Mode Choice Behavior Research Articles

Modeling railway station access mode choice behaviour and rail travel demand

Modeling railway station access mode choice behaviour and rail travel demand

Analyzing the trade transportation and its demand on multimodal transportation system between China and Koreas

Purpose This paper aims to understand the trade transportation situation between China and Koreas, and to explore the possibility of establishing the surface transportation corridor between China and Koreas in the future. Moreover, the paper also intends to find out the mode choice behaviors of shippers, which can be used to analyze the substitute effects of the surface modes on the water one. Design/methodology/approach The paper first analyzes the Sino-Korean bilateral trade and the corresponding trade transportation between China and Koreas. Secondly, it presents the surface transportation network between China and Koreas, and analyzes the warming relations between the North and South. Finally, the modal split of trade transportation between China and Koreas is estimated by establishing a mode choice model based on a questionnaire survey. Findings With the increasingly stable political environment and the physical highway and railway connections, the surface transportation network would become possible. Moreover, the shippers need the multimodal transportation system between China and Koreas, and many shippers would select road or rail mode if a suitable road or rail network were available. Especially, between China and South Korea, the road, rail and water mode may be used evenly, while the road mode may play a more important role between China and North Korea. The surface modes would have a huge substitute effect on the water mode. Originality/value The existing literature conducted research mainly from the perspective of economy and geopolitics, while the topics of transportation between China and Koreas are rarely concerned. This paper intends to throw some light on the situation of the trade transportation between China and Koreas, consider the potential of relation improvement on the Korean Peninsula proactively and study the surface transportation issues between China and Koreas.

Mode shift at bottleneck increasing transit dispatch in peak time

For attracting more auto commuters to shift to transit mode and mitigating congestion at a bottleneck in morning &rush hour, additional dispatches of transit are operated during peak time. Classical bottleneck model combining with Logit-based discrete choice formula is extended to investigate commuters’ mode choice behaviors between private car and public transit. The existence of bi-mode user equilibrium when tolling auto commuter is proofed, and waiting time and time delay costs are formulated in two modes when additional buses are dispatched. Numerical experiments are conducted to examine mode split patterns and aggregate travel cost when additional dispatching service interval varying. Our results show the system aggregate trip cost would reduce prominently when extra buses are added into runs in appropriate time. Especially when waiting time equals 0.65 hour for auto commuters, the system aggregate trip cost would reduce by 70% in theory.

The Response of Urban Travel Mode Choice to Parking Fees considering Travel Time Variability

Increasing automobile use leads to higher costs for traveling associated with emissions, congestion, noise, and other impacts. One option to address this is to introduce high parking charges to reduce the demand for automobile use and encourage the travel mode switch to public transport. To estimate commuters’ mode choice behavior in response to high parking fees, commuters from Nanjing completed an individually customized discrete choice survey in which they chose between driving and taking the bus or metro when choices varied in terms of time and cost attributes. Multinomial logit models were used to estimate commuters’ responses to high parking charges. In the models, the variability of travel times is considered and analyzed in the stated mode choice models. The results suggest that increases in costs of driving will lead to a great reduction in driving demand. The travel time reliability ratio is 0.50 and the value of each minute late is almost 5.0 times more than the average travel time with the restriction of the maximum allowed delays. The methods used in this study could be adopted to estimate the effect of variable pricing strategies on mode choice responses for different trip purposes. The high value given to travel time variability has implications for transport policy in terms of decision making with respect to new pricing strategies. Moreover, the valuation of travel time savings taken into account in this study would be helpful to better understand the effect of high parking fees.

Comparative Study of Logit and Weibit Model in Travel Mode Choice

To quantify travel demand, it is necessary to understand the travelers’ mode choice behavior. The Logit model is widely used in travel mode choice because of its closed form. Nevertheless, the variance of the utility function is unchanged in Logit-based models, indicating that the perceived error of the traveler on the option is fixed as the utility changes, which is inconsistent with the actual situation. While in Weibit-based models, travelers’ perception error of options grows with the increase of the utility. Moreover, the relative difference is captured, and the asymmetric property exists, which is different from Logit-based models. This paper contributes to the literature by comparing the performances of the Logit-based and Weibit-based models. In this article, six discrete choice models for travel mode choice are discussed based on data of Swiss metro, which includes multinomial Logit model, multinomial Weibit model, and derived models. The Weibit-based models outperform the Logit-based models, considering with the adjusted likelihood ratio index of all models in this paper.

