Last-mile Trips Research Articles

First-mile and last-mile externalities: Perspectives from a developing country

Transport equity, which emphasises fair and equitable distribution to reach various significant activities and opportunities such as work and healthcare, has greatly interested researchers and practitioners. Enhancing first-mile and last-mile travel and commuting experiences augment an individual's travel satisfaction. However, challenges with first-mile and last-mile travel lead to social exclusion and inequity concerns in accessing services and a reduction in the utilisation of public transport. There is limited insight regarding commuters' experiences and challenges in this context, particularly in developing countries. This dearth of knowledge makes it difficult to implement measures to enhance connectivity and accessibility. Thus, we investigate the first-mile and last-mile experiences and challenges of commuters in Ghana using qualitative and quantitative data from semi-structured interviews and questionnaire survey, which are rare in this subject's study. The analysis through the logit model showed that commuters with increasing distances for the first and last miles have difficulty with transport accessibility. The results showed that demographic factors like age and gender did not significantly affect first-mile and last-mile accessibility, suggesting that the challenges are experienced across different groups. The thematic analysis revealed five essential themes: (i) cost, (ii) limited accessibility, (iii) safety, long walking distances and (v) temporal factors like weather as challenges commuters encounter with their first-mile and last-mile trips. This research contributes to the extant literature on the experiences and challenges of first-mile and last-mile commutes. It provides depth to the literature by offering perspectives from a developing country. It also holds practical significance for transport authorities and government departments and agencies.

Shared e-scooters: A last-minute mode?

In this paper we assess whether shared e-scooters are being used in hurried situations to avoid arriving late, making trips we define as last-minute trips. We identify trip characteristics for last-minute trips using data from shared e-scooters in Stockholm. Trip arrival time patterns, distances, durations, and speeds are analyzed in relation to desired arrival times. We observe a peak in the number of trips ending before the full hour and a smaller peak of trips ending before the half hour of weekday mornings. These trips have lower average trip durations and higher average speeds, indicating a larger share of last-minute trips. Arrival patterns shift when the assumed preferred arrival time changes, and when the risk associated with arriving late increases. Furthermore, there is an increased share of trips that started close to public transportation around the full hour, indicating that a portion of last-minute trips may also be last-mile trips. Our results show that while last-minute trips are infrequent per user, they do make up a relatively large share of weekday morning trips. These results highlight an important market segment for shared e-scooter services and may also explain why some research reports e-scooter usage replacing walking.

Empirical Study on the Development of Driving Environments for Personal Mobility Vehicles

Personal mobility vehicles (PMVs) are the potential future travel mode, typically for “first-mile and last-mile trips,” in urban areas. Accordingly, the popularity of PMVs is increasing, and the purpose of using PMVs is diversifying in South Korea. Before revision of the law concerning PMVs, the driving ways and roads for PMVs were not defined by regulations in South Korea. Therefore, most PMV users preferred to drive on sidewalks and bicycle lanes to avoid collisions with larger vehicles. Furthermore, PMVs have been involved in many accidents. To solve these problems, the government of South Korea revised the Road Traffic Act to permit PMVs to travel on bicycle lanes and considered building a new type of lane for PMVs based on the results of field experiments conducted in this study. In these experiments, the minimum turning radius with various speeds, driving performance on roads with vertical alignments, lateral placements in curved sections were examined. In addition, conflicts and inconvenience of PMVs driving on bicycle lanes were tested. In the experiments, three different types of PMVs—electric scooter (e-scooter), electric unicycle (e-unicycle), and segway—were used. Through the experiments, the feasibility of using PMVs on bicycle lanes was assessed, and the design criteria for PMV lanes were derived.

Integrating shared autonomous vehicles in Last-Mile public transportation

While public transportation (PT) plays a critical role in urban mobility, the discomfort and the disutility of the last-mile trips make PT unattractive. We study the feasibility of shared autonomous vehicles (AV) as an on-demand alternative to fixed-route buses for last-mile travel. To this end, the bus routes that operate along the edges of the PT network in Bursa, Turkey are selected. The origin and destination (OD) pairs of the trips made on these bus routes are inferred at an individual level. The vehicle routing problem is then formulated by considering the proposed transportation service. Several solution methods are developed for both solution construction and solution improvement phases of the problem. To assess solution methods with real-world data, an agent-based simulation framework is built. It is found that the solution methods successfullysolved a dynamic problem. The results show that the integration of PT using AVs is well-suited to improve the service quality and energy efficiency in the last-mile mobility.

