Development of Joint Stated-Preference-off-Revealed-Preference Model for Shanghai Commute Mode Choices in Response to Parking Fee Management

2021 ◽  
pp. 036119812110271
Author(s):  
Ping Zhang ◽  
Xin Ye ◽  
Ke Wang
Keyword(s):  
Public Transportation ◽  
Travel Demand ◽  
Road Traffic ◽  
Choice Model ◽  
Stated Preference ◽  
Transportation Network ◽  
Model Development ◽  
Revealed Preference ◽  
Random Disturbance ◽  
Travel Demand Management

Facing challenges in parking demand-and-supply imbalance and severe road traffic congestion during peak periods in Shanghai, in this paper we develop an SP-off-RP (stated-preference-off-revealed-preference) choice model to analyze relations between parking fee and commute mode choices based on survey data collected there. The survey questionnaire collects information about travelers’ daily commute, travel choices in the SP context, and personal socioeconomic and demographic attributes. The road network and public transportation network data are also used for model development. The model includes three main travel modes: car, public transit, and non-motorized mode. Variables that significantly influence mode choice and the reasons behind it are discussed, including the parking fee, the level-of-service (LOS) of the three modes, and socioeconomic and demographic variables. In the process of model development, a random sample of full-mode commute trips in Shanghai is integrated to improve model precision. The study reveals that the new random disturbance in the SP context is relatively large. The direct elasticity of the parking fee is estimated at −0.85, which means that when the parking fee increases by 10%, the average probability of choosing a private car for the commute will decrease by 8.5%. It is also found that transit LOS improvements have potential to reduce auto use in Shanghai. The study provides references on parking pricing as an alternative policy for travel demand management in Shanghai.

scholarly journals Effects of Vehicle Restriction Policies on Urban Travel Demand Change from a Built Environment Perspective

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Xiaoyun Cheng ◽  
Kun Huang ◽  
Lei Qu ◽  
Tianbao Zhang ◽  
Li Li
Keyword(s):  
Land Use ◽  
Built Environment ◽  
Public Transportation ◽  
Travel Demand ◽  
Road Traffic ◽  
Transportation Network ◽  
Original Structure ◽  
License Plate ◽  
Contribution Rate ◽  
Four Dimensions

License plate restriction (LPR) policy presents the most straightforward way to reduce road traffic and emissions worldwide. However, in practice, it has aroused great controversy. This policy broke the original structure of the urban transportation mode, which needed some matching strategies to adapt to this change. Investigating this travel demand change is a challenging task because it is greatly influenced by features of the local built environment. Fourteen variables from four dimensions, location, land-use diversity, distance to transit, and street design, are used to depict the built environment; moreover, the severe collinearity underlies these feature variables. To solve the multicollinearity among the variables and high-dimensional problem, this study utilizes two different penalization-based regression models, the LASSO (least absolute shrinkage and selection operator) and Elastic Net regression algorithms, to achieve the variable selection and explore the impacts of the built environment on the change of travel demand triggered by the LPR policy. Travel demand changes are assessed by the relative variation in taxi ridership in each traffic analysis zone based on the taxi GPS data. Built environment variables are measured using the transportation network data and the Baidu Map Service points of interest (POI) data. The results show that regions with a higher level of public transportation service and a higher degree of the land mix have a stronger resilience to the vehicle restriction policy. Besides, the contribution rate of public transportation is stable as a whole, while the contribution rate of richness depends on specific types of land use. The conclusions in this study can provide in-depth insights into the influence of the LPR policy and underpin traffic complementary policies to ensure the effectiveness of LPR.

Large-Scale Application of a Combined Destination and Mode Choice Model Estimated with Mixed Stated and Revealed Preference Data

2017 ◽  
Vol 2669 (1) ◽  
pp. 31-40 ◽  
Author(s):  
Michael Heilig ◽  
Nicolai Mallig ◽  
Tim Hilgert ◽  
Martin Kagerbauer ◽  
Peter Vortisch
Keyword(s):  
Large Scale ◽  
Travel Demand ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Revealed Preference ◽  
Demand Model ◽  
Agent Based ◽  
Preference Data ◽  
Mode Choice Model

The diffusion of new modes of transportation, such as carsharing and electric vehicles, makes it necessary to consider them along with traditional modes in travel demand modeling. However, there are two main challenges for transportation modelers. First, the new modes’ low share of usage leads to a lack of reliable revealed preference data for model estimation. Stated preference survey data are a promising and well-established approach to close this gap. Second, the state-of-the-art model approaches are sometimes stretched to their limits in large-scale applications. This research developed a combined destination and mode choice model to consider these new modes in the agent-based travel demand model mobiTopp. Mixed revealed and stated preference data were used, and new modes (carsharing, bikesharing, and electric bicycles) were added to the mode choice set. This paper presents both challenges of the modeling process, mainly caused by large-scale application, and the results of the new combined model, which are as good as those of the former sequential model although it also takes the new modes into consideration.