An Intercity Freight Mode Choice Model : A Case Study of High Speed Rail Link Northern Line Thailand (Bangkok – Chiangmai)

This paper presents a model capturing the intercity freight mode choice behaviour in high-speed rail system from Bangkok to Chiangmai. The model is developed based on the stated preference data collected from 800 freight operators, wholesaler, retailer, and people. The results show that, when the high-speed rail system from Bangkok to Chiangmai are developing in the future, the suitable products for high-speed rail system are types of an express mail service (EMS), air cargo, gold, jewellery, gold accessories, computer circuit boards, high prices agricultural products such as fruit, and flowers. Most of determining the selling price will fluctuate with the speed of transport and damage impairment of the product. With the application of discrete choice models, the results show that, aside from travel cost and time, loading and unloading, delays time, frequency are statistically significant. The application of model indicated that the holder and freight forwarder which in the line of high-speed rail (Bangkok – Chiangmai) tend to use rail-transport such as double-track rail is 27.71%, high-speed rail is 11.18% and the most is trucks 56.51% which is a policy development point loading and unloading, multimodal transportation efficiency and safety of the portion of the freight high-speed rail increased.

Modeling travel mode choice of young people with differentiated E-hailing ride services in Nanjing China

E-hailing ride service (ERS) has become increasingly popular globally and is changing the urban mobility landscape. There is insufficient research effort in understanding the impact of ERS on travel behavior, in particular among young people. This paper aims to start filling that research gap by first collecting mode choice preference data through a stated preference survey in City of Nanjing, China and then applying nested logit (NL) models and a series of post-estimation analysis to address a number of key research questions of mode choice behavior without and with ERS. Three ERS modes are considered in the Chinese context: DiDi Taxi (D-Taxi), DiDi Express (D-Express), and DiDi Premier (D-Premier), all provided by DiDi Chuxing, the dominant ERS service provider in China. The study finds that age makes little difference in mode choice preference when ERS is introduced between the two age groups considered (18–30 and 31–45). The study results also suggest that young travelers are naturally drawn to ERS for what it represents (a technology innovation) and its business (pricing) model. ERS appears to be a competitive alternative to the conventional modes especially when they are under performed. The study also finds that ERS will likely increase vehicle kilometers traveled (VKT) considerably, which will lead to increase in on-road vehicular emissions, unless some mechanism to switch users to ridesharing is in place.

Factors Affecting Mode Choice in Accessing Railway Station Study in Nakhon Ratchasima

This paper explores the travel mode selection in accessing the railway station. Because the accessibility services were outstandingly undeveloped for over a decade, it is contradicting the growth rate of population and travel demand. Mode choice investigation would explain the practical suggestion of traveler's behavior. The study will give the result of significant factors, which affected mode choice behavior in the specific study area by using field survey and questioners interview method. The binary logistic regression analysis is the core of the study, another technique, a hierarchical technique, will be applied to gain model performance. The satisfaction factors are representing traveler experience in transport modes accessing the railway station tested in modeling processes. Thus, the results can contribute to a better understanding of the significant factors of transport mode selection, and moreover, the expectation for long term management and improvement of the public transport systems.

Influence of psychological factors in mode choice decision making: A structural equation modeling approach

This study investigates the influence of psychological factors in the mode choice of private or public transport among commuters. Theory of Planned Behavior (TPB) was adopted as a theoretical basis for incorporating the influence of psychological factors in mode choice decision making. TPB is a theory designed to predict and explain human behavior in specific contexts. Attitude, subjective norm, perceived behavioral control and intention are the factors considered in TPB. A questionnaire survey was conducted among 400 commuters in the city of Calicut, Kerala, India. Structural equation modeling was adopted to test the relations stated in the Theory of Planned Behavior. ‘Attitude’ was identified as the most significant factor influencing the intention to use public transit. The results of the study are useful to obtain a better understanding of mode choice behavior.

