scholarly journals On the Price of Satisficing in Network User Equilibria

2020 ◽  
Vol 54 (6) ◽  
pp. 1555-1570
Author(s):  
Mahdi Takalloo ◽  
Changhyun Kwon
Keyword(s):  
Travel Time ◽  
Transportation Networks ◽  
User Equilibrium ◽  
Decision Makers ◽  
Total System ◽  
Travel Times ◽  
Traffic Patterns ◽  
Worst Case ◽  
Traffic Pattern

When network users are satisficing decision makers, the resulting traffic pattern attains a satisficing user equilibrium, which may deviate from the (perfectly rational) user equilibrium. In a satisficing user equilibrium traffic pattern, the total system travel time can be worse than in the case of the perfectly rational user equilibrium. We show how bad the worst-case satisficing user equilibrium traffic pattern can be compared with the perfectly rational user equilibrium. We call the ratio between the total system travel times of the two traffic patterns the price of satisficing, for which we provide an analytical bound. We compare the analytical bound with numerical bounds for several transportation networks.

Dynamic Value Pricing on I-15 in San Diego: Impact on Travel Time and Its Reliability

2003 ◽  
Vol 1839 (1) ◽  
pp. 45-54 ◽  
Author(s):  
Janusz Supernak ◽  
Christine Kaschade ◽  
Duane Steffey
Keyword(s):  
Travel Time ◽  
San Diego ◽  
Time Profile ◽  
Travel Times ◽  
Case Scenario ◽  
Worst Case ◽  
San Diego State University ◽  
Time Changes ◽  
Value Pricing ◽  
Express Lanes

Selected results are presented of the Traffic Study, one of 12 studies conducted by San Diego State University for the I-15 Congestion (Value) Pricing Project in San Diego, a 3-year demonstration. The focus is on the project's impact on travel times and their distribution on both the main lanes and the express lanes of I-15 for both ExpressPass and FasTrak phases of the project. Specifically addressed is the issue of reliability of on-time arrival enjoyed by the FasTrak subscribers and the high variability of travel times for the I-15 travelers who use only main lanes of I-15 for their commute. Examination of the ramp and freeway delays shows that in the worst-case scenario, FasTrak subscribers who use express lanes can save up to 20 min avoiding delay on the I-15 main lanes. This finding agrees with the drivers’ perceptions about their time savings when using FasTrak. Travel-time changes during the duration of the project also are examined. There were substantial year-to-year changes in travel times along the I-15 main lanes and the I-8 lanes used as control. The travel-time profile along the I-15 main lanes differed significantly from the profile along I-8, the control corridor, in both a.m. and p.m. peak periods.

scholarly journals Visualizations of Travel Time Performance Based on Vehicle Reidentification Data

2017 ◽  
Vol 2646 (1) ◽  
pp. 84-92 ◽  
Author(s):  
Stanley Ernest Young ◽  
Elham Sharifi ◽  
Christopher M. Day ◽  
Darcy M. Bullock
Keyword(s):  
Travel Time ◽  
Performance Measures ◽  
Traffic Control ◽  
Cumulative Distribution ◽  
Travel Time Reliability ◽  
Travel Times ◽  
Traffic Patterns ◽  
Before And After ◽  
Vehicle Reidentification ◽  
Arterial Performance

This paper provides a visual reference of the breadth of arterial performance phenomena based on travel time measures obtained from reidentification technology that has proliferated in the past 5 years. These graphical performance measures are revealed through overlay charts and statistical distribution as revealed through cumulative frequency diagrams (CFDs). With overlays of vehicle travel times from multiple days, dominant traffic patterns over a 24-h period are reinforced and reveal the traffic behavior induced primarily by the operation of traffic control at signalized intersections. A cumulative distribution function in the statistical literature provides a method for comparing traffic patterns from various time frames or locations in a compact visual format that provides intuitive feedback on arterial performance. The CFD may be accumulated hourly, by peak periods, or by time periods specific to signal timing plans that are in effect. Combined, overlay charts and CFDs provide visual tools with which to assess the quality and consistency of traffic movement for various periods throughout the day efficiently, without sacrificing detail, which is a typical byproduct of numeric-based performance measures. These methods are particularly effective for comparing before-and-after median travel times, as well as changes in interquartile range, to assess travel time reliability.

