Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Bus rapid transit as arterial corridor traffic calming: The relationship between transit infrastructure and motor vehicle operating speeds
No full textObjectives
This article presents an analysis of the traffic-calming effects of bus rapid transit (BRT) by studying changes to motor vehicle speeds before and after implementation of Albuquerque Rapid Transit (ART) infrastructure in Albuquerque, New Mexico. Methods
While ART construction was completed in spring 2018, the BRT buses did not operate until December 2019; providing a unique opportunity to explore the influence of BRT infrastructure sans BRT buses (i.e., to tease apart the effects of BRT infrastructure and operations). We used validated data from StreetLight InSight to compare before/after changes to average motor vehicle speeds and 85th percentile motor vehicle speeds at 46 ART sites and 36 control sites. Results
Findings suggest that infrastructure associated with BRT systems can improve traffic safety by reducing vehicle speeds. Speed decreases at the ART sites were especially strong in terms of 85th percentile decreases, suggesting that the BRT infrastructure is especially effective at limiting excessive speeding. Motor vehicle 85th-percentile speeds along the ART corridor were reduced by 11.5% (compared to a 5.8% decrease at control sites). The 85th-percentile speeds at the ART sites decreased from 32.3 mph to 28.6 mph, which is an especially important range for vulnerable road-user safety outcomes. While ART intersections saw the largest decreases in absolute speeds (a reduction of 4.1 mph in 85th-percentile speeds), ART mid-block sites had larger decreases relative to the control mid-block sites (decreases in 85th-percentile speeds were 73.7% greater at ART mid-block sites than at control mid-block sites). BRT-related lane reductions were linked with particularly strong speed reductions; there were 85th-percentile speed reductions of 4.1 mph (12.6%) when general vehicle lanes were removed versus 2.2 mph (7.8%) when lanes were not removed. Conclusions
Speed reductions were experienced across the ART corridor even though 87.0% of BRT locations did not have a change in posted speed limit, suggesting that physical changes to the roadway associated with BRT were impactful in terms of speed reductions and in turn could possibly promote traffic injury prevention by decreasing the number and severity of crashes
En-route charge scheduling for an electric bus network: Stochasticity and real-world practice
No full textBus electrification, with its high energy conversion efficiency and zero tailpipe emissions, has a significant impact on addressing the petroleum crisis and lowering carbon emissions in urban transportation. However, long charging times and uncertain operational risks hinder their wider adoption. This paper explores the robust en-route charge scheduling problem for electric buses to overcome uncertain energy consumption while ensuring charging accessibility. The problem is first described as a deterministic mixed-integer linear programming model that employs a time-of-use electricity price to balance the charging demand. Additionally, a robust counterpart model is formulated to account for stochastic energy. Numerical studies are designed to evaluate the proposed model in a real network, followed by a sensitivity analysis to investigate the impact of battery type, fleet composition, and depth of discharge on the charging schedule. The results show that the robust optimization model provides system feasibility against uncertainty with a comparable price and emissions
A semi-systematic literature review, identifying the relationship between transit environments and women’s fear of victimization in transportation systems: a global perspective
No full textFemale commuters across the globe face numerous constraints while using public transport (PT) systems. Unfortunately, the gender-specific needs and demands of women are often ignored while designing transportation settings, particularly in developing countries. Consequently, transit fear and victimization have become prevalent in such fragile transport systems. This study aims to shed light on the close association between transit fear, victimization, and the inadequacies of transportation systems. It also explores how these issues have been addressed in academic discourse over time. The study employs a combination of ‘narrative review’ and ‘systematic review’, commonly known as a ‘semi-systematic review’ process. To achieve its objectives, the study reviewed 88 papers, including relevant grey literature for narrative analysis, and conducted different themes and keywords analyses on 116 Scopus-indexed papers for a comprehensive systematic review. However, in the context of developing countries, the Scopus database reveals a scarcity of empirical studies that focus on women’s victimization during transit and gendered transport environment settings. This leads to a significant disparity in recognizing transit victimization, implementing effective mitigation measures, and understanding the patterns of reporting harassment varying substantially between developed and developing nations. While the narrative review provides detailed observations, the bibliometric analysis adds new insights and strengthens the understanding of the narrative review from different perspectives
Revisiting residential self-selection and travel behavior connection using a double machine learning
No full textResidential self-selection (RSS) confounds the connection between the built environment and travel behavior. Existing studies have used endogenous switching regression models to quantify the proportions of the built environment itself and RSS in the observed behavioral difference between different environments. However, the models are sensitive to model specification and assume pre-defined (mostly linear) relationships among variables. This study applies a double machine learning approach to fill the gap. The empirical context is to jointly model residential choice of Bus Rapid Transit (BRT) neighborhoods and weekly driving distance of household owning cars in Jinan, China. The results showed that the RSS effect accounts for about 40% of the observed difference in driving distance between the households living inside and outside of BRT neighborhoods. This results also emphasizes the necessity of relaxing the linearity assumption in the research on the relationships among the built environment, RSS, and travel behavior
Exploring the long-term threshold effects of density and diversity on metro ridership
No full textWhile numerous studies have demonstrated the effects of density and diversity on metro ridership, few studies have explored the long-term mechanisms of these effects. Employing smartcard data and multisource big data from Wuhan between 2015 and 2019, this study applied the panel threshold model to explore the long-term threshold effects of station area density and diversity on metro station-to-station ridership. The results indicated that only when development intensity and land use mix exceeded the threshold values would there be significant positive impacts on ridership at the origins and destinations, and the ridership benefits were significantly reduced when the origin intensity exceeded 1.622 or when the mix exceeded 0.635. Additionally, population density, POI mixture, bus stops and parking lots, station, and network attributes had long-term significant impacts on metro ridership. These findings can contribute to implementing differentiated land development patterns and promoting the sustainable development of TOD strategies
