scholarly journals Modeling reliability benefits

10.32866/7542 ◽  
2019 ◽  
Author(s):  
Jonas Eliasson
Keyword(s):  
Decision Making ◽  
Travel Time ◽  
Road Traffic ◽  
Sufficient Accuracy ◽  
Time Variability ◽  
Travel Time Variability

This paper compares the performance of several models forecasting travel time variability for road traffic, using before/after data from the introduction of the Stockholm congestion charges. Models are estimated on before-data, and the models’ forecasts for the after-situation are compared to actual after-measurements. The accuracy of the models vary substantially, but several models are able to forecast the benefits from reduced travel time variability with sufficient accuracy to make them useful for decision making.

Uncertainty Aversion and Its Role in Travel Decision Making Under Uncertainty

2017 ◽  
Vol 8 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Zheng Li
Keyword(s):  
Decision Making ◽  
Travel Time ◽  
Model Performance ◽  
Time Variability ◽  
Decision Making Under Uncertainty ◽  
Uncertainty Aversion ◽  
Choice Data ◽  
Data Set ◽  
The Impact ◽  
Travel Time Variability

Travel time variability is a random phenomenon, and within the presence of it, uncertainty is associated with decision making. When a choice is made in an uncertain situation, the probability distribution is based on the subjective judgments of a decision maker. This paper introduces a psychological perspective to the concept of travel time variability, by embedding a belief-based weighting, so as to better understand decision making under uncertainty. This research argues that a subjective probability approach accounting for degrees of belief should be addressed in order to capture the impact of travel time variability on decision making. Using a simulated choice data set, the author provides an example of modelling uncertainty aversion, and illustrate its impacts on model performance.

Road Pricing under Travel Time Variability

2019 ◽  
Author(s):  
Gege Jiang ◽  
Hong Kam LO ◽  
Zheng LIANG
Keyword(s):  
Travel Time ◽  
Road Pricing ◽  
Time Variability ◽  
Travel Time Variability

scholarly journals Measuring Recurrent and Nonrecurrent Traffic Congestion

2003 ◽  
Vol 1856 (1) ◽  
pp. 118-124 ◽  
Author(s):  
Alexander Skabardonis ◽  
Pravin Varaiya ◽  
Karl F. Petty
Keyword(s):  
Los Angeles ◽  
Travel Time ◽  
San Francisco ◽  
Traffic Congestion ◽  
Real Life ◽  
Time Variability ◽  
Loop Detectors ◽  
Bay Area ◽  
Freeway Corridors ◽  
Travel Time Variability

A methodology and its application to measure total, recurrent, and nonrecurrent (incident related) delay on urban freeways are described. The methodology used data from loop detectors and calculated the average and the probability distribution of delays. Application of the methodology to two real-life freeway corridors in Los Angeles, California, and one in the San Francisco, California, Bay Area, indicated that reliable measurement of congestion also should provide measures of uncertainty in congestion. In the three applications, incident-related delay was found to be 13% to 30% of the total congestion delay during peak periods. The methodology also quantified the congestion impacts on travel time and travel time variability.

scholarly journals Modeling distributions of travel time variability for bus operations

2015 ◽  
Vol 50 (1) ◽  
pp. 6-24 ◽  
Author(s):  
Zhenliang Ma ◽  
Luis Ferreira ◽  
Mahmoud Mesbah ◽  
Sicong Zhu
Keyword(s):  
Travel Time ◽  
Time Variability ◽  
Travel Time Variability
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