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This paper addresses the topic of transportation network vulnerability within the context of the New York City subway system. We propose a network model for it and an approach based on shortest-path passenger flow simulations in order to quantify delays experienced by passengers arising from disruptive events, particularly from those that occur simultaneously. We determine if and to what extent the effect under such simultaneous scenarios is greater than it would be had the same disruptions occurred as separate events. Our findings can be useful in supporting the planning decisions necessary to prepare for the harmful consequences arising from disruptions to complex urban networks. [ABSTRACT FROM AUTHOR]

The accessibility of public transport presents an important indicator of the quality of passenger public transport system. An adequate network between the rural and urban areas is essential for several reasons, particularly for commuting. A comparative analysis of the public transport options in rural areas with the demographic factors of the analysed areas will enable us to determine, and thereby, evaluate the mobility of commuters. This paper presents some results of the case study of Croatian rural area in the county of Sisak-Moslavina. [ABSTRACT FROM AUTHOR]

The rise of autonomous vehicles (AV) will revolutionize the transportation industry and it will transform the society itself, much like the nineteenth century shift from horse-carriages to automobiles. The automobile industry as well as governments/authorities all around the world are trying to create vehicles and road traffic infrastructures to support this futuristic public/private transportation technology. In our paper we are putting forward a feasible method of implementing the autonomous vehicular technology in a developing country like India as a public transport system in itself or as a feeder system to public transport systems like metro by using the concepts of safe state and kill switch. [ABSTRACT FROM AUTHOR]

Eco-driving is one of the many options to reduce fuel consumption and emissions from transit operations. However, it is not yet clear how effective eco-driving is for different transit service and fuel types. As policymakers consider implementing eco-driving, they also need comparisons of eco-driving against other fuel-conserving strategies, such as purchasing alternative fuel vehicles. Using a case study of transit operations in Atlanta, Georgia, United States, this paper evaluated eco-driving for two very different service types – local urban service and express service. The authors simulated the implementation of transit eco-driving strategies using an innovative, streamlined algorithm designed to minimize fuel consumption by limiting instantaneous vehicle specific power while maintaining average speed and conserving total distance. Fuel consumption and fuel-cycle emissions were compared across the monitored driving cycles and their modified eco-driving cycles. The savings from eco-driving were also compared to fuel and emissions reductions expected via the conversion of the transit fleets to compressed natural gas (CNG), another popular fuel conservation strategy. The results showed that eco-driving would be a potentially very cost-effective strategy for local and express bus transit operations. [ABSTRACT FROM AUTHOR]

Well-designed timetables, with appropriate coordination between the last feeder trains and the last connecting trains so that passengers can enjoy “smooth” transfers, are desired by passengers and are a major service goal of metro corporations. This paper addresses the strategically last train scheduling problem in urban railway transit networks. First, two practical optimization models for last trains are proposed to minimize the standard deviation of transfer redundant times and to balance the last train transfers in subway networks. Second, we design a new heuristic algorithm to solve the developed models. Finally, the models and the heuristic are applied to the Beijing subway network. The results show that the last train timetables for the Beijing subway network have been improved by increasing the average travelling speed and the average technical speed by 9.9% and 8.42%, respectively. This means that the last train passengers can save 97.4 min in total in the Beijing subway network when riding last trains. [ABSTRACT FROM AUTHOR]

Estimating the future state of air quality associated with transport policies and infrastructure investments is key to the development of meaningful transportation and planning decisions. This paper describes the design of an integrated transportation and air quality modelling framework capable of simulating traffic emissions and air pollution at a refined spatio-temporal scale. For this purpose, emissions of Nitrogen Oxides (NO x ) were estimated in the Greater Montreal Region at the level of individual trips and vehicles. In turn, hourly Nitrogen Dioxide (NO 2 ) concentrations were simulated across different seasons and validated against observations. Our validation results reveal a reasonable performance of the modelling chain. The modelling system was used to evaluate the impact of an extensive regional transit improvement strategy revealing reductions in NO 2 concentrations across the territory by about 3.6% compared to the base case in addition to a decrease in the frequency and severity of NO 2 hot spots. This is associated with a reduction in total NO x emissions of 1.9% compared to the base case; some roads experienced reductions by more than half. Finally, a methodology for assessing individuals’ daily exposure is developed (by tracking activity locations and trajectories) and we observed a reduction of 20.8% in daily exposures compared to the base case. The large difference between reductions in the mean NO 2 concentration across the study domain and the mean NO 2 exposure across the sample population results from the fact that NO 2 concentrations dropped largely in the areas which attract the most individuals. This exercise illustrates that evaluating the air quality impacts of transportation scenarios by solely quantifying reductions in air pollution concentrations across the study domain would lead to an underestimation of the potential health gains. [ABSTRACT FROM AUTHOR]

Nowadays, passengers in urban public transport systems do not only seek a short-time travel, but they also ask for optimizing other criteria such as cost and effort. Therefore, an efficient routing system should incorporate a multiobjective analysis into its search process. Several algorithms have been proposed to optimally compute the set of nondominated journeys while going from one place to another such as the generalization of the algorithm of Dijkstra. However, such approaches become less performant or even inapplicable when the size of the network becomes very large or when the number of criteria considered is very important. Therefore, we propose in this paper an advanced heuristic approach whereby a Genetic Algorithm (GA) is combined with a Variable Neighborhood Search (VNS) to solve the Multicriteria Shortest Path Problem (MSPP) in multimodal networks. As transportation modes, we focus on railway, bus, tram and pedestrian. As optimization criteria, we consider travel time, monetary cost, number of transfers and the total walking time. The proposed approach is compared with the exact algorithm of Dijkstra, as well as, with a standard GA and a pure VNS. Experimental results have been assessed by solving real life itinerary problems defined on the transport network of the city of Paris and its suburbs. Results indicate that the proposed combination GA–VNS represents the best approach in terms of computational time and solutions quality for a real world routing system. [ABSTRACT FROM AUTHOR]

Abstract: The analysis of complex systems remains the domain of excellence to grasp for control complexity. Theoretical foundations derived from order theory (Galois lattice, spectral analysis of discrete graphs) provide interesting solutions to study exchanges and flows in a system. These are systemic tools well suited to big linked data mining. Various applications exist in the areas of computer networks, social networks analysis, economic analysis and, knowledge discovery. This paper involves Galois Lattice operations and centrality based on spectral analysis for the discovery of the organization and the existing linkage between transport supply given by the routes served by transport (bus, tram, train) and demand resulting in spatial zones (the stop stations). The main objective of this work is to develop a structural knowledge and patterns discovery framework to discover deep knowledge ensuing from the structural representation of the public transport network. The case study concerns the analysis of urban transportation systems (tram and bus) of the city of Valenciennes (France). However, the approach remains valid for other networks without any alterations or modifications. [ABSTRACT FROM AUTHOR]

