Access Mode Choice Research Articles

Investigation of modal integration for transit-access trips in motorcycle dependent cities—The case study of Hanoi, Vietnam

Micro-mobility has the potential to address first -mile challenges, improving transit accessibility and encouraging public transit usage. However, users’ acceptability of modal integration between various micro-mobility options and public transit remains largely unexplored in the literature. Our study investigates the user behavior for first-mile options, focusing on four alternatives: walking, bicycling, motorcycling, and bus, to access urban mass rapid transit (UMRT) in Hanoi, Vietnam. Based on data collected from 1380 individuals, a Nested Logit Model (NLM) was proposed to analyze the determinants of users’ acceptability under each access mode option as well as evaluate further impacts of shifts in access mode choice on vehicle-kilometer traveled and emissions. The analysis shows that the availability of access modes might increase UMRT use by 47.83%. While this increase further generates additional vehicle-kilometer traveled due to the increase in park-and-ride users, this is offset overall by the large number of motorcycle users shifting to UMRT. Under the most optimistic scenario, modal integration for transit-access trips leads to an average reduction of 17.7% in net vehicle-kilometer traveled or 14.5% in net CO2 emissions or 10.9% in NOx from private vehicles. Our findings also imply that the introduction of parking fees for bicycling- or motorcycling-access trips, while impactful, does not significantly change UMRT choice. Therefore, the pricing schemes should be a focus of parking planning surrounding stations. Finally, a number of policy suggestions for parking planning and first-mile vehicles are presented.

Unraveling passengers’ preferences: investigating airport access mode choice in Tehran, Iran

Airports are imperative elements in fueling the economic growth of a country by reducing the distances between origins and destinations for the movement of both passengers and goods. Managing ground access modes of travel has become essential as the majority of trips are made by private cars, leading to increased environmental issues and congestion. To alleviate these problems, it is vital to identify the factors that shape air passengers' choice of ground access mode. In this work, we utilized inclusive Revealed Preference data (RP) collected through face-to-face interviews and applied a Multinomial Logit (MNL) model to study passengers' ground access mode choice behavior at Mehrabad International Airport, the busiest airport in Iran. The results showed that different factors such as socioeconomic status, travel characteristics, and distance to the airport affect the mode choice behavior of passengers in reaching the airport.

The Impacts of Low-Carbon Incentives and Carbon-Reduction Awareness on Airport Ground Access Mode Choice under Travel Time Uncertainty: A Hybrid CPT-MNL Model

Developing strategies to incentivize travelers towards adopting sustainable mobility options is one of the effective approaches to mitigate carbon emissions. Using Xi’an Xianyang International Airport as a case study, this study aims to explore the effects of low-carbon incentives and carbon-reduction awareness on airport ground access mode choices. In addition, to account for the complex road environment, an innovative stated preference choice experiment was designed, integrating the factor of travel time uncertainty. Then, a hybrid cumulative prospect theory–Multinomial Logit (CPT-MNL) model was also developed. The estimated results revealed that travelers increasingly prioritize emissions reduction and consciously prefer sustainable mobility options to reach the airport. Furthermore, the potential of low-carbon incentives to encourage public transport usage over private vehicles has been highlighted. Notably, travel time uncertainty had a significant impact on the choice of private cars. When the travel time to the airport is uncertain, travelers exhibit a greater inclination towards selecting public transport. The findings of this study offer nuanced insights for transportation authorities, aiding them in fostering the adoption of sustainable mobility options and achieving carbon reduction objectives.

What is the market potential for on-demand services as a train station access mode?

On-demand mobility services (FLEX) are often proposed as a solution for the first/last mile problem. We study the potential of using FLEX to improve train station access by means of a three-step sequential stated preference survey. We compare FLEX with the bicycle, car and public transport for accessing two alternative train stations. We estimate a joint access mode and train station choice model. Estimating a latent class choice model with different nesting structures, we uncover four distinct segments in the population. Two segments (∼50%) with a lower Willingness-to-Pay seem to be more likely to take-up FLEX. Ex-urban car drivers seem to be the most likely segment to adopt FLEX, showing great, since members of this segment are currently frequent users of the private car. Our case study also shows that while FLEX competes primarily with public transport when accessing local stations, it competes primarily with car for reaching distant stations.

