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Related Concept Videos

Decision Making01:20

Decision Making

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
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Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
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Manipulation and Analysis01:21

Manipulation and Analysis

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GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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Decision Making: P-value Method01:09

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
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Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Social Traps01:41

Social Traps

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Social traps are negative situations where people get caught in a direction or relationship that later proves to be unpleasant, with no easy way to back out of or avoid. The concept was orignally introduced by John Platt who applied psychology to Garrett Hardin's "Tragedy of the Commons", where in New England herd owners could let their cattle graze in the common ground. This situation seems like a good idea, but an individual could have an advantage. If they owned...
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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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Adaptive traffic management in cities--comparing decision-making methods.

Sef van den Elshout1, Rinkje Molenaar1, Bart Wester1

  • 1DCMR Environmental Protection Agency Rijnmond, PO Box 843, 3100AV Schiedam, The Netherlands.

The Science of the Total Environment
|January 29, 2014
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Summary

Adaptive traffic management shows minimal benefits for reducing urban air pollution. Permanent traffic reduction measures, like lowering density during rush hours, are more effective than temporary interventions during high pollution events.

Keywords:
Adaptive traffic managementBlack CarbonReal-time decision makingUrban air quality

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Area of Science:

  • Environmental Science
  • Urban Planning
  • Traffic Engineering

Background:

  • Traffic congestion is a primary contributor to urban air pollution.
  • Air quality in cities is a significant public health concern.
  • Effective traffic management strategies are needed to mitigate pollution.

Purpose of the Study:

  • To simulate and assess the impact of adaptive traffic management on reducing traffic-related air pollution.
  • To compare the effectiveness of temporary adaptive interventions with permanent traffic measures.
  • To evaluate the feasibility of using real-time traffic and atmospheric data for pollution control.

Main Methods:

  • Simulations of adaptive traffic management strategies.
  • Comparison with permanent traffic intervention scenarios.
  • Assessment using Black Carbon and NOx concentration data from urban street monitoring in Rotterdam, Netherlands.

Main Results:

  • Generic traffic data and atmospheric knowledge are sufficient for operational decision-making in adaptive traffic management.
  • The net benefits of temporary adaptive traffic interventions are generally very small.
  • Permanent traffic reduction measures, such as lowering density during peak hours, demonstrate a higher impact than short-term pollution-triggered interventions.

Conclusions:

  • Adaptive traffic management, while informed by data, offers limited overall benefits for reducing urban air pollution.
  • Permanent traffic management strategies are more impactful in mitigating traffic-related air pollution than temporary, condition-based interventions.
  • Future urban air quality strategies should prioritize long-term traffic reduction measures over short-term adaptive responses.