Egress Mode Research Articles

Barriers to better bicycle parking for promoting intermodal journeys: An inter-organisational collaboration perspective

Organisational structures in the transport sector are often complex and fragmented, with different authorities responsible for different stages of a traveller's journey. In such circumstances, collaboration across organisational boundaries is required to facilitate intermodal journeys. This paper aims to provide empirically grounded insights into collaboration in transport planning, extending the literature to include cycling as an access and egress mode. This is done by examining the challenge of improving bicycle parking facilities at railway stations in Copenhagen, Denmark. Interviews with key actors involved in public transport and cycling planning reveal three main inter-organisational barriers to improving station bicycle parking in Copenhagen. First, station bicycle parking falls between the responsibilities of different organisations and levels of governance. Second, the absence of an established funding formula contributes to negotiation-oriented rather than collaborative interactions among the stakeholders. Third, the tension between cyclist satisfaction and rail passenger growth targets hinders collective action. In summary, despite Copenhagen's strong cycling identity and the prioritisation of this transportation mode in the city's political decision-making and transport planning, the issue of station bicycle parking highlights the complexity of multi-actor governance of intermodal journeys.

Roles of accessibility and air-rail intermodality in shaping mobility patterns in mega-city regions: Behavioural insights from China

This paper aims to understand mobility patterns in mega-city regions from perspectives of accessibility and air-rail intermodality. Travellers' preferences for intercity mode and its access and egress modes were simultaneously collected in the context of the Beijing-Tianjin-Hebei mega-city region. The accessibility of transport hubs and destinations was measured to enable interpreting mobility behaviour in three dimensions, i.e., travel mode decisions, departure transport hub decisions, and transport service decisions. The calibrated behavioural model highlights a series of determinants regarding level-of-service attributes, travel characteristics, accessibility, socio-demographics, and their interaction. Based on the behavioural insights, twenty domestic cities were selected as destinations for analysing the dynamics of mobility patterns in terms of the competition within the multi-airport system and air-rail cooperation potential in the long-haul market. The elasticity of shifts in transport demand between the primary and secondary airports in the Beijing multi-airport system was assessed under various pricing strategies, highlighting the vital role of the most accessible airport in air traveller decision-making. Moreover, the results underline the effect of air-rail intermodal service upgrades, e.g., offering baggage handling systems and flexible tickets, on stimulating air-rail intermodal mobility in the mega-city region.

Shared micromobility and public transport integration - A mode choice study using stated preference data

This paper uses stated preference data collected in the city of Rotterdam and discrete choice modelling techniques to study the relationship between public transport and shared micromobility. It assumes a hypothetical condition of integrated systems and studies the relationships of complement and competition between these modes. The findings suggest that shared micromobility modes are viable alternatives as egress modes for metro trips. Shared micromobility can be seen as a complement to metro, yet shared e-mopeds proved to also be a viable option as individual modes for long-distance trips. Different characteristics proved to be important in choices in this context: frequency of public transport use, previous use of shared micromobility, and age. Considering the results obtained, collaboration between shared micromobility and transit operators might benefit them as well as travellers. Collaborations should be designed so that they help travellers to decrease total travel time, even if it implies longer egress legs. However, the costs of these shared modes should not be as high as to prevent travellers to use them as egress alternatives. Finally, young travellers and frequent transit users could be specifically targeted, as they showed to have a better perception of shared micromobility.

Smart Bicycles in an Urban Area: Evaluation of a Pilot Scheme in London

Automated or smart bicycle systems are seen as a way to enhance mobility and provide a convenient access and egress mode for public transport. This article summarizes an evaluation of a pilot system that was introduced in the London Borough of Hammersmith and Fulham in August 2004. Underground and commuter rail stations, as well as a heavily-used bus network, serve this densely populated area of London. A survey of users was conducted and data were collected from actual use of the system. Analysis of these data provided some insights into the capabilities of these types of systems to enhance existing public transport services. In particular, it was found that the potential of the system lies primarily with the leisure and recreational market and with providing links to public transport stations. The pilot included “sponsored” nonpaying users who tended to use the system more for commuting and utilitarian trips.