Modeling Access Mode Choice for Inter-Suburban Commuter Rail

This paper presents an analysis of access mode choice by riders of one of the first U.S. suburb-to-suburb commuter railroads, the Westside Express (WES), in the Portland, Oregon metropolitan area. The study uses on-board survey data collected by the region’s transit agency, Tri-Met, during WES’s first year of operation. The data include observed access mode choices, historical mode usage, and subjective assessment of WES attributes. A hierarchical choice model was estimated, using attributes of the access trip, station areas and rider characteristics. The estimation results revealed pre-WES-mode inertia effects in choosing drive access, pro-sustainability attitudes in choosing bike access, the importance of comfort to light rail and auto users, and strongly positive station-area effects of feeder bus lines and parking provision. The hierarchical choice model revealed significant substitution effects between drive and light rail modes and between bike and walk modes. This study provides potentially valuable insights to agencies for the purposes of station-area planning and targeted marketing efforts.

Post-COVID-19 performance evaluation of urban metro transit system in Delhi and influence on access mode

The impact of the COVID-19 pandemic has been observed to affect the travel patterns, routes and traffic in public transportation systems across the world. It is important to evaluate the performance of the Delhi Metro (DM) post-COVID-19 pandemic for its successful operation. In this study, the BLUE line of DM with the longest route and highest number of metro stations has been examined for performance evaluation. The performance is evaluated based on travel time components (access, egress, transfer, waiting and main haul time) to calculate various performance indicators i.e., Level of Service (LOS), Service Time Ratio (STR), Passengers Waiting Index (PWI), Total Travel Ratio (TTR) and Interconnectivity Ratio (IR). The post-COVID-19 LOS evaluation indicates that the users are spending 72.6 % to 84.4 % of their main haul time on their access-egress trips. The STR shows that the users are spending 10.9 % to 12.6 % of their total travel time in waiting and transferring only during the main haul trip. The mean PWI, RI and TTR are noted as 1.008, 0.794 and 2.069 respectively. The IR is observed as 0.312 for the given route. The median and average main haul distances across all access modes are observed to be (12–21) Km. and (19.69 ± 11.19) Km. respectively. It is revealed that the observed mean value of LOS is (0.775 ± 0.575). It is further revealed that the metro fare per trip and the access-egress trip cost per day are significant factors for access mode choice in the case of walking and auto-rickshaw whereas LOS, RI and PWI are other significant operator’s performance indicators influencing the access mode choice. The study reveals that post-COVID-19 the performance indicators exhibit the unsatisfactory performance of DM and there is further scope to improve the UMTS performance.

Airport Access Mode Choice: Analysis of Passengers’ Behavior in European Countries

Transportation systems require many challenges in providing seamless door-to-door mobility. The main initiatives are encouraging a shift from private to other transport modes by providing a fully integrated multimodal service in which the coordination and data sharing among different stakeholders are required. The idea of this paper is to analyze the mode choice, as well as the variables that affect the travelers’ airport access mode choice. For that purpose, we used multinomial logistics (MNL) regression to determine probability of mode choice given various multimodal chain alternatives. The inputs of the proposed model were based on the answers from the participants of the online survey which was disseminated in Europe. Through more than 2000 answers to the survey, we collected the data related to the factors that influence the airport access mode choice, travelers’ attitude, motives for traveling, as well as the socio-demographics of participants. Afterwards, we investigated the influence of the main factors that have an impact on the non-coordination in the multimodal travel chain. The obtained results highlight the impact of the factors “reliability” and “waiting time” in making mode choice.

Post COVID-19 Access-Egress Attributes for Urban Metro Transit Users in Delhi

Abstract The BLUE line of Delhi Metro (DM) has been examined to identify the post COVID-19 access–egress attributes of users. An on-board survey of metro commuters is conducted in February and March 2021. The respondents reported six different modes for access and egress trips to nearest metro stations with 38.7% and 43% users opting for walking for access-egress trip respectively. The E-rickshaw is observed to be most preferred para-transit mode whereas private vehicle has small mode share for access-egress trip. It is revealed that 46.5% of respondents are captive riders whereas 51% owns at least one motorized private vehicle. The average access and egress distance covered by walking is (0.81+ 0.32/0.35) Km respectively. The average access and egress trip time by walking is (11.19+3.73) and (11.07+4.45) minutes respectively. The average access and egress trip time by E-rickshaw is (13.21+4.09) and (12.56+2.95) minutes respectively. The access and egress trip time by motorized modes are in the range of (12.36-14.39) and (10.41-13.56) minutes respectively. The average main haul distance across all access-egress modes is observed to be (19.69+11.19) Km. To understand the factors influencing the access–egress mode choice multinomial logistic (MNL) regression models are proposed. The access-egress time and distance are observed to be significant factors in access-egress mode choice. Less parking facility offered by DM is significant factor in access mode choice. Occasional commuters are only significant factor in context with frequency of travelling in DM.

