An empirical study on travel demand management modeling based on discrete choice method

In view of the problem that the requirements of travel demand management and traffic policy-sensitivity are ignored during the establishment process of the travel demand forecasting model, a discrete-choice-based travel demand forecasting model is proposed to demonstrate its applicability to travel demand management. A car-bus discrete choice model is established, including three variables, i. e,, individual socioeconomic characteristics, time, and cost, and the traffic policy-sensitivity is evaluated through two kinds of traffic policies： parking charges and bus priorities. The empirical results show that travel choice is insensitive to the policy of parking charges as 88. 41% of the travelers are insensitive to parking charges; travel choice is, however, sensitive to the policy of bus priorities as 67.70% of the car travelers and 77.02% of the bus travelers are sensitive to bus priorities. The discrete-choice-based travel demand forecasting model is quite policy-sensitive and also has a good adaptability for travel demand management when meeting the basic functions of the demand forecasting model.

Big Data-Driven Residents’ Travel Mode Choice Choice: A Research Overview

The research on residents'travel mode choice mainly studies how traffic flows are shared by different traffic modes,which is the prerequisite for the government to establish transportation planning and policy.Traditional methods based on survey or small data sources are difficult to accurately describe,explain and verify residents'travel mode choice behavior.Recently,thanks to upgrades of urban infrastructures,many real-time location-tracking devices become available.These devices generate massive real-time data,which provides new opportunities to analyze and explain resident travel mode choice behavior more accurately and more comprehensively.This paper surveys the current research status of big data-driven residents'travel mode choice from three aspects:residents'travel mode identification,acquisition of travel mode influencing factors,and travel mode choice model construction.Finally,the limitations of current research and directions of future research are discussed.

Joint analysis of urban shopping destination and travel mode choice accounting for potential spatial correlation between alternatives

In recent years,there have been important developments in the joint analysis of the travel behavior based on discrete choice models as well as in the formulation of increasingly flexible closed-form models belonging to the generalized extreme value class.The objective of this work is to describe the simultaneous choice of shopping destination and travel-to-shop mode in downtown area by making use of the cross-nested logit(CNL) structure that allows for potential spatial correlation.The analysis uses data collected in the downtown areas of Maryland-Washington,D.C.region for shopping trips,considering household,individual,land use,and travel-related characteristics.The estimation results show that the dissimilarity parameter in the CNL model is 0.37 and significant at the 95% level,indicating that the alternatives have high spatial correlation for the short shopping distance.The results of analysis reveal detailed significant influences on travel behavior of joint choice shopping destination and travel mode.Moreover,a Monte Carlo simulation for a group of scenarios arising from transportation policies and parking fees in downtown area,was undertaken to examine the impact of a change in car travel cost on the shopping destination and travel mode switching.These findings have important implications for transportation demand management and urban planning.

Suburban travel mode choice considering transit accessibility of stops in public transport

To analyze the influence of the transit accessibility of stops on the travel mode choices of suburban residents,the number of the lines passing by the stops within an accessible range of the resident origin and destination(OD)points and the average waiting time are used as the indexes of the transit accessibility of stops.Due to the correlation between travel time and accessible range,the transit accessibility of stops is contrasted as piecewise variables constrained by travel time.Taking the Jimei District of Xiamen,China,as an example,a binary logistic regression model of the suburban travel mode choice is constructed.The results show that it is necessary to construct transit accessibility of stops as piecewise variables.With a higher transit accessibility of stops,more residents will choose public transport.The choice of the travel mode is correlated with family attributes and personal characteristics.Morning and evening peak hours and travel distance have little effect on the choice of travel mode.Compared with the travel in urban areas,residents often chose public transport for travel within the suburbs.This research provides a basis for encouraging public transportation priority policies and decision making for transport planners in the suburbs.

Island Holidays Remain First Choice during Spring Festival Overseas Travel

The Chinese New Year is just around the corner.Data released by a number of travel agencies show that the Spring Festival outbound travel market is booming.The number of tickets booked have increased by 32 percent year on year,and the prices have also increased by 10 percent.In addition,data from travel agency platforms show that economy-class air tickets for some popular travel destinations during the Spring Festival period have been sold out,and up to 65 percent fares can be saved by returning home via transit.