A Simulated Annealing for Optimizing Assignment of E-Scooters to Freelance Chargers

First- and last-mile trips are becoming increasingly expensive and detrimental to the environment, especially within dense cities. Thus, new micro-mobility transportation modes such as e-scooter sharing systems have been introduced to fill the gaps in the transportation network. Furthermore, some recent studies examined e-scooters as a green option from the standpoint of environmental sustainability. Currently, e-scooter charging is conducted by competitive freelancers who do not consider the negative environmental impact resulting from not optimizing the fuel efficiency of their charging trips. Several disputes have been recorded among freelance chargers, especially when simultaneously arriving at an e-scooters location. The paper aims to find the optimal tours for all chargers to pick up e-scooters in the form of routes, such that each route contains one charger, and each e-scooter is visited only once by the set of routes, which are typically called an E-Scooter-Chargers Allocation (ESCA) solution. This study develops a mathematical model for the assignment of e-scooters to freelance chargers and adapts a simulated annealing metaheuristic to determine a near-optimal solution. We evaluated the proposed approach using real-world instances and a benchmark-simulated dataset. Moreover, we compare the proposed model benchmark dataset to the baseline (i.e., state-of-practice). The results show a reduction of approximately 61–79% in the total distance traveled, leading to shorter charging trips.

Exploring micromobility mode preferences for last-mile trips from subway stations

The micromobility mode of transportation is convenient for short-distance trips in urban settings. The popularity of dockless sharing systems is rapidly increasing because of their characteristics of convenient rental/return and mobile payment options. Although many previous studies have examined travel behaviors regarding a single means of micromobility transportation, few have analyzed mode choice behavior among multiple, similar, and competing means of micromobility transportation. To our knowledge, no researcher thus far has examined micromobility as a potential means to solve the last-mile problem from the subway station to the destination. Therefore, a stated preference survey was conducted, analyzing factors and preferences influencing the mode choice of subway users for the last-mile trip. This study considered sharing dockless e-scooters and docked bicycles, as well as walking. It analyzed the differences in mode choice behavior of subway users based on their demographic and socio-economic attributes, as well as travel (travel purpose and distance), mode-specific (fare), and environmental (slope) characteristics. Two logit-based models—the multinomial logit (MNL) and mixed logit (ML) models—and two ML models based on residential areas of Seoul and Gyeonggi, Korea, were developed and compared. The results showed that the ML model was superior to the MNL model regarding model fit and individual parameters. In the ML model, the statistically significant variables included fare, marital status, household size, age, income, disability, and slope of roadway. However, the significance differed by alternative modes: for e-scooters (vs. bicycles), the factors influencing last-mile mode choice behaviors showed greater statistical significance. A comparison of the two ML models by region highlighted major differences in the results for the variables of household size and trip purpose between residents of Seoul and Gyeonggi. Urban transport policymakers interested in introducing micromobility services can use the findings of this study to make more well-informed decisions about traffic congestion problems and increase public transportation revenue in an environmentally friendly manner.

An agent-based model for assessing the financial viability of autonomous mobility on-demand systems used as first and last-mile of public transport trips: A case-study in Rotterdam, the Netherlands

