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Drawing on the California Household Travel Survey, we demonstrate strong associations between choosing to drive and having free parking at work or home. We find that the median household vehicle in California spends 22 hours a day parked, and that households with parking included in the rent or purchase price of their homes are more likely to drive,and less likely to use transit. We further find that employees with free parking at work are more likely to drive for their commutes. We estimate regressions that analyze the decision to work from home. Largely for data reasons, these regressions are less conclusive.

Transportation pricing policies aim to manage vehicular demand for parking, dense urban areas, roadways, and highway lanes. Although pricing policies take various forms, most were designed in a world before the sharing economy and ride-sourcing companies. Hence, the efficacy of existing pricing policies in a world with shared mobility services requires further consideration. Moreover, future pricing policies designed to handle private vehicles and shared ride-sourcing vehicles must consider the behavior of both sets of travelers and vehicle fleets. This study develops a conceptual framework to support systems level analysis of pricing policies for a world with private and shared vehicle usage. It qualitatively analyzes the impact of shared vehicles on the effectiveness of various pricing policies, while also considering the role of vehicle-to-infrastructure technology. This conceptual framework will support future research that uses activity-based travel demand and dynamic network assignment models to evaluate congestion pricing policies in an era of shared mobility. Additionally, the study presents a detailed review of the literature related to transportation pricing together with a trend analysis on congestion pricing policies in Transportation Research Board annual meeting titles and abstracts.

Curb parking is notoriously difficult to find in certain parts of New York City (NYC). NYC Department of Transportation (DOT) is considering implementing demand-responsive pricing for its passenger metered spaces to manage parking demand. This is a pricing mechanism whereby the price of curb parking fluctuates spatially and temporally in accordance with expected or actual demand. This report assesses successful permanent citywide implementations of demand-responsive curb pricing in San Francisco and Seattle to determine the most effective strategies for NYC DOT: these include using meter transaction data and historical occupancy data to estimate current parking occupancy and exploring possibilities of vehicle-mounted license plate recognition technology. To help make demand-responsive pricing more efficient and politically acceptable, the city can implement additional policies such a two-tier system for disability placards to target placard abuse or parking benefit districts to direct meter revenue toward public services on metered blocks. A data-driven demand-responsive curb pricing program that follows a set model for rate adjustments, in conjunction with technology and legislation changes to increase support for the program and reduce parking violations, as described in this report, can effectively increase parking availability in New York City and guide other city transportation agencies in their efforts to do the same.

Parking supply is one of the most neglected elements of the built environment in travel behavior research, despite evidence linking parking with vehicle use. As transportation impacts of new development are increasingly measured by vehicle miles traveled (VMT), explicitly connecting parking characteristics with vehicle travel is necessary to better inform transportation and land use policy. In this paper, we begin to address this research gap and explore the relationship between constrained parking and household VMT. Utilizing the 2017 National Household Travel Survey (NHTS) California add-on sample, we estimate residential parking constraint for households in Los Angeles County. Then, we develop a two-level model framework. Level 1 (Cost) models estimate travel costs, represented by vehicle ownership as a function of parking constraints, the built environment, and demographics. Level 2 (Demand) models regress household-level total and homebased-work VMT on predicted vehicle ownership, controlling for temporal and environmental characteristics. To further explore the relationship between parking and VMT by place type, we applied Level 1 and Level 2 models to develop a suite of scenarios for typical households in Los Angeles County. Our findings support the hypothesis that the built environment (including parking) influences VMT through travel costs (vehicle ownership). Results from scenarios analysis reveal constrained on-site residential parking (

Accessory dwelling units (ADUs) are small, self-contained housing units that share the same lot as a primary dwelling, usually a single-family detached house. In places with major housing shortages ADUs can be an efficient and cost-effective way to increase supply. Over the last few years, the California Legislature has passed laws to reduce barriers to permitting ADUs, and some California cities have liberalized their regulations even further. However, loosening ADU regulations—particularly those related to parking—can spark neighborhood opposition to ADUs. Recent surveys indicate that both homeowners and local government staff remain concerned that ADUs will overwhelm neighborhood parking supplies.Whether these concerns are justified is unclear. A UC Davis-led research team surveyed 396 homeowners in Sacramento and collected lot size and other data to investigate whether the total effective parking supply of the average single-family detached home is sufficient to accommodate the vehicles associated with the residents of both a primary dwelling and a potential ADU. This policy brief summarizes the findings from that research and provides policy implications.View the NCST Project Webpage