MODELING SYSTEM COHERENCE TO KNOW THE PEDESTRIAN’S LEVEL OF SERVICES IN DHAKA CITY

Walking is by far one of the most egress modes of transport. At the same time, pedestrians are the most vulnerable road users in the world because of their openness to the accidents with other motorized modes of transport. However, system coherence is a very important aspect to know the pedestrians’ level-of-service in a city so that the policy makers among the engineers can understand the problems of the walkers for specific road way design considerations and maintenance. This paper tries to focus the issues that are very much related with system coherence as a major part of pedestrian’s level-of-service assessment technique for Dhaka case as well as put a model so that several data can be analyzed in a single platform to know the relations among several variables. Ordered probit model has been used to make such platform for establishing the relations among several variables. Lastly, some policy options have been proposed to increase the safety of the walkways along with interventions needed for a better walkway design.

Environmental impact analysis of on-demand urban air mobility: A case study of the Tampa Bay Area

Urban Air Mobility (UAM) uses electric vertical take-off and landing (eVTOL) vehicles to provide an alternative way of transporting passengers in urban areas. This study proposes a method of comparing air pollutant emissions from using ground transportation versus switching to multimodal UAM, including greenhouse gases and other air pollutants (NO x , SO 2 , PM 2.5 ). A study by Wu and Zhang (2021) addressed planning questions regarding the optimal placement of vertiports and estimated diverted demand from ground transportation modes by combining network design and travel mode choice models. The proposed method is applied to the case study of Tampa Bay region. A sensitivity analysis was conducted to further evaluate the impacts. The study reveals that on-demand UAM (considering vertiport access and egress modes) generates more greenhouse gases and other air pollutants (except NO x ) in the case study region compared to ground transportation modes. The emissions depend on the structure of power production. A lower UAM service price and more vertiports will further increase emissions.

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.

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

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

Modeling and Implications of Airport Ground Egress Mode Choice

Mode choice of airport ground access has been covered by several studies, but there is a lack of research in the case of airport ground egress; that is, mode choices of inbound passengers for ground trips from the airport to the city center. This study aimed to cover this gap by modeling the ground egress mode choice of passengers, employing mixed logit and comparing it with the multinomial logit model. The data for this research was collected at Istanbul’s Sabiha Gokcen International Airport (SAW) in 2015. Analyses included six modes, namely automobile, pick-up, public transit, taxi, shuttle and public transit (SP), and shuttle and taxi (ST). An important outcome was that a mixed logit model with error components outperformed the multinomial logit model. Results showed that significant variables affecting the ground egress mode choice included the income of the passenger, the cost of a ground trip from the airport, auto ownership status, number of luggage and trip purpose. Passengers are less constrained by ground travel time in their airport egress trips than in their airport access trips. By this, a significant finding was that prioritizing egress trip cost over travel time affected the mode choice.

Mode choice behavior for access and egress connection to transit services

In the aims to investigate the potential market of Transportation Network Companies (TNCs) to serve as first/last mile connection for transit services, this study investigated the influential factors that affect transit users’ choices of access and egress modes, including TNC or taxi, drive alone (park and ride), carpool (kiss and ride, carpool or shuttle), Micromobility modes (bike-sharing, scooters), walking, and wheelchair. The data for this study comes from a transit on-board survey conducted in Spring 2017 for the Orlando metropolitan area. Moreover, the Smart Location Database was also integrated to investigate how land use characteristics may contribute to users' choice for access and egress modes. Separate multinomial logit models were developed to investigate the mode choice for access and egress links, respectively. Various personal, trip, and land use characteristics showed significant impacts. Particularly, trips going to airports or universities/colleges had much higher probabilities of using TNC for access and egress purposes, while sports events and medical visits were less likely to be connected through TNC services. Visitors were also less likely to start their trips with TNCs. A longer distance between the origin and the transit service showed positive impacts on the use of TNC services. Higher household income also showed a positive influence on TNC usage. In view of land use characteristics, higher employment and household entropy, and high diversity at the origin reduced the probability of using motorized modes, including TNCs, for access purposes. On the destination side, high regional diversity seemed to encourage the use of TNCs and drive alone modes for egress purposes.