Kriging Geostatistical Methods for Travel Mode Choice: A Spatial Data Analysis to Travel Demand Forecasting

This paper aims to compare the results of two techniques of Kriging (Ordinary Kriging and Indicator Kriging) that are applied to estimate the Private Motorized (PM) travel mode use (car or motorcycle) in several geographical coordinates of non-sampled values of the concerning variable. The data used was from the Origin/Destination and Public Transportation Opinion Survey, carried out in 2007/2008 at S?o Carlos (SP, Brazil). The techniques were applied in the region with 110 sample points (households). Initially, Decision Tree was applied to estimate the probability of mode choice in surveyed households, thus determining the numeric variable to be used in Ordinary Kriging. For application of Indicator Kriging it was used the variable “main travel mode” in a discrete manner, where “1” represented the use of PM travel mode and “0” characterized others travel modes. The results obtained by the two spatial estimation techniques were similar (Kriging maps and cross-validation procedure). However, the Indicator Kriging (KI) obtained the highest number of hit rates. In addition, with the KI it was possible to use the variable in its original form, avoiding error propagation. Finally, it was concluded that spatial statistics was thriving in travel demand forecasting issues, giving rise, for the both Kriging methods, to a travel mode choice surface on a confirmatory way.

A tour-based analysis of travel mode choice accounting for regional transit service

The aim of this work is to explore the impact of regional transit service on tour-based commuter travel behavior by using the Bayesian hierarchical multinomial logit model, accounting for the spatial heterogeneity of the people living in the same area.With two indicators, accessibility and connectivity measured at the zone level, the regional transit service is captured and then related to the travel mode choice behavior. The sample data are selected from Washington-Baltimore Household Travel Survey in 2007,including all the trips from home to workplace in morning hours in Baltimore city. Traditional multinomial logit model using Bayesian approach is also estimated. A comparison of the two different models shows that ignoring the spatial context can lead to a misspecification of the effects of the regional transit service on travel behavior. The results reveal that improving transit service at regional level can be effective in reducing auto use for commuters after controlling for socio-demographics and travel-related factors.This work provides insights for interpreting tour-based commuter travel behavior by using recently developed methodological approaches. The results of this work will be helpful for engineers, urban planners, and transit operators to decide the needs to improve regional transit service and spatial location efficiently.

Influence of land use characteristics and trip attributes on commuting mode choice: a case of Nanjing

The effects of socio-demographics, land use characteristics and trip attributes on the commute mode choice are studied with a nested logit （NL） model. Based on the random utility maximum theory, the NL model is formulated. The analysis is carried out in the main area of Nanjing. Direct and cross elasticities are calculated to analyze the effects of travel time and travel cost on the selection of travel mode choice. The results reveal that the non-motorized travel modes are more attractive in the areas with higher housing and employment accessibility and car owners are found to be more likely to commute to work by car. The bus and subway choice probabilities are more sensitive to changes in travel times than to changes in travel costs. In conclusion, a comprehensive public transit system and effective integration of land use and transportation policies help to relieve the traffic congestion levels caused by the increasing urban sprawl.

Love Is Intensified by Absence- Book Review on "The Time Traveler's Wife"

In this paper,a review was finished according to a novel-"The Time Traveler's Wife".It use time travel to explore miscommunication and distance in relationships.A lot of knowledge could be obtained from the passage.

Denial of Sartre's Existentialism in The Time Traveler's Wife

By contrast with Sartre's existentialism,The Time Traveler's Wife depicts another humanistic world.Moreover,such things as meaning,reason,compensation and peace are indispensable in this world.

基于线性密集台阵的2023年甘肃积石山M_(S)6.2地震断层低速带研究

2023年12月18日,甘肃省积石山县发生M_(S)6.2逆冲型地震。该地震发生在祁连活动地块拉脊山北缘断裂带,在断裂两侧曾发生过20余次5级左右中强地震,地震活动频次高,因此研究拉脊山断裂带特征具有重要意义。根据拉脊山断裂走向和此次地震余震分布,在刘集乡布设一条线性密集台阵,利用不同方位的余震事件计算体波的走时延时和放大效应。结果表明,P波和S波分别存在6个采样点(约0.012 s)和15个采样点(约0.03 s)的走时延时,推断出台阵西侧存在一个约150 m宽近似垂直的断层低速带,且该结果与远震P波相似性系数矩阵结果一致。

Tour Level Mode Choice Analysis of Madison Area in Wisconsin

This study is to investigate what factors and how they affect tours (trip chains) behavior. The key issue is the understanding and definition of tour and tour level mode. Also, these definitions should fit for the data. A semi-home based tour definition is stated, and a competing mode based tour mode is defined. Based on the definition, this study used Madison Area Data from National Household Survey to estimate a MNL structured model. It is found that travel distance could be a positive factor for car mode. Meanwhile, the number of trips is also a positive factor for choosing car.

EDITOR＇S CHOICE： FOCUS ON RECENT LITERATURE

In a clinical situation, repair of distal peripheral nerve defects can present a major challenge to neurosurgenns. Construction of tissue-engineered nerves is a novel solution for repairing peripheral nerve defects. The sciatic nerve is the largest peripheral nerve in the body and is known to have a relatively constant anatomical position, sufficient diameter to be easily exposed and operated upon with good repeatability, satisfactory local blood circulation, and is difficult to infect. Owing to these advantages, rat models of sciatic nerve defects are commonly used to study nerve regeneration and repair.

