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 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 Updated COVID-19 Outbreak Forecast for San Diego County, April 2020

Outbreak ◽  
2020 ◽  
Author(s):  
Emily Eshraghian ◽  
Nathan Jacobs ◽  
Jeffrey Morgan
Keyword(s):  
San Diego ◽  
Weighted Average ◽  
San Diego County ◽  
Case Scenario ◽  
Worst Case ◽  
Social Distancing ◽  
Hospital Capacity ◽  
First Case ◽  
Scenario Model ◽  
Incident Cases

Here we extend and update our earlier projections of COVID-19 hospitalizations in San Diego County (1), and report a more optimistic outlook through the end of April 2020. San Diego confirmed its first case of COVID-19 on March 7, 2020. Several mitigation efforts were enacted on various dates, including a state-mandated stay-at-home order and enforcement of social distancing in public areas. Though mitigation strategies are helping lower the burden of disease, incident cases continue to increase exponentially. Our updated model includes data up to April 7 and does not forecast beyond April 30. Our approach uses a “wisdom of crowds” strategy (see link to methods for details) where a range of outbreak models from worst case scenario (Model A) to best case scenario (Model C) were presented to experts and non-experts (n=8) who were asked to vote on a most plausible model for expected COVID-19 spread. Final vote tallies were used to create a weighted average (Model M) as the official model projection. Our model predicts that San Diego County will not hit hospital capacity for standard hospital beds (panel a) nor for intensive care unit (ICU) beds (panel b) within April 2020. If current conditions continue, we predict the expected “surge” in hospitalizations to occur without surpassing hospital capacity, and that hospitalizations will decrease thereafter until the outbreak has been contained. However, it is important to note that factors such as changes in social distancing policies, even if occurring when existing or incident cases are low, may still result in new outbreaks and future spikes in hospitalizations. Furthermore, no models have been extensively validated for COVID-19. We encourage all residents of San Diego to continue rigorously following social distancing practices to improve the likelihood of best case scenarios and limit the scope of possible worst case scenarios.

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.

Travel-time monitoring with vibroseis

1981 ◽  
Vol 71 (6) ◽  
pp. 1903-1927
Author(s):  
R. W. Clymer ◽  
T. V. McEvilly
Keyword(s):  
Travel Time ◽  
Single Channel ◽  
Travel Times ◽  
Near Surface ◽  
First Arrival Travel Times ◽  
First Arrival ◽  
Time Variations ◽  
Time Changes ◽  
Time Accuracy ◽  
A Site

Abstract The general failure of searches for precursory seismic travel-time variations associated with strike-slip earthquakes in California has led to this investigation into the feasibility of using a controlled-source seismic method to improve significantly the precision of travel-time measurements, and to investigate the nature of any detected travel-time changes. Travel times have been measured over a period of several years at sites south of Hollister, California, along the seismically active creeping zone of the San Andreas fault, using a single-channel VIBROSEIS system with real-time on-site data processing. At a site near Bear Valley, 7 km from the fault, no variations in the travel time of a deep crustal reflection were observed that could be associated with local earthquakes. However, significant variations (0.5 to 2.5 msec) of first arrival travel times observed near the Cienega Winery may have been associated with a series of nearby earthquakes and with a creep event. Major sources of measurement error have been identified in source variations and in rainfall-induced variations in near-surface properties. The former limits the precision of the deep reflection measurements to about 0.05 per cent of the travel time and the first arrival measurements to about 0.1 per cent of the travel time. The second effect is apparent as seasonal oscillations in travel time of as much as 15 to 20 msec, and also in wavelet amplitude and waveform, giving an implied travel-time accuracy of about 0.2 per cent for the deep reflection measurements and about 1 per cent for first arrivals. While these noise levels are disappointing, they can be reduced significantly by improved field procedures. Ongoing experiments are testing such procedures.

