The Institute of Transportation Studies at UC Berkeley has supported transportation research at the University of California since 1948. About 50 faculty members, 50 staff researchers and more than 100 graduate students take part in this multidisciplinary program, which receives roughly $40 million in research funding on average each year. Alexandre Bayen, Professor of Civil and Environmental Engineering and Professor of Electrical Engineering and Computer Science, is its director.
These problem sets comprise a supplement to Fundamentals of Transportation and Traffic Operations (C. Daganzo, Pergamon, 1997). Academicians can also obtain a companion set of solutions by writing to "Institute of Transportation Studies, Publications Office, 109 McLaughlin Hall, University of California, Berkeley, CA 94720" or by sending e-mail to email@example.com.
Public Transportation Systems:Basic Principles of System Design,Operations Planning and Real-TimeControl
This document is based on a set of lecture notes prepared in 2007-2010 for a University of California, Berkeley graduate course, Public Transportation Systems, a course targeted to first year graduate students with diverse academic backgrounds. Systems are examined in order of increased complexity so that generic insights evident in simple systems can be put to use as knowledge building blocks for the study of more complex systems. The document is organized in eight modules: five on planning (general, shuttle systems, corridors, two dimensional systems, and unconventional transit); two on management (vehicles and employees); and one on operations (how to stay on schedule).
Optimal Infrastructure System Maintenance and Repair Policies with Random Deterioration Model Parameters
Accurate facility deterioration models are important inputs for the selection of Infrastructure Maintenance, Repair, and Reconstruction (MR & R) policies. Deterioration models are developed based on expert judgment or empirical observations. These resources, however, might not be sufficient to accurately represent the performance of infrastructure facilities. Incorrect deterioration models may lead to wrong predictions of infrastructure performance and selection of inappropriate MR & R policies. This results in higher lifecycle costs. Existing infrastructure MR & R decisionmaking models assume that deterioration models represent the real deterioration process of infrastructure facilities. This assumption ignores the uncertainty in empiricallyderived facility deterioration models. This dissertation presents a methodology for selecting MR & R policies for systems of infrastructure facilities under uncertainty in the deterioration model parameters. It is assumed that inspections reveal the true conditions of facilities. Based on the inspection results, the deterioration model parameters can be updated to express the deterioration process more accurately. It is expected that more appropriate maintenance policies will be selected as a result. In the first part of this dissertation, it is assumed that facility inspections are performed at the beginning of every year. The model parameters are updated and MR & R policies are selected every year using the updated deterioration models. In the second part, the assumption is relaxed and alternate inspection frequencies are considered. In this case, the updates of the model parameters and the selection of optimal MR & R policies are executed only after an inspection. The results of the parametric analyses demonstrate that updating the deterioration models reduces the expected system costs. The results also show that relaxing the facility inspection frequency can reduce the total costs further.
This dissertation presents dynamic stochastic optimization models for Air Traffic Flow Management (ATFM) that enables decisions to adapt to new information on evolving capacities of National Airspace System (NAS) resources. Uncertainty is represented by a set of capacity scenarios, each depicting a particular time-varying capacity profile of NAS resources. We use the concept of a scenario tree in which multiple scenarios are possible initially. Scenarios are eliminated as possibilities in a succession of branching points, until the specific scenario that will be realized on a particular day is known. Thus the scenario tree branching provides updated information on evolving scenarios, and allows ATFM decisions to be re-addressed and revised. First, we propose a dynamic stochastic model for a single airport ground holding problem (SAGHP) that can be used for planning Ground Delay Programs (GDPs) when there is uncertainty about future airport arrival capacities. Ground delays of non-departed flights can be revised based on updated information from scenario tree branching. The problem is formulated so that a wide range of objective functions, including non-linear delay cost functions and functions that reflect equity concerns can be optimized. Furthermore, the model improves on existing practice by ensuring efficient use of available capacity without necessarily exempting long-haul flights. Following this, we present a methodology and optimization models that can be used for decentralized decision making by individual airlines in the GDP planning process, using the solutions from the stochastic dynamic SAGHP. Airlines are allowed to perform cancellations, and re-allocate slots to remaining flights by substitutions. We also present an optimization model that can be used by the FAA, after the airlines perform cancellation and substitutions, to re-utilize vacant arrival slots that are created due to cancellations. Finally, we present three stochastic integer programming models for managing inbound air traffic flow of an airport, when there is adverse weather impacting the arrival capacity of the airport along with its arrival fixes. These are the first models, for optimizing ATFM decisions, which address uncertainty of future capacities of multiple NAS resources.
