scholarly journals Evaluating the Traffic and Emissions Impacts of Congestion Pricing in New York City

2020 ◽  
Vol 12 (9) ◽  
pp. 3655 ◽  
Author(s):  
Amirhossein Baghestani ◽  
Mohammad Tayarani ◽  
Mahdieh Allahviranloo ◽  
H. Oliver Gao
Keyword(s):  
New York ◽  
Travel Behavior ◽  
Traffic Congestion ◽  
Network Performance ◽  
Travel Demand ◽  
Transportation Network ◽  
Congestion Pricing ◽  
Central Business District ◽  
Demand Model ◽  
Business District

Traffic congestion is a major challenge in metropolitan areas due to economic and negative health impacts. Several strategies have been tested all around the globe to relieve traffic congestion and minimize transportation externalities. Congestion pricing is among the most cited strategies with the potential to manage the travel demand. This study aims to investigate potential travel behavior changes in response to cordon pricing in Manhattan, New York. Several pricing schemes with variable cordon charging fees are designed and examined using an activity-based microsimulation travel demand model. The findings demonstrate a decreasing trend in the total number of trips interacting with the central business district (CBD) as the price goes up, except for intrazonal trips. We also analyze a set of other performance measures, such as Vehicle-Hours of Delay, Vehicle-Miles Traveled, and vehicle emissions. While the results show considerable growth in transit ridership (6%), single-occupant vehicles and taxis trips destined to the CBD reduced by 30% and 40%, respectively, under the $20 pricing scheme. The aggregated value of delay for all vehicles was also reduced by 32%. Our findings suggest that cordon pricing can positively ameliorate transportation network performance and consequently, improve air quality by reducing particular matter inventory by up to 17.5%. The results might facilitate public acceptance of cordon pricing strategies for the case study of NYC. More broadly, this study provides a robust framework for decision-makers across the US for further analysis on the subject.

Effect of Auto Restraint Policies on Travel Behavior

2005 ◽  
Vol 1932 (1) ◽  
pp. 156-163 ◽  
Author(s):  
Yoram Shiftan ◽  
Arnon Golani
Keyword(s):  
Travel Behavior ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Stated Preference ◽  
Congestion Pricing ◽  
Point Of View ◽  
City Center ◽  
Policy Makers ◽  
New Policies ◽  
Economic Vitality

Auto restraint policies are becoming increasingly popular among urban planners and policy makers as a way of managing travel demand and traffic in city centers. Because urban access is considered crucial to the economic success of a downtown area, certain constituencies, such as business and retail, have historically been opposed to such policies. To address these concerns and design appropriate policies, it is important to understand how visitors to a city center are likely to respond to new policies. This paper presents a model for estimating the likely response to two potential auto restraint policies in the center of Tel Aviv, the largest metropolitan area in Israel: an increase in parking cost and the use of congestion pricing in the form of a cordon around the city center. The models are based on the responses of center visitors to a stated preference survey. The results show that for both workers and nonworkers, most drivers who respond to the policy will do so by changing their mode of travel, and, in the case of congestion pricing, by also changing the time of their trip. The minority will respond by changing their destination or canceling their trip. This is an encouraging result from a policy point of view because changing time or mode is considered a positive shift, whereas changing destination or canceling the trip is considered negative. The results indicate that auto restraint policies can be effective in reducing traffic congestion and air pollution in city centers without hampering their economic vitality.

Optimizing route choice in multimodal transportation networks

2014 ◽  
Vol 41 (9) ◽  
pp. 800-810 ◽  
Author(s):  
Behzad Rouhieh ◽  
Ciprian Alecsandru
Keyword(s):  
Public Transportation ◽  
Travel Behavior ◽  
Traffic Congestion ◽  
Transportation Networks ◽  
Routing Algorithm ◽  
Central Business District ◽  
Subsequent Work ◽  
Traveler Information ◽  
Multimodal Transportation ◽  
Business District

