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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.

Background: Delegation of clinical tasks from physiotherapists to physiotherapy support workers is common yet varies considerably in musculoskeletal outpatient physiotherapy services, leading to variation in patient care. This study aimed to explore patients' preferences and estimate specific trade-offs patients are willing to make in treatment choices when treated in musculoskeletal outpatient physiotherapy services. Methods: A discrete choice experiment was conducted using an efficient design with 16 choice scenarios, divided into two blocks. Adult patients with musculoskeletal conditions recruited from a physiotherapy service completed a cross-sectional, online questionnaire. Choice data analyses were conducted using a multinomial logit model. The marginal rate of substitution for waiting time to first follow-up physiotherapy appointment and distance from the physiotherapy clinic was calculated and a probability model was built to estimate the probability of choosing between two distinct physiotherapy service options under different scenarios. Results: 382 patient questionnaires were completed; 302 participants were treated by physiotherapists and 80 by physiotherapists and support workers. There was a significant preference to be seen by a physiotherapist, have more follow-up treatments, to wait less time for the first follow-up appointment, to be seen one-to-one, to see the same clinician, to travel a shorter distance to get to the clinic and to go to clinics with ample parking. Participants treated by support workers did not have a significant preference to be seen by a physiotherapist and it was more likely that they would choose to be seen by a support worker for clinic scenarios where the characteristics of the physiotherapy service were as good or better. Conclusions: Findings highlight that patients treated by support workers are likely to choose to be treated by support workers again if the other service characteristics are as good or better compared to a service where treatment is provided only by physiotherapists. Findings have implications for the design of physiotherapy services to enhance patient experience when patients are treated by support workers. The findings will contribute to the development of "best practice" recommendations to guide physiotherapists in delegating clinical work to physiotherapy support workers for patients with musculoskeletal conditions. [ABSTRACT FROM AUTHOR]

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.

This study introduces a methodology to model parking cost and residential parking zones within the agent-based simulation framework MATSim. An overview of related research and a description of the implementation are given. The results suggest that parking pricing has a larger impact on the share of motorized transport than longer access and egress walks to the activity. Raising parking costs could prove to be an effective tool to reduce motorized transport. [ABSTRACT FROM AUTHOR]

This work addresses the challenges of implementing shared e-scooter services (SSS) in urban areas. Despite their potential for sustainable mobility, issues like road safety and street cluttering persist. Policy regulation is crucial, and recent efforts have focused on free-floating e-scooter parking legislation. To assist decision-making, this paper proposes an agent-based framework to design SSS parking supply and evaluate its impact. The methodology is applied in Lyon, France, where the SSS is gaining more and more territory. The main outcomes show parking regulation can introduce conflicting objectives, with a reduction of SSS use due to an increase in the access and egress walking distance. [ABSTRACT FROM AUTHOR]

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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.

Today’s urban design of new quarters in the fringes of German metropolises shows a renaissance of the garage building as a cluster for car parking. In contrast to the past, parking garages are planned as multifunctional “mobility hubs.” Planners enrich them with new mobility and sharing options and incorporate sports or social infrastructure facilities on the roof and the ground floor, thus contributing to vibrant neighborhoods. In contrast to the internationally renowned example of Nordhavn (Copenhagen), we observe a decentralization in the mainstreaming of the approach: Mobility hubs are to become constitutive parts of small subcenters. In this respect, they can be seen as a common leitmotiv for urban design in Germany’s metropolises. The hubs form a new model of local mobility, guaranteeing a certain flow of pedestrians and freeing the adjacent streets of car traffic. Integrated into a system of alternative modes of transportation and nearby mass transit, those infrastructural and mobility clusters might contribute to a change in mobility habits and ultimately reduce car dependence. If their underlying mobility policies can be implemented and if they are ultimately more successful than traditional parking garages or even create an incentive not to use private cars at all remains open to further investigation. For this purpose, the article will trace the emergence of mobility hubs in the discourse and practice of urban design with a particular focus on major new developments at the periphery of German cities. It analyzes urban design competitions and the formal planning and implementation following them.