The transportation sector is responsible for a significant part of the U.S.’s greenhouse emissions, with a considerable amount being generated by medium-and heavy-duty trucks. However, when it comes to the trucking industry, ‘green’ routing studies do not consider other critical practical factors, like working hours regulations and parking availability. Due to parking shortages, routes and schedules that do not account for parking availability may lead to last-minute changes that make them more polluting than expected. Similarly, working hours regulations influence the timing of required rest stops, which may force drivers to deviate from initially selected routes and schedules with negative consequences to fuel consumption and emissions.This study addresses a variant of the shortest path and truck driver scheduling problem under parking availability constraints which focuses on optimizing fuel consumption and emissions by controlling the truck's travel speed and accounting for time-dependent traffic conditions. As it is impossible to be absolutely certain about the future parking availability of any location during planning, the case of stochastic parking availability was also studied. When studying the trade-offs between prioritizing emissions reduction or trip duration, it was found that although focusing on emissions reduction can increase trip duration significantly, this impact is greatly reduced when considering scenarios with limited parking availability. The problem formulation was further extended to model drivers’ possible recourse actions when unable to find parking and the ensuing costs. This formulation was used to study how the solutions are affected by the level of information provided to drivers. It was found that ignoring uncertainty in parking availability results in inconsistent performance even when restricting parking to periods when probability of finding parking is high. Furthermore, results might not reflect the intent of the cost function used, e.g., minimizing illegal parking events and/or the priority assigned to emissions reduction. Giving drivers full information about the probability of finding parking at any time/location significantly improves performance and reduces illegal parking-related risks, but also substantially increase problem complexity and computation time. Using full information regarding parking availability but restricting the parking times to high availability time-windows can reduce complexity while maintaining consistent, although reduced, performance.View the NCST Project Webpage

AbstractWe analyze what ridehail drivers do when searching for paid fares. We use a dataset of 5.3 million trips in San Francisco and partition each search trip into cruising, repositioning, and parking segments. We find that repositioning accounts for nearly two-thirds (63%) of the time between trips, with cruising and parking accounting for 23% and 14% respectively (these figures exclude short trips). Our regression models suggest that drivers tend to make reasonable choices between repositioning and parking, heading to high-demand locations based on the time of day. However, we also find evidence of racial disparities, supporting previous studies of both taxis and ridehailing that indicate that drivers tend to avoid neighborhoods with high proportions of residents of color.

We analyze what ridehail drivers do when out of service between paid trips. We use a dataset of 5.3 million trips in San Francisco and partition each out of service trip into cruising, repositioning, and parking segments. We find that repositioning accounts for nearly two-thirds (63%) of the time between trips, with cruising and parking accounting for 23% and 14% respectively (these figures exclude short trips). Our regression models suggest that drivers tend to make reasonable choices between repositioning and parking, heading to high-demand locations based on the time of day. However, we also find suggestive evidence of racial bias, supporting previous studies of both taxis and ridehailing that indicate that drivers tend to avoid neighborhoods with high proportions of residents of color.

The Davis Amtrak station, a stop on the regional Capital Corridor line has the third highest passenger usage along the Capitol Corridor and up until early 2020, ridership was increasing. However, the station’s parking lot fills up before 6am on weekday mornings and this poses an access challenge to passengers. City of Davis Transportation staff have planned shared-use mobility programs as a cost-effective solution to make commuting by train easier, more productive, affordable, and travel-time competitive. This research brief summarizes findings from a University of California, Davis study, the objective of which was to inform and evaluate the City’s planned programs.