We put forward a new data object called the public transit travel time cube and demonstrate how the cube can be used in the analysis of transit travel time changes over space and time. The travel time cube contains the shortest path transit travel time between sets of origins and destinations in the city, at all times of day. Once computed, a wide range of investigations become readily available to the transit planner or transportation researcher. We conduct three demonstrative analyses using travel time cubes for the Wasatch Front, Utah and the Portland region in Oregon. Our studies investigate how travel times were impacted by service cuts and expansions in the two regions respectively and the impact this had on jobs accessibility. We also use the travel time cube to study the last mile problem, and compute the travel time savings and the stability gained by solving the last mile problem with bicycling. The paper concludes with an expanded discussion on the merits of the travel time cube and outlines four avenues for continued research. [ABSTRACT FROM AUTHOR]

Travellers formulate their optimal strategyto follow for their trip, every time they may shift to another mode. Trip generalized cost is perceived based on quality of service aspects and type of traveller. One of the most known models to assess service quality is the GAP model, proposed by Parasuraman et al. (1985), which considersboth consumer and provider beliefs, expectations, perceptions and standards. The present paper deals with the fifth GAP of the model, known as the quality GAP, thus expected versus perceived quality of service, for the assessment of the transit service quality. This GAP has been estimated for the case of the transit system in Greece. An internet based questionnaire was used to collect user expectations and perceptions of 26 selected transit quality indicators, based on a 5 point likert scale. Then, a decision tree was developed, using the J48 algorithm, which linked user perceptions and expectations with the overall service quality assessment. The decision tree analysis depicts the importance of various quality components in the generalized cost estimation. Findings showed that the performance indicator “Availability of information by phone, mail”, was the most crucial parameter for the overall assessment of the service, while both performance and importance variables participated in the tree formulation. Tree paths provide guidance for transit operators and/or decision makers for increasing the quality of their services and at the same time enhance performance efficiency and operation profitability. [ABSTRACT FROM AUTHOR]

The multimodal transport system concept, transportation systems management technology and other researcher's related studies of multimodal hub planning are analysed in the paper. A methodology for multimodal transport management support systems development is proposed based on the performed theoretical analysis. The proposed methodology includes three subsystems: transport traffic control support system, transport cruising time synchronization system, and user support system. The information of the population of the Latvian cities and other necessary data has been collected and processed using open source statistical data bases. The available transport timetables and structure details of the JSC “Riga International Coach Terminal” (further in text – Terminal) and Passenger Train Station are used as the input data for simulation model. The developed methodology is approbated using simulation technology. The proposed public transport multimodal node development methodology is tested on the Terminal bimodal transport hub “train - international bus”. The experiments are performed by analyzing capacity of waiting hall and passenger service level based on the average passenger transfer time between transport arrival and departure. Finally, recommendations on the increasing of the operation efficiency of the bimodal transport hub “train - international bus” are given. [ABSTRACT FROM AUTHOR]

The hydrogen-driven fuel-cell electric buses, which bear the advantages of emission free, high storage content and long mileage range, provide a promising choice for decarbonizing the public transportation system. Also, the operation centers for fuel-cell electric buses can be upgraded as the hydrogen-based microgrids to achieve higher economic benefits and resilience levels. To support the low-carbon and resilience-oriented planning of microgrid-aided bus centers, this paper presents a two-stage robust optimization formulation with integer corrective decisions. In particular, the first-stage problem is to optimize the microgrid siting decisions as well as the capacity configuration of renewable-powered electrolyzers, fuel-cell stacks and hydrogen refueling stations for maximizing the annualized benefits. Then, a min – max problem is introduced in the second-stage to improve the load survival value subject to the planning decisions and the worst-case contingency scenario. Also, various corrective actions, e.g., the emergency response of fuel-cell electric buses using vehicle-to-grid functionality, the energy scheduling of stationary equipment in hydrogen refueling stations and the adaptive network reconfiguration, are considered for resilience enhancement of the local power network. As the resulting robust optimization formulation is with a challenging mixed-integer recourse structure, the nested column-and-constraint generation algorithm is designed. Numerical results on exemplary power network and public transportation system validate the effectiveness of the proposed planning methodology, which has the potential to be profitable under normal operations while improving the load survivability under severe disastrous occasions. Moreover, our customized nested column-and-constraint generation shows a satisfactory solution performance, which facilitates prompt disaster relief actions of energy-transportation network. • Hydrogen-based microgrids are planned to support the fuel-cell bus operation centers. • Robust optimization model is proposed for low-carbon and resilience-oriented planning. • The emergency response of fuel-cell buses for back-up power supply is modeled. • Efficient solution is obtained by nested column-and-constraint generation algorithm. • Methods are verified on exemplary power network and public transportation system. [ABSTRACT FROM AUTHOR]

The development of 5G technology provides huge potential for the Internet of Vehicles (IoV). In the IoV scenario, the secure exchange of traffic warning data is necessary to guarantee the safety of pedestrians, vehicles, and public transport facilities. However, there remain a series of challenging issues to achieve data secure sharing while ensuring efficiency. Current solutions such as the data outsourcing storage of traditional centralized cloud servers may cause information leakage due to their incomplete credibility. To address these problems mentioned above, this paper proposes an edge-aided searchable data sharing scheme based on blockchain for IoV in a 5G environment. First, the proposed scheme stores the search index of the keyword and the hash value of the data ciphertext on the blockchain to ensure its integrity and authenticity, and the smart contract automatically verifies the search trapdoor. And then, an edge caching mechanism is designed to quickly feedback on users' retrieval needs based on a cloud-edge collaboration model. In addition, attribute-based searchable encryption is used to ensure that only the users who meet the access attributes and policy can decrypt the encrypted traffic warning data, which can achieve fine-grained access control and keyword search simultaneously. Finally, security analysis and performance evaluation demonstrate that our scheme is secure and more efficient compared with other schemes. [ABSTRACT FROM AUTHOR]

In 2008-9 the first idea of mapping the situation in Petržalka - Bratislava from traffic planning point of view defined the possibility to create a new situation for development of tramway infrastructure across the river Danube. The paper is dealing with the tools of traffic engineering surveys observing the situation in modal split and capacity of bridges in Bratislava from which was created a complex transport model. The results from the transport model showed the future collapse by overflowed situation on the street network and found the way to start with preparing the new Carrying System of Integrated Public Transport using the multi-modality of rail tracks in the agglomeration of Bratislava. Nowadays Bratislava has its first section of new tramway infrastructure from the downtown of the city connecting the all radials of the city toward the southern largest housing estate Petržalka. This section is prepared for operation. [ABSTRACT FROM AUTHOR]