A semi-compensatory choice model with probabilistic choice set: combining implicit choice set within probabilistic choice set formation

The standard random utility model assumes a fully rational and compensatory choice behaviour. However, various research studies have proven that non-compensatory /semi-compensatory choice behaviour is more realistic. This paper proposes a semi-compensatory framework for the discrete choice model that combines probabilistic choice set formation along with implicit choice constraints in choice making. It combines the Independent Availability Logit (IAL) with Implicit Constrained Multinomial Logit model (CMNL). The model is applied to investigate the mode choice behaviour of the Ottawa-Gatineau regions of Canada’s capital by using the household travel survey data. The explanatory power and elasticity measures of the proposed model are compared with IAL and MNL models. It is found that the IAL-CMNL model outperforms both IAL and MNL models and can reproduce the choice set formation process more effectively. The empirical investigation shows that the IAL-CMNL model results in relatively higher tolerance and softer constraints for cut-off violations compared to the IAL model. Elasticity calculations and outcomes of this research highlight the importance of capturing choice set formation and constrained choice behaviour in the choice modelling.

Analysis of the potential demand for battery electric vehicle sharing: Mode share and spatiotemporal distribution

Carsharing is considered one of the solutions to urban transport problems. As a new mode in the urban transport system in China, there are still initial questions of how carsharing will perform and what the impacts will be. Accordingly, this study considers battery electric vehicle sharing and investigates its potential demand, with Beijing as the case study. A nested logit model is established and calibrated to analyze mode choice behavior. Further, real trip data is used to estimate the potential demand for battery electric vehicle sharing. In addition, the temporal and spatial distribution of potential demand, the impact of battery electric vehicle sharing on the mode split, and the impact of pricing strategies are analyzed. The results show that an optimistic mode split of battery electric vehicle sharing is 4.23% when the average distance between travelers and stations is 0.5 km. The main source of potential demand is public transport. However, the substitution effect of battery electric vehicle sharing for private vehicles is weak. The potential trips are concentrated in the morning peak period, mainly starting in residential or integrative areas, and ending in commercial areas or green spaces. Commuting and long-distance trips are more sensitive to decreases in price, such that they are more likely to be completed as battery electric vehicle sharing trips. This price decrease could also increase the potential trip ratio during the evening peak period. These findings are useful to governments and operators for implementing policies such as station planning, relocation, and pricing strategies.

Modelling Pedestrians’ utilization of crossing facilities along urban streets

A pedestrian intending to cross roadway has to decide whether to uses crossing facility or to cross the street illegally or recklessly. An incorect decision will expose the pedestrian to risk of accident. Pedestrians are always characterized as the most vulnerable road users. Some scholars have studied the risk of crossing a road, laying an emphasis on walk trip frequency or mode choice behaviors. Quite differently, this research is one of the first to probe into, and model, the utilization of zebra crossings among pedestrians in Malaysia. The goal of this paper is to work on a sustainable pedestrian zebra crossing utilization index model taking guidance from the pedestrian and Zebra characteristics. The paper sheds new light on the Pedestrian’ decision towards Zebra crossing, where pedestrian utilization decision of Zebra crossing served to optimize the result of a model created for utilisation choice behavior. Data from the observation done across 9 study locations along urban streets was collected, binary logit model (BLM) techniques were employed for result analyses. The results show that among the different variables, vehicle speed, pedestrian age and gender, and presence of baggage were discovered to be significant and had a direct effect on the probability of pedestrians’ utilisation decision. It is anticipated that this study would improve the understanding of relevant parties, improve pedestrians’ crossing behaviors, and lead to better pedestrians crossing behaviors.

Analysis of Emergency Evacuation Modal Choice Behavior with Spatial Indicators: Case Study in Xi’an, China

To reduce the impact of a natural or man-made disaster, an evacuation is often implemented to transfer the population in the potentially impacted area to a safe zone. Evacuation is an effective measure for dealing with emergency events. This paper presents a multinomial logit model for modal choice behavior in a short-notice emergency evacuation, which incorporates spatial indicators into the utility function. The study examined the determinants of evacuees’ modal choice for three evacuation distances and analyzed determinants impacting the mechanism of the modal choice decision process. The data collected in Xi’an was used to provide empirical evidence for the relationship between spatial indicators and modal choice behavior. The findings of this study will help emergency planners and policy-makers develop strategies for evacuation planning and will enable a better understanding of emergency modal choice behaviors.