Advanced traveler information systems provide travelers with pre-trip and en route travel information necessary to improve the trip decision making process based on various criteria (e.g., avoiding the negative impacts of traffic congestion, selecting specific travel modes, etc.). This study investigates an adaptive routing methodology for multimodal transportation networks. To integrate transit networks, the model takes into account both the predefined timetables of public transportation services and the variability of travel times. A graph theory based methodology is proposed to capture travel behavior within a multimodal network. The study advances a routing algorithm based on Markov decision processes. Special network modeling elements were defined to allow the developed algorithm to select the most efficient transportation mode at each junction along a given route. The proposed methodology is applied to a small real-world network located in the central business district area of Montreal, Quebec. The network includes bus, subway, and bicycle transportation facilities. The simulations were run under the assumption that users do not use private vehicles to travel between arbitrary selected origin and destination points. The developed routing algorithm was applied to several simulation scenarios. The results identified what is the most efficient combination of transportation modes that the travelers have to use given certain traffic and transit service conditions. Larger and more complex networks of motorized and non-motorized modes with stochastic properties will be investigated in subsequent work.

scholarly journals MODELING AND ESTIMATING THE CAPACITY OF URBAN TRANSPORTATION NETWORK WITH RAPID TRANSIT

Transport ◽  
2014 ◽  
Vol 29 (2) ◽  
pp. 165-174 ◽  
Author(s):  
Lin Cheng ◽  
Muqing Du ◽  
Xiaowei Jiang ◽  
Hesham Rakha
Keyword(s):  
Travel Behavior ◽  
Travel Demand ◽  
Transportation Network ◽  
Urban Transportation ◽  
Network Capacity ◽  
Rapid Transit ◽  
Demand Model ◽  
Trip Distribution ◽  
Capacity Model ◽  
The Impact

To study the impact of the rapid transit on the capacity of current urban transportation system, a two-mode network capacity model, including the travel modes of automobile and transit, is developed based on the well-known road network capacity model. It considers that the travel demand accompanying with the regional development will increase in a variable manner on the trip distribution, of which the travel behavior is represented using the combined model split/trip distribution/traffic assignment model. Additionally, the choices of the travel routes, trip destinations and travel modes are formulated as a hierarchical logit model. Using this combined travel demand model in the lower level, the network capacity problem is formulated as a bi-level programming problem. The latest technique of sensitivity analysis is employed for the solution of the bi-level problem in a heuristic search. Numerical computations are demonstrated on an example network, and the before-and-after comparisons of building the new transit lines on the integrated transportation network are shown by the results.

scholarly journals Mode Choice Modeling to Shift Car Travelers towards Park and Ride Service in the City Centre of Karachi

2021 ◽  
Vol 13 (10) ◽  
pp. 5638
Author(s):  
Irfan Ahmed Memon ◽  
Saima Kalwar ◽  
Noman Sahito ◽  
Mir Aftab Hussain Talpur ◽  
Imtiaz Ahmed Chandio ◽  
...  
Keyword(s):  
Public Transportation ◽  
Travel Behavior ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Mode Choice ◽  
Central Business District ◽  
Choice Models ◽  
City Centre ◽  
Travel Demand Management ◽  
Park And Ride

Currently, congestion in Karachi’s central business district (CBD) is the result of people driving their cars to work. Consequently, a park and ride (P&R) service has proved successful in decreasing traffic congestion and the difficulty of finding parking spaces from urban centers. The travelers cannot be convinced to shift towards the P&R service without an understanding of their travel behavior. Therefore, a travel behavior survey needs to be conducted to reduce the imbalance between public and private transport. Hence, mode choice models were developed to determine the factors that influence single-occupant vehicle (SOV) travelers’ decision to adopt the P&R service. Data were collected by an adapted self-administered questionnaire. Mode choice models were developed through logistic regression modeling by using the Statistical Package for the Social Sciences version 22. The findings concluded that more than 70%, specifically motorbike users, to avoid mental stress, and to protect the environment are willing to adopt the P&R service. Moreover, to validate the mode choice models, logit model training and a testing approach were used. In conclusion, by overcoming these influencing factors and balancing push and pull measures of travel demand management (TDM), SOV users can be encouraged to shift towards P&R services. Thus, research outcomes can support policymakers in implementing sustainable modes of public transportation.