scholarly journals Likelihood of Motorcyclists Transferring to Safer Mode of Transport in Cairo, Egypt

2019 ◽  
Vol 8 (6) ◽  
pp. 2411-2416
Keyword(s):  
Travel Time ◽  
Road Traffic ◽  
Choice Model ◽  
Stated Preference ◽  
Urban Transportation ◽  
Research Work ◽  
Revealed Preference ◽  
Travel Cost ◽  
Mode Decision ◽  
Road Traffic Crashes

Road traffic injuries and mortality are mainly caused by motorcycle crashes. Practically, 50% of people who meet their death in road traffic accidents (RTAs) are motorcyclists. The issue is increasingly articulated in progressing nations where the use of motorcycles has gained popularity in the past decades. Moreover, death and fatalities caused by accidents involving motorcyclists are also in the rise due to the increasing trend. Hence, motorcyclists are encouraged to use alternative modes of transportation that are safer in the attempt to minimise losses. As a result, a policy ought to be created to enhance urban transportation service and control motorcycle proprietorship. The current research that lays the groundwork aims to contribute a more elaborated analysis on motorcycle user mode decision conduct as well as an excellent comprehension of the conceivable efforts that can be taken to support motorcyclists to shift to a safer mode of transportation, particularly bus. In the current research work, the binary logit mode choice model was created for two elective modes in order to distinguish the separate practices of motorcyclists and bus users and assess their reactions to a situation that can minimize both time and expenses involved in bus travel. In addition, it should be noted that this paper surveyed a total of 327 travellers from Greater Cairo Region (GCR) in Egypt, the bus users were identified through revealed preference, while the motorcyclists were identified through revealed and stated preference surveys. In this case, travel time, travel cost, age, sexual orientation, income level, trip purpose, education level, and privacy significantly influence motorcycle user mode decision conduct. The likelihood of motorcyclists to utilize the use of buses was additionally analyzed dependent on a situation of minimized bus travel time and travel cost. These elements are very important in a program that attempts to draw in motorcyclists to utilize public transport, particularly bus. The outcomes can help the process of decision making on all levels in assigning the necessary assets prudently for the advancement of urban transportation services, reduced number of road traffic crashes, and increased road safety. This examination, which is the first of its sort in Egypt, assesses the model choice behaviour for motorcyclists

Stated Preference Survey Pivoted on Revealed Preference Survey for Evaluating Employer-Based Travel Demand Management Strategies

2017 ◽  
Vol 2651 (1) ◽  
pp. 108-117 ◽  
Author(s):  
M. Sami Hasnine ◽  
Adam Weiss ◽  
Khandker Nurul Habib
Keyword(s):  
Confidence Rating ◽  
Travel Demand ◽  
Stated Preference ◽  
Probability Model ◽  
Demand Management ◽  
Revealed Preference ◽  
Empirical Models ◽  
Efficient Design ◽  
Travel Demand Management ◽  
Commuting Mode

This paper presents a study of commuters’ responses to various employer-based transportation demand management (TDM) strategies that was conducted in the Region of Peel, Ontario, Canada. The study involves design and implementation of a web-based survey of daily commuting mode choices and an efficient design-based stated preference (SP) experiment on the mode choice effects of potential employer-based TDM strategies. For the SP experiments, the survey also collected an elicited confidence rating from the respondents. The survey of 835 random commuters was conducted in fall 2014 and spring 2015. The paper uses empirical models of mode choices (revealed and stated) and an ordered probability model of the elicited confidence rating information to evaluate the data quality. The empirical models reveal that parking cost, monthly parking scheme, indoor parking facilities, emergency ride home, and bike share had higher impacts on commuting mode choices than did bike access facilities and a carshare strategy at the workplace. In relation to respondents’ confidence on SP responses, commuters with a higher number of cars in the household and with longer commuting distances seemed more certain and confident in their responses than did others. In addition, females were found to be more confident when answering SP choice questions.

scholarly journals Mode choice analysis using discrete choice model from transport user (Case study: Jakarta LRT, Indonesia)

2018 ◽  
Vol 181 ◽  
pp. 03001
Author(s):  
Dwi Novi Wulansari ◽  
Milla Dwi Astari
Keyword(s):  
Discrete Choice ◽  
Public Transportation ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Light Rail ◽  
Choice Analysis ◽  
Mode Choice Model