The Sensitivity of Model Results to Specification of Network-Based Level of Service Attributes: An Application of a Mixed Logit Model to Trave Mode Choice

The need for travel demand models is growing worldwide. Obtaining reasonably accurate level of service (LOS) attributes of different travel modes such as travel time and cost representing the performance of transportation system is not a trivial task, especially in growing cities of developing countries. This study investigates the sensitivity of results of a travel mode choice model to different specifications of network-based LOS attributes using a mixed logit model. The study also looks at the possibilities of correcting some of the inaccuracies in network-based LOS attributes. Further, the study also explores the effects of different specifications of LOS data on implied values of time and aggregation forecasting. The findings indicate that the implied values of time are very sensitive to specification of data and model implying that utmost care must be taken if the purpose of the model is to estimate values of time. Models estimated on all specifications of LOS-data perform well in prediction, likely suggesting that the extra expense on developing a more detailed and accurate network models so as to derive more precise LOS attributes is unnecessary for impact analyses of some policies.

EDITOR’S CHOICE: FOCUS ON RECENT LITERATURE

Following spinal cord injury, nerve repair is difficult due to limited regenerative potential of the central nervous system and inability of oli- godendrocytes to guide axonal growth. Several factors pose a challenge for neural regeneration following spinal cord injury. First, glial scars and cavities, which form after spinal cord injury, hinder axonal growth and result in degenerative necrosis of the nerve fibers. Second.

Transportation Users’ Attitudes and Choices of Ride-Hailing Services in Two Cities with Different Attributes

The rapid technological developments in the 21st century created new opportunities for shared-use economy applications around the globe. Among other services, Transportation Network Companies (TNCs) like Uber and Lyft emerged in the US as a transportation alternative that offered a higher level of availability, reliability, and convenience than traditional modes. However, TNCs deployment was also blamed for increases in vehicle miles traveled (VMT) in large cities that embraced TNC services early on. Concerns about TNC adoption are also magnified by the current controversy in policy and legislation as to the regulation of TNCs. These new realizations create a need to examine the transportation users’ attitudes and perceptions regarding ride-hailing service, after nearly a decade of service in the Unites States market. In doing so, this paper compares and contrasts results from two recently completed studies aiming at creating links between socio-demographic factors and TNC use. The paper describes the methods employed to collect the data and presents findings from the analysis of 790 users’ responses in the Birmingham, AL and Miami Beach, FL markets. The study documents preferences and attitudes toward TNCs and highlights similarities and differences in travel behaviors related to local considerations. Moreover, the study uses the Least Absolute Shrinkage and Selection Operator (Lasso) method to identify predictors for TNC use based on the users’ responses in Birmingham and Miami Beach case studies. Vehicle availability and waiting time emerged as the only significant predictors for the Birmingham region whereas vehicle ownership, vehicle use, residency, and prior use of transit and TNC where some of the predictors identified for the Miami Beach area. Understanding the characteristics of TNC users and the leading reasons that drive people towards the use of TNCs services is expected to help transportation agencies and TNC providers in their efforts to plan for transportation services that meet customer needs in the future.

NASH EQUILIBRIA WITHOUT CONTINUITY OF THE CHOICE RULES

The proposal in Alcantud and Alo′s-Ferrer [1], where players that express their tastes according to choice rules facing a competitive situation, is further exploited here. We prove that, under lack of continuity of the choice rules it is also possible to ensure the existence of equilibrium. We shall appeal to general situations that are fulfilled by well-established models, where players have non-transitive preferences of various types.

EDITOR'S CHOICE: FOCUS ON RECENT LITERATURE

Central nervous system injury often leads to incorrect links formed between dendrites and axons in neurons in the regeneration process resulting in histological injury and related dysfunction. The surrounding environment of neurons also inhibits neuronal regeneration by not providing enough support.

Editor's Choice——Retinal ganglion cell damage and regeneration

Retinal ganglion cell apoptosis is considered to be the main cause of loss of vision in glaucoma patients. Microglia cells are phagocytic cells present in the retina. In the retina of glaucoma rat models, microglia cells become activated, which suggests a role for microglia in the pathogenesis of optic nerve injury in glaucoma patients. The retinal ganglion cell is the only cell that can produce action potential in the retina,

Editor's Choice—Adenovirus-mediated gene transfection of stem cells

Neural stem cells transplantation plays an important role in repair and cell replacement therapy for nervous system degenerative diseases. However, the self-repair effects are minimal because of a limited absolute number, as well as the local microenvironment, post-transplantation. A combined treatment utilizing stem cell transplantation and gone therapy can exert a dual effect involving stem cells and neurotrophic factors. The adenovirus carrier is