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.

Sequenced Ordered Logit Model Considering Latent Variables for Determining Trip Satisfaction of Metro Passengers

Improving the public transportation system to compete with the private modes requires an understanding of passenger perceptions of the service quality (SQ). In the literature, various models have been developed to identify effective SQ attributes and to assess their relationship with passenger satisfaction. However, most of them either ignore the socioeconomic and trip characteristics or consider them by a market segmentation approach. Since these variables can affect passenger perceptions, it is important to include them in the model. This paper aims to capture the effect of socioeconomic and trip variables by combining them with SQ attributes in a satisfaction analysis. An ordered logit model considering SQ latent variables is calibrated to model passenger satisfaction. The measurement part of a Structural Equation Model (SEM) is applied to construct latent variable structures. The case study was on the Tehran metro. The SQ attributes were used to form five SQ latent variables: “comfort,”“information,”“cleanliness,”“service,” and “safety/security.” The results indicate that socioeconomic and trip characteristics, as well as the SQ latent variables, had a significant effect on passenger satisfaction. From the results of this study, “service” and “comfort” were found to be the most effective contributors to satisfaction levels among the SQ latent variables. Among socioeconomic and trip characteristics, gender, education, driving license, egress mode, access time, and trip origin type (i.e., work, education, etc.) were also important in passenger satisfaction.

Modeling demand for ridesourcing as feeder for high capacity mass transit systems with an application to the planned Beirut BRT

Ridesourcing (Uber, Careem, Lyft, …) is emerging as a main player in the transportation industry. However, its relation to mass transit remains ambiguous, with divided opinions on its complementarity or substitutive effect towards high capacity public transportation systems. This study examines the integration of ridesourcing and transit, particularly focusing on modeling the demand for mass transit when ridesourcing is used as an access or egress mode to mass transit. It extends the existing literature on the integration of transit and new mobility concepts by providing a modeling framework that incorporates all stages of multi-modal trips such as those that involve using mass transit. A mixed logit with error component structure is presented to capture correlations in unobserved factors across multi-modal alternatives sharing similar modes at certain stages. The framework incorporates uni-modal and multi-modal travel alternatives and distinguishes between access, main mode, and egress stages without applying constraints on possible combinations. An application to Beirut’s planned Bus Rapid Transit (BRT) system, performed on a data set of 392 respondents, reveals that ridesourcing as a feeder mode is mostly popular with young commuters while also being perceived as more reliable than feeder buses and jitneys. Awareness and familiarity are major drivers for the service implying higher potential in the future. A complementarity effect with transit is found as the introduction of ridesourcing at the feeders’ level is expected to drive an additional 2% of commuters to use the BRT. Decreasing ridesourcing fare is effective for its integration with transit, as a fare decrease of 50% increases BRT market share from 33.53% to 36.89% of all motorized trips, implying possible synergies between the two modes. Forecasting results further reveal that additional taxes on parking used by car commuters and increasing park and ride capacity at BRT stations are effective policies to augment BRT ridership.

