Road traffic has presented problems in recent years regarding mobility. The way we move from A to B has brought on new challenges due to a growing population, increasing time constraints and changes to lifestyles. With the roads and users being busier, changes are required to improve road traffic mobility.
Statistical and machine learning techniques can play key roles in solving these problems. This has been demonstrated already by modelling sustainable methodologies towards other aspects of societies' mobility. This Research Topic invites researchers to discuss the application of these techniques to traffic mobility issues, including the advances that can be made and any disadvantages.
To improve traffic mobility problems, statistical and machine learning techniques can be used. These techniques can be applied to Traffic Impact and Assessments, Traffic Engineering, Mobility Studies and Transport Planning.
A valid method for a statistical approach to analysing road traffic mobility can determine the most positive outcome, prior to making practical changes. One application can also be to evaluate people’s perceptions of mobility problems in the traffic sector, and to propose practical solutions in line with their needs.
This Research Topic deals with application of advanced statistical and machine learning techniques in the above ways, to improve traffic mobility.
This Research Topic invites original research, review articles, and opinion pieces from relevant researchers.
The Research Topics examines the following areas:
-Application of statistical techniques for solving mobility challenges.
-Application of machine learning techniques for prediction or solving traffic mobility challenges.
-Methods, data sources or techniques to determine the social perception of traffic mobility problems.
-Proposal of practical solutions and technological advances for traffic mobility problems.
Keywords:
Statistical analysis, Machine learning techniques, Environmental characteristics, Social Perception, Mobility
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Road traffic has presented problems in recent years regarding mobility. The way we move from A to B has brought on new challenges due to a growing population, increasing time constraints and changes to lifestyles. With the roads and users being busier, changes are required to improve road traffic mobility.
Statistical and machine learning techniques can play key roles in solving these problems. This has been demonstrated already by modelling sustainable methodologies towards other aspects of societies' mobility. This Research Topic invites researchers to discuss the application of these techniques to traffic mobility issues, including the advances that can be made and any disadvantages.
To improve traffic mobility problems, statistical and machine learning techniques can be used. These techniques can be applied to Traffic Impact and Assessments, Traffic Engineering, Mobility Studies and Transport Planning.
A valid method for a statistical approach to analysing road traffic mobility can determine the most positive outcome, prior to making practical changes. One application can also be to evaluate people’s perceptions of mobility problems in the traffic sector, and to propose practical solutions in line with their needs.
This Research Topic deals with application of advanced statistical and machine learning techniques in the above ways, to improve traffic mobility.
This Research Topic invites original research, review articles, and opinion pieces from relevant researchers.
The Research Topics examines the following areas:
-Application of statistical techniques for solving mobility challenges.
-Application of machine learning techniques for prediction or solving traffic mobility challenges.
-Methods, data sources or techniques to determine the social perception of traffic mobility problems.
-Proposal of practical solutions and technological advances for traffic mobility problems.
Keywords:
Statistical analysis, Machine learning techniques, Environmental characteristics, Social Perception, Mobility
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.