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Availability and utilization of residential parking locations remain a crucial yet often overlooked aspect of urban planning and policy making. Thus, this study investigates questions about residential parking within National Travel Surveys (NTS) across 49 OECD-affiliated countries. The study used a layered framework, differentiating parking locations by on/off-street, public/private access, proximity to dwellings, and infrastructure type to analyze questions and response options. A document review revealed significant variability in the inclusion of residential parking questions, with only 24 of 49 evaluated countries conducting NTS and only 15 explicitly addressing residential parking locations, often via one question. While questions are often similar, the response options are often ambiguous, sometimes misleading, and vary significantly. Based on the results, we identified the following recommendations: (1) adopt and rephrase parking-related questions in new and existing NTS, (2) provide guidance to users on how certain response options are defined, (3) for a more comprehensive understanding of residential parking dynamics, include a question on availability and actual usage, (4) add "National Travel Survey" as a keyword in applicable surveys, and (5) provide easy access to documentation to facilitate data retrieval and international comparison. [ABSTRACT FROM AUTHOR]

Availability and utilization of residential parking locations remain a crucial yet often overlooked aspect of urban planning and policy making. Thus, this study investigates questions about residential parking within National Travel Surveys (NTS) across 49 OECD-affiliated countries. The study used a layered framework, differentiating parking locations by on/off-street, public/private access, proximity to dwellings, and infrastructure type to analyze questions and response options. A document review revealed significant variability in the inclusion of residential parking questions, with only 24 of 49 evaluated countries conducting NTS and only 15 explicitly addressing residential parking locations, often via one question. While questions are often similar, the response options are often ambiguous, sometimes misleading, and vary significantly. Based on the results, we identified the following recommendations: (1) adopt and rephrase parking-related questions in new and existing NTS, (2) provide guidance to users on how certain response options are defined, (3) for a more comprehensive understanding of residential parking dynamics, include a question on availability and actual usage, (4) add “National Travel Survey” as a keyword in applicable surveys, and (5) provide easy access to documentation to facilitate data retrieval and international comparison.

This study formulates the joint decisions of commuters on departure time and parking location choices in a morning commute problem where the commuters travel with autonomous vehicles (AVs) or human-driven vehicles (HVs). Under a mixed traffic environment, we aim to explore the impacts of parking capacity and parking pricing on the equilibrium travel pattern and the system performance. We build a dynamic equilibrium model for the morning commute problem by assuming that the parking slots can be grouped into central and peripheral clusters based on the distance between the parking location and the workplace. We first analyze the parking location preferences of commuters towards the two parking clusters under a mixed traffic environment. We then examine the equilibrium conditions and identify all the equilibrium travel patterns. We further analyze the system performance measured by the total travel cost with respect to the parking prices and the capacity of the central cluster. The optimal parking pricing scheme is also derived to minimize the total travel cost. We conduct numerical analysis to demonstrate the change in the total travel cost against the parking capacity of the central cluster and its parking price. Sensitivity analysis is performed to show the impacts of the network configuration on the total travel cost. [ABSTRACT FROM AUTHOR]

This paper proposes an electric vehicle charging station (EVCS) network design in urban communities using hybrid technique. The proposed approach consists of Reptile Search Algorithm (RSA) and Honey Badger Algorithm (HBA), which is jointly called as RSA-HBA technique.In this paper, a modeling method is embedded in the proposed technique to control the optimal design and sorts of electric vehicle distribution equipment for the community, considering the heterogeneity on demand and driver behaviors.Distance from home, drivers' arrival patterns, willingness to walk, parking location and traffic on weekdays and weekends are certain important random data parameters deemed under this technique. To asymptotically coverage an optimal solution, the hybrid algorithm is used. A hybrid technique is proposed to direct the computational challenges for huge-scale phenomena. A detailed computational experiment is conducted to quantify the performance of the proposed technique. The performance of the proposed hybrid system is executed in the MATLAB platform and related with various methods. [ABSTRACT FROM AUTHOR]

This study formulates the joint decisions of commuters on departure time and parking location choices in a morning commute problem where the commuters travel with autonomous vehicles (AVs) or human-driven vehicles (HVs). Under a mixed traffic environment, we aim to explore the impacts of parking capacity and parking pricing on the equilibrium travel pattern and the system performance. We build a dynamic equilibrium model for the morning commute problem by assuming that the parking slots can be grouped into central and peripheral clusters based on the distance between the parking location and the workplace. We first analyze the parking location preferences of commuters towards the two parking clusters under a mixed traffic environment. We then examine the equilibrium conditions and identify all the equilibrium travel patterns. We further analyze the system performance measured by the total travel cost with respect to the parking prices and the capacity of the central cluster. The optimal parking pricing scheme is also derived to minimize the total travel cost. We conduct numerical analysis to demonstrate the change in the total travel cost against the parking capacity of the central cluster and its parking price. Sensitivity analysis is performed to show the impacts of the network configuration on the total travel cost.