Stochastic Traffic Assignment Model Based on Travel Time Reliability

2011 ◽  
Vol 130-134 ◽  
pp. 3716-3720
Author(s):  
Yi Ran Cheng ◽  
Yin Han ◽  
Xin Kai Jiang ◽  
Jia Lei Gu
Keyword(s):  
Travel Time ◽  
Equilibrium Model ◽  
Choice Behavior ◽  
Transportation Networks ◽  
Route Choice ◽  
User Equilibrium ◽  
Travel Time Reliability ◽  
Stochastic User Equilibrium ◽  
Model Based ◽  
Route Choice Behavior

Considering the un-deterministic transportation networks, the paper proposes the change of the route choice decisions under the stochastic transportation networks. The route choice behavior is described as a choice for a time shortest route which is subject to a time-reliability level. The paper also considered this new route choice behavior in the stochastic user equilibrium model, and proposed stochastic user equilibrium model based on the optimized reliability travel time route choice behavior in the stochastic networks. The equivalence and uniqueness of the solution of the model are demonstrated. Numerical results of a small network show that the proposed model can reflect the real traveler’s route choice behavior in stochastic transportation networks.

scholarly journals Robust Stop-Skipping at the Tactical Planning Stage with Evolutionary Optimization

2019 ◽  
Vol 2673 (3) ◽  
pp. 611-623 ◽  
Author(s):  
Konstantinos Gkiotsalitis
Keyword(s):  
Travel Time ◽  
Solution Space ◽  
Minimax Principle ◽  
Tactical Planning ◽  
Travel Times ◽  
Worst Case ◽  
Planning Stage ◽  
Traffic Conditions ◽  
Time Variations ◽  
Improved Performance

The planning of stop-skipping strategies based on the expected travel times of bus trips has a positive effect in practice only if the traffic conditions during the daily operations do not deviate significantly from those expected. For this reason, we propose a non-deterministic approach which considers the uncertainty of trip travel times and provides stop-skipping strategies which are robust to travel-time variations. In more detail, we show how historical travel-time observations can be integrated into a Genetic Algorithm (GA) that tries to compute a robust stop-skipping strategy for all daily trips of a bus line. The proposed mathematical program of robust stop-skipping at the tactical planning stage is solved using the minimax principle, whereas the GA implementation ensures that improved solutions can be obtained even for high-dimensional problems by avoiding the exhaustive exploration of the solution space. The proposed approach is validated with the use of five months of data from a circular bus line in Singapore demonstrating an improved performance of more than 10% in worst-case scenarios which encourages further investigation of the robust stop-skipping strategy.

scholarly journals Parking Pricing and Model Split under Uncertainty

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Chengjuan Zhu ◽  
Bin Jia ◽  
Linghui Han ◽  
Ziyou Gao
Keyword(s):  
Travel Time ◽  
Confidence Level ◽  
Time Budget ◽  
Route Choice ◽  
Analytic Solutions ◽  
User Equilibrium ◽  
Travel Times ◽  
Modal Split ◽  
Parking Pricing ◽  
The Impact

In order to investigate different route choice criteria in a competitive highway/park-and-ride (P&R) network with uncertain travel times on the road, a bilevel programming model for solving the problem of determining parking fees and modal split is presented. In the face of travel time uncertainty, travelers plan their trips with a prespecified on-time arrival probability. The impact of three route choice criteria: the mean travel time, the travel time budget, and mean-excess travel time, is compared for parking pricing and modal split. The model at user equilibrium is described as a minimization model. And the analytic solutions are given. Analytic solutions show that both flow and travel time at equilibrium are independent of the price difference of travel expense on money. The main findings from the numerical results are elaborated. While given a confidence level, the flow on the highway changed significantly with the criteria, although the differences of the travel times are small. Travelers can be guided to choose their modes coordinately by improving the quality of the transit service. The optimal parking fees can be affected markedly by the confidence level. Finally, the influence of the log-normal distribution parameters is tested and analyzed.