Automated Vehicles (AVs) can drop off passengers at predetermined destinations and relocate to less expensive, remote parking facilities, which offers the potential to repurpose valuable urban land near activity centers for alternative uses beyond vehicle storage. While some researchers believe AVs are the core element to solving parking problems, relieving urban land use, and enabling low-emission travel, others contend that AVs could incentivize increased Vehicles Miles Traveled (VMT) and exacerbate congestion. To bridge these disparate perspectives, this study endeavors to elucidate the environmental ramifications of AVs on parking through a comprehensive literature review. Based on an initial sample of 299 retrieved papers, 52 studies were selected as the result of the selection criteria detailed in the paper. The selected papers were categorized into five gradual parts to answer the raised research questions. As a principal finding of this study, our research provides city planners, traffic operators, and scholars with full-picture insights and trustworthy guidance, emphasizing the pivotal role of AVs in deciphering the sustainable impact on the urban environment. [ABSTRACT FROM AUTHOR]

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 growth of motorized vehicle ownership has outpaced the limited availability of public land and parking spaces. Illegal parking lots and attendants in Yogyakarta worsen this problem. As an illegal parking area, illegal parking attendants do not have the legality to collect fees from the community, so collecting money from parking users is an act of illegal levies. As a result, the rights of parking users as consumers tend to be neglected without any protection from authorized institutions or officials. This phenomenon is increasingly widespread and has been going on for quite a long time, so the impression appears there is an element of omission by state officials. The research method utilized was a qualitative descriptive, interactive approach that involved collecting data through observation, documentation, and interview. The primary data were recruited through an interview, and some informants were determined with the purposive technique, which was informants or source determination based on a certain consideration. Based on the results, parking management has been managed in such a way on Regional Regulation of Yogyakarta Number 2 of 2019. Regarding parking, the Regional Regulation (Perda) is followed up with the Mayor’s Regulation of Yogyakarta number 2 of 2019. The objectives of the parking regulations are to embody safe and orderly parking service, implement law protection and certainty, and ensure transparency of Locally-Generated Revenue Receipt in the parking area.

The paper presents the results of experimental studies of drivers` behavior when interacting with obstacles caused by parked vehicles. Today, parking cars on two-lane streets is a significant problem for drivers while driving as it creates obstacles. Drivers need to spot a parked car in time and perform a lane change maneuver. It affects the trajectories of vehicles and the functional state of the driver. The driver needs a certain amount of time to maneuver, which consists of the reaction time, the decision to change the lane, and the execution of the action. It complicates traffic conditions for the driver and creates danger for driving. If the driver does not receive information about the parking location on the street with high-speed traffic in time, the probability of danger increases significantly. In addition, drivers try to change the traffic lane, which is further occupied by parking, in advance to reduce the impact of parking on the functional state of their bodies. There is also a deviation in the cross-section of the street when the speed of movement increases relative to the parked car, which finally indicates a change in the position in the traffic lane. It was established that drivers individually choose the trajectories of changing the traffic lane by the speed of movement. In addition, each driver subjectively decides to start changing the traffic lane at his discretion when an obstacle occurs at a certain distance. Angular velocity was used as an indicator of the probability of finding an obstacle object in a dangerous state. Angular speed is the main parameter in the orientation of the driver and signals the danger. When the angular velocity was 0.015-0.03 rad/c, drivers tried to complete the maneuver and leave a certain distance from the obstacle (safety gap). It indicates some interval of angular velocity in relation to the perception of an obstacle object in space and the sense of danger. The resulting patterns of changing lanes by drivers allow for determining the safe distance to parking and ensuring traffic safety by using appropriate markings and road signs.

