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A Review of Big Data Applications in Urban Transit Systems

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High-Accuracy and high-efficiency 3-D sensing and associated data processing techniques are urgently needed for today’s roadway inventory, infrastructure health monitoring, autonomous driving, connected vehicles, urban modeling, and smart cities. 3D geospatial data acquired by digital photogrammetry or laser scanning or LiDAR systems have become one of the most critical data sources to support the

Map-based localization and sensing are one of the key components in autonomous driving technologies, where high quality 3D map reconstruction is fundamentally utmost important. However, due to the highly dynamic and uncontrollable properties of real world environment, building a high quality 3D map is not straightforward and requires several strong assumptions. To address this challenge, we present

Recently, 3D deep learning technologies require a large amount of supervised 3D point-cloud data to learn statistical models for various ITS-related tasks, e.g. object classification, object detection, object segmentation, etc. However, manually annotating 3D point-cloud data is time-consuming and labor-intensive. Therefore, this paper aims at co-locating 3D objects from mobile LiDAR point clouds without

The increasing growing need for optimization of transportation in a sustainable and green environment is fundamental for the future of mobility. Companies, governments, and non-governmental institutions are trying to find new ways to contribute to this challenge. In particular, the approach is to improve the efficiency and the quality of the movement of diversification of an integrated way of transportation

Modern transportation systems, such as computer networks, have become increasingly faster, aiming to “shorten” distances and travel time. This trend allows thinking about new services and induces to reconsider existing ones starting from new technologies, as for Intelligent Transportation Systems. Thereby, an all-encompassing scenario laying at the intersection of several domains, including manufacturing

The mixed traffic flow, which comprises both cooperative automated vehicles (CAVs) and human-driven vehicles, is becoming more common in modern urban areas. CAVs can expand the capabilities such as that can be achieved with automation and vehicular communication individually. However, the energy-saving benefits may be one of the exceptions when three or more vehicles drive in a row under the mixed

With the emerging connected automated vehicles, 5G and Internet of Things (IoT), vehicles and road infrastructure become connected and cooperative, enabling Cooperative Intelligent Transport Systems (C-ITS). C-ITS are transport system of systems that involves many stakeholders from different sectors. While running their own systems and providing services independently, stakeholders cooperate with each

Studies on public transportation in Europe suggest that European inhabitants use buses in ca. 56% of all public transport travels. One of the critical factors affecting such a percentage and more, in general, the demand for public transport services, with an increasing reluctance to use them, is their quality. End-users can perceive quality from various perspectives, including the availability of information

An effective, efficient, and ecological transport service needs a decision support system to inform the administrations, while intelligently assisting citizens’ daily transportation choices. This work presents a full-fledged Gamification Platform to develop and run sustainable mobility campaigns promoting individual green mobility behaviors. We organize geolocalized and temporal information on users’

Origin-destination matrices help understand the movement of people within cities. This work is built upon the premise that stakeholders, e.g. decision makers, need to analyze mobility flows from spatio-temporal perspectives that are appropriate to their context of analysis. The data retrieved from sensors and Intelligent Transportation Systems are useful for this purpose due to their lower acquisition

Empowered with advanced computation units, autonomous sensing platforms and various wireless access capabilities, connected and autonomous vehicles evolve over time and become tightly coupled and closely cooperative. Being one of the most active research fields in both academic and industry, the Internet of Vehicles (IoV) enables various types of vehicular applications, such as autonomous driving,

The advent of Connected and Autonomous Vehicles (CAVs) and Mobile Internet technologies is reshaping the public transport sector. Autonomous buses are equipped with varying advanced sensors, and hold great promises to enhancing the responsiveness and flexibility of public transit system. In the context of CAVs, transit operators can not only optimize service headway but also adjust bus capacity to

The emergence of electric buses (EBs) is expected to alleviate traffic pollution. However, the promotion of EBs requires a long transition period; during this period, EBs cannot wholly replace conventional buses (CBs). In addition, compared with CBs, EBs have long charging times and short cruising ranges, resulting in short operating times being available for the scheduling process. Therefore, to effectively

Differing from the conventional fixed-route transit, Demand Responsive Connector (DRC) is scheduled to pick up passengers based on requests, and delivers them to a common destination (e.g., a metro station). The demand for DRC is affected by not only the fare and travel time, but also time reliability. The latter’ impact is non-negligible because of the uncertainty nature of DRC on collecting the temporally

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Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges

Existing unconventional intersection designs mainly apply to large intersections, such as the intersection of two major roads, in which there are numerous lanes on each leg and the allowed queue length is long. This paper presents a new unconventional intersection design to improve the operational efficiency of the intersections with limited traffic lanes and short distance for vehicular queuing, such