Resilience analysis of an urban rail transit for the passenger travel service
No full textThe frequent occurrence of natural disasters and operational incidents poses a significant threat to urban rail transit (URT) systems. Therefore, it is crucial to design a resilient URT network that can offer commuters convenient and reliable services. In this study, we construct a URT life-cycle resilience assessment model oriented towards passenger travel service. This proposed methodology is applied to the Beijing rail transit using real-world data. The results indicate that the importance of stations depends not only on topology but also on passenger flow and redundancy alternatives. The loop line exhibits greater resilience and can efficiently evacuate passengers in the event of a disturbance. Additionally, hub transfer stations that connect to suburban areas, while not central in the network\u27s topology, emerge as potential weak points. The findings of this study carry substantial implications for the URT\u27s daily operational management and decision-making processes
Railway line planning with passenger routing: Direct-service network representations and a two-phase solution approach
No full textThe railway line planning problem (LPP) plays a crucial role in determining the quality of services provided to passengers, as well as operation costs borne by railway companies. In periodic railway LPPs, it is common to consider passenger transfers between train lines to realize a general passenger travel cost setting in the railway system. While detecting passenger transfers requires incorporating passenger routing into mathematical formulations, thereby significantly complicating the problem. Studies on transfer-included LPPs are generally based on the Change&Go network that is constructed based on a pre-given line pool, which however is usually non-exhaustive due to computational intractability. To efficiently include passenger transfers in large-scale railway LPPs, this paper proposes a novel extended direct-service network representation of LPP, where lines are dynamically generated within the optimization process, and part of passenger transfers between lines can be precisely captured without the need for explicit modeling of passengers’ distribution on specific lines. A two-phase solution approach based on the representation is designed. The first phase formulates LPP with part of transfers as a path-based service network design model, solved using a branch-price-and-cut algorithm. The second phase conducts a neighborhood search around the first-phase solution to seek better ones when considering all passenger transfers. Numerical results showcase the good performance of the two-phase solution approach. It delivers optimal solutions in 18 out of 24 test instances for a small case and achieves optimality gaps within 2.85% across all small instances. The large case study of China’s Shandong high-speed railway network whose line pool size reaches millions demonstrates the scalability of the approach and its advantage over the traditional Change&Go method with partial line pools and an exact model developed in the paper
Integrating shared e-scooters as the feeder to public transit: A comparative analysis of 124 European cities
No full textE-scooter sharing is a potential feeder to complement public transit for alleviating the first-and-last-mile problem. This study investigates the integration between shared e-scooters and public transit by conducting a comparative analysis in 124 European cities based on vehicle availability data. Results suggest that the integration ratios of e-scooter sharing in different cities show significant variations and range from 5.59% to 51.40% with a mean value of 31.58% and a standard deviation of 8.47%. The temporal patterns of integration ratio for first- and last-mile trips present an opposite trend. An increase in the integration ratio for first-mile trips is related to a decrease in the integration ratio for last mile in the time series. Additionally, these cities can be divided into four clusters according to their temporal variations of the integration ratios by a bottom-up hierarchical clustering method. Meanwhile, we explore the nonlinear effects of city-level factors on the integration ratio using explainable machine learning. Several factors are found to have noticeable and nonlinear influences. For example, the density of public transit stations and a higher ratio of the young are positively associated with the integration ratio to a certain extent. The results potentially support transport planners to collectively optimize and manage e-scooter sharing and public transport to facilitate multi-modal transport systems
Entire route eco-driving method for electric bus based on rule-based reinforcement learning
No full textElectric bus (EB) has gradually become one of the main ways of transportation in cities due to the low energy consumption and low pollutant emissions. As battery endurance is easily affected by various factors such as external temperature, vehicle load, and driving habits, the anxiety for the endurance of EB has become a concern for researchers. To bridge the gap, an eco-driving method based on deep reinforcement learning (DRL) is proposed to achieve the entire route energy-saving. Firstly, the significant factors including the dynamic passenger load and air conditioner is considered for the energy consumption model of the EB. Secondly, a rule-based reinforcement learning algorithm is utilized for optimizing the driving speed and strategy, which can accelerate the convergence of the proposed model and improve the average reward of the reward function. Thirdly, by adjusting the reward function of reinforcement learning algorithm, three eco-driving modes of EB, namely efficiency priority mode, energy-efficiency balance mode and energy saving priority mode under various operational states are proposed. Finally, the results indicate that the efficiency priority mode achieves about an 8% increase in traffic efficiency and a reduction of approximately 20% in energy consumption compared to the baseline model. With the energy-efficiency balance mode, the model attains a 34.05% reduction in energy consumption with almost the same traffic efficiency. Under the energy saving priority mode, the proposed model exhibits a minor reduction in traffic efficiency within an acceptable limit but decreases energy consumption by 40.69%, achieving the optimization goals
Revisiting the richness of integrated vehicle and crew scheduling
No full textThe last decades have seen a considerable move forward regarding integrated vehicle and crew scheduling in various realms (airline industry, public transport). With the continuous improvement of information and communication technology as well as general solvers it has become possible to formulate more and more rich versions of these problems. In public transport, issues like rostering, delay propagation or days-off patterns have become part of these integrated problems. In this paper we aim to revisit an earlier formulation incorporating days-off patterns and investigate whether solvability with standard solvers has now become possible and to which extent the incorporation of other aspects can make the problem setting more rich and still keep the possible solvability in mind. This includes especially issues like delay propagation where in public transport delay propagation usually refers to secondary delays following a (primary) disturbance. Moreover, we investigate a robust version to support the claim that added richness is possible. Numerical results are provided to underline the envisaged advances