This paper reviews the critical issues of the current urban planning, mobility and accessibility in the post-earthquake (2009) settlement configuration of L’Aquila urban area (Italy), the medieval centre of which has a unique architectural and artistic heritage. The purpose of the study is to analyse the L’Aquila urban planning experiences in order to trace the relationship between the mobility and the spatial structure of the city. The current scenario is considered both as the result of the historical evolution of the settlement and as a dynamic system in which a mix of natural forces, decisional choices and technical expertise have operated. The result of the research is a preliminary proposal for the implementation of the public transportation system that is obtained by integrating a re-designed existing railway line with a sustainable concepts of mobility based on a “dense grid” network. [ABSTRACT FROM AUTHOR]

To maximize private vehicle usage efficiency and alleviate urban congestion, many studies and actual field operations on vehicle sharing have been done since the mid ‘90s. The classic carsharing system, which is known as a round-trip, is operated out of fixed stations so that customers can pick up and drop off the vehicle at the same station. Although many private carsharing companies offer one-way or free-floating trips currently for customers’ convenience, studying characteristics of round-trip carsharing is still significant in making cost-beneficial, fuel-efficient, and less-congested driving environments in urban areas. The main objective of this research is a comprehensive analysis for discovering relationships between critical factors of round-trip carsharing operations based on the city of Cagliari, Italy, by analysing data retrieved from the local carsharing providing company, PlayCar, with the association rules approach. This paper investigates round-trip carsharing behaviour characteristics from various angles, including demand analysis of reservation by hourly and daily manner, geographic analysis, and connectivity to public transportations. The association rules technique was used to discover the relationships between the characteristics and understand their attributes. [ABSTRACT FROM AUTHOR]

Non-emergency Patient Transport Services (PTS) are provided by ambulance companies for patients who do not require urgent and emergency transport. These patients require transport to or from a health facility like a hospital, but due to clinical requirements are unable to use private or public transport. This task is performed nowadays mainly by human operators, spending a high amount of time and resources to obtain solutions that are suboptimal in most cases. To overcome this limitation, in this paper we present NURA (Non-Urgent transport Routing Algorithm), a novel algorithm aimed at ambulance route planning. In particular, NURA relies on a genetic algorithm to explore the solution space, and it includes a scheduling algorithm to generate detailed routes for ambulances. Experimental results show that NURA is able to outperform human experts in several real scenarios, reducing the time spent by patients in ambulances during non-emergency transportations, increasing ambulance usage, while saving time and money for ambulance companies. [ABSTRACT FROM AUTHOR]

In this paper, the life behavior of a shock model is studied, when the external shocks occur according to a binomial process whose interarrival times between successive shocks follow a geometric distribution. The system transits into a lower partially working state upon the occurrence of each interarrival time between two successive shocks less than a critical threshold, say δ. The system fails when k out of interarrival times between two successive shocks are less than δ , or the magnitude of the shock is larger than the other critical level, say γ. Such a model creates a multi-state system having a number of different states. The probability mass functions of system's life time, the time spent by the system in a perfectly functioning state, and the total time spent by the system in partially working states are derived for the proposed model. The corresponding probability generating functions are also derived. The case of Markov shock occurrences is also studied. To illustrate the model studied in this paper, some numerical examples are also considered. Finally, an application in insurance is also provided. [ABSTRACT FROM AUTHOR]

Electric buses (EBs) have gained increasing popularity in public transportation services due to zero-emission and less noise. However, range limitations have substantially hindered the mass adoption of EBs. How to reduce energy consumption is a pressing challenge for bus operations and businesses. This paper develops a whole trip energy-optimal speed control model for connected electric buses passing multiple signalized intersections considering the passenger load, with the help of advanced connected technology. First, the energy consumption related to speed, acceleration and statical features is investigated based on longitudinal dynamics. Then, the energy-optimal speed control model is developed that comprehensively considers passenger load, stop-free passage through multiple signalized intersections and constraints such as travel speed, acceleration, arrival time at stations and intersections. The model is simplified and recast into a mixed-integer linear programing (MILP) with high computational efficiency. Finally, numerical experiments show that the model could reduce energy consumption by approximately 40% compared to the greedy strategy. Sensitive analysis indicates that the model's performance is robust to vehicle mass and forecast error in passenger load. [ABSTRACT FROM AUTHOR]

The emergence of dockless bike-sharing (DBS) has made it more convenient for residents to travel within the city. The integration of public transit and DBS provides an effective method to sustainable transportation development. While some studies have accounted for heterogeneity of travel behavior, very few have considered how attitudes and preferences towards DBS affect combined travel mode choice. This study aims to reveal the effect of residents' attitude towards bike-sharing on combined travel mode choice using stated-preference data collected in Beijing, China. An integrated model of choice model and latent variables based on nested logit model (ICLV-NL) is used to incorporate two latent variables of social benefit and satisfaction with bike-sharing into the discrete choice model and thereby captures relationships between attitudinal factors and observed variables. The results indicate that compared with multinomial logit and nested logit models, the ICLV-NL model yields a better fit and explanatory power. The ICLV-NL model results show that positive impressions on bike-sharing make residents more likely to choose the integration of public transit and DBS, and the pick-up distance of DBS significantly affects the use of DBS as a feeder mode to public transit. Surprisingly, the status of DBS does not have a significant impact on travel mode choice. This paper provides more insights into the choice of the integration of DBS and public transit, which is helpful to the development of green and sustainable transportation. • An ICLV-NL model is proposed to account for the unobservable attitude factors towards DBS. • Users' attitudes, including social benefits and satisfaction with DBS, positively affect the choice of integration mode. • Female, high-education, low-income, and young passengers are more likely to utilize the integration of DBS and public transit. [ABSTRACT FROM AUTHOR]