The continuing urbanization and corresponding increase in transport demand are putting pressure on the accessibility, safety, sustainability, livability, and efficiency of urbanized regions. Public transport is regarded as a sustainable mode of transport for these regions and therefore transport policies aim to increase its attractiveness. However, public transport is facing last-mile connectivity problems. The application of Autonomous Mobility on-Demand (AMoD) as a feeder service for public transport hubs can potentially improve the first and last-mile trip leg which increases the attractivity of public transport. However, will such a system be financially viable when applied in an urban area? and what kind of operation will lead to the highest system performance? In this research, this question is addressed by proposing a method that connects macro transport modeling and agent-based modeling (ABM). An existing gravity-based travel demand estimation model built in a macro simulation tool is used to predict passenger demand across all the OD pairs of a city. For those OD pairs that can use the AMoD as first /last mile this is modeled using an agent-based rationale to be able to simulate the behavior of passengers and vehicles within that specific area of the city. The simulation model is applied to the case study area of the south of Rotterdam, in The Netherlands, where metro Station Zuidplein and the rail Station Lombardijen function as two AMoD hubs. Using the case study, the impact of relocation, ridesharing, and charging strategy is assessed in regards to financial viability. Among other insights, results show that the AMoD service leads to a profit on a typical business day for the operating companies despite the high-quality level of the service (very low average waiting time for a vehicle). If this particular system would not consist of automated vehicles and one would have to pay a salary to drivers, it would not be possible to make a profit on a typical business day. Moreover, results show that activating dynamic ridesharing and using wireless fast chargers at the stations results in the most financially viable operation. Activating automatic relocations results in the most costly operation.

Does the bus rapid transit reduce motorcycle use? Evidence from the Jakarta metropolitan area, Indonesia

Countries of lower average income, higher population density, and higher level of urbanization tend to have higher motorcycle ownership levels. Motorcycles bring safety and environmental challenges to Global South cities. The Jakarta metropolitan area in Indonesia adopted bus rapid transit (BRT) in 2004, but motorcycle ownership growth continued since. This empirical study examines what predicted motorcycle use in 2018, fourteen years after the opening of the BRT system TransJakarta, with particular attention paid to the potential impacts of the BRT on motorcycle use. It contributes to the understanding of high-capacity transit’s impacts on motorcycle travel in a Global South context. It tested literature review-based hypotheses with multinomial logit and left-censored tobit models predicting mode choice among motorcycle-based and bus-based modes as well as trip distance of motorcycle-based modes. The main dataset analyzed in this research contains 4,978 commuting-to-the-office first-leg trips. Model results suggested: proximity to the BRT is associated with office commute mode choice preference of the BRT over both motorcycle-based modes controlling for poverty rate, population density, and trip distance, and the effect is stronger on private motorcycles; similarly, proximity to the BRT is associated with reduced office commute trip distance in trips made by both motorcycle-based modes controlling for poverty rate and population density, and the effect is stronger on private motorcycles; village-level poverty rate is positively associated, and village-level population density is negatively associated, with private motorcycle trip distance. Such findings are generally in line with the literature. As the modal share of BRT is still low, transport policies in motorcycle-stressed cities with BRT could promote transit ridership by raising the relative costs of using private motorcycles such as parking costs, reducing the relative travel time of the BRT by increasing frequency and speeds, and improving the user-friendliness of first mile and last-mile trips connecting the BRT.

LAST MILE TRIPS: Logistics distribution infrastructure in smart cities and the experiences of service provision in the Metropolitan Region of Recife - PE

The present research aims to explore the main technologies added in the last mile logistics distribution infrastructure models used in smart cities, as well as relate them to the experiences of companies that provide these services in the Metropolitan Region of Recife (MRR). In order to do so, a case study is presented on the logistics distribution system used by a company that performs last mile delivery in the MRR. The data were collected through the application of a questionnaire to the manager of the company in question. Considering the studies analyzed on the subject, the implementation of new models of last mile logistics distribution in smart cities around the world, such as pick-up points, lockers, crowdsourcing and crowdshipping, was evident. Regarding the logistics distribution infrastructure used in the MRR, the results obtained showed that the application of the new models is still limited. It is concluded that the existence of public/private partnerships is essential for the introduction and strengthening of new last mile logistics distribution systems used in cities, whether they are considered smart or not.

Complementarity of dockless mircomobility and rail transit

Shared micromobility services have undergone rapid growth in cities throughout the world, including expansions in bike sharing and e-scooter sharing services. Shared micromobility provides a potential complement to public transit by accommodating first and last-mile trips. I analyze detailed data on shared, dockless bikes and e-scooters from Seattle, Washington. I find micromobility vehicles cluster near Seattle's rail transit stations. During the study period, Seattle expanded its rail system into a new section of the city. I use the system expansion as a natural experiment to provide evidence of complementarity between shared micromobility and public transit. Using a differencein-difference strategy I find that, after a new light rail station opened, the flow of new micromobility vehicles increased significantly within a 5 min walking radius of the station. I provide causal evidence that local rail transit increases the use of dockless micromobility vehicles.

