Re-envisioning the Park-and-Ride concept for the automated vehicle (AV) era with Private-to-Shared AV transfer stations

Cities implemented park-and-ride (PNR) systems to decrease congestion in dense urban areas while providing transit options to travelers who live in a city\u27s low- to medium-density regions. The success of PNR systems is mixed, as they suffer from several disadvantages, namely, the uncertainty of parking locations and infrequent and/or unreliable transit services, and the fact that travelers still need to walk to their destination. Motivated by the premise of PNR systems and the potential of automated vehicles (AVs), to address each of the shortcomings of PNR systems, this study proposes a future system with near-ubiquitous AVs where travelers transfer from privately owned AVs (PAVs) to shared-use, shared-ride AVs (SAVs), called a PAV-SAV transfer system. This study proposes a modeling framework to assess the potential market share of the PAV-SAV transfer system and the network impacts (e.g., congestion, vehicle miles traveled) of the proposed system. Finally, the study identifies good designs for the PAV-SAV transfer system using scenario analysis. The critical design variables are the location of transfer stations, the capacity of SAVs, and the transfer station connector links. For the Greater Los Angeles area, the computational results show a market share for PAV-SAV of almost 18% for person trips terminating in downtown Los Angeles. In all scenarios, the proposed PAV-SAV system decreases vehicle hours traveled (VHT) across the whole network with significant decreases in the urban core. For all designs, the PAV-SAV system decreases vehicle miles traveled (VMT) compared to a network without PAV-SAV transfer stations, albeit only slightly. Locating transfer stations closer to the urban core, increasing vehicle capacities, and connecting transfer stations to both arterial links and highway links improves network performance (i.e., VMT and VHT) and increases the market share of the PAV-SAV system

Impacts of COVID-19 on the premiums of proximity to railway stations: An in-depth analysis using passenger flows

As a result of the coronavirus (COVID-19) pandemic, work and leisure patterns have changed significantly, as have commuting and travel behavior. This has led to changes in the degree of dependence and demand for mass transportation. This paper proposes that these changes decrease people\u27s demand to live near public transportation services and cause the decline of the positive externality created by public transit as measured by house prices. This paper explores the train stations of Taiwan\u27s two largest cities (Taipei and Kaohsiung) by adopting various hedonic price models to estimate the COVID-19 effect on the premiums of proximity to rail stops. We then analyze whether the changes in premiums are affected by the passenger flow at the station. This paper uses four variables to measure passenger flows: the number of total passengers on services, the net number of passengers (the number leaving the local area minus the number of arriving at the local area), and the expected numbers of commuters and non-commuters. The empirical results of this paper show that after the COVID-19 outbreak, the monetary value of the proximity of railway stations decreased significantly. However, the COVID-19 effect on different stations is heterogeneous. The post-COVID-19 decrease in the positive externality associated with proximity to a rail station is significantly affected by passenger flows. The changes in the positive externality of stations found in this study suggest the public has reduced their dependence on stations due to changes in commuting behavior. We urge the government to pay attention to whether the commuting flows and the public\u27s demand for public transportation have shifted and the use of vehicles and road transportation has risen

Causal identification of transit-induced property value uplift in Canada\u27s Waterloo Region: A spatio-temporal difference-in-differences method application

Renewed interest in light-rail transit (LRT) in North America has heightened the need for an improved understanding of transit impacts on land value uplift (LVU). A number of studies have investigated the relationship, with findings varying with local contexts and estimation methods. Most of these studies focus on the aggregate effects of transit using cross-sectional models, but do not examine the spatial and temporal heterogeneity in transit impacts through quasi-experimental approaches. To bridge this gap, we build a set of spatio-temporal difference-in-differences (STDID) models for the causal identification of transit-induced land-value uplift, taking the new LRT line in Canada\u27s Waterloo Region as the case study. The study contributes to the transit-induced LVU literature in several ways. First, we account for the space-time influence of recent comparable sales in price determination, a transaction data-generating process often excluded in hedonic studies. Second, our models reveal the disaggregate effects of transit policies in different station areas and transit phases. Third, we provide a pre-LRT analysis in a car-dependent mid-sized urban area, which offers insight into speculative investment in TOD areas and/or resident anticipation of future accessibility benefits. The findings can provide guidance for value-capture programs and cost-benefit analysis for transit-oriented development in mid-sized cities