Low-density areas like suburbs can be challenging to serve with fixed-route transit. Demand responsive transit has been used to service these areas with mixed results, but suburban travellers may respond to ridesourcing integrated with transit more positively because of the improved booking and dispatching interface offered by ridesourcing. This paper explores how suburban residents perceive transit-integrated ridesourcing, both for cost and time attributes of the system and in comparison to other travel modes in the area (cycling, auto, taxi or Uber, and transit). A Hierarchical Bayes mixed logit model was estimated using the results of a revealed-preference/stated-preference survey, revealing that transit-integrated ridesourcing had similar preferences to fixed-route transit. Across time and cost variables, respondents were more sensitive to walk time, transfer time, the number of transfers, parking cost, and taxi or Uber fare, and were minimally impacted by changes in the IVTT deviation of their trip times. The change in utility for the length of transit or transit-integrated ridesourcing in-vehicle travel time versus auto in-vehicle travel time was found to have a strongly linear relationship, while other attributes exhibited non-linearity to different degrees, particularly walk time, transfer time, transit-integrated ridesourcing fare, and taxi or Uber fare. Respondents who were female, younger, taking home-based school trips, or had lower household incomes were more open to transit-integrated ridesourcing and transit than other demographic groups. The likelihood of taking each of the five travel modes was assessed after COVID-19, finding generally minimal to negative impact for transit-integrated ridesourcing. Insights into vehicle and transit pass ownership, existing travel alternatives, and a prior transit-integrated ridesourcing pilot in the area are presented. • Transit-integrated ridesourcing service perceived similarly to fixed public transit. • A Hierarchical Bayes model was estimated from the sample of RP/SP responses to capture user heterogeneity. • Mode constant, walk time, transfers, parking cost, taxi or Uber fare were also weighted heavily by respondents. • Travel time deviation not found to be significant for any mode. • Female, young, school-bound, and lower-income people more open to on-demand service. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has caused an unprecedented decrease in transit ridership around the world. Some major cities in the United States have lost over 80% of their transit riders, and some transit agencies have been forced to reduce service and work with a skeleton crew at times. Although the future of the COVID-19 pandemic and its long-term effect on transit systems are still unclear, much can be learned from previous disruptive events, such as terrorist attacks and epidemics, in the past 30 years, so as to draw qualitative and quantitative insights about the public reactions, ridership recovery periods, and transit agency responses during and after those events. The goal is to facilitate the understanding of the current COVID-19 pandemic and inform future decisions of transit agencies. This paper provides a historic review of the impacts of terrorist attacks such as the London and Madrid bombing, the Tokyo sarin gas, and the 9/11 attacks; and past epidemics and pandemics, such as Severe Acute Respiratory Syndrome (SARS), H1N1 swine flu, Middle East Respiratory Syndrome (MERS), and Ebola. It was found that most of these reviewed incidents (except for the 9/11 attacks) did not impose prolonged post-event effects on transit ridership for more than one year. In addition, executive orders (e.g., school closures), transportation service levels (e.g., screening time for air travel and rail station closures), public fear, media reports, and reduced tourists were frequently mentioned as key factors that impacted transit ridership. The review also identified measures that could potentially help restore transit ridership, such as sanitizing vehicles and facilities, adjusting services, and launching promotions and advertisements. Finally, insights on the ongoing COVID-19 pandemic are drawn through comparisons with historical events. [ABSTRACT FROM AUTHOR]

Dockless bicycle sharing (DBS) has become a popular form of public transport worldwide over recent years, which contributes mightily to solving the increasingly frequent traffic congestion and parking issues in urban areas. However, its spatiotemporal usage patterns and determinants have not been fully investigated. In particular, the existing studies have not provided clear insight into the effect of traffic status on DBS trips. To address this shortcoming, this study proposes a model framework to understand DBS from multiple aspects. Within this framework, descriptive statistics and visualisation methods are employed to explore the spatiotemporal travel patterns of DBS in the downtown area of Shanghai. By adopting spatial panel models, the impacts of the built environment, weather, and traffic status on DBS in different regions are examined, and the heterogeneity analysis of traffic status factors is further conducted. The results have shown that DBS in Shanghai has obvious tidal distribution characteristics. The supply of DBS exceeds the demand in the peripheral areas of the city, while the opposite is true in the city centre. In addition, the traffic state index, bus stop density, residential and commercial land area have a positive contribution to DBS usage and have obvious positive spatial spillover effects. The results from the heterogeneity analysis have revealed that the influencing mechanism of DBS usage varies by location and riding duration. These findings of the present paper can provide an effective basis for DBS demand distribution forecasting, regional rebalancing, and connecting traffic planning, thereby facilitating the usage of DBS, promoting intermodal transport, and reducing carbon emissions. • Analysed the spatiotemporal characteristics of dockless bicycle-sharing (DBS) usage. • Explored the impact of traffic status on DBS trips. • The spatial distribution of DBS has a strong tidal distribution phenomenon. • Traffic state index, bus stop density, residential and commercial land area were discovered to promote DBS usage. [ABSTRACT FROM AUTHOR]

This paper aims at creating a sustainability governance framework to assess the public transport companies in developing countries. In contrast to previous research studies, governance criteria, namely transparency and accountability, are involved in the sustainability assessment. Eventually, four dimensions of key performance indicators are suggested: economic, environmental, institutional and social. Each of them describes a completely different perspective of sustainable development. A numerical illustration is provided at the end to evaluate three public transport companies from a developed country to give an overview of the framework implementation using simple additive weighting method. • A sustainability governance indicator-based framework for public transport companies is designed. • This framework may promote for a sustainable transport companies particularly in developing countries. • This framework integrates the main pillars of transport sustainability and governance in one model. • Economic, environmental, social and institutional dimensions are involved through a set of up-to-date SMART indicators. • Transparency and accountability, are namely involved in this framework. [ABSTRACT FROM AUTHOR]

Dockless micromobility services have potential as a fast and flexible solution to short-distance trips and public transit's first-mile/last-mile (FM/LM) access problem; however, these services also have limitations, including uneven spatial distribution, low capacity, and user out of pocket expense. This can impact on the ability of micromobility to enhance public transit accessibility. We introduce accessibility increment measures – the amount by which public transit accessibility improves due to micromobility services. We apply these measures to hypothetical trips using public transit and micromobility data from Columbus, Ohio, USA. We find dockless scooters can increase accessibility by multimodal public transit trips, with increments in the first mile significantly outweighing last mile accessibility increments. Accessibility increments are highly concentrated in the city center due to the distributions of scooters and bus stops. We also find that scooters' accessibility increment contribution is highly unequal: a small number of scooters contribute most of the accessibility increments. Monetary cost simulations show that the first-mile accessibility increment will rapidly decrease and last-mile increment slightly increase with lower willingness to pay. Capacity simulations show a group of users' accessibility increment will rapidly decrease as the group size increases, but this depends on whether they are competing or collaborating for scooters. Our results show that despite showing promising potentials, vendors and policymakers still need to address these issues to make collaboration between public transit and dockless micromobility sustainable and equitable. The paper provides measures and evidence for future transit and micromobility planning for scooter vendors and transit authorities. • Micromobility can incrementally improve public accessibility. • Accessibility increments are greater for first mile public transit access than last mile. • Accessibility improvements are very unequal across space and mobile devices. • Ability to pay and capacity constraints limit accessibility improvements. • Collaboration between public transit and micromobility is promising but faces challenges. [ABSTRACT FROM AUTHOR]