In the field of cycle policy and planning, alongside ambitions to expand segregated cycle networks, there is a push across many countries for increasing the quality and quantity of cycle parking as a critical component of cycling infrastructure. In order to support these measures, planning guides have been developed to guide the expansion and improvement of cycle parking facilities. A common feature of these policies and guides for cycle parking interventions is an absence of dialogue with, or reference to, peer-reviewed research investigating cycle parking and the potential effectiveness of different approaches to cycle parking planning. The use of such research could help to create cycle parking that may be more effective in attracting and providing for people cycling. On this basis, we engage in a literature review of a select body of cycling research whose findings could contribute to more effective cycle parking planning practice. Drawing on our review, we propose a number of tentative ‘elements’ for effective public cycle parking planning practice: visibility, protection, accessibility, proximity, integration, and diversification. These elements could be used in conjunction with local knowledge and context-specific assessment measures to maximise the potential effectiveness of cycle parking planning in different regions, and can be situated as part of a wider struggle to acquire public space for cycling within car-dominant contexts.

Shared autonomous vehicles (SAVs) have great potential for achieving beneficial changes to the society. Although recent studies have explored the traffic safety, economic benefits and environmental impact, parking decisions of SAVs is rarely considered. SAVs need to park to avoid cruising during the interval between services. Appropriate parking decisions can contribute to reduce the vehicle kilometers traveled (VKT). This study synergistically considers routing and parking of SAVs for system optimization. Since the problem is NP-hard, we develop a variable neighborhood search (VNS) heuristic to solve it. The heuristic aims to minimize the VKT, the number of SAVs and the parking cost by systematic changes of neighborhood. A series of experiments based on the Anaheim network prove the high solving efficiency and quality of the heuristic. Results also indicate that the marginal cost of the system decreases with the increase in travel demand and the VKT increases with the increase in parking fees. [ABSTRACT FROM AUTHOR]

Today's urban design of new quarters in the fringes of German metropolises shows a renaissance of the garage building as a cluster for car parking. In contrast to the past, parking garages are planned as multifunctional "mobility hubs." Planners enrich them with new mobility and sharing options and incorporate sports or social infrastructure facilities on the roof and the ground floor, thus contributing to vibrant neighborhoods. In contrast to the internationally renowned example of Nordhavn (Copenhagen), we observe a decentralization in the mainstreaming of the approach: Mobility hubs are to become constitutive parts of small subcenters. In this respect, they can be seen as a common leitmotiv for urban design in Germany's metropolises. The hubs form a new model of local mobility, guaranteeing a certain flow of pedestrians and freeing the adjacent streets of car traffic. Integrated into a system of alternative modes of transportation and nearby mass transit, those infrastructural and mobility clusters might contribute to a change in mobility habits and ultimately reduce car dependence. If their underlying mobility policies can be implemented and if they are ultimately more successful than traditional parking garages or even create an incentive not to use private cars at all remains open to further investigation. For this purpose, the article will trace the emergence of mobility hubs in the discourse and practice of urban design with a particular focus on major new developments at the periphery of German cities. It analyzes urban design competitions and the formal planning and implementation following them. [ABSTRACT FROM AUTHOR]

Bicycle parking is a critical piece of cycling infrastructure and yet there is little known about who and how often these facilities are used. This study investigates the use patterns, occupancy, duration times, and rotation rates of on-street bike parking in Barcelona, Spain. We sampled all city districts with rectangular plots that included 163 bicycle parking sites. We visited them 4–15 times during two field work campaigns in spring and summer 2021. We measured total occupancy, bicycle type (bike-share, children, abandoned, private), and developed a method to estimate rotation rates, turnover and service levels. We estimate that Barcelona has approximately 18,730 bicycles parked on the street every day, of which 8% are dockless shared bikes, 5% are children bikes and 3% are abandoned bikes or bike parts. We find that 10% of bike parking sites were saturated (average occupancy 90%+) and 30% reached saturation in at least one measurement. Contrary to our hypothesis, we do not find strong diurnal temporal variations, as occupancy rates are remarkably stable over the day across the city. We estimate that 35% of bicycles parked on the streets are for long term parking (1 week+) or storage, while only 12% of bicycles are short-term day-users. To improve the management of on-street bicycle parking, cities must maintain an updated spatial data set of bike parking locations and understand the patterns of who and when they are used. [ABSTRACT FROM AUTHOR]

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.