With the development of 5G communication and transportation infrastructure, transportation systems face challenges to serve future smart cities regarding effective operation and cost optimization for electric vehicle networks. Thus, heterogeneous networking optimization approaches for these vehicles have been investigated, which have great potential in real-time communications, intelligent processing

Multi-view vehicle re-identification (Re-ID) aims to retrieve all images of a target vehicle from a large gallery where the vehicles are captured from non-overlapping cameras. However, the drastic variation in vehicle appearance under different viewpoints greatly affects the performance of the multi-view vehicle Re-ID model, so the key issue in multi-view vehicle Re-ID is learning an effective feature

Smart city emerges a promising paradigm for improving operational efficiency of city and comfort of people. With embedded multi-sensors, Unmanned Aerial Vehicles (UAVs) hold great potential for collecting sensing data and providing social services in smart city. However, due to the limited battery lifetime and processing capacities of UAVs, the efficient offloading scheme of UAVs is urgently needed

In the above article [1] , on pages 11 and 14, math appears incorrectly in some paragraphs.

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Research Advances and Challenges of Autonomous and Connected Ground Vehicles

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In future mobility environment, virtual drivers of autonomous vehicles should be monitored for the sake of safety by evaluating their driving behaviors. Evaluating human drivers of non-autonomous vehicles also can be helpful to improve performance of safety control systems. This paper evaluates driving behaviors based on transition probabilities among multiple driving modes. We estimate transition

A cooperative integrity monitoring (CIM) algorithm is proposed in this work. Under the CIM architecture, the algorithm can fully exploit the global navigation satellite system (GNSS) data and inter-vehicle measurements data to improve the detection and isolation of faulty measurements due to multipath or non line of sight (NLOS). Taking the advantages of cooperative scheme, a residual decomposition

Fully convolutional network is a powerful tool for per-pixel semantic segmentation/detection. However, it is problematic when coping with crack detection using partially accurate ground truths (GTs): the network may easily converge to the status that treats all the pixels as background (BG) and still achieves a very good loss, named “All Black” phenomenon, due to the unavailability of accurate GTs

The growth in online goods delivery is causing a dramatic surge in urban vehicle traffic from last-mile deliveries. On the other hand, ride-sharing has been on the rise with the success of ride-sharing platforms and increased research on using autonomous vehicle technologies for routing and matching. The future of urban mobility for passengers and goods relies on leveraging new methods that minimize

The customized bus (CB) is an innovative type of transit service that can provide a personalized efficient transit services for passengers and environmental friendliness and congestion alleviation in metropolitan areas. This work develops an integrated optimization method for CB stop deployment, route design, and timetable development optimization problems while meeting travel demands as much as possible

With the rapid development of high-speed and heavy-load electrified railway, the peak impact and the regenerative braking energy content of traction load become increasingly significant, which has become an important problem affecting the construction and operation benefits of electrified railway. On the basis of comprehensively solving the power quality problems of electrified railway, a multi-application

Demand responsive transit (DRT) services in suburban regions serve residents as the complements of the public transportation. Since suburban DRT service usually faces demand fluctuation in some special situations, such as terrible weather, DRT operators have recourse to temporal rental vehicles to satisfy all requests. There are two types of rental contracts. In the first case, the costs of rental

A novel bilevel programming model for designing feeder bus routes to simultaneously consider bus stop selection, bus routing, and passenger route/trip choice behavior is developed in this work. The objective of the upper-level model is to minimize the total in-vehicle travel time of passengers. The objective of the lower-level model is to determine bus stop locations and assign passenger demand to

We investigate the performance of a dual-hop intervehicular communications (IVC) system with relay selection strategy. We assume a generalized fading channel model, known as cascaded Rayleigh (also called n*Rayleigh), which involves the product of n independent Rayleigh random variables. This channel model provides a realistic description of IVC, in contrast to the conventional Rayleigh fading assumption

A Survey on Electric Buses—Energy Storage, Power Management, and Charging Scheduling R. Deng, Y. Liu, W. Chen, and H. Liang In recent years, aiming to reduce the metropolitan air pollution caused by fossil fuel-powered vehicles, the electrification of transportation, such as electric vehicles (EVs) and electric buses (EBs), has attracted great attention from the automobile industry, academia, and public

As a significant part of the next-generation smart grid, electric vehicles (EVs) are essential for most countries to achieve energy independence, secure energy supply, and alleviate the pressure on environmental protection and energy security. Although EVs have grown rapidly, the slow recharge time is still the biggest obstacle to a wider application. While gasoline vehicles can pump enough gasoline