The paper proposes a continuum approximation-based optimization model, considering vehicle emissions, to jointly optimize a bimodal transit network service in a heterogeneous environment where the passenger demand is not uniformly distributed over space and time. Correspondingly, the designed transit service characteristics, including the spacing of lines and stations, line headways and lengths, may vary over space and time to better cater for variable passenger demands. A successive substitution solution approach and an endpoint method are employed to generate an optimal solution. Experiments are conducted to illustrate the properties of the model and validate the solution methods. The results indicate that a trunk-feeder bimodal transit network is preferable under a higher-level heterogeneous demand. A rail-bus system is much more desirable compared to a bus rapid transit (BRT)-bus bimodal system in a larger and more developed city. Another interesting finding is that the scale of at-stop emission cost reduction is significantly larger than that of inter-stop emission. Compared to the conventional bimodal transit network design models without accounting for vehicle emissions, the incorporation of an emission factor into the optimization model can reduce both the total system and emission costs, which consequently achieves a more sustainable bimodal transit system. [ABSTRACT FROM AUTHOR]

• Developing a framework to estimate solar PV potential of urban fleet-wide electric buses. • Publicly street-view panoramas, GPS trajectory data and DEM data are used as input. • A case study of Qingdao, China with 547 bus routes, 28,661 street-view panoramas is studied. • Benefits under different driving conditions and operation schedules are evaluated. Transforming the road public transport to run on renewable energy is vital solution to achieve carbon neutral and net zero goals. This paper evaluates the potential of using solar radiation-generated electricity as an auxiliary power supplementary for the battery of electric buses, based on a developed framework that using publicly street-view panoramas, GPS trajectory data and DEM data as input parameters of solar radiation model. A case study of Qingdao, China with 547 bus routes, 28,661 street-view panoramas shows that the solar-radiation electricity generated at noon during the operation accounts for about one-fifth, one-eighth of the total electricity consumption of a bus traveling one kilometer in a sunny day and a cloudy day, respectively. Spatial variability shows significant solar-radiation power generation advantages in newly-launched areas and expressway. The solar power generated in a sunny day can make a bus half of passengers and with air conditioner off at least one extra trip in 2:1 replacement schedule, and nearly close to one extra trip in 4:3 replacement schedule. A correlated relation between the solar-radiation power generation benefit and the operation schedule of electric buses is observed, implying that the high cost of 2:1 replacement schedule for long-distance routes during summer or winter can be reduced. The proposed framework can help us evaluate and understand the feasibility of solar radiation-generated electricity energy of electric bus fleets covering the large-scale urban areas at different times, locations, and weather conditions, so as to support effective decisions at better planning of PV-integrated electric buses. [ABSTRACT FROM AUTHOR]

With the rapid development of urban rail transit, train parking accuracy has received much attention, especially for subway lines with platform screen doors. In actual operation, several balises are mounted on the track to enhance the parking accuracy by providing exact positioning data for the train. Currently, the number and positions of the balises are determined by experience and iterative experiments that may greatly increase the costs. Combining expert knowledge and train dynamics, this paper formulates a balise arrangement optimization (BAO) model to study the relationship between the number & locations of balises and parking errors. The resistances, nonlinearity and time delay in train braking system and variable initial speeds that a train enters the parking area are considered in the formulation of BAO model. Moreover, we propose a genetic algorithm (GA) to solve the BAO model and present numerical experiments based on field data collected from Beijing Subway Yizhuang Line. The results indicate that the BAO model can enhance the parking accuracy to about 0.10 m via changing the positions of the balises. Furthermore, we found that: (1) more balises lead to better performance of train parking accuracy; (2) four or five balises are appropriate for balancing the device cost and parking errors. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of regularity in public transport usage based on a largescale bus transportation data of Lisbon, Portugal. By exploring the combined information from the bus boarding history of riders and bus arrivals at each bus stop, an analysis of individual bus usage was performed. Daily and weekly patterns were extracted, from which it was observed that a rider takes, on average, 2 trips, visits 1.93 distinct stops, and uses 1.55 distinct bus lines daily. Inter-trip time analysis revealed a daily cycle, and a study of the interaction between riders and bus infrastructure explored how usage was concentrated on particular bus lines and stops. [ABSTRACT FROM AUTHOR]

Urban mobility became a major challenge around the world, with frequent congestion and ever growing travel time. Albeit recent advances in the area of Intelligent Transportation Systems (ITS), it is still difficult to predict and manage the road infrastructure due to dynamics and instability of the traffic. One key issue is how, given some traffic monitoring information, a vehicle decides to dynamically change its route. In this paper, we analyze algorithms of the anytime class to make the route planning considering GPS traces of buses in Rio de Janeiro, as a measurement of traffic flows. Anytime algorithms inform, in a timely fashion, a sub-optimal response and progressively improves it as time goes by. We evaluate time and memory consumption, route length, arrival time, average velocity, distance traveled, and pathways on an experimental platform composed of Raspberry Pi nodes. For different time windows, the results show that ARA* allows finding alternative routes that, if used, help reduce traffic congestion. [ABSTRACT FROM AUTHOR]

Many objective and subjective factors affect individual tendencies. Such subjective factors include personality traits, attitudes, identities, perceptions, and feelings. The choice of transportation mode is an individual tendency that is considered important in policy-making decisions, and it can affect sustainable transportation, particularly in metropolitan areas. The present study’s main aim is to determine the impact of the Big Five Personality Factors on individual preferences toward public transportation modes. We use data from a survey conducted in January and February of 2015 at Imam Khomeini International Airport (IKIA). Passengers were asked to indicate their preferred mode of transportation to access the IKIA and to respond to questions on the NEO Five-Factor Inventory. Based on 557 valid responses, hybrid discrete latent class modeling was conducted to understand the heterogeneity in the respondents’ individual preferences regarding the Big Five Personality Factors and their preferences toward public modes of transportation. The results indicated that individuals who display neuroticism were more likely than the others to be concerned about carrying heavy luggage and about inclement weather conditions when using public transportation. In addition, interesting results indicated that conscientious individuals likely paid more attention to travel cost than to any other attribute of public transportation, and the model of the conscientious latent personality trait was a better fit to the data. Finally, this paper examined the taste heterogeneity of each personality trait and the results indicate the usefulness of considering personality traits in mode choice models for richer insights toward sustainable transportation. [ABSTRACT FROM AUTHOR]

