The modal shift to and from public transit has shown an intriguing degree of variation within and across cities, meriting further exploration in this paper. The authors found, through mapping the modal shifts reported by members, that shifts away from public transit are most prominent in core urban environments with high population density. Shifts toward public transit in response to bikesharing appear most prevalent in lower density regions on the urban periphery.
Tomorrow is the last day of the semester - well done, students! You made it to the end! It's also the last Friday Seminar for the school year. Wrapping things up in style, Berkeley Ph.D. candidate Lu Hao will present her research, "Quantifying the Impact of Flight Predictability on Strategic and Operational Airline Decisions."
The idea of predictability or (inversely) variability is not new in the field of ground transportation, where (un)predictability mainly refers to the unpredictable variations in travel time and is thus directly related to uncertainty of travel time. In the realm of commercial air transportation, there is limited knowledge of how to quantify predictability and assess the potential benefit of improved predictability. Moreover, different aspects in airline decision making require different considerations when trying to measure and assess flight predictability.
In this work, the concept and metric for flight predictability is developed for both strategic and operational airline decision making. For both aspects, the appropriate measure for predictability is defined and the behavioral relationship between predictability and decision making is revealed. The potential benefits from improved predictability are then assessed for the two aspects, using airport departure queue assignment optimization and benefit pool analysis. The saving from improved predictability is significant for both cases, if the right metric is used. Comparing the two aspects, the difference in measuring flight predictability is rooted in the different perspectives of airlines’ consideration.
The Seminar takes place in 212 O'Brien (note the different location!) from 4-5 PM on May 16, 2014. There will be no cookie hour.
It's almost the end of the semester, but we still have two more Friday Seminars! This week is the penultimate seminar featuring Ph.D. candidate Joshua Seeherman. He'll be presenting his research, "The Impact of Adverse Weather on Freeway Bottleneck Performance."
Daily commutes in and out of major cities by automobile will likely encounter multiple locations of delay known as bottlenecks where demand exceeds capacity. It has been long perceived that the performance of these bottlenecks decrease when they are affected by adverse weather such as rain, snow, or fog. This project utilizes existing methodology to measure the discharge rate for four freeway bottlenecks in Orange County, California during both clear and adverse conditions. After confirming that the results agree with past literature, a new model will be proposed attributing different periods of bottleneck congestion during either wet, windy, or foggy conditions to specific weather characteristics. Generic results that can be applied to multiple sites will be shown which will validate the new proposal and hopefully provide guidance for other locations where wet weather is a significant source of delay.
The seminar will take place today, Friday May 9, 2014 from 4:00-5:00 PM in 212 O'Brien. (Note the room change!) Cookie Hour is on this week as well, at 3:30 in the library.
The Spring semester may be winding up, but we still have Friday Seminars! This week features UC Berkeley Ph.D. candidate Yi Liu presenting, "Incorporating Predictability into Cost Optimization for Ground Delay Programs."
When there is foreseen congestion at an airport, Ground Delay Programs (GDPs) are often implemented to balance arrival demand with available arrival capacity by holding inbound flights at their departure airports. Through this, GDPs transfer expensive airborne delay in the terminal airspace of the arrival airport to cheaper and safer ground delay at the departure airports. In the implementation of GDPs, emphasis has mainly been put on maximizing throughput while predictability is overlooked. As a result, planned and unplanned delays are assigned the same cost coefficient in the GDP cost optimization problem. This ignores the fact that unplanned delays require extra effort from both the flight operator side and the traffic manager side and cause more pain for the passengers, which should correspond to higher costs.
This work introduces the goal of predictability into GDP cost optimization under capacity uncertainty. This is accomplished by assigning extra premiums to unplanned delays and planned but un-incurred delay, due to their unpredictability. To estimate delay components in the cost functions, two stochastic GDP models are developed using continuous approximation and deterministic queueing theory: a static no-revision model and a dynamic model considering one GDP revision. The results from the case study show that unpredictability can have a strong impact on GDP decisions. Depending on the value of predictability, the proposed method may reduce system-wide cost by 10%.
The seminar takes place this Friday, May 2, 2014 in 534 Davis from 4-5 PM. Cookie Hour will commence at 3:30 in the library. See you there!
This week's Friday Seminar features UC Berkeley Ph.D. candidate Juan Argote presenting his research on control methods for transit services in, "Improving Bus Service with a Scalable Dynamic Holding Control":
Service unreliability is widely recognized as one of the main deterrents for travelers to use buses as their mode of transportation. Bus systems are exposed to an adverse feedback loop that generates a tendency for them to fall out of sync. This tendency can be counteracted by the application of control strategies that regulate the motion of the buses. This is well known among transit operators and some research has been devoted to address the issue. However, existing methods that are simple enough to be scalable can only handle headway-based operations of a single line.
This research proposes a scalable control method that applies dynamic holding based on real-time conditions and that allows buses to stay on schedule. A formulation that generalizes dynamic holding control strategies is developed for isolated bus lines. Stability conditions are derived and a quasi-optimal control that requires minimal data is also presented. The performance of this control is validated through simulation. The control is then extended to corridors where multiple bus lines overlap. A real-world case study in San Sebastián, where a system of coordinated on-board devices was deployed, is used to validate the control performance in this type of scenario. Finally, the resilience of the control is assessed considering multiple potential adversities.
The seminar takes place on Friday, April 25 in 534 Davis from 4-5 PM. Cookie Hour will be in the library at 3:30.
This research confirms that the success of deploying an EV charging stations infrastructure will be highly dependent on the price the user will have to pay, on the cost of the infrastructure deployed and on the adhesion of the EV users to this kind of infrastructure. These variables are not independent and, consequently, the coordination of public policies and private interest must be promoted in order to reach an optimal solution that does not result in prohibitive costs for the users.