Distribution-free travel time reliability assessment with probability inequalities
By Manwo Ng, Wai Yuen Szeto, S. Waller. 2011
59 citations recorded by the source corpus.
An assumption that pervades the current transportation system reliability assessment literature is that probability distributions of the sources of uncertainty are known explicitly. However, this distribution may be unavailable (inaccurate) in reality as we may have no (insufficient) data to calibrate the distribution. In this paper we relax this assumption and present a new method to assess travel time reliability that is distribution-free in the sense that the methodology only requires that the first N moments (where N is a user-specified positive integer) of the travel time to be known and that the travel times reside in a set of bounded and known intervals. Because of our modeling approach, all sources of uncertainty are automatically accounted for, as long as they are statistically independent. Instead of deriving exact probabilities on travel times exceeding certain thresholds via computationally intensive methods, we develop semi-analytical probability inequalities to quickly (i.e. within a fraction of a second) obtain upper bounds on the desired probability. Numerical experiments suggest that the inclusion of higher order moments can potentially significantly improve the bounds. The case study also demonstrates that the derived bounds are nontrivial for a large range of travel time values.
Subfields: Civil and Structural Engineering, Statistics and Probability, Transportation
View Paper: https://www.semanticscholar.org/paper/39659784a2e9f176fdb28ddc6dcdfdb8e123303c
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In Civil and Structural Engineering
In Statistics and Probability
In Transportation
Citations in the corpus
- Travel through time: the story of research on travel time reliability (2013, methodology): “Dynamic assignment models including reliability factors have been reported by Jiang, Mahmassani, and Zhang (2011), Nakayama et al. (2012), Ng, Szeto, and Waller (2011) and Ng and Waller (2012).”