Model Calibration and Forecasts of Air Travel Demand with Categorized Household Socioeconomic Attributes

2020 ◽  
Vol 2674 (6) ◽  
pp. 363-371
Author(s):  
Jungin Kim ◽  
Ikki Kim ◽  
Jaeyeob Shim ◽  
Hansol Yoo ◽  
Sangjun Park
Keyword(s):  
Travel Behavior ◽  
Household Income ◽  
Travel Demand ◽  
Behavioral Model ◽  
Income Group ◽  
Air Travel ◽  
Jeju Island ◽  
Demand Model ◽  
Air Travel Demand ◽  
Travel Demand Model

The objectives of this study were to (1) construct an air demand model based on household data and (2) forecast future air demand to explain the relationship between air demand and individual travel behavior. To this end, domestic passenger air travel demand at Jeju Island in South Korea was examined. A multiple regression model with numerous explanatory variables was established by examining categorized household socioeconomic data that affected air demand. The air travel demand model was calibrated for 2009–2015 based on the annual average number of visits to Jeju Island by households in certain income groups. The explanatory variable was set using a dummy variable for each household income group and the proportion of airfare to GDP per capita. Higher household income meant more frequent visits to Jeju Island, which was well-represented in the model. However, the value of the coefficient for the highest income was lower than the value for the second-highest income group. This suggested that the highest income group preferred overseas travel destinations to domestic ones. The future air demand for Jeju airport was predicted as 26,587,407 passengers in 2026, with a subsequent gradual increase to approximately 33,000,000 passengers by 2045 in this study. This study proposed an air travel demand model incorporating household socioeconomic attributes to reflect individual travel behavior, which contrasts with previous studies that used aggregate data. By constructing an air travel model that incorporated socioeconomic factors as a behavioral model, more accurate and consistent projections could be obtained.

scholarly journals Analyzing the Issue of On-street Parking in Commercial Areas: A Case Study of the City of Hyderabad, Pakistan

2018 ◽  
Vol 01 (02) ◽  
pp. 01-09
Author(s):  
Baig Farrukh ◽  
Sahito Noman ◽  
Bano Arsla ◽  
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Survey Methodology ◽  
Greenhouse Gas Emission ◽  
Central Business District ◽  
Rapid Urbanization ◽  
Analysis Technique ◽  
Business District ◽  
Public Views ◽  
The City

In developing countries, rapid urbanization has created an enormous pressure on land use, infrastructure and transportation. The fast growing ratio of motorized vehicles in urban areas is the main cause of environmental degradation. Almost 80% of the greenhouse gas emission is from vehicles in cities. In the city centers, on-street parking is considered the major cause of traffic congestion. The aim of this study was to evaluate the problems of on-street parking and disorderly parking at Central Business District (CBD) of Hyderabad city. The field survey methodology was adopted to perceive the current traffic problems in the city center and traffic count survey was carried out in both peak and off hours. The data was analyzed using descriptive statistics frequency analysis technique with the help of Statistical Package for the Social Sciences (SPSS). The findings revealed that increasing number of vehicles, on-street parking, improper parking, encroachment, inadequate parking space and poor condition of roads are the main causes of traffic congestion. The study bridges up the research gap of determining public views about on-street parking challenges in the context of Hyderabad, Pakistan and provides statistical results which may equally be adapted by policy makers and transportation planners in order to improve the traffic situation.

Examining the Equity Impacts of Autonomous Vehicles: A Travel Demand Model Approach

2019 ◽  
Vol 2673 (5) ◽  
pp. 23-35 ◽  
Author(s):  
Jesse Cohn ◽  
Richard Ezike ◽  
Jeremy Martin ◽  
Kwasi Donkor ◽  
Matthew Ridgway ◽  
...  
Keyword(s):  
Performance Measures ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Travel Demand ◽  
Autonomous Vehicle ◽  
Demand Model ◽  
The Status ◽  
Mode Share ◽  
Transit Agencies ◽  
Travel Demand Model

As investments in autonomous vehicle (AV) technology continue to grow, agencies are beginning to consider how AVs will affect travel behavior within their jurisdictions and how to respond to this new mobility technology. Different autonomous futures could reduce, perpetuate, or exacerbate existing transportation inequities. This paper presents a regional travel demand model used to quantify how transportation outcomes may differ for disadvantaged populations in the Washington, D.C. area under a variety of future scenarios. Transportation performance measures examined included job accessibility, trip duration, trip distance, mode share, and vehicle miles traveled. The model evaluated changes in these indicators for disadvantaged and non-disadvantaged communities under scenarios when AVs were primarily single-occupancy or high-occupancy, and according to whether transit agencies responded to AVs by maintaining the status quo, removing low-performing routes, or applying AV technology to transit vehicles. Across the performance measures, the high-occupancy AV and enhanced transit scenarios provided an equity benefit, either mitigating an existing gap in outcomes between demographic groups or reducing the extent to which that gap was expanded.