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.

Sustainable mobility reduces the consumption of space and resources, facilitates access, promotes economic dynamism, and creates a sustainable environment. This paper investigated the possibility of switching to a sustainable mobility system through parking management in the Mzab Valley and the city of Ghardaia, one of Algeria's classified heritage sites. Using the quantitative descriptive approach and the road network analysis method, the current situation of parking lots shows a high diversity and characterization of parking lots. The most important factors affecting parking lots were also identified, such as population density, vehicle ownership, and the road network. The study shows medium connectivity of the road network and traffic problems with a road saturation coefficient of almost 60%, where access to parking lots increases from 5 minutes to 10 minutes when driving to the city centre. The city centre has a high concentration of parking lots (81%). Furthermore, parking frequency is 5% higher in the morning compared to the evening, with an overall capacity of 12,495 parked cars and a deficit of 10,500 parking spaces. Linking the study to the social and policy aspects, the results indicate that trips for non-compulsory reasons dominate over mandatory trips for workers, where 50% of the population owns a private car and 10% use public transport. Based on the SWOT method, strengths, weaknesses, opportunities, and threats to be adjusted were identified. This research defines short- and medium-term solutions as a global vision for improving sustainable mobility in the Mazabite context or a similar region.

On-street parking information (OSPI) systems help reduce congestion in the city by lessening parking search time. However, current systems use features mainly relying on costly manual observations to maintain a high quality. In this paper, on top of traditional location-based features based on spatial, temporal and capacity attributes, vehicle parked-in and parked-out events are employed to fill the quality assurance gap. The parking events (PEs) are used to develop dynamic features to make the system adaptive to changes that impact on-street parking availability. Additionally, a parking behavior change detection (PBCD) model is developed as an OSPI supplementary component to trigger potential parking map updates. The evaluation shows that the developed OSPI availability prediction model is on par with state-of-the-art models, despite having simpler but more enhanced and adaptive features. The foundational temporal and aggregated spatial parking capacity features help the most, while the PE-based features capture variances better and enable adaptivity to disruptions. The PE-based features are advantageous as data are automatically gathered daily. For the PBCD model, impacts by construction events can be detected as validation. The methodology proves that it is possible to create a reliable OSPI system with predominantly PE-based features and aggregated parking capacity features.

Autonomous grounded vehicle-based social assistance/service robot parking in an indoor environment is an exciting challenge in urban cities. There are few efficient methods for parking multi-robot/agent teams in an unknown indoor environment. The primary objective of autonomous multi-robot/agent teams is to establish synchronization between them and to stay in behavioral control when static and when in motion. In this regard, the proposed hardware-efficient algorithm addresses the parking of a trailer (follower) robot in indoor environments by a truck (leader) robot with a rendezvous approach. In the process of parking, initial rendezvous behavioral control between the truck and trailer robots is established. Next, the parking space in the environment is estimated by the truck robot, and the trailer robot parks under the supervision of the truck robot. The proposed behavioral control mechanisms were executed between heterogenous-type computational-based robots. Optimized sensors were used for traversing and the execution of the parking methods. The truck robot leads, and the trailer robot mimics the actions in the execution of path planning and parking. The truck robot was integrated with FPGA (Xilinx Zynq XC7Z020-CLG484-1), and the trailer was integrated with Arduino UNO computing devices; this heterogenous modeling is adequate in the execution of trailer parking by a truck. The hardware schemes were developed using Verilog HDL for the FPGA (truck)-based robot and Python for the Arduino (trailer)-based robot. [ABSTRACT FROM AUTHOR]

The paper deals with the possibilities of implementing dynamic tariff regulation of on-street parking spaces in the capital city of Prague. Achieving optimal results is conditioned by the implementation of advanced technologies, but at the same time, the dynamic tariff regulation must follow the applicable legislation and, above all, be accepted by drivers. For this reason, the paper briefly discusses the technical and legislative possibilities of implementation, and most attention is paid to the conducted survey of user needs. The survey investigates the impact of parking prices on drivers' motivation to park their vehicles in the area. [ABSTRACT FROM AUTHOR]

