal speed control of autonomous vehicle based on a self-adaptive PID of radial basis function neural network
      Road safety analysis for high-speed vehicle in complex environments based on the viability kernel
      Exploration and evaluation of individual difference to driving fatigue for high-speed railway: a parametric SVM model based on multidimensional visual cue
      Lane detection method based on lane structural analysis and CNNs
      In-use emissions testing of diesel-driven buses in Southampton: is selective catalytic reduction as effective as fleet operators think?
      Enhancement of safety and comfort of cyclists at intersections
      traffic flow prediction model based on deep belief network and genetic algorithm
      Improved license plate localisation algorithm based on morphological operations
      Automated visual inspection of target parts for train safety based on deep learning

Most viewed content for this Journal


Most cited content for this Journal

This is a required field
Please enter a valid email address