This research describes field studies of how on-ramp metering can increase the capacity of freeway merges. Some effects of on-ramp metering have been known for a long time. We have known that on-ramp metering can 1) increase freeway flow and speed upstream of a merge; and 2) reduce system-wide delay by alleviating gridlock-causing queues that have blocked off-ramps. However, past studies have not conclusively shown that on-ramp metering can increase the maximum outflow (capacity) of freeway merges. The experiments conducted in the present study verify that on-ramp metering can increase freeway merge capacities. Detailed traffic data collected from videos for more than 30 rush periods at two merge bottlenecks unveil six major research findings: 1) merge capacity diminishes after merges became active bottlenecks; 2) the mechanism of "capacity drop" has been identified and was found to be reproducible across all days and it both sites. By metering the on-ramp in certain strategic ways, the capacity drop mechanism can be 3) reversed; and 4) even averted; 5) such metering strategies can be fully automated using loop detector measurements; and 6) control strategies other than ramp metering also hold promise for increasing merge capacities. These findings provide much-needed information concerning how to control freeway traffic. They also offer basis for more realistic theories of merging traffic flow.
Transportation Periodicals And Newsletters Currently Received At The Institute Of Transportation Studies Library, University Of California At Berkeley
This publication is intended to serve as a convenient reference to selected transportation periodicals and newsletters currently (2000) received by UC Berkeley's Harmer E. Davis Transportation Li-brary. This latest version of Transportation Periodicals and Newsletters represents a thourough revision of earlier editions (1989, 1993, and 1995) published under the same (or similar) title. The subject content of this listing reflects the subject strengths of the H.E. Davis Transportation Library: highways and traffic, air transportation, railroads, and urban transit. Water and pipeline modes are represented to a lesser extent. Collection emphasis at the Transportation Library is placed on planning, design, construction, and operations and most titles fall within this context. However, some titles in transportation business and economics do appear. While primary emphasis is placed on English language publications published in the United Sates, significant transportation journals from abroad are also included in the pages which follow.
This bibliography is intended to serve as a guide to the major sources ofinformation in Intelligent Transportation Systems (ITS). While the focus is on the United States, some international materials have been included. Emphasis is on current materials, although publications of historical interest have also been included. Resources listed include print and electronic materials, as well as websites on the Internet. This bibliography is based primarily on the holdings of the Harmer E. DavisTransportation Library at the Institute of Transportation Studies, University of California at Berkeley. References for electronic documents and resources, and websites, are current as of November 2006.The electronic version of this bibliography is a component of the 6th edition of Sources of Information in Transportation, a collaborative effort by members of theTransportation Division of the Special Libraries Association.
This bibliography, containing over 650 entries, is intended to serve as a guide to the major sources of information on highways. While sources listed focus primarily on the United States and Canada, some international materials have been included. Though emphasis is on current publications, some materials of historical interest have also been included. Resources listed in the bibliography include both print and electronic materials, with many Internet sites falling within that latter category. The bibliography was a collaborative effort and was compiled by twelve members of the Transportation Division of the Special Libraries Association. The resultant bibliography is part of a larger Transportation Division project, a revised edition of the Division's multi-volume work, Sources of Information in Transportation. The full, multi-volume new edition (its 5th ) will be available in electronic format on the Internet, with a publication date of late 2001 anticipated. Information concerning the new edition of Sources of Information in Transportation may be found at the Division's website: http://www.library.nwu.edu/transportation/slatran/
Estimating the producer surplus – the revenue above the average long-run cost – is an important part of social cost-benefit analyses of changes in petroleum use. This paper estimates the producer surplus associated with changes in gasoline fuel use in the United States, and then applies the estimates of producer surplus to two kinds of social cost-benefit analyses related to petroleum use: (1) estimating the wealth transfer from consumers to producers as a result of policies that affect oil use and oil imports to the US, and (2) comparing the actual average cost of gasoline with the average cost of environmentally superior alternatives to gasoline, such as hydrogen. Our results show that a 50% reduction in gasoline use in the US in 2004 would have saved the US $72 billion in producer surplus payments to foreign oil producers. Applying our estimates to the comparison of the social lifetime cost of hydrogen vehicles versus gasoline vehicles, we find that inconsistently counting producer surplus from a US national perspective while counting climate change damages from a global perspective can overstate the present value lifetime costs of gasoline vehicles by $2,200 to $9,800 per vehicle.