Estimation of Route Choice Behaviors of Bike-Sharing Users as First- and Last-mile Trips for Introduction of Mobility-as-a-Service (MaaS)

Bicycling has been considered the sustainable alternatives of first- and last-mile trips for Mobility-as-a-Service (MaaS) in integrated transport systems. This study aims to analyze the route choice behaviors of bike-sharing users for the first- and last-mile trips in MaaS, incorporating the connectivity to the subway stations. The observed GPS data is employed to generate the route travels of bike-sharing users, and the choice set generation algorithm, i.e., the k-medoids clustering method, is applied to extract the representative alternatives in route choice models. This study analyzes the path-size logit model to compare the route choice behaviors incorporating peak periods, and access and egress trips. The bike-sharing use at the evening-peak period is more frequent than the other periods. Also, the bike-sharing users are found to be positively associated with the ratio of bike lanes for the access and egress trips to the subway stations, whereas they are reluctant to detour for their trips. The finding of this research is that the extension of bike facilities on access and egress to the subway stations is necessary to improve the bike-sharing use for the first- and last-mile trips in MaaS.

Evaluation of e-scooters as transit last-mile solution

E-scooters are an alternative for short trips and are particularly suitable for solving the last-mile transit problem, yet their impact on transit is not well understood. There is a need to understand the e-scooter demand patterns and users’ characteristics to develop adequate policies and regulations. In this research, we consider the problem of modeling the interaction of e-scooters and bus transit services and provide an overview of e-scooter trips and user characteristics. We use a revealed-preference survey to evaluate the e-scooter usage in one of the highest-demand areas in the City of Austin, corresponding to a university campus. We explore population characteristics, mode shift, and mode interaction. Then, using publicly available datasets, we provide a causal analysis to evaluate the nature of the relationship between e-scooter and transit trips in the whole city. Assessing this relationship is challenging because several factors affect the demand of both types of trips (e.g., location of attractive zones), known as confounding variables. We develop a methodological framework to isolate the effects of confounding variables on transit trips using a two-stage regression procedure. The first stage aims to isolate confounding variables using a gradient boosting regression. The second stage models first and last-mile trips using a negative binomial and a zero-inflated negative binomial count model. The university survey indicated that 12 percent of the e-scooter users employed transit to complement their trips. Although small in magnitude, the data modeling results show that a statistically significant relationship was found on the university campus and downtown areas, supporting the survey results and extending the analysis to other areas of the city. However, the overall interaction between the two modes has a small magnitude. The proposed methodology can be used to identify areas with potential e-scooter and transit interaction.

Last-Mile Shuttle Planning for Improving Bus Commuters’ Travel Time Reliability: A Case Study of Beijing

This study proposes a multiobjective mixed integer nonlinear programming model for a last-mile shuttle service to improve bus commuters’ travel time reliability. The approach aims to assign the routes that pick up the transit passengers located at the different stops by shuttle service. A bilevel optimization model is established: the upper model of route design considers the tradeoff between time cost and fare cost when some of the passengers take the shuttles, and the lower model assigns the demand of transit passengers. The proposed model effectively captures the reliability of travel time because related parameters are estimated by a statistical fitting test with a large number of real-world bus geographic information system (GPS) data. Moreover, dynamic demand diverting from conventional transit to shuttle service and travel time reliability, including passenger in-vehicle time (IVT) and waiting time (WT), are fully considered in this model. Since the task is a nonlinear programming model, a two-stage algorithm combined with linearization processing is presented to find an optimal solution. Finally, from the case study of Zhongguancun Software Park zone in Beijing, it is indicated that when last-mile shuttle service is provided, bus passengers’ travel time reliability of last-mile trips can be improved by 14%. The study can be an important reference for improving the low reliability widely existing in the current transit commuters’ last-mile problem.