Credibly identifying how the built environment shapes behavior is empirically challenging, because people select residential locations based on differing constraints and preferences for site amenities. Our study overcomes these research barriers by leveraging San Francisco's affordable housing lotteries, which randomly allow specific households to move to specific residences. Using administrative data, we demonstrate that lottery-winning households' baseline preferences are uncorrelated with their allotted residential features such as public transportation accessibility, parking availability, and bicycle infrastructure---meaning that neighborhood attributes and a building's parking supply are effectively assigned at random. Surveying the households, we find that these attributes significantly affect transportation mode choices. Most notably, we show that essentially random variation in on-site parking availability greatly changes households' car ownership decisions and driving frequency, with substitution away from public transit. In contrast, we find that parking availability does not affect employment or job mobility. Overall, the evidence from our study robustly supports that local features of the built environment are important determinants of transportation behavior.

Culver City is anticipating a surge in economic growth in upcoming years, attributed to an influx of large employers. Its challenge will be in meeting growth objectives while managing increasing traffic congestion and emissions – a tall order on any given day, but especially so in light of the ongoing coronavirus pandemic. Culver City faces additional headwinds in counteracting potentially long-term, destructive changes to travel behavior, and operating under constrained city budgets during these times of austerity. This report focuses on three promising, cost-effective, and infrastructure-light strategies local officials can consider to advance their vision of a more walkable, bikeable, sustainable, and livable Culver City with improved circulation; they are: formation of a local transportation management association, transforming parking management, and consideration of various road pricing schemes. An analysis of local employment patterns, regulations, and traffic conditions informs our context-specific recommendations for their implementation in Culver City.

Expanding the network of bus lanes in Los Angeles can alleviate slow bus speeds, which are caused by the fact that most buses share a lane with general traffic. Many corridors in the city feature curb lanes that allow traffic during peak hours, but restrict access to allow parking in the off-peak. Introducing a bus lane on these corridors during peak periods, instead of a travel lane, offers an opportunity to improve bus service while preserving parking outside of peak hours. This report examines bus performance along 75 miles of peak-hour parking restriction (PHPR) corridors to determine whether bus lanes could improve travel times for riders and increase net person throughput. I developed a novel methodology to scrape the real-time position of LA Metro buses from a publicly accessible application programming interface (API) and convert collected coordinates into accurate representations of bus speeds on PHPR lanes. Using two months of data, I describe the speed of buses on PHPR lanes and calculate the potential travel time savings provided by bus lanes. With these findings in hand, I draw on historical traffic counts and the planned person capacity of LA Metro bus service to weigh the potential benefits of bus lanes. I find that bus speeds and travel times on PHPR lanes will likely universally benefit from bus lanes. However, only one-half of studied corridors will see an increase in net person throughput with the addition of a bus lane, typically on corridors with more frequent bus service.

The lack of appropriate and convenient truck parking locations has been identified as a major safety, cost, and environmental issue in both the United States and the European Union. Without access to appropriate parking locations, drivers might be forced to either drive while tired, increasing the risk of accidents, or park illegally in unsafe locations, posing a potential safety hazard to themselves and other drivers. The parking shortage also impacts shipment costs and the environment, since drivers burn more fuel while looking for places to park or idling their engines to provide cab power when parked in inappropriate locations.This research brief summarizes findings from the associated project, the objective of which was to generate parking assist algorithms that can help truck drivers better plan their trips. By providing information about parking availability, the researchers hope to induce truck drivers to better distribute themselves among existing rest areas. This would decrease the peak demand in the most popular truck stops and attenuate the problems caused by the parking shortage.View the NCST Project Webpage

The Bay Area Rapid Transit District (BART), the Metropolitan Transportation Commission (MTC), and Scoop Technologies, Inc. (Scoop) partnered on a program to better integrate carpool access to public transit by matching transit passengers into carpools with a transit station as their destination using the carpool matching app Scoop and providing a seamless way to reserve and pay for highly-coveted parking spaces at BART stations. This report discusses how the project was developed and implemented and the project outcomes and lessons learned.

