Solute Travel-Time Estimates for Tile-Drained Fields: II. Application to Experimental Studies

1975 ◽  
Vol 39 (6) ◽  
pp. 1024-1028 ◽  
Author(s):  
W. A. Jury
Keyword(s):  
Travel Time ◽  
Experimental Studies ◽  
Time Estimates

scholarly journals The Effect of Route-choice Strategy on Transit Travel Time Estimates

2019 ◽  
Author(s):  
Nate Wessel ◽  
Steven Farber
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Imperfect Information ◽  
Optimal Path ◽  
Shortest Paths ◽  
Route Choice ◽  
Travel Times ◽  
Selection Strategies ◽  
Time Estimates ◽  
Average Travel Time

Estimates of travel time by public transit often rely on the calculation of a shortest-path between two points for a given departure time. Such shortest-paths are time-dependent and not always stable from one moment to the next. Given that actual transit passengers necessarily have imperfect information about the system, their route selection strategies are heuristic and cannot be expected to achieve optimal travel times for all possible departures. Thus an algorithm that returns optimal travel times at all moments will tend to underestimate real travel times all else being equal. While several researchers have noted this issue none have yet measured the extent of the problem. This study observes and measures this effect by contrasting two alternative heuristic routing strategies to a standard shortest-path calculation. The Toronto Transit Commission is used as a case study and we model actual transit operations for the agency over the course of a normal week with archived AVL data transformed into a retrospective GTFS dataset. Travel times are estimated using two alternative route-choice assumptions: 1) habitual selection of the itinerary with the best average travel time and 2) dynamic choice of the next-departing route in a predefined choice set. It is shown that most trips present passengers with a complex choice among competing itineraries and that the choice of itinerary at any given moment of departure may entail substantial travel time risk relative to the optimal outcome. In the context of accessibility modelling, where travel times are typically considered as a distribution, the optimal path method is observed in aggregate to underestimate travel time by about 3-4 minutes at the median and 6-7 minutes at the \nth{90} percentile for a typical trip.

scholarly journals Efficient meta-heuristics for the multi-objective time-dependent orienteering problem

2021 ◽  
Author(s):  
Yi Mei ◽  
Flora D Salim ◽  
Xiaodong Li
Keyword(s):  
Travel Time ◽  
Memetic Algorithm ◽  
Experimental Studies ◽  
Time Dependent ◽  
Ant Colony System ◽  
Orienteering Problem ◽  
Multi Objective ◽  
Optimization Task ◽  
Objective Time ◽  
Two Factors

In this paper, the Multi-Objective Time-Dependent Orienteering Problem (MOTDOP) is investigated. Time-dependent travel time and multiple preferences are two of the most important factors in practice, and have been handled separately in previous work. However, no attempts have been made so far to consider these two factors together. Handling both multiple preferences and time-dependent travel time simultaneously poses a challenging optimization task in this NP-hard problem. In this study, two meta-heuristic methods are proposed for solving MOTDOP: a Multi-Objective Memetic Algorithm (MOMA) and a Multi-objective Ant Colony System (MACS). Two sets of benchmark instances were generated to evaluate the proposed algorithms. The experimental studies show that both MOMA and MACS managed to find better solutions than an existing multi-objective evolutionary algorithm (FMOEA). Additionally, MOMA achieved better performance than MACS in a shorter time, and is less sensitive to the parameter setting. Given that MACS inherits promising features of P-ACO, which is a state-of-the-art algorithm for multi-objective orienteering problem, the advantage of MOMA over MACS and FMOEA demonstrates the efficacy of adopting the memetic algorithm framework to solve MOTDOP. Graphical Abstract https://ars.els-cdn.com/content/image/1-s2.0-S0377221716301990-fx1_lrg.jpg © This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/

Frequency of Probe Reports and Variance of Travel Time Estimates

1997 ◽  
Vol 123 (4) ◽  
pp. 290-297 ◽  
Author(s):  
Ashish Sen ◽  
Piyushimita (Vonu) Thakuriah ◽  
Xia-Quon Zhu ◽  
Alan Karr
Keyword(s):  
Travel Time ◽  
Time Estimates

Estimating Corridor Travel Time by Using Transit Vehicles as Probes

2003 ◽  
Vol 1855 (1) ◽  
pp. 60-65 ◽  
Author(s):  
Frederick W. Cathey ◽  
Daniel J. Dailey
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Travel Times ◽  
Information Density ◽  
Time Estimates ◽  
Real Time Applications

A corridor approach to travel-time estimates by using transit vehicles as probes is presented. These estimates increase the information density along the corridor, compared with use of only probe information at specified points. Speed estimates are provided that track the significant changes identified in inductance-loop data, but the estimate of the speed appears to be conservative. Comparison of instantaneous travel times, often used for real-time applications, and travel time computed by using a corridor speed surface indicates that the instantaneous travel times have a delay in tracking changes in the corridor and have higher maximum travel time.

Impact of Underreporting on Mileage and Travel Time Estimates: Results from Global Positioning System-Enhanced Household Travel Survey

2003 ◽  
Vol 1854 (1) ◽  
pp. 189-198 ◽  
Author(s):  
Jean Wolf ◽  
Marcelo Oliveira ◽  
Miriam Thompson
Keyword(s):  
Travel Time ◽  
Global Positioning System ◽  
Travel Demand ◽  
Positioning System ◽  
Gps Technology ◽  
Travel Survey ◽  
Household Travel Survey ◽  
Time Estimates ◽  
Global Positioning ◽  
Household Travel

Trip underreporting has long been a problem in household travel surveys because of the self-reporting nature of traditional survey methods. Memory decay, failure to understand or to follow survey instructions, unwillingness to report full details of travel, and simple carelessness have all contributed to the incomplete collection of travel data in self-reporting surveys. Because household trip survey data are the primary input into trip generation models, it has a potentially serious impact on transportation model outputs, such as vehicle miles of travel (VMT) and travel time. Global Positioning System (GPS) technology has been used as a supplement in the collection of personal travel data. Previous studies confirmed the feasibility of applying GPS technology to improve both the accuracy and the completeness of travel data. An analysis of the impact of trip underreporting on modeled VMT and travel times is presented. This analysis compared VMT and travel time estimates with GPS-measured data. These VMT and travel time estimates were derived by the trip assignment module of each region's travel demand model by using the trips reported in computer-assisted telephone inter views. This analysis used a subset of data from the California Statewide Household Travel Survey GPS Study and was made possible through the cooperation of the metropolitan planning organizations of the three study areas (Alameda, Sacramento, and San Diego, California).

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