The interplay between dockless bikeshare and bus for small-size cities in the US: A case study of Ithaca

As another mode of shared transportation, bikeshare can substitute or complement public transit. Prior studies mainly relied on self-reported survey data or aggregated station-level data from docked bikeshare systems, and their conclusions and implications were focused on large cities. It is largely unknown how and to what extent a dockless bikeshare system complements or substitutes public transit, especially in small cities. This study was set to measure the interplay between Lime dockless bikeshare and bus service in Ithaca, NY – a typical small-size college town – and its environs. By joining about 3.42 million records of bus stop data and 102 thousand Lime bikeshare trip data from 2019, two types of Bikeshare-Bus-Linkage (BBL) trips were identified, namely (1) the first-mile trip where a user rides a Lime to board a bus, and (2) the last-mile trip where a user bikes to their destination after alighting a bus. BBL trips were identified using a spatiotemporal proximity framework based on two important parameters: the catchment radius and the time window between a bus stop event and a Lime trip. Different values were tested with a sensitivity analysis, and the parameters were finally set at 100 ft. and 5 min. As such, 3026 BBL trips were identified, which was 3% of total Lime ridership or 0.1% of total bus ridership. Our findings indicated that Lime provided useful first- and last-mile transfers to bus service for commuters. The complementary effect was particularly strong in the urban core and with transit development and employment land use areas. Moreover, in the morning peak, there were more first-mile trips from residential areas to bus stops in the urban core, while in the evening peak more last-mile trips started from bus stops in the urban core to residential areas. Based on the unique first-mile and last-mile trip patterns identified, policy implications and recommendations for bikeshare operators, local government, transit agencies, and transportation policymakers were discussed to better integrate bikeshare and public transit.

Mobility service design via joint optimization of transit networks and demand-responsive services

This paper proposes a modeling framework to design an integrated mobility service system that is composed of a local demand-responsive transportation (DRT) component and a fixed-route transit network component. The region is partitioned into disjoint local zones, and a trip is characterized into an intra- or inter-zonal one based on whether its origin and destination belong to the same zone. The transit network provides backbone line-haul service to inter-zonal trips, while the DRT system targets intra-zonal trips as well as the first-mile and last-mile legs of inter-zonal trips. The system components can be broadly defined, and this paper considers, as examples, conventional non-shared taxi or ride-sharing for the DRT service, and regular bus, bus rapid transit (BRT), or metro for the backbone network. For quantitative analysis of the DRT services, new aspatial queuing network models are developed to capture various DRT operations for serving trips with randomly distributed origins and destinations (i.e., intra-zonal trips) and those with origins or destinations concentrated at a set of fixed transit stations (i.e., first- or last-mile trip legs) at the same time. Each queuing model is integrated with the transit network design model, through proper service region partition, to derive closed-form formulas for the agency and passenger costs. Then, we formulate constrained non-linear programs that simultaneously optimize the zone partition, the fleet size and repositioning operation for the local DRT service, as well as the spacing and headway of a grid transit network. We apply the proposed models to a variety of transit technologies and application scenarios, so as to demonstrate applicability of the models, and to show promising performance of the proposed systems.

Measuring the perceived need for motorcycle-based ride-hailing services on trip characteristics among university students in Yogyakarta, Indonesia

Since the emergence of ride-hailing services has changed travel behaviors, a greater understanding of the ride-hailing mode enables us to explore choices and assists in the drafting of more effective policies. This paper aims to investigate the degree of perceived need for motorcycle-based ride-hailing services among university students because young and well-educated people dominate this service. By involving 632 respondents and considering 12 trip characteristics, the Rasch model was used as an instrument to measure the students’ perceived needs and inherent resistance to motorcycle-based ride-hailing services. The model results revealed that the students perceived the highest need for motorcycle-based ride-hailing services for their first- and last-mile trips when they needed to travel out of town by public transport. A need for this service was also perceived by the students for trips at peak periods, trips within tight schedules, trips to downtown areas, trips to campus, and food delivery. In contrast, the study found a weakly perceived need for motorcycle-based ride-hailing for shopping goods and documents delivery, trips for shopping, social, and momentary activities, and short-distance trips. The empirical findings also showed that the variable of gender, monthly income, motorcycle ownership, frequency of use, and time spent as motorcycle-based ride-hailing users contributed to differences of perceived need. The research findings can help the government in deciding effective policies for ride-hailing, especially those related to riding safety and increasing urban transit demand.