In the urban landscape, parking structures have evolved to become lean, level- of-service driven objects that occupy valuable space. Recent urban trends have caused planners to rethink the definition of parking structures and their contribution to the functions of the city. In light of the new narrative on the urban parking structure, how can the City of Los Angeles better support efforts to construct parking garages in a manner that enables them to be repurposed for some use other than parking in the future?

This dissertation aims to study effective and efficient ways for both travelers and transportation authorities to consider the actions of the other side when they make their corresponding travel or management decisions, such that certain common goals, such as mitigating congestion, reducing cost in travel expenses and improving the overall reliability of the transportation system can be achieved.A novel dynamic traffic routing (DTR) with an adaptive signal control framework is developed to utilize the fast developing wireless communication technologies that makes V2X (Vehicle To Everything) possible. The hyper-path based dynamic traffic routing method takes stochasticity of link travel time into consideration, which ensures robust and reliable routing decisions. In addition, online travel time updating is incorporated into the DTR model. The online updating presented in this dissertation uses both historical information (a priori knowledge) and new information, thanks to the V2X system, to form a posteriori knowledge about the link travel time. Various distributed traffic signal control methods are proposed and tested concurrently with the DTR model to cope with the different levels of the traffic demand. Simulation models are built to test and compare the models developed in this dissertation against the traffic routing methods and traffic signal control models in the literature. In the extensive simulation tests, the author discovers that enabling vehicle re-routing in the network can reduce the average travel time as well as reduce the average queue length at the intersections.

This dissertation consists of three chapters that investigate policies aiming for improving private automobile transportation from different angles.The first chapter focuses on the efficiency of marked versus unmarked on-street parking. The study uses computer simulation that assigns queues of randomly generated vehicles to marked and unmarked spaces using a parallel world method, to directly test which method is more efficient and accommodate more cars. The simulation results show that unmarked spacing is more efficient only when the curb is shorter, or not close to any integer times of the optimal length of one marked space, and when drivers are all considerate when choosing the parking location. This simulation study also finds vehicle downsizing only helps the owners of the downsized vehicles themselves, while making it more difficult for all other people to find parking.The second chapter focuses on the engine size tax in China. Using regressions based on data of vehicle trims offered in China from 2004 to 2016, the study shows that the engine size tax drove automakers to downsize engines and cluster sizes around cutoff points related to the taxes. The tax affects fuel efficiency in opposite directions. On one hand, engine size tax encouraged engine downsizing in China and contribute to an improvement in fuel efficiency. On the other hand, using cutoff points to differentiate tax rates also encouraged automakers to use turbocharging technology to increase horsepower, which compromised improvements in fuel consumption.The third chapter focuses on the impacts of fuel price changes on vehicle consumption in US and China. This study conducted a comparative analysis of US and China automobile market using historical vehicle sales data linked with gasoline prices and vehicle attributes including fuel consumption rates. The results reveal a major difference in vehicle purchasing behavior between US and China. US consumers are strongly affected by fuel price and purchase vehicles with better fuel economy when gasoline prices are higher and vice versa, while Chinese consumers do not seem to be affected by gasoline price changes much. This difference implies different policies are needed to reduce fuel consumption in the two countries.

Truck parking has been identified as a major issue both in the USA and E.U. and has been selected by the American Transportation Research Institute as the most important research need for the trucking industry in 2015. The lack of appropriate and convenient parking locations has been the cause of several safety issues over the past years as drivers might be forced to either drive while tired and increase the risk of accidents or park illegally in unsafe locations, which might also pose a safety hazard to them and other drivers. Additionally, the parking shortage also impacts the shipment costs and the environment as the drivers might spend more fuel looking for parking or idling for power when parked in inappropriate locations.This project’s objective was to study the truck parking problem, generate useful information and parking assist algorithms that could assist truck drivers in better planning their trips. By providing information about parking availability to truck drivers, the researchers expect to induce them to better distribute themselves among existing rest areas. This would decrease the peak demand in the most popular truck stops and attenuate the problems caused by the parking shortage.In this project, several parking availability prediction algorithms were tested using data from a company’s private truck stops reservation system. The prediction MSE (mean squared error) and classification (full/available) sensitivity and specificity plots were evaluated for different experiments. It is shown that none of the tested algorithms is absolutely better than the others and has superior performance in all situations. The results presented show that a more efficient way would be to combine them and use the most appropriate one according to the situation. A model assignment according to current time of the day and target time for prediction is proposed based on the experiment data.View the NCST Project Webpage