Mode shift impacts of optimal time-dependent congestion pricing in large networks: A simulation-based case study in the greater toronto area

This paper presents a case study on commuter’s departure time, route and mode choice responses to optimized tolling in the Toronto, Ontario, Canada. The study integrates a toll optimization component into an integrated framework of econometric departure time choice, dynamic traffic assignment model, and random utility maximization (RUM) based mode choice model. An iterative optimization algorithm is used to generate optimal tolling structure which explicitly considers heterogeneous user preferences through econometric departure time choice modelling component. The mode choice component is exogenously retrofitted in an integrated econometric departure time choice modelling component and dynamic operational traffic assignment model to capture individual mode choice behaviour in response to variable congestion pricing. The integrated model results show that individuals are more likely to switch driving routes and departure times than commuting modes when making tradeoffs between schedule delay cost, travel time cost, and toll cost. It is found that the optimal toll scenario improves the network-wide travel time. The modelling framework presented in this study can test a wide range of policy scenarios including the time-variable tolling of congested highways, and high occupancy toll lanes. While the integrated framework presented here is tested at a large scale on the Greater Toronto Area (GTA), we believe the approach can be applied to large-scale networks globally where the objective is seeking the best network-wide spatial and temporal traffic distribution.

Identification of Determinant Factors Influencing Modal Choice Behavior and Satisfaction Level of Commuters: A Case of Rajshahi City

The term commuter is defined as a person who travels some distance to work on a regular basis Asensio et al. [1]. A large number of commuters are attracted.

Analysis of Travel Mode Choice Behavior Considering the Indifference Threshold

An effective way to optimize traffic structures is by changing travel costs, thereby moving travelers from private transportation to public transportation. However, according to the existing studies, the traveler will not transfer from one mode to another unless the change in travel utility is greater than the indifference threshold. Therefore, the “indifference threshold” is one of the most important factors influencing a traveler’s choice of behavior. This study defines the “indifference threshold” as the traveler’s sensitivity to changes in travel utilities. In the framework of the theory of planned behavior (TPB), a structural equation model (SEM) considering the indifference threshold is established to analyze a traveler’s mode choice behavior. The analysis results showed that a travelers’ sensitivity to changes in travel utilities has the greatest impact on mode-choice behavior intentions and mode choice behavior. Perceptual behavior control has the strongest influence on travel choice behavior. In addition, in order to further explore the heterogeneity of a traveler’s behavior, the travelers were subdivided into four types, by establishing a latent class model (LCM) considering the indifference threshold. Finally, different traffic management suggestions are proposed for different types of travelers.

Modelling the impact of fused grid network design on mode choice behaviour

IntroductionThe fused grid (FG) is a an alternative model developed by the Canada Mortgage and Housing Corporation to combine the easy orientation and connectivity of the traditional grid pattern with the land use efficiency and quietness of the contemporary cul-de-sac pattern. One of the main distinguishing principles of the FG design relative to contemporary neighbourhood patterns are the FG's higher non-motorized network connectivity versus vehicle network connectivity. This paper reports on research related to the influence of FG design principles on non-motorized use for home-to-work commuting and home-to-shopping trips. MethodsThis study uses a macroscopic-level approach to investigate the impact of FG on mode choice behaviour through hypothetically retrofitting an existing neighbourhood in Kelowna, BC, using the FG design principles. First, the change in travel distance and time due to retrofitting the neighbourhood was estimated using ArcGIS. Then, the modal shift in home-to-work and home-to-shopping trips due to the change in travel distance and time was estimated using multinomial logit mode choice models that were developed using the 2013 Okanagan household travel survey. ResultsThe results suggest that the influence of travel time on choosing the auto mode is much stronger and more significant for home-to-work trips compared to home-to-shopping trips. The results also show that retrofitting the road network resulted in reducing auto modal share by 13 percent and increasing non-motorized modes by 64 percent for home-to-work trips. However, an insignificant shift in modal share towards non-motorized modes for home-to-shopping trips was found. ConclusionsIn conclusion, this study demonstrated the effectiveness of the FG principles in reducing auto use and increasing non-motorized modes use for home-to-work trips. In addition, the study revealed that infrastructure investments related to providing more accessibility for non-motorized users might have more impact on decreasing auto use compared to restricting vehicular network connectivity.