The paper deals with the possibilities of implementing dynamic tariff regulation of on-street parking spaces in the capital city of Prague. Achieving optimal results is conditioned by the implementation of advanced technologies, but at the same time, the dynamic tariff regulation must follow the applicable legislation and, above all, be accepted by drivers. For this reason, the paper briefly discusses the technical and legislative possibilities of implementation, and most attention is paid to the conducted survey of user needs. The survey investigates the impact of parking prices on drivers’ motivation to park their vehicles in the area.

The Totally Asymmetric Simple Exclusion Process (TASEP) is a paradigm of out-of-equilibrium Statistical Physics that serves as a simplistic model for one-way vehicular traffic. Since traffic is perturbed by cars cruising for parking in many metropolises, we introduce a variant of TASEP, dubbed SFP, in which particles are initially cruising at a slower speed and aiming to park on one of the sites adjacent to the main road, described by a unidimensional lattice. After parking, they pull out at a finite rate and move at a normal speed. We show that this stylized model, which breaks many of the conservation rules applicable in other TASEP variants, exhibits singular features, in particular non-monotonic variations of the steady-state current with the injection rate and re-entrant transitions in the phase diagram, for some range of parameters. These features are robust to variations in the update rule and the boundary conditions. Neither the slow speed of cruising cars nor the perturbation of the flow due to pull-out maneuvers, taken in isolation, can rationalize these observations. Instead, they originate in a cramming (or ‘paper jam’) effect which results from the coupling of these mechanisms: injecting too many cars into the system saturates the first sites of the road, which prevents parked cars from pulling out, thus forcing cruising cars to travel farther along the road. These strong discrepancies with even the qualitative trends of the baseline TASEP model highlight the importance of considering the effect of perturbations on traffic.

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.

Considering the wide applications of big data in transportation, machine learning and mobile internet technology, artificial intelligence (AI) has largely empowered transportation systems. Many traditional transportation planning and management methods have been improved or replaced with smart transportation systems. Hence, considering the challenges posed by the rising demand for parking spaces, traffic flow and real-time operational management in urban areas, adopting artificial intelligence technologies is crucial. This study aimed to establish a systematic framework for representative transportation scenarios and design practical application schemes. This study begins by reviewing the development history of smart parking systems, roads and transportation management systems. Then, examples of their typical application scenarios are presented. Second, we identified several traffic problems and proposed solutions in terms of a single parking station, routes and traffic networks for an entire area based on a case study of a smart transportation systematic framework in the Xizhang District of Wuxi City. Then, we proposed a smart transportation system based on smart parking, roads and transportation management in urban areas. Finally, by analyzing these application scenarios, we analyzed and predicted the development directions of smart transportation in the fields of smart parking, roads and transportation management systems.

During the COVID pandemic, at least 97 US cities closed downtown streets to vehicles to create commercial pedestrian streets with the goal of encouraging active travel and economic activity at safe social distances. This study addressed three questions about these programs for businesses located on a pedestrian street: 1) what factors influenced their feelings about the program; 2) what concerns did businesses located on pedestrian streets have; and 3) how did the pedestrian street program impact a business’s revenue as compared to other businesses in the area on streets that did not close. We created a geographic database of these pedestrian streets and identified nearly 14,000 abutting businesses, from which we collected interview and survey data. The interviews and survey results highlight key issues surrounding businesses’ experiences with pedestrian streets. Businesses abutting pedestrian streets had a slightly higher opinion of these programs than businesses not abutting these streets. A test of the effect of pedestrian street interventions on business revenue using a pseudo-control group showed the effect to be uncertain but, on average, negligible. The findings point to steps that cities can take to maximize the benefits of pedestrian streets for local businesses.