Dynamic Value Pricing as Instrument for Better Utilization of High-Occupancy Toll Lanes: San Diego I-15 Case

2003 ◽  
Vol 1839 (1) ◽  
pp. 55-64 ◽  
Author(s):  
Janusz Supernak ◽  
Duane Steffey ◽  
Christine Kaschade
Keyword(s):  
Public Relations ◽  
San Diego ◽  
Level Of Service ◽  
Steady Increase ◽  
Volume Distribution ◽  
Peak Period ◽  
Fee Structure ◽  
San Diego State University ◽  
Value Pricing ◽  
High Occupancy Toll

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, California, a 3-year federal demonstration that converted underutilized high-occupancy-vehicle (HOV) lanes into a high-occupancy toll (HOT) facility. The studies addressed traffic and traveler-related aspects, as well as economic, equity, and public relations issues. The Traffic Study constituted the core of the evaluation effort. One of the project's main objectives was better utilization of the express lanes to carry more traffic during peak commuting periods. This study examines the possibility that dynamic, traffic-sensitive value pricing, represented by the FasTrak phase of the project, is uniquely suited to improve both utilization and volume distribution during peak periods while effectively controlling level of service on the facility. Measures of utilization and volume distribution were defined and studied in spring and fall waves of the study. The study confirms statistically significant improvements in both peak-period utilization and volume distribution across the study waves. The results strongly suggest that the FasTrak program's dynamic fee structure was able to create desirable redistribution of a portion of express lane traffic from the middle of the peak to the shoulders. The fixed-fee structure of ExpressPass, the preceding program, was not able to create such redistribution. Despite the steady increase of express lane volume during the entire 3-year demonstration, the comfortable level of service C required by law was maintained at virtually all times.

Commuters’ Departure Time Decisions in Brussels, Belgium

1997 ◽  
Vol 1607 (1) ◽  
pp. 139-146 ◽  
Author(s):  
André De Palma ◽  
Asad J. Khattak ◽  
Deepak Gupta
Keyword(s):  
Travel Time ◽  
Urban Areas ◽  
Ordinary Least Squares ◽  
Similar Amount ◽  
Travel Times ◽  
Trade Off ◽  
Schedule Delay ◽  
Trade Offs ◽  
Departure Time ◽  
Time Changes

Factors that influence commuters’ departure time decisions are explored, especially the trade-off between travel time and schedule delay. Stated and reported behavior data obtained from a survey of commuters in Brussels, Belgium, were used to analyze the influence of socioeconomic and contextual variables. The key findings were as follows. Daily schedules for flextime and fixed-time commuters were quite similar, suggesting that flextime commuters do not extensively use their flexibility to avoid peak-period congestion. When commuters changed their departure times between home and work, their arrival times shifted by a similar amount. This implies that the shortening of travel time is not as critical as other reasons, such as requirements and personal convenience, in motivating departure time changes. Furthermore, 35 to 50 percent of the respondents were unwilling to change their departure times to save 10 min of travel time. Therefore, departure time changes may not be feasible in many cases for the range of travel times encountered in urban areas. Among those willing to make further trade-offs by changing departure times, the values for the early and late schedule delay–travel time trade-off were similar for both the stated and the reported preferences and were broadly consistent with those from other studies. The travel time–schedule delay trade-off values are calculated for the a.m. and p.m. commutes. Commuters who experienced longer travel times were more likely to change their departure times. When changing departure times, females and managers were less likely to depart from home later than usual, and managers were also more likely to depart earlier than usual. To analyze relationships empirically, ordinary-least-squares and tobit models of departure time are estimated. Finally, the implications are discussed.

Forecasting Multiple-Period Freeway Link Travel Times Using Modular Neural Networks

1998 ◽  
Vol 1617 (1) ◽  
pp. 163-170 ◽  
Author(s):  
Dongjoo Park ◽  
Laurence R. Rilett
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Transportation Systems ◽  
Time Profile ◽  
Identification System ◽  
Route Guidance ◽  
Travel Times ◽  
Test Bed ◽  
Link Travel Time ◽  
Time Information

With the advent of route guidance systems (RGS), the prediction of short-term link travel times has become increasingly important. For RGS to be successful, the calculated routes should be based on not only historical and real-time link travel time information but also anticipatory link travel time information. An examination is conducted on how realtime information gathered as part of intelligent transportation systems can be used to predict link travel times for one through five time periods (of 5 minutes’ duration). The methodology developed consists of two steps. First, the historical link travel times are classified based on an unsupervised clustering technique. Second, an individual or modular artificial neural network (ANN) is calibrated for each class, and each modular ANN is then used to predict link travel times. Actual link travel times from Houston, Texas, collected as part of the automatic vehicle identification system of the Houston Transtar system were used as a test bed. It was found that the modular ANN outperformed a conventional singular ANN. The results of the best modular ANN were compared with existing link travel time techniques, including a Kalman filtering model, an exponential smoothing model, a historical profile, and a real-time profile, and it was found that the modular ANN gave the best overall results.