Door-to-door travel in 2035 – A Delphi study

Intermodal, door-to-door (D2D) travel is gaining momentum for airlines, airports, and feeder traffic providers. At the same time, competition is increasing; having a better understanding of future travelers’ requirements regarding D2D mobility is crucial for the mobility sector, for planning long-term, adapting products and services accordingly, and improving the overall passenger experience. Little information is available on this matter and gathering data in the future may be challenging. This paper considers future projections of European air passengers, and their requirements, for the entirety of the D2D travel chain, including long-haul air travel and airport access and egress modes. The research is based on a two-round Delphi survey (time horizon 2035) with 38 experts, incorporating panelists from the transport industry, academia, and consultants. The Delphi survey is supplemented with findings from a preliminary study, combining expert interviews (N = 18), a literature review, and an expert workshop. Based on the results from a hierarchical cluster analysis, the paper presents three possible future scenarios: (1) personalized D2D travel, (2) integrated D2D travel, and (3) the game changer.

Integrated route choice and assignment model for fixed and flexible public transport systems

The recent technological innovations in various ICT platforms have given rise to innovative mobility solutions. Such systems could potentially address some of the inherent shortcomings of a line/schedule based public transport system. Previous studies either assumed that flexible on-demand services are used as an exclusive door-to-door service or offered as a feeder connection to high-capacity public transport services. However, users may combine line/schedule based public transport systems (Fixed PT) and on-demand services (Flexible PT) so that their travel impedance is minimized. To this end, we propose a multimodal route choice and assignment model that allows users combining Fixed and Flexible PT or use them as individual modes while demand for these services is endogenously determined. The model takes into account the dynamic demand–supply interaction using an iterative learning framework. Flexible public transport can be used to perform any part of the trip, ranging from a first/last mile service to an exclusive direct door-to-door connection. The developed model is implemented in an agent based simulation framework. The model is applied to a network centered around the city of Amsterdam, The Netherlands. Scenarios where Fixed PT and Flexible PT are offered as mutually exclusive modes or can be combined into a single journey, are analysed. Results indicate that Flexible PT is predominantly used for covering <30% of the trip length, indicating that it is mainly used as an access or egress mode to Fixed PT. This results with an overall increase in the share of public transport trips. Also, the average waiting time of Flexible PT users when used in combination with Fixed PT are lower than the scenario where each of them is used as an exclusive mode.

Analysis of travel characteristics and access mode choice of elderly urban rail riders in Denver, Colorado

With the proportion of the elderly increasing worldwide, significant research efforts have been devoted to understanding the travel characteristics of the ageing population. Our research contributes to a limited number of studies that have investigated how the elderly (65+) access urban rail in comparison to younger adults (19–64). Using descriptive and econometric analyses of on-board survey data from Denver, Colorado, we respond to the following two research questions: (1) How do trip characteristics, including access and egress mode, trip purpose, choice of station, and travel time of elderly urban rail riders differ from those of their younger counterparts? (2) Do the determinants of access mode choice, such as built environment and individual characteristics, impact differently the choices of elderly and younger adult riders? Our results indicate that the elderly urban rail users differ from the average elderly population in the US in terms of their employment status (46% of the elderly Denver rail riders are employed). Consequently, dissimilarities in travel behavior between elderly and younger adult riders are on average lower than expected, although important differences are still observed. Results from a multinomial probit model on access mode choice for trips between home and a rail station show that younger adults and employed elderly travelers place higher importance on travel time when choosing a mode to access a station compared to non-employed elderly travelers. On the other hand, the built environment and vehicle ownership have a significantly higher influence on access mode choice for elderly compared to younger adult travelers.