This paper presents a simple approximate procedure for traffic analysis that can be described geometrically without calculus. The procedure, which is graphically intuitive, operates directly on piecewise linear approximations of the N-curves of cumulative vehicle count. Because the N-curves are both readily observable and of direct interest for evaluation purposes (e.g., they yield the total vehicle-hours and vehicle-miles of travel in a time interval, and the vehicular accumulation as a function of time) the predictions made with this method should be practical and easy to test.
Inflation and increased fuel economy have reduced the buying power of the revenues collected from state and federal motor fuel taxes. Because fuel taxes are almost always collected on a per-gallon basis, in most states they must be raised by specific acts of the legislature and it is becoming increasingly difficult to find the political support necessary to raise them. A number of states have experimented with fuel taxes that adjust automatically by being indexed to the price of gasoline, to the consumer price index, or to some indicator of highway construction and maintenance costs. This paper reviews experience with indexed motor fuel taxes in the United States, and finds that in many cases indexed taxes have failed to produce the anticipated results because declines in fuel prices often cause declines in indexed fuel taxes. Indexing gas tax rates to the Consumer Price Index appears to be the best way of insuring that fuel tax revenues keep pace with inflation. Fuel taxes are the mainstay of transportation finance in the United States. The federal government and every state levy taxes on gasoline and diesel fuel. Motor fuel taxes have much to recommend them fiscally, politically, and administratively. First and foremost, as a "user fee" this tax is widely regarded to be inherently fair. It can be assumed that we benefit from the transportation system in proportion to the extent to which we use it, and motor fuel taxes charge us roughly in proportion to our use of the road and highway system. Furthermore, the tax is paid by motorists in small increments and is relatively hidden in the sales price of motor fuel. This has tended to minimize organized public opposition to it. The tax is also easy to administer and collect from both the taxpayer's and the government's point of view. The motor fuel tax is usually collected from fuel distributors rather than from retailers or consumers. This minimizes opportunities for evasion and reduces the cost of collection to an historical average of one-half of one percent of tax proceeds. By contrast, prior to the advent of electronic toll collection, highway tolls could often involve collection and administrative costs that amounted to as much as twenty percent of the proceeds. As motor fuel consumption has soared over the past eight decades, so have tax proceeds, enabling users of the nation's highway system to finance its construction and maintenance.
UC Berkeley Develops New User-Friendly Tool to Expedite the Evaluation of Connected Automated Vehicle Technologies
Connected Automated Vehicles (CAVs) are similar to other automated vehicles with the distinguishing difference being that CAVs obtain information about road conditionsdirectly from other vehicles and infrastructure (e.g., traffic signals, road sensors) rather than relying solely on onboard sensors. Different CAV technologies are currently being tested and evaluated to assess the prospects for future implementation. These tests involve moving CAV-equipped vehicles on a physical test track and recording how the vehicles operate under different traffic conditions (Figure 1). Since it is difficult and expensive to recreate multiple real-world driving conditions on a single test track, virtual environments are typically used to simulate different traffic conditions, such as traffic signal operation, actions by other vehicles on the road, and other scenarios. These virtual hardware-in-the-loop (HIL) tests can expedite CAV performance evaluation and inform future system implementation; however, existing HIL test systems often lack the ability to manage large amounts of test data, which limits the value and use of these tests.
2001: An Airspace Odyssey SUMMARY PROCEEDINGS OF THE 2001 AIRPORT NOISE SYMPOSIUM AND AIRPORT AIR QUALITY SYMPOSIUM
These proceedings summarize the presentations made at the 16th Airport Noise Symposium and 2nd Airport Air Quality Symposium, organized by the Technology Transfer Program of the Institute of Transportation Studies (ITS) and held in San Diego, California, from February 25 to March 2, 2001. The presentation slides for many of the presentations at both symposia are available on the ITS Technology Transfer Program website at .
The symposia were organized in conjunction with the National Center of Excellence for Aviation Operations Research, the Federal Aviation Administration, the Federal Interagency Committee on Aviation Noise, and the Port of San Diego, and with the active support and assistance of the individuals and organizations represented on the Symposia Program Committee, listed at the end of these proceedings.