scholarly journals Designing Vehicle Turning Restrictions Based on the Dual Graph Technique

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Lihui Zhang ◽  
Hongsheng Qi ◽  
Dianhai Wang ◽  
Zhong Wang ◽  
Jian Yang
Keyword(s):  
Travel Time ◽  
Heuristic Algorithm ◽  
Design Problem ◽  
Transportation Network ◽  
Dual Graph ◽  
User Equilibrium ◽  
Total System ◽  
Nonlinear Constraints ◽  
Dual Transformation

This paper investigates the turning restriction design problem that optimizes the turning restriction locations so as to minimize the total system travel time under the assumption of asymmetric user equilibrium. We first transform a transportation network into a dual graph, where traffic turning movements are explicitly modeled as dual links. The dual transformation allows us to derive a link-based formulation for the turning restriction design problem. Asymmetric user equilibrium is incorporated in the model as a set of nonlinear constraints. A dual-based heuristic algorithm is employed to solve the problem, by sequentially solving a relaxed turning restriction design problem and a design updating problem.

Fuzzy ART Neural Network Model for Automated Detection of Freeway Incidents

1998 ◽  
Vol 1634 (1) ◽  
pp. 56-63 ◽  
Author(s):  
Sherif S. Ishak ◽  
Haitham M. Al-Deek
Keyword(s):  
Neural Networks ◽  
False Alarm ◽  
False Alarm Rate ◽  
Back Propagation ◽  
Incident Detection ◽  
Traffic Patterns ◽  
Traffic Pattern ◽  
Detection Algorithms ◽  
Fuzzy Art ◽  
Freeway Incidents

Pattern recognition techniques such as artificial neural networks continue to offer potential solutions to many of the existing problems associated with freeway incident-detection algorithms. This study focuses on the application of Fuzzy ART neural networks to incident detection on freeways. Unlike back-propagation models, Fuzzy ART is capable of fast, stable learning of recognition categories. It is an incremental approach that has the potential for on-line implementation. Fuzzy ART is trained with traffic patterns that are represented by 30-s loop-detector data of occupancy, speed, or a combination of both. Traffic patterns observed at the incident time and location are mapped to a group of categories. Each incident category maps incidents with similar traffic pattern characteristics, which are affected by the type and severity of the incident and the prevailing traffic conditions. Detection rate and false alarm rate are used to measure the performance of the Fuzzy ART algorithm. To reduce the false alarm rate that results from occasional misclassification of traffic patterns, a persistence time period of 3 min was arbitrarily selected. The algorithm performance improves when the temporal size of traffic patterns increases from one to two 30-s periods for all traffic parameters. An interesting finding is that the speed patterns produced better results than did the occupancy patterns. However, when combined, occupancy–speed patterns produced the best results. When compared with California algorithms 7 and 8, the Fuzzy ART model produced better performance.

scholarly journals “In cities, it’s not far, but it takes long”: comparing estimated and replicated travel times to reach life-saving obstetric care in Lagos, Nigeria

2021 ◽  
Vol 6 (1) ◽  
pp. e004318
Author(s):  
Aduragbemi Banke-Thomas ◽  
Kerry L M Wong ◽  
Francis Ifeanyi Ayomoh ◽  
Rokibat Olabisi Giwa-Ayedun ◽  
Lenka Benova
Keyword(s):  
Travel Time ◽  
Friction Surface ◽  
Obstetric Care ◽  
Travel Times ◽  
Night Time ◽  
Google Maps ◽  
Surface Approach ◽  
Low Resource ◽  
Life Saving ◽  
The Cost

