The Impact of Workforce Commuting Patterns on Parking Demand

2015 ◽  
Author(s):  
Tayo Fabusuyi ◽  
Robert Cornelius Hampshire
Keyword(s):  
Commuting Patterns ◽  
The Impact ◽  
Parking Demand

The impact of future cities on commuting patterns: An agent-based approach

2018 ◽  
Vol 46 (6) ◽  
pp. 1079-1096
Author(s):  
Marcello Marini ◽  
Anna P Gawlikowska ◽  
Andrea Rossi ◽  
Ndaona Chokani ◽  
Hubert Klumpner ◽  
...  
Keyword(s):  
Urban Areas ◽  
Simulation Models ◽  
Single Family ◽  
Simulation Framework ◽  
Agent Based ◽  
Commercial Activities ◽  
Transportation Sector ◽  
Commuting Time ◽  
Commuting Patterns ◽  
The Impact

Over the next 35 years, the population of Switzerland is expected to grow by 25%. One possible way to accommodate this larger population is to transform smaller cities in Switzerland through the direct intervention of urban planners. In this work, we integrate agent-based simulation models of people flow, mobility and urban infrastructure with models of the electricity and gas systems to examine the increase of the density of existing residential zones and the creation of new workplaces and commercial activities in these urban areas. This novel simulation framework is used to assess, for the year 2050, two different scenarios of urbanization in a region with small urban areas. It is shown that a densification scenario, with a preference for multi-dwelling buildings, consumes 93% less land than a sprawl scenario, with a preference for single-family houses. The former scenario also accommodates 27% more people than the latter scenario, as there is a higher penetration of battery electric vehicles – and therefore reduced air pollution from the transportation sector – and also a larger shift of commuters to the use of public transport. However, in the former scenario, the commuting time is 20% longer. The outcome of this work demonstrates how this novel simulation framework can be used to support the formulation of policies that can direct the transformation of urban areas.

scholarly journals Impact Analysis of Parking Price Adjustment on the Quality of Service of Airport Parking Lots for Light Vehicles

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Cheng Cheng ◽  
Peng Qi
Keyword(s):  
Quality Of Service ◽  
Impact Analysis ◽  
Demand Management ◽  
Evaluation Framework ◽  
Daily Maximum ◽  
Before And After ◽  
Parking Lot ◽  
The Impact ◽  
Parking Demand

Pricing is a common measure for parking demand management that has been implemented worldwide. However, the impact of parking price on a parking lot’s quality of service is seldom discussed. This study investigated the impacts of a ladder daily maximum fee charging strategy on the quality of service of the Hongqiao International Airport parking lot based on automatic transaction data before and after the strategy was implemented. An evaluation framework considering managers’ and users’ perspectives was designed. The estimation results show that the new price regulation method largely discouraged long-term parking demand and improved the availability of airport parking facilities, especially during long holidays. As a consequence, throughput and income largely increased in the airport, and there were extra time costs during vehicle departures. The price elasticity of parkers with different parking durations was further estimated. The results showed that price sensitivity is relatively inelastic but varies based on parking duration.

Analysis on the Impact of Floating Parking Fees on Parking Demand

CICTP 2018 ◽  
2018 ◽  
Author(s):  
Huanmei Qin ◽  
Yingying Dun ◽  
Jinmeng Zhang ◽  
Xiuhan Yang
Keyword(s):  
The Impact ◽  
Parking Demand

Measuring the Length of a Two-Lane Curbside Based on Traffic Features

2020 ◽  
Vol 2674 (12) ◽  
pp. 590-599
Author(s):  
Siyang Liu ◽  
Chenjing Zhou ◽  
Jian Rong ◽  
Jianming Ma ◽  
Yi Wang
Keyword(s):  
Traffic Flow ◽  
Dwell Time ◽  
Rational Design ◽  
Geometric Design ◽  
Level Of Service ◽  
Car Following ◽  
Traffic Capacity ◽  
Road Space ◽  
The Impact ◽  
Parking Demand

The geometric design of airport curbsides is critical for both airport planners and passengers as it affects airport ground traffic capacity and creates airline delays. Rational design of curbsides can yield increased efficiency in the use of road space and time resources. Yet a limited number of studies have reported the impact of traffic features on curbside’s geometric design. This paper provides a two-lane curbside measurement with a simulation model to calculate the length of curbsides, which solves the curbside berth supply and curbside length calculation problems using a refined curbside parking model (RCPM) with constraints of a car-following (CF) model, as well as uniformly distributed speed, dwell time, and parking demand; it thereby unveils the detailed microscopic mechanisms of interaction of traffic features and curbsides’ length. The required lengths of curbsides under various parking demands are obtained after a set of numerical simulations. The result further reveals the significant impacts of car-following and braking behaviors, particularly under the huge parking demands on curbside traffic flow. It also demonstrates that a certain delay is created and a suboptimum level of service (LOS) occurs even though satisfying all parking demands, which indicates that lengthening the curbside and increasing parking supply do not necessarily improve the LOS.

Bikeshare Users on a Budget? Trip Chaining Analysis of Bikeshare User Groups in Chicago

2019 ◽  
Vol 2673 (7) ◽  
pp. 329-340
Author(s):  
Siyue Yang ◽  
Candace Brakewood ◽  
Virgile Nicolas ◽  
Jake Sion
Keyword(s):  
Smartphone App ◽  
The Third ◽  
Trip Chaining ◽  
Large Numbers ◽  
Usage Patterns ◽  
User Groups ◽  
Shared Bicycle ◽  
Turn Over ◽  
Commuting Patterns ◽  
The Impact

This analysis focuses on a smartphone app known as “Transit” that is used to unlock shared bicycles in Chicago. Data from the app were utilized in a three-part analysis. First, Transit app bikeshare usage patterns were compared with system-wide bikeshare utilization using publicly available data. The results revealed that hourly usage on weekdays generally follows classical peaked commuting patterns; however, daily usage reached its highest level on weekends. This suggests that there may be large numbers of both commuting and recreational users. The second part aimed to identify distinct user groups via cluster analysis; the results revealed six different clusters: (1) commuters, (2) utility users, (3) leisure users, (4) infrequent commuters, (5) weekday visitors, and (6) weekend visitors. The group unlocking the most shared bikes (45.58% of all Transit app unlocks) was commuters, who represent 10% of Transit app bikeshare users. The third part proposed a trip chaining algorithm to identify “trip chaining bikers.” This term refers to bikeshare users who return a shared bicycle and immediately check out another, presumably to avoid paying extra usage fees for trips over 30 min. The algorithm revealed that 27.3% of Transit app bikeshare users exhibited this type of “bike chaining” behavior. However, this varied substantially between user groups; notably, 66% of Transit app bikeshare users identified as commuters made one or more bike chaining unlocks. The implications are important for bikeshare providers to understand the impact of pricing policies, particularly in encouraging the turn-over of bicycles.

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