Overcrowding has grown to be an increasingly important issue for public transit in Guangzhou, China. To capture traveler benefits of reduced crowding from improved public transport, it is necessary to identify the relevant importance of crowding to travelers. This paper analyzes the disutility of crowding in metro car and bus transit with discrete choice models. Based on the stated preference survey data from college students in Guangzhou, the results show that there is non-negligible impact of crowding on passenger travel. The relationship between the disutility of crowding and standee density is not linear; that is, the disutility increases at a modest rate as the standee density increases when it is easy to move around in cars and increases rapidly when it is difficult to move around in cars. Also, there is only a slight difference between the effects of crowding on metro and bus transit. [ABSTRACT FROM AUTHOR]

Studies on public transit have emphasized the role of passenger satisfaction with service quality in travel choice decisions and indicated that satisfaction depends on various service attributes. Few studies have, however, systematically examined the underlying relationships among service attributes to assess their influence on passenger overall satisfaction. Therefore, to contribute to this rapidly-emerging literature, this paper applies Bayesian networks to quantify the influence of each service aspect on passenger overall satisfaction with regular bus service quality. This analysis involved 609 passengers who participated in a 2013 regular bus service survey in Nanjing, China. The derived Bayesian network shows the relationships among service attributes and passenger overall satisfaction graphically. In particular, service aspects such as running on schedule, acceptable waiting time, available seats, clean onboard environment, pleasant environment at stations, convenient design for transfers, and air-conditioning were the key determinants of overall satisfaction with bus service. [ABSTRACT FROM AUTHOR]

Given a set of GPS tracks on a road network and a number k , the K-Primary-Corridor (KPC) problem aims to identify k tracks as primary corridors such that the overall distance from all tracks to their closest primary corridors is minimized. The KPC problem is important to domains such as transportation services interested in finding primary corridors for public transportation or greener travel (e.g., bicycling) by leveraging emerging GPS trajectory datasets. However, the problem is challenging due to the large amount of shortest path distance computations across tracks. Related trajectory mining approaches, e.g., density or frequency based hot-routes, focus on anomaly detection rather than identifying representative corridors minimizing total distances from other tracks, and thus may not be effective for the KPC problem. Our recent work proposed a k -Primary Corridor algorithm that precomputes a column-wise lookup table of network Hausdorff distances. This paper extends our recent work with a new computational algorithm based on lower bound filtering. We design lower bounds of network Hausdorff distances based on the concept of track envelopes and propose three different track envelope formation strategies based on random selection, overlap, and Jaccard coefficient respectively. Theoretical analysis on proof of correctness as well as computational cost models are provided. Extensive experiments and case studies show that our new algorithm with lower bound filtering significantly reduces the computational time of our previous algorithm, and can help effectively determine primary bicycle corridors. [ABSTRACT FROM AUTHOR]

Research on demand-responsive collective transportation facilities that can act as feeder services to time-table based public transportation (PT) requires detailed and accurate information about the PT infrastructure, including the attachment of bus stops to the appropriate network link. Due to the size of the infrastructure, the data integration shall be automated. This paper describes the effort to prepare data from publicly available OpenStreetMap (OSM) and General Transit Feed Specification (GTFS) sources. Procedures are proposed (i) to build a network derived from OSM suitable for simulations in transportation, (ii) to extract bus stops from GTFS and remove anomalies and (iii) to find candidate network links to attach them. [ABSTRACT FROM AUTHOR]

Cities have become important drivers in promoting strategies for sustainable development. The primary objective of this article is to analyze the differences between public transportation in Newcastle upon Tyne, the city considered the most sustainable in the United Kingdom, and Florianópolis, a city with great potential for sustainable policies located in southern Brazil. This comparison may provide models, ideas and actions for the development of Florianópolis as a model of sustainability in South America. Therefore, a comparative analysis is provided: to observe changes, build models, and verify similarities and differences, while seeking to discover which behaviors govern political and social phenomena in the area of urban sustainability. This paper provides a comparative description of social and economic indicators: gross domestic product (GDP) per capita, inflation, employment, as well as the historical population evolution of the two cities. This work contrasts the sustainable transport model used by Newcastle and the reality of the transport needs of Florianópolis. This article is the first in a series to analyze the indicators for sustainable cities, focusing mainly on the reality of the South American city. [ABSTRACT FROM AUTHOR]

Recently, the policy to reduce private car sharing and switch the private car users to public transportation has gained much attention. Research has shown the accordance that developing public transportation to promote sustainable transportation. However, sometimes the subway and bus transit with high congestion level do not match the comfortable degree of demand, and the transit with fixed routes cannot satisfy the flexibility of transport. Hence, the customized shuttle bus becomes a new way of public transportation. Most studies on the implementation and application of customized shuttle bus are only for large cities. However, limited studies have been conducted on the key contributing factors of customized shuttle bus in medium city. In this paper, Harbin City, the capital city of Heilongjiang Province, is selected as the case study. The contingent valuable method is employed and 332 individuals complete in the SP (Stated Preference) and RP (Revealed Preference) survey to measure the individual willingness to choose customized shuttle bus. Key contributing factors that are expected to influence customized shuttle bus are analyzed by logistic regressions. The results show that there are four key contributing factors that influence people to choose customized shuttle bus, which are private car, distance between home and work place, travel satisfaction level and work overtime. Finally, some suitable proposals for the implementation of customized shuttle bus are proposed, which are helpful to make public transportation policy in Harbin and other developing cities. [ABSTRACT FROM AUTHOR]

The urban rail transit system is the important basis to support the metropolitan regions of the world cities and has great significance to the formation and development of such metropolitan regions. From the perspective of relieving the urban traffic congestion, the development of rail transit requires multiple-levels and diversity; it's the key to accurately position the functions of the subway, the light rail, the suburban railway and even the national railway; then the functions should be integrated through the respective positioning and on the basis of the characteristics of different rail transit so as to give maximum play to the rail transit system. The paper dissected the basic composition, spatial layout, service objects, passenger flow scale and historical evolution of the rail transit system within the spatial system in the metropolitan regions of such world cities as Tokyo, London, New York and Paris. It compared and analyzed the main gap of Beijing's rail transit system and put forward the countermeasures and suggestions for the future development of rail transit. [ABSTRACT FROM AUTHOR]