Sidewalks and crosswalks do not benefit pedestrians if they are blocked by automobiles. In New York City, local media have documented that cars outside of law-enforcement offices routinely park on sidewalks and in crosswalks. This study systematically and longitudinally pursues this topic by tracking the geographic extent of this obstructive parking via in-person observation of the streets surrounding all 77 New York Police Department (NYPD) station houses, across all five boroughs. Combined with review of historical street imagery, this approach reveals widespread and longstanding parking on sidewalks, and to a lesser extent, in crosswalks. Of 77 NYPD station houses, 70 (91%) exhibited parking of at least one of these kinds, with sidewalk parking often extending along the entire block (and not simply in front of station houses), on adjacent blocks, and on both sides of the street. This renders many sidewalks impassable – forcing pedestrians into traffic – and in many cases directly abuts residences and businesses, curtailing access to such destinations. Longitudinally, such obstructive parking was present across 82% of 703 street-imagery data points, indicating this has largely become the default (and not occasional) use of adjacent sidewalks. In-person observation also demonstrated other ways this parking has had negative effects surrounding NYPD station houses, including double parking, obstruction of bus and bike lanes, and blocking of fire hydrants. These findings broaden the study of pedestrian accessibility and safety beyond the quality and design of sidewalks and intersections, to include chronic automotive obstruction, and indicate that parking behavior surrounding public-sector offices, if left unchecked, significantly degrades walkability.

Along with society's development, transportation has become a key factor in human daily life, increasing the number of vehicles on the streets. Consequently, the task of finding free parking slots in metropolitan areas can be dramatically challenging, increasing the chance of getting involved in an accident and the carbon footprint, and negatively affecting the driver's health. Therefore, technological resources to deal with parking management and real-time monitoring have become key players in this scenario to speed up the parking process in urban areas. This work proposes a new computer-vision-based system that detects vacant parking spaces in challenging situations using color imagery processed by a novel deep-learning algorithm. This is based on a multi-branch output neural network that maximizes the contextual image information to infer the occupancy of every parking space. Every output infers the occupancy of a specific parking slot using all the input image information, unlike existing approaches, which only use a neighborhood around every slot. This allows it to be very robust to changing illumination conditions, different camera perspectives, and mutual occlusions between parked cars. An extensive evaluation has been performed using several public datasets, proving that the proposed system outperforms existing approaches. [ABSTRACT FROM AUTHOR]

Shared e-scooter programs often generate complaints about improper parking because it creates unappealing clutter and can make it difficult for pedestrians to use the sidewalk. We examine how cities can address noncompliant scooter parking and explore public perceptions of this problem with two related studies. First, we conducted field experiments in Washington, DC (hereafter "DC"), and Auckland, New Zealand. We observed scooter parking and then evaluated the efficacy of three interventions to mitigate noncompliant parking. We find low rates of noncompliance, but the precise rate is highly dependent on how we define noncompliance. We also find that in-app message reminders and sidewalk decals marginally lowered rates of noncompliant parking, but the largest improvement in compliance occurred after DC implemented a requirement that scooters be physically locked to bike racks. Second, we examined public perceptions of improper parking by asking people how much noncompliant parking they think occurs and what practices they think constitute noncompliant parking. We find that the public overestimates improper parking of scooters and underestimates improper parking of bicycles and cars. Given their unfamiliarity with scooter parking regulations, respondents use pedestrian accessibility and tidiness as heuristics to determine what counts as proper scooter parking. Our results suggest that intuitive parking solutions that align with perceptions of orderly parking, such as bike racks or on-street parking corrals, can improve rider compliance and may reduce public dissatisfaction with shared scooter parking. [ABSTRACT FROM AUTHOR]