A latent class analysis to understand riders’ adoption of on-demand mobility services as a complement to transit

On-demand app-based shared mobility services have created new opportunities for complementing traditional fixed-route transit through transit agencies’ efforts to incorporate them into their service provision. This paper presents one of the first studies that rigorously examine riders’ responses to a pilot aimed at providing such a transit-supplementing service. The study conducts latent class analysis on riders of the Via to Transit program, a mobility pilot in the Seattle region where on-demand service was offered to connect transit riders to light rail stations. The analysis identifies three distinct rider groups with heterogenous responses to the on-demand service: (1) riders who previously used private cars or ride-hailing; (2) riders who were pedestrians and bikers but switched likely because of safety concern; (3) mostly socio-economically disadvantaged riders who previously relied on the bus, but switched to the new service for the convenience and speed. These results point to rich transportation policy implications, which can inform decision-making by public transit agencies as they are exploring alternative ways to deliver the mobility services

Delivering Transit Oriented Development (TOD) in low to medium density contexts. Actor relationships and market conditions in smaller Swedish cities

This article analyses actor relationships in Transit Oriented Development (TOD) planning in order to better understand the preconditions necessary for planning processes to result in TOD in lower density contexts, in suburbs, or small cities. Empirically, the analysis builds on a comparative case study of TOD planning projects. The focus in the analytical work is on understanding how market conditions in lower density contexts influence the conditions for TOD planning projects, and how this feeds through to planning processes. The overall conclusion is that we should not expect that planning processes in small cities with low to medium densities of populations and activities differ much from those in more ‘classic’ highly urban TOD locations. Market conditions had an impact on planning processes, but once in the planning stage conditions for implementation depended more on the ability to handle competing interests and less on market conditions. In terms of policy recommendations, it is important for actors to develop a joint vision of the built environment of the site in question that channels organizations’ individual actions in a joint direction. The ability to achieve such a joint vision for the design of the site in question may be more important in small towns than in more ‘typical’ TOD contexts in denser urban areas. This is because all enablers need to work together in a positive way in such location – which may be marginal from a market point of view – for the development to be able to go ahead

Passive transit accessibility: Modelling and application for transit gap analysis and station area assessment

This paper presents a passive transit accessibility model and showcases its applications to Brisbane, Australia, as a robust decision support tool for transport and urban planning. Active accessibility describes how easy it is for a person to reach essential activities such as work, education or shopping, while passive accessibility refers to the ease of an activity located in a given area being reached by potential users such as workers, students or shoppers. The passive accessibility measure can help determine the location of new activity centres where good transit access is essential to serve nearby communities. Two case studies are presented to demonstrate the application of the model. First, the model is used to examine the passive transit accessibility of major employment and commercial areas in Brisbane, Australia, to identify areas deemed in needs of transit service improvement. Second, the model is incorporated into the node–place modelling framework for assessment of potential transit oriented development (TOD). The node–place model offers a conceptual framework for evaluating the (re)development potential or enhancing the transit supply of station areas. The node–place model is used to classify 1186 analysis zones in Brisbane. The study identifies areas that have potential for transforming into TODs after improving transit accessibility or changing land use or development

Revealing latent trajectories of (intended) train travel during and after COVID-19

This study investigates whether the decline in public transit ridership is a temporary phenomenon or indicative of a structural shift in travel patterns and attitudes. We estimate a latent class trajectory model using data from a comprehensive and large-scale survey administered by the Dutch national train operator conducted at eight different points in time after the onset of the pandemic. Six latent trajectories in train use and stated future intentions to use the train are revealed, showing different ‘recovery’ pathways. Whereas low-educated frequent commuters travel almost as much as before, highly educated frequent commuters and mixed-purpose travellers still travel much less, even in the last wave when all restrictions are lifted. The results indicate that travellers belonging to these classes have structurally changed their behaviour. The shift to working from home is more pronounced than the shift to private car use