The wide use of smart card automatic fare collection (AFC) systems in public transit makes it popular to analyse public transit user behaviour based on smart card data. Most smart-card-based researches are time-related, but smart card data time is not always reliable because smart card systems are usually off-line and lack of maintenance in China, and smart card data of different buses often shares different time references. This paper explores the application of dynamic time warping to unify time reference of smart card data. Based on the analysis of the relationship between boarding time in smart card data and arrival-departure time in automatic vehicle location (AVL) data, a smart card data time reference unification algorithm was proposed. The results indicate that the algorithm can work out reliable time offsets by numerical calculation and runs well with integral automatic vehicle location data. Due to the fact that the time reference of smart card data for each bus changes daily, the best way to put an end to smart card time reference problem is to make smart card systems online, such as combining smart card readers with automatic vehicle location systems. [ABSTRACT FROM AUTHOR]

Passengers often have to transfer between different subway lines to reach their destinations. Time coordination of first trains between feeder and connecting lines plays an important role in reducing passenger transfer waiting time. This paper addresses the first train synchronization problem, and proposes a first train coordination model which aims at minimizing total passenger transfer waiting time. Taking into account the specification of the first train problem, we use mixed-integer variables to enable the correct calculation of the waiting time for the “first available” train at each transfer station. In addition, we develop a simulated annealing algorithm to deal with a case study of the Beijing subway network. Results indicate that the proposed approach reduces the passenger waiting time from 705.1 min of the original first train timetable to 567.42 min of the scheduled one. [ABSTRACT FROM AUTHOR]

The paper discusses the possible economic effect on regional development by developing applicable methodology and analysing differences in costs, both operational costs and initial investments, of two types of buses serving urban public transportation systems – diesel fuelled internal combustion engine bus and battery electric bus. Comparison of initial investments to operate the both types of buses shows large initial investments involved when electric energy is being added/used. At the same time operational costs, including energy costs, show opposite picture, especially with large annual distances covered – electrical energy is substantially cheaper. The research shows, that within current state of affairs in Latvia, initial investments of changing public transportation fleet to electric buses and the costs of battery replacement still outweighs the monetary advantages gained from lower operational costs and additional environmental benefits. [ABSTRACT FROM AUTHOR]

Public transport accessibility measurement includes various dimensions: travel cost, options, constrains, quality etc. Making decisions for improving the public transport accessibility involves the authorities of different areas so the result should be reached by the interaction between all the parties involved. Also the needs of all the residents should be considered. Urban public transport development should be implemented with attention to the needs of people with movement disorders, unfortunately this aspect usually remains indecisive as not of primary importance. The aim of this paper is to apply the public transport accessibility for people with movement disorders measurement system for Vilnius city. The result of such assessment would be the base for recommendations to improve the existing public transport services. [ABSTRACT FROM AUTHOR]

Park and Ride is one of Transport Demand Management (TDM) scheme, which is very popular in some congested city with wide parking area at the border line or outskirt area. Palembang is capital city of South Sumatera Province, which has three Terminals in the border area with surrounding kabupaten (district). Right now the Terminal is not functioned appropriately because many public transport vehicles are loading and unloading passengers outside the Terminal, or on the street nearby the Terminal. On the other hand, the city centre itself has been crowded of private vehicles (car and motor cycle). The current on street parking system has been no longer adequate. According to Cities Development Initiatives for Asia (CDIA) study 2011, about 1382 cars and 1431 motorcycles need a place to park in the city centre. The aims of this paper are to present the characteristics of trips surrounding the Terminal and to know their potential of accepting Park and Ride system, and to plan the program and policy regarding Park and Ride in Palembang. The Data was collected by doing Home Interview survey in Palembang, with 4000 sample of Households (Buchari, 2011). Method of Analysis is descriptive Analysis, Cross tabulation, matrices analysis and multimodal analysis. The data from previous study was used to analyze the interconnection Terminal location with trips from surrounding areas. The results showed the potential shifting from private vehicle user to park and ride user. [ABSTRACT FROM AUTHOR]

This paper presents an approach towards intelligent route planning in public transport systems. The approach focuses on formal modelling of the semi-dynamic intelligent route planning and optimisation. For these purposes, it is essential to have a well de- veloped formal model covering real-time and space aspects. The proposed solution allows designers to extend a public transport system with additional routes, which are created dynamically based on the requests from passengers. The model can be applied within a sustainable Smart City both for (fully or partially) autonomous transport systems and for the decision support systems of a smart transport system. [ABSTRACT FROM AUTHOR]

The bus vehicle scheduling problem addresses the task of assigning vehicles to cover the trips in a timetable. In this paper, a clonal selection algorithm based vehicle scheduling approach is proposed to quickly generate satisfactory solutions for large-scale bus scheduling problems. Firstly, a set of vehicle blocks (consecutive trips by one bus) is generated based on the maximal wait time between any two adjacent trips. Then a subset of blocks is constructed by the clonal selection algorithm to produce an initial vehicle scheduling solution. Finally, two heuristics adjust the departure times of vehicles to further improve the solution. The proposed approach is evaluated using a real-world vehicle scheduling problem from the bus company of Nanjing, China. Experimental results show that the proposed approach can generate satisfactory scheduling solutions within 1 min. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new spatial autoregressive threshold panel model and its estimation method are proposed. • PM 2.5 concentration in adjacent provinces increases 1% can lead to that in observing province increases 0.7678%. • The influence effects of socioeconomic and climatic factors on PM 2.5 are different at low and high economic levels. • Applying nonlinear spatial econometric techniques in environment research. Reducing PM 2.5 is an important way to ameliorate air quality. Research on driving factors of PM 2.5 can provide empirical support for controlling cross-regional linkage air pollution. In this paper, we first propose a new spatial autoregressive threshold panel model and its estimation method, and then apply this methodology to study influencing elements of PM 2.5 using the panel data of China during 2000–2019. The results reveal that China's provincial PM 2.5 has a significant positive spatial spillover effect, and its major driving factors have significant two regimes threshold characteristic when economic development is divided into low and high levels. Specifically, (1) PM 2.5 concentration in adjacent provinces increases 1% can lead to that in observing province increases 0.7741%. (2) The positive impacts of population size, energy structure and humidity on PM 2.5 are significant at low economic level, and become not significant at high economic level. (3) The influence of industrialization, economic development, energy intensity, urbanization and wind speed on PM 2.5 in two regimes is significantly positive, and elasticity coefficients of industrialization and economic development decrease with improvement of economic level while energy intensity, urbanization and wind speed are on the contrary. (4) The influence of possession of civil vehicles on PM 2.5 changes from negative to positive as economic level increases. (5) Temperature has no significant effect on PM 2.5 concentration. (6) The influence of precipitation on PM 2.5 is significantly positive in regime II and not significant in regime I. Therefore, local governments should strengthen cooperation with adjacent provinces and jointly adopt effective measures to cut down on PM 2.5 pollution. The provinces with low economic level should accelerate economic transformation, improve industrial production efficiency, optimize energy structure, and advocate green and low-carbon lifestyle. The provinces with high economic level need to further expand consumer demand, actively develop tertiary industries, promote new energy vehicles and vigorously develop public transport. [ABSTRACT FROM AUTHOR]