The Metro Crenshaw/LAX rail-transit line is currently under construction and planned for completion in 2019. The rail-transit line will connect the Metro Expo Line to the Los Angeles Airport. Installation of the project will require road surface space at some segments and as a result, it will run at-grade in the Park Mesa Heights Neighborhood of South Los Angeles. Construction on the commercial Crenshaw Boulevard from 48th Street to Slauson Boulevard requires the removal of over 300 parking spaces. Business owners along the corridor fear that the loss of parking will create barriers for employees and customers to access their establishments. This report examines shared parking as a parking management treatment that can increase the supply of parking without building more of it. The report assesses the technical and political feasibility of a shared parking program.

Community members of the Silver Lake Neighborhood in Los Angeles have recently been complaining about a parking issue in the area. They claim that parking is scarce, especially in residential areas, and have asked the Silver Lake Neighborhood Council to resolve the issue, perhaps with a public parking structure. Additionally, the neighborhood has a reputation of having a parking issue, and visitors perceive this scarcity as a problematic as well. Numerous parties have been blamed, such as businesses not providing enough parking, or even residents. The client believes that residents are using the infrastructure inefficiently (I.E. using supplied parking with their units as storage or converting the space into an extra room) and causing a spillover of parking onto the streets. As a result, the Silver Lake Neighborhood Council has initiated this study, conducted by a UCLA graduate student in the Masters in Urban and Regional Program, to determine the extent of these claims and recommend solutions.

This paper investigates the economics of curbside parking time limits. It argues that curbside parking time limits provide a way to subsidize short-term parking without generating cruising for parking. The paper develops the argument in the context of the integrated model of downtown parking and traffic congestion presented in Arnott and Rowse (2009), extended to incorporate heterogeneity in value of time and parking duration.

Carsharing provides users access to a shared vehicle fleet for short-term use throughout the day, reducing the need for private vehicles. The provision of on-street and public off-street parking dedicated to carsharing is an important policy area confronting public agencies. As of July 2009, approximately 377,600 individuals were carsharing members in North America in about 57 metropolitan areas. A total of 17 jurisdictions, one state (California), and eight public transit operators in North America have formal and informal carsharing parking policies, pilot projects, and proposed legislation. These are reviewed in this paper, along with a framework for carsharing parking policy that reflects three levels of governmental support. In addition, the authors examine carsharing parking policies in three jurisdictions in the San Francisco Bay Area, which accounts for an estimated 50,000 carsharing members and 1,100 shared-use vehicles. Supporting this examination is an intercept survey on carsharing parking (n=425) conducted in the Bay Area. Results show that most people supported the conversion of some type of spaces for carsharing use, and 48% thought that carsharing organizations should compensate the city for on-street spaces. At the same time, converting most types of spaces was opposed by at least 20% of respondents. Neighborhood residents were generally more in favor of parking conversion for carsharing than people visiting the area for work or errands. Finally, a majority (61%) felt that non-profits should have priority over for-profit organizations for carsharing spaces and should pay less than for-profit organizations.

This paper investigates the economics of curbside parking time limits. It argues that curbside parking time limits provide a way to subsidize short-term parking without generating cruising for parking. The paper develops the argument in the context of the integrated model of downtown parking and traffic congestion presented in Arnott and Rowse (2009), extended to incorporate heterogeneity in value of time and parking duration.

Free or underpriced curb parking creates a classic commons problem. Studies have found that between 8% and 74% of cars in congested traffic were cruising in search of curb parking, and that the average time to find a curb space ranged between 3 and 14 min. Cities can eliminate the economic incentive to cruise by charging market-clearing prices for curb parking spaces. Market-priced curb parking can yield between 5% and 8% of the total land rent in a city, and in some neighborhoods can yield more revenue than the property tax.