A GIS-Based Methodology for Evaluating the Increase in Multimodal Transport between Bicycle and Rail Transport Systems. A Case Study in Palermo

Background: In a world where every municipality is pursuing the goals of more sustainable mobility, bicycles play a fundamental role in getting rid of private cars and travelling by an eco-friendly mode of transport. Additionally, private and shared bikes can be used as a feeder transit system, solving the problem of the first- and last-mile trips. Thanks to GIS (Geographic Information System) software, it is possible to evaluate the effectiveness of such a sustainable means of transport in future users’ modal choice. Methods: Running an accessibility analysis of cycling and rail transport services, the potential mobility demand attracted by these services and the possible multimodality between bicycle and rail transport systems can be assessed. Moreover, thanks to a modal choice model calibrated for high school students, it could be verified if students will be really motivated to adopt this solution for their home-to-school trips. Results: The GIS-based analysis showed that almost half of the active population in the study area might potentially abandon the use of their private car in favour of a bike and its combination with public transport systems; furthermore, the percentage of the students of one high school of Palermo, the Einstein High School, sharply increases from 1.5% up to 10.1%, thanks also to the combination with the rail transport service. Conclusions: The GIS-based methodology shows that multimodal transport can be an effective way to pursue a more sustainable mobility in cities and efficiently connect suburbs with low-frequent public transport services to the main public transport nodes.

Understanding the socioeconomic characteristics of paratransit drivers and their perceptions toward electric three-wheeled rickshaws in Delhi, India

In India, electric rickshaws (ERs) prove to be a sustainable and affordable paratransit mode for the public. The ER service is also creating employment and income opportunities for the unskilled labor force. Many Indian state governments are proposing ER services to cater to first and last-mile trips. Therefore, planners must identify the significant factors that can affect ER services' adoption and expansion. Because of this, the present study investigates the perceptions of drivers of three prominent paratransit modes toward ERs. The research also provides a better understanding of the socio-economic conditions of these paratransit drivers. The study utilizes data of 620 paratransit drivers obtained from a face-to-face survey conducted in Delhi, India. Grey relation analysis is applied to assess the three paratransit driver groups' perceptions about ERs. The data reveals that paratransit drivers belong mostly to low financial and educational backgrounds. Male drivers constitute many paratransit drivers in the city. The lack of facilities such as designated parking and fixed charging stations and fare regulation is perceived as critical ER services barriers. Similarly, the absence of separate lanes and unsafe overtaking attempts by fast-moving vehicles are the major causes of accidents involving ERs. Further, the light body of ERs and careless driving and traffic rule violations of drivers in mixed traffic conditions are the primary safety issues. The study also highlights potential policy recommendations to design an efficient electric version of the paratransit service for achieving sustainable development goals.

Factors affecting heterogeneity in willingness to use e-scooter sharing services

This study investigated the factors affecting heterogeneity in people’s intention to use e-scooter sharing (ESS) service. For the investigation, the data were collected in Seoul, Korea, and a latent class adjacent-category ordinal logit model was estimated. The results show that the respondents could be divided into two groups. One group comprises those who tend to prefer to use the ESS service for commuting, and the other group involves those who tend to prefer the service for the first-mile and last-mile trip. According to the estimated class membership characteristics, the members involved in the first group tend to be younger, higher earners and less satisfied with the current public transportation than the other members who are associated with the second group. These results suggest that the preferred trip situation and purpose for using ESS services could vary not only depending on people’s socio-demographics but also the quality of public transportation.

Electric scooter sharing: How do people value it as a last-mile transportation mode?

With its advantages in urbanized areas, the electric scooter sharing (ESS) system has received considerable popularity as a transportation mode for short-distance trips. In this paper, people’s preferences toward ESS for last-mile trips were analyzed using a stated preference experiment. We designed the experiment to scrutinize how people value ESS-riding compared with other conventional last-mile transportation modes. The values of travel time components such as access and riding times are estimated using a mixed logit model. The values of riding transportation modes were significantly greater than that of walking for a last-mile trip. However, none of the time values of two modes—those from a conventional last-mile mode and ESS—was dominating because the difference in the dispersions of each made the time value curves intersect around their medians. Considering the results, we have concluded that ESS is a competitive transportation mode in last-mile situations.