BackgroundTravel time to comprehensive emergency obstetric care (CEmOC) facilities in low-resource settings is commonly estimated using modelling approaches. Our objective was to derive and compare estimates of travel time to reach CEmOC in an African megacity using models and web-based platforms against actual replication of travel.MethodsWe extracted data from patient files of all 732 pregnant women who presented in emergency in the four publicly owned tertiary CEmOC facilities in Lagos, Nigeria, between August 2018 and August 2019. For a systematically selected subsample of 385, we estimated travel time from their homes to the facility using the cost-friction surface approach, Open Source Routing Machine (OSRM) and Google Maps, and compared them to travel time by two independent drivers replicating women’s journeys. We estimated the percentage of women who reached the facilities within 60 and 120 min.ResultsThe median travel time for 385 women from the cost-friction surface approach, OSRM and Google Maps was 5, 11 and 40 min, respectively. The median actual drive time was 50–52 min. The mean errors were >45 min for the cost-friction surface approach and OSRM, and 14 min for Google Maps. The smallest differences between replicated and estimated travel times were seen for night-time journeys at weekends; largest errors were found for night-time journeys at weekdays and journeys above 120 min. Modelled estimates indicated that all participants were within 60 min of the destination CEmOC facility, yet journey replication showed that only 57% were, and 92% were within 120 min.ConclusionsExisting modelling methods underestimate actual travel time in low-resource megacities. Significant gaps in geographical access to life-saving health services like CEmOC must be urgently addressed, including in urban areas. Leveraging tools that generate ‘closer-to-reality’ estimates will be vital for service planning if universal health coverage targets are to be realised by 2030.

Estimation of Path Travel Time Distributions in Stochastic Time-Varying Networks with Correlations

2021 ◽  
pp. 036119812110184
Author(s):  
Monika Filipovska ◽  
Hani S. Mahmassani ◽  
Archak Mittal
Keyword(s):  
Time Dependence ◽  
Travel Time ◽  
Correlation Structure ◽  
Time Varying ◽  
Travel Times ◽  
Trajectory Data ◽  
Time Varying Networks ◽  
Transportation Research ◽  
Search Approach ◽  
Stochastic Time

Transportation research has increasingly focused on the modeling of travel time uncertainty in transportation networks. From a user’s perspective, the performance of the network is experienced at the level of a path, and, as such, knowledge of variability of travel times along paths contemplated by the user is necessary. This paper focuses on developing approaches for the estimation of path travel time distributions in stochastic time-varying networks so as to capture generalized correlations between link travel times. Specifically, the goal is to develop methods to estimate path travel time distributions for any path in the networks by synthesizing available trajectory data from various portions of the path, and this paper addresses that problem in a two-fold manner. Firstly, a Monte Carlo simulation (MCS)-based approach is presented for the convolution of time-varying random variables with general correlation structures and distribution shapes. Secondly, a combinatorial data-mining approach is developed, which aims to utilize sparse trajectory data for the estimation of path travel time distributions by implicitly capturing the complex correlation structure in the network travel times. Numerical results indicate that the MCS approach allowing for time-dependence and a time-varying correlation structure outperforms other approaches, and that its performance is robust with respect to different path travel time distributions. Additionally, using the path segmentations from the segment search approach with a MCS approach with time-dependence also produces accurate and robust estimates of the path travel time distributions with the added benefit of shorter computation times.

scholarly journals Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Cong Bai ◽  
Zhong-Ren Peng ◽  
Qing-Chang Lu ◽  
Jian Sun
Keyword(s):  
Travel Time ◽  
Dynamic Model ◽  
Kalman Filtering ◽  
Prediction Models ◽  
Support Vector ◽  
Travel Times ◽  
Travel Time Prediction ◽  
Real World Data ◽  
Time Prediction ◽  
Bus Travel Time

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

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