For significant characteristics such as high efficiency and environmental protection, electric vehicles (EVs) have become a new technology trend in the intelligent transportation system (ITS). Data like real time traffic situation and charge point occupation in ITS shows significant real-time characteristics. Distributed storage system, an effective technology to ensure reliable sharing of dynamic

With the development of extreme fast charging technology, charging stations need to use energy storage stations to reduce the rising peak to average power ratio (PAPR). Lithium-ion capacitor (LIC) is a chemical power source that uses both Faraday process and non-Faraday process to store energy. Because of its attractive performance in terms of rate characteristics and chemical stability, it is suitable

Power simulation of lithium ion battery through battery model is of great significance for dynamic response simulation, heat generation calculation and charge-discharge strategy development. The accuracy and applicability of the model become crucial. In order to demonstrate the battery transient characteristics more effectively, a novel identification method for parameters of the 2 nd order RC equivalent

Sustainable development of the transport system has been the consensus around the world for the past decades. Encouraged by the urgent need for cleaner alternatives to fossil fuels, vehicle electrification has been advancing at an unprecedented pace. As a major component of the multimodal transportation system, public transit is at the forefront of adopting battery technology into its operation. Battery

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

The rapid and convenient travel of people and the timely transportation of goods depend on the correct decision of the Intelligent Transportation Systems (ITS). Due to the decision-making of ITS requires a large amount of data to support, UAV-enabled periodic data collection is an effective method. However, due to the limited resources of UAV, UAV cannot directly collect data from all storage devices

With the advent of the Internet of Things, especially the Internet of Vehicles, abundant environmental and mobile data can be generated continuously. A personalized recommender system is one of the important methods for solving the problem of big data overload. However, to make use of these mobile data from vehicles, traditional recommender services are confronted by severe challenges. Therefore, we

The global trends in urbanization have caused many problems, among which Urban Traffic Control (UTC) becomes a priority issue for most big cities in many countries. As traffic demand changes rapidly, appropriate control policies are required to be generated in real time in order to, e.g., minimize congestion to reduce average travel time and air pollution. A practical way to meet the challenge is to

Due to the advanced capabilities of the Internet of Vehicles (IoV) components such as vehicles, Roadside Units (RSUs) and smart devices as well as the increasing amount of data generated, Federated Learning (FL) becomes a promising tool given that it enables privacy-preserving machine learning that can be implemented in the IoV. However, the performance of the FL suffers from the failure of communication

In the MaaS (Mobility as a Service) age, the alternatives of route choice for a trip will not be the single mode paths, but the combined routes utilizing more than one travel mode in the multi-modal transportation systems. When modeling the multi-modal combined route choices, alternative routes are correlated not only because of the overlapping of physical links, but also because of the overlapping

As an emerging urban public transport mode, responsive feeder transit system is flexible and can offer door-to-door services between new districts at margins with low urban transit coverage and trunk bus station. In this study, a joint optimization of running route and scheduling for responsive feeder transit under mixed demand (i.e., reservation and real-time demands) of the time-dependent road network

For practical reasons, surveys that aim for a large number of respondents tend to restrict themselves to closed-ended responses. Despite potentially bringing richer insights, the use of open-ended questions poses great challenges in terms of extracting useful information while significantly increasing the analysis time. Nevertheless, automatic text analysis techniques speed up the analysis of open-ended

Accurate bus passenger flow prediction contributes to informed decisions and full utilization of transit supply. Passenger flow is affected by an extensive range of attributes featuring travel environment, which can be collected through multi-source information. A successful prediction model should not only fully utilize the latent knowledge hidden in multi-source data, but also address the resulting

The explosive growth of the Internet of Things and modern networking technologies lay the foundation for the development of intelligent transportation systems and smart cities. To analyzing massive data under the required time for transportation issues, the edge computing paradigm is applied, which pre-processing large amounts of data at the network edge to save bandwidth and improve response time

The Internet of Vehicles (IoV) enables real-time data exchange among vehicles and roadside units and thus provides a promising solution to alleviate traffic jams in the urban area. Meanwhile, better traffic management via efficient traffic light control can benefit the IoV as well by enabling a better communication environment and decreasing the network load. As such, IoV and efficient traffic light

In 2015, the Board of Governors of IEEE Intelligent Transportation Systems Society had approved the proposal to name the Best Paper Award in IEEE Transactions on Intelligent Transportation Systems as the George N. Saridis Best Transactions Paper Award. After nearly five years of preparation and planning, and almost one year of hard and concentrated effort by the Award Committee, we are pleased to announce

A Systematic Literature Review About the Impact of Artificial Intelligence on Autonomous Vehicle Safety