Jakarta Light Rail Transit (Jakarta LRT) has been planned to be built as one of mass rail-based public transportation system in DKI Jakarta. The objective of this paper is to obtain a mode choice models that can explain the probability of choosing Jakarta LRT, and to estimate the sensitivity of mode choice if the attribute changes. Analysis of the research conducted by using discrete choice models approach to the behavior of individuals. Choice modes were observed between 1) Jakarta LRT and TransJakarta Bus, 2) Jakarta LRT and KRL-Commuter Jabodetabek. Mode choice model used is the Binomial Logit Model. The research data obtained through Stated Preference (SP) techniques. The model using the attribute influences such as tariff, travel time, headway and walking time. The models obtained are reliable and validated. Based on the results of the analysis shows that the most sensitive attributes affect the mode choice model is the tariff.

scholarly journals Railway and road discrete choice model for foreign trade freight between Antioquia and the Port of Cartagena

2016 ◽  
Vol 36 (3) ◽  
pp. 22 ◽  
Author(s):  
Juan Diego Pineda Jaramillo ◽  
Iván Reinaldo Sarmiento Ordosgoitia ◽  
Jorge Eliécer Córdoba Maquilón
Keyword(s):  
Qualitative Research ◽  
Discrete Choice ◽  
Logit Model ◽  
Choice Model ◽  
Stated Preference ◽  
Revealed Preference ◽  
Freight Transportation ◽  
Multinomial Logit Model ◽  
Discrete Choice Model ◽  
The Cost

Most Colombian freight is transported on roads with barely acceptable conditions, and although there is a speculation about the need for a railway for freight transportation, there is not a study in Colombia showing the variables that influence the modal choice by the companies that generate freight transportation. This article presents the calculation of demand for a hypothetical railway through a discrete choice model. It begins with a qualitative research through focus group techniques to identify the variables that influence the choice of persons responsible for the transportation of large commercial companies in Antioquia (Colombia). The influential variables in the election were the cost and service frequency, and these variables were used to apply a Stated Preference (SP) and Revealed Preference (RP) survey, then to calibrate a Multinomial Logit Model (MNL), and to estimate the influence of each of them. We show that the probability of railway choice by the studied companies varies between 67% and 93%, depending on differences in these variables.

scholarly journals Ridesourcing and Travel Demand: Potential Effects of Transportation Network Companies in Bogotá

2020 ◽  
Vol 12 (5) ◽  
pp. 1732 ◽  
Author(s):  
Daniel Oviedo ◽  
Isabel Granada ◽  
Daniel Perez-Jaramillo
Keyword(s):  
Public Transportation ◽  
Travel Demand ◽  
Transportation Network ◽  
Open Data ◽  
Primary Data ◽  
Small Scale ◽  
Modal Shift ◽  
Economic Implications ◽  
Before And After ◽  
Transportation Network Companies

This paper proposes a modal-shift analysis methodology based on a mix of small-scale primary data and big data sources to estimate the total amount of trips that are reallocated to transportation network companies (TNCs) services in Bogotá, Colombia. The analysis is focused on the following four modes: public transportation, private vehicles, conventional taxis, and TNC services. Based on a stated preferences survey and secondary databases of travel times and costs, the paper proposes a methodology to estimate the reallocation of travel demand once TNCs start operating. Results suggests that approximately one third of public transportation trips are potentially transferred to TNCs. Moreover, potential taxi and private vehicle–transferred trips account for almost 30% of the new TNC demand. Additionally, approximately half of the trips that are reallocated from public transport demand can be considered as complementary, while the remaining share can be considered as potential replacing trips of public transportation. The paper also estimates the potential increase in Vehicle-km travelled in each of the modes before and after substitution as a proxy to the effects of demand reallocation on sustainability, finding increases between 1.3 and 14.5 times the number of Vehicle-km depending on the mode. The paper highlights the role of open data and critical perspectives on available information to analyze potential scenarios of the introduction of disruptive technologies and their spatial, social, and economic implications.