We report shared e-scooter ridership and rider perceptions on Virginia Tech's Blacksburg campus before and after introduction of mandatory e-scooter parking corrals in January 2022. The analysis relies on a panel of 131 e-scooter riders surveyed in Fall 2021 and Spring 2022. Although parking corrals were perceived favorably prior to implementation, perceptions became more negative afterwards. Respondents said corrals were not located where needed, difficult to find, fully occupied, and took too much extra time to use. After parking corrals were introduced, ridership declined 72% overall and also fell for all socio-economic subgroups. The heaviest user groups, like undergraduate males, were most likely to quit. The first study identifying desired and actual egress times for e-scooters, we found that roughly two-thirds of riders desired egress times under 2 min and one quarter under 1 min. Prior to the introduction of parking corrals, 82% of riders reported actual egress times under 2 min, and 43% under 1 min. Those who kept riding after the introduction of e-scooter corrals reported longer actual egress times and a stronger stated desire for egress times under 2 min. Communities should be careful when imposing e-scooter parking restrictions to ensure that e-scooter egress time is sufficiently low—ideally within an easy 2 min walk of popular origins and destinations. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates car parking users’ behaviors from social media perspective using social network based analysis of online communities revealed by mining the associated hashtags in Twitter. We propose a new interpretable community detection approach for mapping user’s car parking behavior by combining Clique, K-core and Girvan–Newman community detection algorithms together with a content-based analysis that exploits polarity, relative frequency and dominant topics. Twitter API was used to collect relevant data by tracking popular car-parking hashtags. A social network graph is constructed using a similarity-based analysis. Finally, interpretable communities are inferred by monitoring the outcomes of clique, K-core and Girvan–Newman community detection algorithms. This interpretability is linked to the aggregation of keywords, hashtags and/or location attributes of the tweet messages as well as a visualization module that enables interaction with users. In parallel, a global trend analysis investigates parking types and Twitter influence with respect to both sentiment polarity and dominant trends (extracted using KeyBERT based approach) is performed. The implementation of this social media analytics has uncovered several aspects associated to car-parking behaviors. A comparison with some state-of-the-art community detection methods has also been carried out and revealed some similarities with our developed approach.

This article aims to analyze the quality of public services regarding public roadside parking in Pekalongan City. The problem in this study is focused on parking problems, namely limited land or vehicle parking lots so that people park their vehicles arbitrarily. In addition, it is also due to the actions of several parking attendants who collect parking fees that exceed the provisions and the presence of illegal or unofficial parking attendants who make parking arrangements and collect parking fees. In order to approach these problems, the theoretical references from Zeitaml and Ilosa are used, namely tangible, reliability, responsiveness, assurance, empathy, transparency and security. The data were collected through direct observation and interviews with informants and analyzed qualitatively. This study concludes that the quality of parking services on the edge of public roads is not good. This is indicated by the three dimensions that state that they are not good, namely reliability, responsiveness and assurance, although four dimensions state that they are quite good, namely tangible, assurance, empathy, transparency and security, so that the quality of parking services on the edge of public roads needs to be improved.

Digital vigilantism is one of the challenges of e-democracy. Many scholars recognize the threat of vigilantism to civil society. However, we believe it can also reinforce weak government institutions. We consider digital vigilantism as an alternative to e-participation tools. This study aims to determine a model of digital vigilantism in Russia based on the analysis of the social media activity of StopXam in the context of the development of alternative e-democracy institutions. Considering vigilantism as an example of an informal institution, we analyze vigilantism following Helmke and Levitsky typology. The case chosen for analysis is one of the largest Russian vigilant StopXam movement that can be compared with the government initiative Moscow Helper. To identify the model of digital vigilantism in Russia, we conduct a social network analysis in respect to five communities in Vk.com, a Russian social network: “StopXam”, “StopXam Moscow”, the official community of “Moscow Helper”, the unofficial community of “Moscow Helper”, the community of opponents of “Moscow Helper” application. The findings of this study suggest that vigilantism could be considered as an instrument of informal institutionalization, which can be used by political actors (primarily the government) as a tool for setting the rules of the game that correspond to established public values. The creation of groups that are ready to observe the general principles of the game’s rules and impose common values with only minor, occasional violations of the letter of the law is becoming a working model of managed vigilantism. This model tends towards the routine practice of vigilantism, which limits the potential for online mobilization.

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