scholarly journals Built Environment Correlates of the Propensity of Walking and Cycling

2020 ◽  
Vol 12 (20) ◽  
pp. 8752
Author(s):  
Longzhu Xiao ◽  
Linchuan Yang ◽  
Jixiang Liu ◽  
Hongtai Yang
Keyword(s):  
Built Environment ◽  
Traffic Congestion ◽  
Central Business District ◽  
Decision Makers ◽  
Policy Implications ◽  
Research Attention ◽  
Bus Stop ◽  
Intersection Density ◽  
Business District ◽  
Public Health Promotion

Walking and cycling are not only frequently-used modes of transport but also popular physical activities. They are beneficial to traffic congestion mitigation, air pollution reduction, and public health promotion. Hence, examining and comparing the built environment correlates of the propensity of walking and cycling is of great interest to urban practitioners and decision-makers and has attracted extensive research attention. However, existing studies mainly look into the two modes separately or consider them as an integral (i.e., active travel), and few compare built environment correlates of their propensity in a single study, especially in the developing world context. Thus, this study, taking Xiamen, China, as a case, examines the built environment correlates of the propensity of walking and cycling simultaneously and compares the results wherever feasible. It found (1) built environment correlates of the propensity of walking and cycling differ with each other largely in direction and magnitude; (2) land use mix, intersection density, and bus stop density are positively associated with walking propensity, while the distance to the CBD (Central Business District) is a negative correlate; (3) as for cycling propensity, only distance to CBD is a positive correlate, and job density, intersection density, and bus stop density are all negative correlates. The findings of this study have rich policy implications for walking and cycling promotion interventions.

scholarly journals An Empirical Activity Sequence Approach for Travel Behavior Analysis in Vilnius City

2020 ◽  
Vol 12 (2) ◽  
pp. 468 ◽  
Author(s):  
Vytautas Dumbliauskas ◽  
Vytautas Grigonis
Keyword(s):  
Empirical Research ◽  
Travel Behavior ◽  
Survey Methodology ◽  
Travel Demand ◽  
Sampling Strategy ◽  
Research Approach ◽  
Demand Model ◽  
Sustainable Mobility ◽  
Activity Sequence ◽  
Analysis Of Results

The approach defines the process of conducting an empirical research of the travel behavior patterns of residents of Vilnius city. It defines survey methodology and important mobility parameters such as activity sequences and their probabilities of homogeneous urban population segments during the weekday. This empirical research is based on a travel diary survey that was planned and executed in cooperation with Vilnius Municipality during preparation of sustainable mobility plan. The following work describes the research object, the questionnaire design, sampling strategy and the analysis of results based on characteristics of respondents. An innovative activity sequence-focused travel behavior research approach designed to collect data for a tour-based travel demand model.

scholarly journals SOLVING TRAFFIC CONGESTION FROM THE DEMAND SIDE

2015 ◽  
Vol 27 (6) ◽  
pp. 529-538 ◽  
Author(s):  
Ying-En Ge ◽  
Olegas Prentkovskis ◽  
Chunyan Tang ◽  
Wafaa Saleh ◽  
Michael G. H. Bell ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Traffic Congestion ◽  
Travel Demand ◽  
State Of The Art ◽  
Demand Management ◽  
Relevant Literature ◽  
Short Review ◽  
Active Management ◽  
Demand Side ◽  
Travel Demand Management

It is nowadays widely accepted that solving traffic congestion from the demand side is more important and more feasible than offering more capacity or facilities for transportation. Following a brief overview of evolution of the concept of Travel Demand Management (TDM), there is a discussion on the TDM foundations that include demand-side strategies, traveler choice and application settings and the new dimensions that ATDM (Active forms of Transportation and Demand Management) bring to TDM, i.e. active management and integrative management. Subsequently, the authors provide a short review of the state-of-the-art TDM focusing on relevant literature published since 2000. Next, we highlight five TDM topics that are currently hot: traffic congestion pricing, public transit and bicycles, travel behavior, travel plans and methodology. The paper closes with some concluding remarks.

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