Estimating Price and Service Elasticity of Urban Transportation Demand with Stated Preference Technique: Case in Korea

2003 ◽  
Vol 1839 (1) ◽  
pp. 167-172 ◽  
Author(s):  
Sungwon Lee ◽  
Yeong Heok Lee ◽  
Jee Hyung Park
Keyword(s):  
Travel Demand ◽  
Stated Preference ◽  
Demand Management ◽  
Parameter Estimate ◽  
Demand Elasticity ◽  
Fuel Price ◽  
Travel Demand Management ◽  
Passenger Car ◽  
Transportation Demand ◽  
Car Travel

Price and service elasticities of passenger car travel are estimated using stated preference and sample enumeration methodology. Moreover, the effects of hypothetical travel demand management policies are analyzed by changes on modal share using the elasticity estimates. The elasticity of passenger car travel with fuel price is estimated to be within the range of −0.078 to −0.171. The parameter estimate of the fare variable is estimated to be statistically insignificant in every subgroup of car users. This finding suggests that fare policies are relatively ineffective for increasing transit modal shares in Korea. Meanwhile, car users' responsiveness to changes in parking costs is estimated to be much higher than for fuel cost. This suggests that parking regulations or pricing policies may be effective in reducing travel by passenger car. The elasticity with in-vehicle time, which is a key attribute of public transport amenities, is estimated to be particularly high, implying that policy measures such as introducing express buses or express urban trains could be effective in reducing passenger car travel. The demand elasticity of service levels of mass transit represented by the degree-of-crowdedness proxy turns out to be very high. Reducing crowdedness in public transit can be very effective in attracting more passengers, or at least in retaining current patronage.

scholarly journals Can Road Toll Convince Car Travelers to Adjust Their Departure Times? Accounting for the Effect of Choice Behavior under Long and Short Holidays

2020 ◽  
Vol 12 (24) ◽  
pp. 10470
Author(s):  
Haiyan Zhu ◽  
Hongzhi Guan ◽  
Yan Han ◽  
Wanying Li
Keyword(s):  
Traffic Congestion ◽  
Choice Behavior ◽  
Road Traffic ◽  
Stated Preference ◽  
Revealed Preference ◽  
The Road ◽  
Departure Time ◽  
Departure Time Choice ◽  
Mnl Model ◽  
Peak Travel

The adjustment of road toll is an important measure that can alleviate road traffic congestion by convincing car travelers to travel during off-peak times. In order to reduce congestion on the expressway on the first day of a holiday, factors that affect the departure times of holiday travelers must be comprehensively understood to determine the best strategy to persuade car travelers to avoid peak travel times. This paper takes holiday car travelers as the research object and explores the characteristics and rules of departure time choice behavior for different holiday lengths. Based on Utility Maximization Theory, a multinomial logit (MNL) model of departure time choice for a three-day short holiday and a seven-day long holiday was established. Model calibration and elastic analysis were carried out using Revealed Preference/Stated Preference (RP/SP) survey data. Additionally, the influence of the highway toll policy on departure times for long and short holidays was analyzed. The results show that the rate of first-day departures is much higher than that of other departure times for both short and long vacations under the current policy of free holiday passage on highways. Factors such as trip duration, size of the tourist group, the number of visits, travel range, travel time, monthly income, occupation, age and road toll have a significant influence on the departure time decisions of holiday car travelers, and the effect and degree of influence are markedly different for different holiday lengths. The effects of tolls for each departure time and different pricing scenarios on the choice behavior of travelers are different between long and short holidays. Furthermore, the effectiveness of the road toll policy also varies for travelers with different travel distances. This study can provide useful information for the guidance of holiday travelers, the management of holiday tolls on expressways and the formulation of holiday leave time.

World Expo 2010 Promotes the Reduction in Carbon Emissions of Urban Transport

2014 ◽  
Vol 522-524 ◽  
pp. 1826-1830
Author(s):  
Lin Hui Zeng ◽  
Guang Ming Li
Keyword(s):  
Public Transport ◽  
Public Transportation ◽  
Carbon Emission ◽  
Travel Demand ◽  
Demand Management ◽  
Ghg Emissions ◽  
Vital Role ◽  
Urban Transport ◽  
Transport Sector ◽  
Travel Demand Management

Transport sector is one of the main sources of anthropogenic greenhouse gases (GHG) emissions. Comprehensive countermeasures are needed in cities to mitigate transport GHG emissions. After reviewing green traffic measures that implemented by Shanghai since bidding for Expo 2010, this paper analyzes the achievement that Shanghai has made in carbon mitigation. The results showed that travel demand management and the constrcution public transportation infrastructure promoted by the event played a vital role in promoting mode shift to form public transport oriented traffic system. Carbon emission intensity of Shanghais urban transport declined steadily from 1.66 kg/trip to 1.55 kg/trip. The CO2 reduction attributable to mode shifts amounted to 4.99 million tons. It demonstrated that Shanghai Expo has promoted the city in carbon emission reduction through public transport improvement, new energy vehicles innovation, car growth restriction measures and green commuting initiate.

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