Does neighborhood design matter for walk access to metro stations? An integrated SEM-Hybrid discrete mode choice approach

This study explores effects of various subjective and objective built environment (BE) factors on access mode choice to Metro stations. Personal interview surveys were conducted among 600 Metro users from catchment area of Metro stations in Delhi, India to collect information regarding their socio-economic status, access travel characteristics, and degree of satisfaction on twenty microscale BE factors related to walking environment. Secondary data on mesoscale factors such as population- and employment-density and land-use diversity were also collected. Exploratory factor analysis on microscale factors yielded a four-factor solution, i.e., Comfort, Safety & Security, Traffic, and Mobility which is confirmed by confirmatory factor analysis. These four factors were utilized to derive an endogenous variable “Neighborhood Design”. Four access mode choice models were developed subsequently using hybrid discrete choice models taking Neighborhood Design as walkability measure. The results indicated that Neighborhood Design, population, and land-use densities affect mode choice positively and significantly. The research indicates that improving microscale Neighborhood Design and certain mesoscale factors within catchment areas of stations could influence the peoples’ choice of walking to the stations. Sensitivity analysis also shows that improvement in the neighborhood design attributes will lead to a higher share of walk access to metro stations.

Analysis of Access and Egress Mode Choice to High-Speed Railway Stations

Analysis of Access and Egress Mode Choice to High-Speed Railway Stations

Joint Modeling of Access Mode and Parking Choice of Air Travelers Using Revealed Preference Data

Airport ground access mode choice is distinct from everyday mode choice decisions, necessitating context-specific choice model estimation. Understanding airport ground access mode choice decisions is not only important for developing infrastructure planning strategies, but also for assessing the impacts of emerging modes on airport revenues, particularly from parking. However, parking choice is an often-overlooked dimension in airport ground access choice modeling. This paper addresses this gap through the development of a joint model of airport access mode and parking option choice using a passenger survey conducted at Dallas-Fort Worth (DFW) International Airport in 2015. Compared with a traditional conditional logit model that does not consider parking options available at DFW airport, the joint model of mode and parking decisions was found to generate more realistic values of travel time and was shown to have better predictive performance, both of which are critical for obtaining better airport parking revenue estimates and identifying traveler cohorts who may respond more strongly to potential policies targeting curb congestion and parking demand.

Preferences of urban rail users for first- and last-mile autonomous vehicles: Price and service elasticities of demand in a multimodal environment

Integrating autonomous vehicles (AVs) into transit networks is a critical problem for metropolitan areas worldwide. This study investigates the preferences of urban rail/rapid transit users for first- and last-mile AV services, which are not well understood. First, it develops an access mode choice model incorporating on-demand transit access enabled by AVs. Second, the model is estimated with stated choice data obtained from a survey of 2,300 residents living within 1–5 km of their nearest rail stations in the Tokyo metropolitan area, in which choice tasks are based on recent access to home-end stations. Finally, estimated models are used to compute elasticities of demand for access modes with respect to AV cost and wait time. The results show that price sensitivities of demand for AV services lie within a reasonable range of transit fare elasticities. AVs have diverse substitution patterns with existing modes. Riding in AV services is more likely to be a substitute for riding on buses/in slower modes of transit for all travel purposes, and for driving cars, particularly for leisure trips, but less likely for cycling and walking, particularly for work trips. The AV wait time elasticities might vary according to the waiting environment and conditions. The results also suggest that AVs may particularly benefit those who currently have restrictions in accessing transit.