Reducing Probabilistic Weather Forecasts to the Worst Case Scenario: Anchoring Effects

2008 ◽  
Author(s):  
Sonia Savelli ◽  
Susan Joslyn ◽  
Limor Nadav-Greenberg ◽  
Queena Chen
Keyword(s):  
Case Scenario ◽  
Worst Case ◽  
Weather Forecasts ◽  
Worst Case Scenario ◽  
Anchoring Effects

EXPEDITION TO MALI, 2020

2020 ◽  
pp. 12-28
Author(s):  
D. V. Vaniukova ◽  
◽  
P. A. Kutsenkov ◽  
Keyword(s):  
Mass Murder ◽  
The State ◽  
Case Scenario ◽  
Worst Case ◽  
Traditional Art ◽  
Peter The Great ◽  
State Museum ◽  
Bobo Dioulasso ◽  
Oriental Studies ◽  
The Village

The research expedition of the Institute of Oriental studies of the Russian Academy of Sciences has been working in Mali since 2015. Since 2017, it has been attended by employees of the State Museum of the East. The task of the expedition is to study the transformation of traditional Dogon culture in the context of globalization, as well as to collect ethnographic information (life, customs, features of the traditional social and political structure); to collect oral historical legends; to study the history, existence, and transformation of artistic tradition in the villages of the Dogon Country in modern conditions; collecting items of Ethnography and art to add to the collection of the African collection of the. Peter the Great Museum (Kunstkamera, Saint Petersburg) and the State Museum of Oriental Arts (Moscow). The plan of the expedition in January 2020 included additional items, namely, the study of the functioning of the antique market in Mali (the “path” of things from villages to cities, which is important for attributing works of traditional art). The geography of our research was significantly expanded to the regions of Sikasso and Koulikoro in Mali, as well as to the city of Bobo-Dioulasso and its surroundings in Burkina Faso, which is related to the study of migrations to the Bandiagara Highlands. In addition, the plan of the expedition included organization of a photo exhibition in the Museum of the village of Endé and some educational projects. Unfortunately, after the mass murder in March 2019 in the village of Ogossogou-Pel, where more than one hundred and seventy people were killed, events in the Dogon Country began to develop in the worst-case scenario: The incessant provocations after that revived the old feud between the Pel (Fulbe) pastoralists and the Dogon farmers. So far, this hostility and mutual distrust has not yet developed into a full-scale ethnic conflict, but, unfortunately, such a development now seems quite likely.

Risk-Based Robust Bidding Strategies for EVs’ Aggregators in Day-ahead Markets with Uncertainty

2020 ◽  
Author(s):  
Ahmed Abdelmoaty ◽  
Wessam Mesbah ◽  
Mohammad A. M. Abdel-Aal ◽  
Ali T. Alawami
Keyword(s):  
Robust Optimization ◽  
Electricity Market ◽  
Real Life ◽  
Optimization Approach ◽  
Case Scenario ◽  
Worst Case ◽  
Bidding Strategies ◽  
Wind Generators ◽  
Proposed Model ◽  
Optimal Bidding

In the recent electricity market framework, the profit of the generation companies depends on the decision of the operator on the schedule of its units, the energy price, and the optimal bidding strategies. Due to the expanded integration of uncertain renewable generators which is highly intermittent such as wind plants, the coordination with other facilities to mitigate the risks of imbalances is mandatory. Accordingly, coordination of wind generators with the evolutionary Electric Vehicles (EVs) is expected to boost the performance of the grid. In this paper, we propose a robust optimization approach for the coordination between the wind-thermal generators and the EVs in a virtual<br>power plant (VPP) environment. The objective of maximizing the profit of the VPP Operator (VPPO) is studied. The optimal bidding strategy of the VPPO in the day-ahead market under uncertainties of wind power, energy<br>prices, imbalance prices, and demand is obtained for the worst case scenario. A case study is conducted to assess the e?effectiveness of the proposed model in terms of the VPPO's profit. A comparison between the proposed model and the scenario-based optimization was introduced. Our results confirmed that, although the conservative behavior of the worst-case robust optimization model, it helps the decision maker from the fluctuations of the uncertain parameters involved in the production and bidding processes. In addition, robust optimization is a more tractable problem and does not suffer from<br>the high computation burden associated with scenario-based stochastic programming. This makes it more practical for real-life scenarios.<br>

Sign in / Sign up

Export Citation Format

Share Document