• The reliability and economy of UMES integrated with PTH are assessed. • Modeling of PTH flexibility considering both energy- and service-related constraints. • A system operation model combining energy management, vehicle dispatch and V2G is proposed. • A holistic evaluation framework embedded with multi-modal operation simulation is developed. • Influential factors for the contribution of PTH flexibility are analyzed. Growing penetration of renewable energy sources (RES) and emerging electrified loads (EEL) are bringing about increased difficulties for the power balancing and efficient operation of energy system, due to the impact of remarkable volatilities introduced. Public transport hub (PTH), as a new-style infrastructure of traffic service carriers, is regarded to offer a cogent solution to this problem, in terms of their potential operational flexibilities permitted by energy regulation, vehicular dispatch, and vehicle-to-grid (V2G) programs. As such, this paper carries out a comprehensive study to investigate the implication of harnessing PTH-enabled flexibility in a context of urban multi-energy system (UMES). The proposed methodology is established on a holistic reliability/economic analysis framework which is designed to indicate how UMES's performances would vary with different utilization of PTH resources. In order to portray the real-time controllability of PTH during operation, a PTH model that takes into account the impacts of both energy- and service-related aspects has been developed, with particular focus on the interdependencies between the energy and transportation sector. The operational simulation of UMES in presence of PTHs is implemented by using a multi-modal-based optimization model, which captures the effects of PTH flexibility under both normal and contingency scenarios integratedly. By embedding the above formulation into a sequential Monte Carlo simulation-based assessment framework, the contribution of PTH to the reliability and economy of UMES can be determined. Numerical studies are conducted based on an illustrative electricity-gas-heat test case and the real PTH datasets in Beijing. The simulation results confirm the significance of PTH-enabled flexibility in improving the performances of UMES. Also, it is demonstrated that the reserving strategy adopted, the composition of vehicle model, and the travel demand profile of passengers are the noteworthy factors that influence the profitability of PTH exploitation. [ABSTRACT FROM AUTHOR]

The accurate detection of the mobile context information of public transportation vehicles and their passengers is a key feature to realize intelligent transportation systems. A topical example is in-vehicle presence detection that can, e.g. , be used to ticket passengers automatically. Unfortunately, most existing solutions in this field suffer from low spatiotemporal accuracy which impedes their use in practice. In previous work, we addressed this challenge through a deep learning-based framework, called DeepMatch , that allows us to detect in-vehicle presence with a high degree of accuracy. DeepMatch utilizes the smartphone of a passenger to analyse and match the event streams of its own sensors with the event streams of counterpart sensors provided by a reference unit that is installed inside the vehicle. This is achieved through a new learning model architecture using Stacked Convolutional Autoencoders to compress sensor input streams by feature extraction and dimensionality reduction as well as a deep convolutional neural network to match the streams of the user phone and the reference device. The sensor stream compression is offloaded to the smartphone, while the matching is performed in a server. In this paper, we introduce DeepMatch2. It is an amended version of DeepMatch that reduces the amount of data to be transferred from the user and reference devices to the server by the factor of four. Further, DeepMatch2 improves the already good accuracy of DeepMatch from 97.81% to 98.51%. Moreover, we propose a travel inference algorithm, based on DeepMatch2 , to detect the duration of whole passenger trips in public transport vehicles with a high degree of precision. This is needed to create intelligent and highly reliable auto-ticketing systems. Thanks to the high accuracy of 98.51% by DeepMatch2 , the inferences can be carried out with a negligible error rate. [ABSTRACT FROM AUTHOR]

Vehicular Ad-hoc Network (VANET) means connectivity between wireless interface and mobile vehicle equipment which could be of either homogeneous or heterogeneous nature. VANET is an emerging part of research due to its ability to create intelligent transport systems. Roadside fixed equipment (RSU), and on-board unit (OBU) can be either public means of transport service providers or private (belonging to companies or individuals). In this infrastructure, messages flow from vehicle to vehicle and vehicle to roadside via wireless technologies such as IEEE 8.02.11.P and IEEE 1609 WAVE. The main issue in VANET implementation is the design of routing topology that gives accurate vehicle-to-vehicle transmission. In VANET, every participating vehicle node works as a single-vehicle node or wireless router, allowing vehicles that are 100–500 m far from creating a network and connected to each other by a large range using dynamic source routing (DSR) protocol. In this paper, we focus on improving connectivity by integrating simulation of urban mobility (SUMO) with NETSIM and present a new algorithm for packet delivery in different dense environments. In this work, we propose a vehicle connectivity algorithm for less (40), moderate (50), and more (60) number of vehicles and also analyze the threshold value of successfully delivered packets through simulation and the proposed algorithm. In the simulations and proposed method, the overall link and application throughput in VANET is enhanced, and the outcome shows that the connectivity is better than in the other techniques. This study has achieved good throughput in a dense vehicle environment. Performance of the networks has been measured through throughput, delay, packet delivery ratio (PDR), overhead head transmission for less (40), moderate (50), or more (60) number of vehicles on different road paths. [ABSTRACT FROM AUTHOR]

Sustainable mobility is critical to achieve sustainable development goals. Public policy makers worldwide have introduced different policy instruments to motivate sustainable mobility such as promoting car sharing and introducing car license plate lottery. Limited attention has been devoted to studying the effects of these types of policies on consumers' accessibility in urban mobility system, in particular when these policies are intended to achieve the same objective of promoting sustainable mobility. To fill this gap, based on the consumer discrete choice behavioral theory, this paper designs a stated choice experiment and performs discrete choice analysis to investigate how the interactions of these two policies influence consumers' mobility preferences and consumer surplus-based accessibility. By collecting data in Beijing, as an empirical context, we identify a nested logit model with a hierarchical choice structure, where bus and underground fall in the nest of public transit , while car sharing, private car and taxi are independent alternatives. Consumers who are participating in the car license plate lottery are more likely to choose car sharing, and car sharing can largely compensate for the loss of accessibility caused by the car license plate lottery policy, which implies that car sharing and the car license plate lottery policy are indeed complementary policies. However, the introduction of car sharing can also lead to an unintended consequence of higher total car usage by attracting more public transit users who never intended to buy or drive cars. This study contributes to the literature by proposing and implementing a generic theoretical framework for analyzing consumer preference-based accessibility for developing a sustainable mobility system and provides important practical implications. [ABSTRACT FROM AUTHOR]