MODE CHOICE BEHAVIOR FOR GROUND ACCESS TO AIRPORTS: A CASE OF ISTANBUL ATATÜRK INTERNATIONAL AIRPORT (IST) AND SABIHA GOKCEN INTERNATIONAL AIRPORT (SAW)

Accessing airports has been a problem for passengers due to traffic congestion in cities. Thus, in order to catch the flights on time, passengers consider many factors to choose the transportation mode for airport access. Some of the factors are covariates, and they can be listed as age of the passenger, number of luggage carried, travel cost and travel time to the airport, group size of the passengers, and reliability of access modes. These covariates, may differ for each airport; and hence, in this paper, we investigated the differences of these covariates between Istanbul Ataturk International Airport (IST) and Istanbul Sabiha Gokcen International Airport (SAW). Analysis of Variance (ANOVA) and post-hoc tests were conducted to investigate the covariates that affect the mode choice to access IST and SAW. The results indicated that these two airports have differences in terms of the effect of these selected six covariates on airport access mode choice. Reliability of the modes, travel time, travel cost, age of the passenger and traveling group size affected the mode choice to access IST. On the other hand, only reliability of the modes, travel time and travel cost had effects on airport access mode choice for SAW. Based on the analysis, some recommendations for the decision makers were also provided.

Market segmentation analysis for airport access mode choice modeling with mixed logit

Accessing airports can be considered as a crucial issue since passengers need not miss their flights. This issue makes the mode choice to access the airports important to study on and develop policies regarding it. Many studies show destination type as domestic or international affects the airport access mode choice, along with other factors. In this study, we investigate the effect of destination type of mode choice using mixed logit, using market segmentation approach. Market segmentation regarding destination type as domestic or international is a first in airport access mode choice modeling. Revealed-preference data was collected by face-to-face passenger surveys at Ataturk International Airport in Istanbul, Turkey, in 2015. We did market segmentation analysis for Multinomial Logit (MNL) and Mixed Logit (ML) models. When MNL and ML models were compared, it was observed that ML was superior to MNL. Further, results of market segmentation analysis revealed that using segmented models produced more accurate results than using the pooled model; both in MNL and ML. This finding was also supported by the value of time estimates; there were significant differences between domestic and international travel markets in terms of airport access mode choice. These results showed that different transportation policies may be introduced for domestic and international traveler segments, which also were explained.

Modelling of Ground Access Mode Choice: Empirical Evidence from Mehrabad International Airport, Tehran, Iran

Abstract The aim of this study is to investigate air travellers’ behaviour with regard to choices for ground access to this airport. Questionnaire data were collected from 684 respondents. Multinomial logit modelling was employed for this purpose. These findings indicate that in families with at least one car of their own, the tendency for using bus and carpooling was decreased. In addition, it was found that those in the 36 - 40 age group were more inclined to take the taxi. Finally, the results of this study suggest that with the growing price of the private car, the tendency to use it was diminished. Therefore, if transportation authorities seek to reduce the use of personal cars, it is possible to make the use of private cars expensive with increasing the parking cost in the airport. This may lead to the reduction of using private cars in land access to Mehrabad airport.

Modeling Mode Choice of Air Passengers’ Ground Access to Brisbane Airport

Like other developed countries, Australia is experiencing considerable growth in air travel demand. This growth is putting tremendous pressure on airports to improve the capacity and level of service of access and egress modes. The main goal of this study was to develop a robust mode choice model for passengers’ access to airports, in the context of Brisbane, Australia. The novelty of this study includes (1) the use of recent techniques to combine passengers’ revealed and stated preferences for mode of access to airports and (2) the development of both traditional multinomial logit (MNL) as well as mixed logit (MXL) models using these data. The data were collected from 1,435 passengers through an online survey of both revealed and stated preferences, with the stated preferences pivoting on their most recent trip to Brisbane Airport. With these data, access mode choice models were estimated. MNL and MXL models were estimated that directly considered the effects of passenger mode choice inertia as well as novel passenger-specific characteristics. These factors had a large, statistically significant effect on the estimated models. The benefit of the MXL model was shown in the results, as the passengers’ value of time from the MXL model was A$105.15/h, which was strikingly lower than the MNL-estimated value of time. In addition, there were notably high direct elasticities for bus and shuttle with respect to travel time, and for car and taxi with respect to travel cost.