This paper proves that kinematic wave (KW) problems with concave (or convex) equations of state can be formulated as calculus of variations problems. Every well-posed problem of this type, no matter how complicated, is reduced to the determination of a shortest tree in a relevant region of spacetime where cost is predefined. A duality between KW theory and /least cost networks is thus unveiled. In the new formulation space-time curves that constrain flow, such as sets of moving bottlenecks, become space-time shortcuts. These shortcuts become part of the network and affect the nature of the solution but not the speed with which it can be obtained. Complex boundary conditions are naturally handled in the new formulation as constraints/shortcuts of this type.
This paper shows how to reduce the bullwhip effect by introducing advance demand information (ADI) into the ordering schemes of supply chains. It quantifies the potential costs and benefits of ADI, and demonstrates that they are not evenly distributed across the chain. Therefore, market-based strategies to re-distribute wealth without penalizing any supplier are presented. The paper shows that if a centralized operation can eliminate the bullwhip effect and reduce total cost, then some of this reduction can also be achieved with decentralized negotiation schemes. Their performance is evaluated under different modes of probabilistic supplier behavior. For some forms of behavior the optimum is reached. But if suppliers are greedy and impatient the expected gain in wealth is relatively small. This is a case of economic "market failure."
We consider a Generalized, Multiple Depot Hamiltonian Path Problem (GMDHPP) and show that it has an algorithm with an approximation ratio of 3/2 if the costs are symmetric and satisfy the triangle inequality. This improves on the 2-approximation algorithm already available for the same.
Trust and Compassion in Willingness to Share Mobility and Sheltering Resources in Evacuations: A case Study of the 2017 and 2018 California Wildfires
Advances in the sharing economy – such as transportation network companies (e.g., Lyft, Uber) and home sharing (e.g., Airbnb) – have coincided with the increasing need for evacuation resources. While peer-to-peer sharing under normal circumstances often suffers from trust barriers, disaster literature indicates that trust and compassion often increase following disasters, improving recovery efforts. We hypothesize that trust and compassion could trigger willingness to share transportation and sheltering resources during an evacuation.
To test this hypothesis, we distributed a survey to individuals impacted by the 2017 Southern California Wildfires (n=226) and the 2018 Carr Wildfire (n=284). We estimate binary logit choice models, finding that high trust in neighbors and strangers and high compassion levels significantly increase willingness to share across four sharing scenarios. Assuming a high trust/compassion population versus a low trust/compassion population results in a change of likelihood to share between 30% and 55%, depending on scenario. Variables related to departure timing and routing – which capture evacuation urgency – increase transportation sharing willingness. Volunteers in past disasters and members of community organizations are usually more likely to share, while families and previous evacuees are typically less likely. Significance of other demographic variables is highly dependent on the scenario. Spare seatbelts and bed capacity, while increasing willingness, are largely insignificant. These results suggest that future sharing economy strategies should cultivate trust and compassion before disasters via preparedness within neighborhoods, community-based organizations, and volunteer networks, during disasters through communication from officials, and after disasters using resilience-oriented and community-building information campaigns.
A Revealed Preference Methodology to Evaluate Regret Minimization with Challenging Choice Sets: A Wildfire Evacuation Case Study
Regret is often experienced for difficult, important, and accountable choices. Consequently, we hypothesize that random regret minimization (RRM) may better describe evacuation behavior than traditional random utility maximization (RUM). However, in many travel related contexts, such as evacuation departure timing, specifying choice sets can be challenging due to unknown attribute levels and near-endless alternatives, for example. This has implications especially for estimating RRM models, which calculates attribute-level regret via pairwise comparison of attributes across all alternatives in the set. While stated preference (SP) surveys solve such choice set problems, revealed preference (RP) surveys collect actual behavior and incorporate situational and personal constraints, which impact rare choice contexts (e.g., evacuations). Consequently, we designed an RP survey for RRM (and RUM) in an evacuation context, which we distributed from March to July 2018 to individuals impacted by the 2017 December Southern California Wildfires (n=226). While we hypothesized that RRM would outperform RUM for evacuation choices, this hypothesis was not supported by our data. We explain how this is partly the result of insufficient attribute-level variation across alternatives, which leads to difficulties in distinguishing non-linear regret from linear utility. We found weak regret aversion for some attributes, and we identified weak class-specific regret for route and mode choice through a mixed-decision rule latent class choice model, suggesting that RRM for evacuations may yet prove fruitful. We derive methodological implications beyond the present context toward other RP studies involving challenging choice sets and/or limited attribute variability.