How technology commitment affects mode choice for a self-driving shuttle service

Although automation of motorized vehicles has the potential to transform public transport as we know it, prospective users are still skeptical. Trials with shared autonomous vehicles (AVs) offer an opportunity to assess future demand in a more realistic setting. In the context of an autonomous shuttle service trial operating on public road-space in Switzerland, we carried out a mode choice experiment with a random sample of 773 potential users. Study participants could choose between a rental bike, walking, and the autonomous bus at varying costs, travel time, occupation, and weather conditions. Based on attitudinal survey items on technology commitment, consisting of technology acceptance, control, and competence that were integrated into a latent variable model, we study how technology commitment affects mode choice behaviour. While results show a comparably low willingness to pay, they also indicate that technology acceptance is a robust predictor of autonomous bus usage. In line with the technology adoption life cycle argument, potential users are currently mainly technology enthusiasts. Thus, in order to also “bring on board” the less technophile parts of the population, improved communication of AV benefits will be required.

Travel-To-School Mode Choice Modelling Employing Artificial Intelligence Techniques: A Comparative Study

Many techniques including logistic regression and artificial intelligence have been employed to explain school-goers mode choice behavior. This paper aims to compare the effectiveness, robustness, and convergence of three different machine learning tools (MLT), namely the extreme learning machine (ELM), support vector machine (SVM), and multi-layer perceptron neural network (MLP-NN) to predict school-goers mode choice behavior in Al-Khobar and Dhahran cities of the Kingdom of Saudi Arabia (KSA). It uses the students’ information, including the school grade, the distance between home and school, travel time, family income and size, number of students in the family and education level of parents as input variables to the MLT. However, their outputs were binary, that is, either to choose the passenger car or walking to the school. The study examined a promising performance of the ELM and MLP-NN suggesting their significance as alternatives for school-goers mode choice modeling. The performances of the SVM was satisfactory but not to the same level of significance in comparison with the other two. Moreover, the SVM technique is computationally more expensive over the ELM and MLP-NN. Further, this research develops a majority voting ensemble method based on the outputs of the employed MLT to enhance the overall prediction performance. The presented results confirm the efficacy and superiority of the ensemble method over the others. The study results are likely to guide the transport engineers, planners, and decision-makers by providing them with a reliable way to model and predict the traffic demand for transport infrastructures on the basis of the prevailing mode choice behavior.

Studying the tastes effecting mode choice behavior of travelers under transit service disruptions

Public transit (PT) service disruption is a phenomenon which is quite common across the world and is characterized by significant delays or cancelations of transit services. These disruptions can substantially affect commuter trips, particularly in cities with significant PT mode share, which triggers a change in both short-term and long-term traveler behavior. While service disruptions due to cancelations have been well studied in the literature, there has been limited work on studying the impacts of disruptions due to significant service delays on traveler behavior. This study analyzes data from a joint revealed preference cum stated preference (RP-SP) survey conducted in the Chicago metropolitan area in the US to understand traveler’s mode choice under the two forms of PT service disruptions. The trip specific attributes of the other competing alternatives for an individual were extracted using Google’s application programming interface (API) in the survey. The collected data is analyzed using the latent class choice model formulation. The results show that travelers find canceled PT service situations 3 times more onerous than service disruptions due to delays. While the value of travel time savings under disruptions due to delays and cancelations for rail users is found to be around US$10/hr and US$32/hr respectively, for bus users the values are US$19/hr and US$43/hr respectively. The findings from this study provide separate sets of preferences under each disruption scenario to planners. This information will be useful in planning remedial actions aimed at minimizing the impact of transit service disruptions.