Tri-reference-point hypothesis development for airport ground access behaviors

Studies have applied single-reference-point or safety margin hypotheses to examine how advanced traveler information affects travel behaviors. However, these theories may fail to fully capture the trade-offs among origin departure time, airport access time, and terminal processing time in terms of airport ground access behaviors. In this study, we developed a tri-reference-point hypothesis and assumed that the rate of change of utility may change at the air passenger’s preferred (PAT), earliest acceptable (EAT), and latest acceptable (LAT) airport arrival times. With an empirical data set collected from 304 passengers at Taipei Songshan Airport, the study examined the tri-reference-point hypothesis by analyzing airport ground access mode choice behaviors with a pooled framework that combined revealed and stated preferences. Moreover, the study developed four alternative specifications for schedule delay variables, assuming that air passengers used different reference points to determine relative gains and losses of the expected airport arrival time. The specifications included selecting both EAT and LAT as the zero-utility points (an indifference-band specification) and either one of PAT, EAT, and LAT as the single zero-utility point. Regardless of which specification was employed for schedule delay variables, the tri-reference-point hypothesis was generally supported. In particular, a significant difference of the rate of change of utility around PAT, EAT, and LAT was identified in the analysis results. When managing increasing road travel times and increasingly congested terminals, air passengers were more willing to retime their origin departure time to an earlier time than to switch their ground access mode. The implications of the analysis results for airport ground access management are discussed in the study.

Understanding the Role of Cycling to Urban Transit Stations through a Simultaneous Access Mode and Station Choice Model

Governments worldwide are aiming to increase sustainable mode use to increase sustainability, livability, and accessibility. Integration of bicycle and transit can increase catchment areas of transit compared with walking and thus provide better competition to non-sustainable modes. To achieve this, effective measures have to be designed that require a better understanding of the factors influencing access mode and station choice. At the national/regional level this has been thoroughly studied, but there is a knowledge gap at the urban level. This study aims to investigate which factors influence the joint decision for tram access mode and tram station choice. The joint investigation can identify trade-offs between the access and transit journeys. Furthermore, the effect of each factor on the bicycle catchment area is investigated. Using data from tram travelers in The Hague, Netherlands, a joint simultaneous discrete choice model is estimated. Generally, walking is preferred to cycling. The findings of this study suggest that access distance is one of the main factors for explaining the choice, where walking distance is weighted 2.1 times cycling distance. Frequent cyclists are more likely also to cycle to the tram station, whereas frequent tram users are less inclined to cycle. Bicycle parking facilities increase the cycling catchment area by 234 m. The transit journey time has the largest impact on the catchment area of cyclists. Improvements to the system, such as fewer stops, higher frequency (like light rail transit), or both, therefore would result in a much longer accepted cycling distance.

Role of perception of bicycle infrastructure on the choice of the bicycle as a train feeder mode

This paper examines the impact of the perception of bicycle infrastructure on the choice of the bicycle as a feeder mode to access train stations in the Netherlands. The latent factors act in addition to traditional travel time and cost variables, describing the quality of cycling infrastructure at and around railway stations. The analysis is based on a large scale revealed and stated preference survey in the wider metropolitan area of The Hague and Rotterdam (n = 1524). Hybrid choice models for access feeder mode choice were estimated, where the attitude toward cycling to affected the users’ perception of the cycling infrastructure, which in turn affected the utility of cycling. The results show that both the quality of cycling infrastructure and latent factors, describing the perceived quality of cycling infrastructure, station connectivity and the general attitude toward cycling, have a significant impact on cycling to the station. The effect of the travel time and cost characteristics on access mode choice significantly changes depending on the perception of the quality of the infrastructure, as well as the attitude toward cycling and frequency of train use. Bicycle parking cost and distance to the platform is the most critical observed factor influencing bicycle access choice to the train stations.

Development of a large-scale transport model with focus on cycling

Abstract This study presents a transport model to better model cycling demand. The model improves modelling of cycling in several ways compared to a conventional transport model. First, it uses a detailed bicycle network containing information about existing bicycle infrastructure. Second, generalised cost measures based on different bicycle route choice models are calculated and compared to evaluate how to best represent the impact of bicycle infrastructure in the model. Third, the model utilizes a refined zone system with smaller zones of size 250 m × 250 m. Using these smaller zones, more short-distance tours are included in the model, and these are predominantly walking and cycling trips. Fourth, the model considers cycling also as an access mode choice to public transport. Therefore, the model treats cycling and public transport as both competing and complementary modes. Results show that the model captures detailed individual heterogeneity in cycling demand for different trip purposes. Impacts of bicycle infrastructure, land use characteristics and individual/household socio-demographics are investigated. Detailed individual level travel time and generalised cost are derived for cyclists of different socio-demographics. The result highlights the importance of choosing a good measure of generalised cost, given that different bicycle route choice models result in different effects of bicycle infrastructure. In future applications, the model can be used to evaluate proposed bicycle investments regarding their impact on link flow, bicycle route choice, modal shift and generation of completely new tours. The model can also be a powerful tool in a cost-benefit analysis of bicycle investments.