A branch-and-cut algorithm for scheduling train platoons in urban rail networks

With the emerging of virtual coupling technologies, the concept of train platoon, where different vehicles can be flexibly and dynamically grouped or decoupled, has become a hot research topic. In this study, we investigate the scheduling of train platoons for urban rail networks with time-dependent demand to mitigate passenger inconvenience. We propose a mixed-integer linear programming (MILP) model that simultaneously optimizes the train-platoon (de)coupling strategies, arrival/departure times at each station, and the running orders of trains, while considering limited rolling stock resources at the depots and the safety of trains at cross-line zones. To tackle computational challenges in real-world instances, we develop a customized branch-and-cut solution algorithm, based on the analysis of mathematical properties of our MILP model, to generate (near-)optimal solutions more efficiently. In particular, we propose three sets of valid inequalities that are dynamically added to the model to strengthen the linear relaxation bounds at each node. We also design a customized branching rule in the search tree by imposing to branch on the key decision variables regarding the train orders at the cross-line zones. Real-world case studies based on the operational data of Beijing metro network are conducted to verify the effectiveness of our approach. The results demonstrate that our branch-and-cut-based approach evidently outperforms commercial solvers in terms of solution quality and computational efficiency. Compared to the current train schedule with fixed compositions in practice, our approach with flexible coupling strategies can reduce the passenger dissatisfaction by over 15%

A composite index for the evaluation of sustainability in Latin American public transport systems

Latin American public transport (PT) systems are the backbone of urban transport with high ridership levels but at the same time, they face substantial deficits in terms of their sustainability. No comprehensive framework for PT sustainability assessment exists so far that is tailored to the specific local situation in this region. Therefore, this study develops for the first time a theoretically sound and feasible index for assessing the sustainability of PT systems in Latin America, the Sustainable Public Transport Index for Latin America (SPTI-LATAM). The index is based on an Assessment Indicator Model (AIM) with overall 49 indicators in the five dimensions system effectiveness, social, environmental, economic, governance and integrated transport planning. The SPTI-LATAM is designed with three levels: 1) the basic index (BSPTI) containing 32 indicators; 2) the extended index (ESPTI) including 11 additional indicators; and 3) the global index (GSPTI) with 6 additional indicators. The BSPTI is computed for eleven case study cities to demonstrate its feasibility and to analyze the sustainability of PT systems in the region. The framework uses the Equal Weighting Aggregation (EWA) method for assigning weights to each indicator, the Weighted Sum Model (WSM) for aggregating the indicators to the overall index and international standards and benchmarks for normalization. The final scores of the BSPTI show that the case study cities have still challenges to reach sustainability since only two cities had scores slightly higher than the half of achievable points (55 and 51), while eight cities had scores between 40 and 50 points, and one city achieved 39 points. Deficits are identified mainly for PT service quality, for the environmental performance, for the governance dimension and less for PT system coverage. Overall, the analysis of the BSPTI-LATAM for the 11 case study cities shows that the index is suitable for benchmarking sustainability of local PT systems and ready to be used in research and practice

Integrated impact of urban mixed land use on TOD ridership: A multi-radius comparative analysis

The global trend toward urbanization has spurred the widespread adoption of transit-oriented development (TOD). While previous research has extensively explored the relationship between land use and TOD ridership, much of it has focused on linear associations at a singular scale. Leveraging recent advancements in nonlinear modeling and the accessibility of open-source data, this study employs a comprehensive two-step methodology. Firstly, K-means clustering algorithm categorizes TOD sites in Shenzhen into three distinct clusters, providing a site-based understanding of their characteristics. Subsequently, a Light Gradient Boosting Machine (LightGBM) classification model, complemented by SHapley Additive exPlanations (SHAP) values for interpretation, quantitatively evaluates the influence of mixed land use on TOD ridership across various catchment areas. As for the findings, we discover that land-use factors have different effects on TOD site patronage at different buffer radii and delve into the intricacies of these effects. Further results reveal non-linear relationships with varying degrees of positivity and negativity. For instance, residents and health sites positively impact patronage across all buffer radii, while certain commercial land uses exhibit a negative influence. The study demonstrates how the importance of different land-use structures varies across these clusters, shedding light on the nuanced impacts of land use on TOD catchment areas. Our research optimizes land-use mixes based on predominant cluster characteristics by offering actionable recommendations for urban managers