Mobile Apps and Transportation: A Review of Smartphone Apps and A Study of User Response to Multimodal Traveler Information
In recent years, technological and social forces have pushed smartphone applications (apps) from the fringe to the mainstream. Understanding the role of transportation apps in urban mobility is important for policy development and transportation planners. This study evaluates the role and impact of multimodal aggregators from a variety of perspectives, including a literature review; a review of the most innovative, disruptive, and highest-rated transportation apps; interviews with experts in the industry, and a user survey of former multimodal aggregator RideScout users. Between February and April 2016, researchers conducted interviews with experts to gain a stronger understanding about challenges and benefits of data sharing between private companies and public agencies. Key findings from the expert interviews include the critical need to protect user privacy; the potential to use data sharing to address integrated corridor and congestion management as well as various pricing strategies during peak hours; along with the potential benefits for improving coordination between the public and private sectors. In March 2016, researchers surveyed 130 people who had downloaded the RideScout app to evaluate attitudes and perceptions toward mobile apps, travel behavior, and modal shift. The goal was to enhance understanding of how the multimodal apps were impacting the transportation behavior. The survey did found that respondents used multimodal apps in ways that yielded travel that was less energy intensive and more supportive of public transit. Looking to the future, smartphone applications and more specifically multimodal aggregators, may offer the potential for transportation planners and policymakers to enhance their understanding of multimodal travel behavior, share data, enhance collaboration, and identify opportunities for public-private partnerships.
Integrated management of travel corridors comprising of freeways and adjacent arterial streets can potentially improve the performance of the highway facilities. However, several research gaps exist in data collection and performance measurement, analysis tools and control strategies. In this project first we analyzed high resolution data consisting of time-stamped records of every event involving vehicles, together with the signal phase at real-world signalized intersections and developed procedures for estimating performance measures. Next, we assessed the performance of a new microscopic simulator for signalized arterials. The model predictions were in close agreement with the predictions from widely used models in practice. We also developed and applied control strategies for freeway-arterial coordinated control to avoid queue override and developed a methodology to provide estimates of the amount and impacts of freeway diverted traffic in case of no-recurrent (incident related) congestion.
Public transit investments are a large and growing share of all transportation investments in the state of California, and such critical investments should be evaluated partly on their economic benefits. Taking such benefits into account could alter investment, service, and service restructuring decisions taken by transit agencies in the state. The relationship of public transportation to economic productivity, and spatial patterns of industrial location, is understudied. This project investigated how changes in rail transit service in California metropolitan areas (Los Angeles, the San Francisco Bay Area, and San Diego) are associated with firm clustering by industry and with commercial property values. A mixed methods approach was used. One strand of the research involved first, describing location patterns by industry according to transit access, and second, quantitatively modeling the relationship between transit access and (a) employment densification by industry and (b) commercial property values, using instrumental variables techniques with dynamic panel modeling in order to better infer causal relationships. The second strand consisted of interviews and other qualitative research aimed at finding possible explanations for firm location and expansion, and firm productivity. The quantitative research found that rail development generally promotes employment agglomeration and increased land value, but the magnitude of such effects differs across regions. San Francisco County had the highest employment densification and land value associated with rail proximity, while the LA region also had a relatively strong relationship between rail access and both employment density and property value. Rail access in the southern part of the San Francisco Bay Area, where Silicon Valley is situated, had a small relationship with employment densification but a positive effect on land values. On the contrary, rail development in the San Diego region was positively associated with employment density, but negatively associated with land value appreciation. Our interviews were consistent with these quantitative findings, and suggested that the differences between regions are due to differences in historical land development and use patterns as well as urban land regulations. In the San Francisco Bay Area, developers and real estate brokers report that rail transit plays the greatest role in the City of San Francisco, with relatively weak importance in Silicon Valley due to higher parking provisions and employer-provided transportation amenities such as shuttles. In the Los Angeles metropolitan area, rail transit is most highly valued in the dense downtown Los Angeles area, and is perceived to be playing an increasingly important role across the region as in places where traffic congestion is high and increasing.
Related Research Centers & Groups
- UC Berkeley Center for Future Urban Transport: A Volvo Center of Excellence
- California Partners for Advanced Transportation Technology
- Safe Transportation Research & Education Center
- UC Berkeley Transportation Sustainability Research Center
- UC Davis Institute of Transportation Studies
- UC Irvine Institute of Transportation Studies
- UCLA Institute of Transportation Studies
- University of California Institute of Transportation Studies