Parking problems caused by a lack of parking spaces have exacerbated traffic congestion and worsened environmental pollution. An analysis of the cruising process for parking can provide new perspectives to reduce cruising. Based on a parking survey conducted in Beijing, the authors collected a large amount of trajectory data of cruising vehicles. Then, fluctuation indexes of trajectories were proposed to analyse travellers' cruising processes for parking. The spectral clustering method based on a hidden Markov model (HMM) was used to recognise the cruising trajectories. The recognition performance for three‐dimensional trajectory data is better. Cruising trajectories for Clusters 1, 2, 3, 4, and 6 have large fluctuations and a weightier effect on road traffic. These groups can be taken as target groups for intelligent parking guidance and recommendations. The recognition accuracies for parking location and parking status increase with increasing intercepted trajectory lengths. 150 m from far to near the desired destination can be used as a threshold of the cruising trajectory length to accurately predict travellers' parking location and status. These research results can be applied in intelligent parking systems to dynamically predict parking situations, formulate parking guidance schemes and information release strategies, and improve parking efficiency. [ABSTRACT FROM AUTHOR]

This study is the first in the literature to model the joint equilibrium of departure time and parking location choices when commuters travel with autonomous vehicles (AVs). With AVs, walking from parking spaces to the work location is not needed. Instead, AVs will drop off the commuters at the workplace and then drive themselves to the parking spaces. In this context, the equilibrium departure/arrival profile is different from the literature with non-autonomous vehicles (non-AVs). Besides modeling the commuting equilibrium, this study further develops the first-best time-dependent congestion tolling scheme to achieve the system optimum. Also, a location-dependent parking pricing scheme is developed to replace the tolling scheme. Furthermore, this study discusses the optimal parking supply to minimize the total system cost (including both the travel cost and the social cost of parking supply) under either user equilibrium or system optimum traffic flow pattern. It is found that the optimal planning of parking can be different from the non-AV situation, since the vehicles can drive themselves to parking spaces that are further away from the city center and walking of commuters is avoided. This paper sheds light on future parking supply planning and traffic management. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a time-dependent network equilibrium model that simultaneously considers a traveler’s choice of departure time, route, parking location and parking duration in road networks with multiple user classes and multiple parking facilities. In the proposed model, travelers are differentiated by their trip purpose and parking duration, parking locations are characterized by facility type and parking charge, and the decision-making process of travelers on travel and parking choices is assumed to follow a hierarchical choice structure. The model is formulated as a variational inequality problem, and is solved by a heuristic solution algorithm. Numerical results for two example networks are presented to show the solution quality and investigate the solution sensitivities to some input data. It is found that parking behavior is significantly affected by travel demand, walking distance, parking capacity, and parking charge. The proposed model provides a useful tool for studying the complex temporal and spatial interaction between road traffic and parking congestion, and can be used to assess the effects of various parking policies and infrastructure improvements at a strategic level. [Copyright &y& Elsevier]

Fully automated vehicles (AVs) have the potential to drive empty (without a passenger). For privately-owned AVs, such empty repositioning has the potential benefit of avoiding parking costs at their destination. AV owners could have their vehicle drop them off at their destination, then drive elsewhere to park. Although previous studies have considered the congestion effects of AVs repositioning to park at their owner's residence, this study models the choice of parking location when AVs reposition away from the traveler's destination. We model this behavior through a modified static traffic assignment with a logit model for destination choice, in which AV passenger-carrying trips can create a second empty repositioning trip to an alternate parking zone. The traffic assignment is formulated as a variational inequality. Numerical results on the Chicago sketch network show the effects of AV market penetration, fuel costs, and parking fees on the number of repositioning trips, as well as the impacts of repositioning trips on network congestion. Next, we study the problem of adjusting zone-specific parking costs to influence the repositioning behavior. In particular, when zones have asymmetric parking infrastructure costs, optimized parking fees combined with empty repositioning can encourage AVs to park at cheaper locations, thus reducing the land used for parking at zones with high land value. This network design problem is formulated as a bi-level program. Since it is bi-level and non-convex, a genetic algorithm is used to find a good solution. Results on the Sioux Falls test network show that the adjusted parking costs are effective at reducing the congestion caused by empty repositioning and encouraging more optimal parking choices for repositioning AVs. • Static traffic assignment with destination choice for automated vehicle parking • Empty repositioning at varying market penetrations and demands affects congestion • Network design problem of adjusting parking costs and available parking spaces • Genetic algorithm is effective at encouraging more optimal parking behavior [ABSTRACT FROM AUTHOR]