Understanding the relation between distance and train station choice behavior of cyclists in the western region of the Netherlands

Abstract With 35,000 km of bicycle pathways, cycling is common among persons of all ages less than 65 years in the Netherlands. Bicycle is often seen as a standalone travel mode but when integrated as part of a multimodal trip with train, it can be an important solution for long distance journeys, offering more flexibility and faster access time than other travel modes to a railway station. In this paper we investigate which factors influence departure train station choice on combined bicycle-train trips in the western region of the Netherlands. We explore the effects of an individual’s socio-economic characteristics, their multi-modal trip attributes, as well as neighborhood characteristics and station attributes. Observations from the Dutch National Travel Survey over the years 2015-2017 are considered for analysis where bicycle is used as either an access or egress mode. A multinomial logit model is estimated in which the choice set of an individual is determined by the stations in the proximity. Results show that stations as far as the fourth closest station are considered as a relevant option for an individual. Additionally, station type and neighborhood characteristics were among the most significant contributors to station choice in the western region of the Netherlands

Analysis of user perception towards a key set of attributes related to Bicycle-Metro integration: A case study of Hyderabad, India

Presently, there is no consensus on the factors which might influence a metro-commuter towards choosing the bicycling as a last mile connectivity option in Indian context. Hence, a broader understanding of the end-user preferences towards key set of determinants related to bicycle-metro sharing is necessary to formulate effective policy measures, which would subsequently lead to sustainable cities and improved well-being of commuters. This article is an attempt to demonstrate a scientific approach to prioritize among an important set of determinants influencing commuter’s decision to use bicycle as an access or egress mode to metro rail. The demonstrated methodology also makes an effort to understand the sources of heterogeneity towards user perception as well. Hyderabad, an Indian metropolitan city, which has recently introduced metro-rail, has been selected as the case study city.Initially, a set of key determinants related to bicycling in general and bicycle-metro integration in particular is identified and commuter’s perception towards these determinants is collected based on a typical five-point likert scale item. Subsequently, the sources of heterogeneity among user responses were explored by using Kruskal Wallis H test, a non-parametric statistical measure. Results clearly indicate that user perception towards several determinants were significantly influenced by trip-specific characteristics such as trip frequency, trip purpose etc. Overall, a clear evidence of heterogeneity among user perceptions on the factors indicates the need for conducting separate analyses for different socio-economic sub-groups. Prioritization of the identified determinants was carried out by an established MADM technique, namely, RIDIT-analysis for different categories of commuters.

Re-examination of the standards for transit oriented development influence zones in India

Transit oriented development (TOD) is a land-use and transport integrated urban planning strategy that is highly acclaimed for promoting sustainable city development. This review aims to identify the problems regarding adoption of TOD standards or guidelines formulated by developed countries in developing countries, such as India, and the necessity of conducting adaptability studies on TOD influence areas. The existing studies show that the size of the influence area varies among different cities and travel modes. Accordingly, no single size influence zone is suitable for all cases. This review highlights the necessity of carefully considering the spatial extent of influence areas and modes other than walking as access or egress modes in the Indian context. Moreover, this review aims to provide insight on how to plan TOD in the context of developing countries, because the mobility patterns in these countries differ considerably from those in the developed world.

Rapid Transit Systems: Smarter Urban Planning Using Big Data, In-Memory Computing, Deep Learning, and GPUs

Rapid transit systems or metros are a popular choice for high-capacity public transport in urban areas due to several advantages including safety, dependability, speed, cost, and lower risk of accidents. Existing studies on metros have not considered appropriate holistic urban transport models and integrated use of cutting-edge technologies. This paper proposes a comprehensive approach toward large-scale and faster prediction of metro system characteristics by employing the integration of four leading-edge technologies: big data, deep learning, in-memory computing, and Graphics Processing Units (GPUs). Using London Metro as a case study, and the Rolling Origin and Destination Survey (RODS) (real) dataset, we predict the number of passengers for six time intervals (a) using various access transport modes to reach the train stations (buses, walking, etc.); (b) using various egress modes to travel from the metro station to their next points of interest (PoIs); (c) traveling between different origin-destination (OD) pairs of stations; and (d) against the distance between the OD stations. The prediction allows better spatiotemporal planning of the whole urban transport system, including the metro subsystem, and its various access and egress modes. The paper contributes novel deep learning models, algorithms, implementation, analytics methodology, and software tool for analysis of metro systems.