IEEE Transactions on Intelligent Transportation Systems

Accurate and timely traffic flow information is important for the successful deployment of intelligent transportation systems. Over the last few years, traffic data have been exploding, and we have truly entered the era of big data for transportation. Existing traffic flow prediction methods mainly use shallow traffic prediction models and are still unsatisfying for many real-world applications. T... View full abstract»

Wheel defects on railway wagons have been identified as an important source of damage to the railway infrastructure and rolling stock. They also cause noise and vibration emissions that are costly to mitigate. We propose two machine learning methods to automatically detect these wheel defects, based on the wheel vertical force measured by a permanently installed sensor system on the railway networ... View full abstract»

In recent years, the range of sensing technologies has expanded rapidly, whereas sensor devices have become cheaper. This has led to a rapid expansion in condition monitoring of systems, structures, vehicles, and machinery using sensors. Key factors are the recent advances in networking technologies such as wireless communication and mobile ad hoc networking coupled with the technology to integrat... View full abstract»

Intelligent vehicles have increased their capabilities for highly and, even fully, automated driving under controlled environments. Scene information is received using onboard sensors and communication network systems, i.e., infrastructure and other vehicles. Considering the available information, different motion planning and control techniques have been implemented to autonomously driving on com... View full abstract»

Semantic segmentation is a challenging task that addresses most of the perception needs of intelligent vehicles (IVs) in an unified way. Deep neural networks excel at this task, as they can be trained end-to-end to accurately classify multiple object categories in an image at pixel level. However, a good tradeoff between high quality and computational resources is yet not present in the state-of-t... View full abstract»

Traffic flow prediction is a fundamental problem in transportation modeling and management. Many existing approaches fail to provide favorable results due to being: 1) shallow in architecture; 2) hand engineered in features; and 3) separate in learning. In this paper we propose a deep architecture that consists of two parts, i.e., a deep belief network (DBN) at the bottom and a multitask regressio... View full abstract»

This paper presents methods for collecting and analyzing physiological data during real-world driving tasks to determine a driver's relative stress level. Electrocardiogram, electromyogram, skin conductance, and respiration were recorded continuously while drivers followed a set route through open roads in the greater Boston area. Data from 24 drives of at least 50-min duration were collected for ... View full abstract»

For the last two decades, intelligent transportation systems (ITS) have emerged as an efficient way of improving the performance of transportation systems, enhancing travel security, and providing more choices to travelers. A significant change in ITS in recent years is that much more data are collected from a variety of sources and can be processed into various forms for different stakeholders. T... View full abstract»

The vehicular announcement network is one of the most promising utilities in the communications of smart vehicles and in the smart transportation systems. In general, there are two major issues in building an effective vehicular announcement network. First, it is difficult to forward reliable announcements without revealing users' identities. Second, users usually lack the motivation to forward an... View full abstract»

This paper provides a review of the literature in on-road vision-based vehicle detection, tracking, and behavior understanding. Over the past decade, vision-based surround perception has progressed from its infancy into maturity. We provide a survey of recent works in the literature, placing vision-based vehicle detection in the context of sensor-based on-road surround analysis. We detail advances... View full abstract»

Intelligent vehicle cooperation based on reliable communication systems contributes not only to reducing traffic accidents but also to improving traffic flow. Adaptive cruise control (ACC) systems can gain enhanced performance by adding vehicle-vehicle wireless communication to provide additional information to augment range sensor data, leading to cooperative ACC (CACC). This paper presents the d... View full abstract»

Vehicle automation has been one of the fundamental applications within the field of intelligent transportation systems (ITS) since the start of ITS research in the mid-1980s. For most of this time, it has been generally viewed as a futuristic concept that is not close to being ready for deployment. However, recent development of “self-driving” cars and the announcement by car manufacturers of thei... View full abstract»

We propose a novel system for the automatic detection and recognition of text in traffic signs. Scene structure is used to define search regions within the image, in which traffic sign candidates are then found. Maximally stable extremal regions (MSERs) and hue, saturation, and value color thresholding are used to locate a large number of candidates, which are then reduced by applying constraints ... View full abstract»

High-speed railway (HSR) brings convenience to peoples' lives and is generally considered as one of the most sustainable developments for ground transportation. One of the important parts of HSR construction is the signaling system, which is also called the “operation control system,” where wireless communications play a key role in the transmission of train control data. We discuss in detail the ... View full abstract»

We introduce the KAIST multi-spectral data set, which covers a great range of drivable regions, from urban to residential, for autonomous systems. Our data set provides the different perspectives of the world captured in coarse time slots (day and night), in addition to fine time slots (sunrise, morning, afternoon, sunset, night, and dawn). For all-day perception of autonomous systems, we propose ... View full abstract»

Driver driving style plays an important role in vehicle energy management as well as driving safety. Furthermore, it is key for advance driver assistance systems development, toward increasing levels of vehicle automation. This fact has motivated numerous research and development efforts on driving style identification and classification. This paper provides a survey on driving style characterizat... View full abstract»

Big data is becoming a research focus in intelligent transportation systems (ITS), which can be seen in many projects around the world. Intelligent transportation systems will produce a large amount of data. The produced big data will have profound impacts on the design and application of intelligent transportation systems, which makes ITS safer, more efficient, and profitable. Studying big data a... View full abstract»

The accurate detection and classification of moving objects is a critical aspect of advanced driver assistance systems. We believe that by including the object classification from multiple sensor detections as a key component of the object's representation and the perception process, we can improve the perceived model of the environment. First, we define a composite object representation to includ... View full abstract»

Considering the increase of urban population and traffic congestion, smart parking is always a strategic issue to work on, not only in the research field, but also from economic interests. Thanks to information and communication technology evolution, drivers can more efficiently find satisfying parking spaces with smart parking services. The existing and ongoing works on smart parking are complica... View full abstract»

With the remarkable progress of cooperative communication technology in recent years, its transformation to vehicular networking is gaining momentum. Such a transformation has brought a new research challenge in facing the realization of cooperative vehicular networking (CVN). This paper presents a comprehensive survey of recent advances in the field of CVN. We cover important aspects of CVN resea... View full abstract»

We propose a novel traffic sign detection system that simultaneously estimates the location and precise boundary of traffic signs using convolutional neural network (CNN). Estimating the precise boundary of traffic signs is important in navigation systems for intelligent vehicles where traffic signs can be used as 3-D landmarks for road environment. Previous traffic sign detection systems, includi... View full abstract»

Recent technology advances significantly push forward the development and the deployment of the concept of smart, such as smart community and smart city. Smart transportation is one of the core components in modern urbanization processes. Under this context, the connected autonomous vehicle (CAV) system presents a promising solution towards the enhanced traffic safety and mobility through state-of... View full abstract»

Fine-grained vehicle model recognition is a challenging problem in intelligent transportation systems due to the subtle intra-category appearance variation. In this paper, we demonstrate that this problem can be addressed by locating discriminative parts, where the most significant appearance variation appears, based on the large-scale training set. We also propose a corresponding coarse-to-fine m... View full abstract»

This paper provides an in-depth description of the best rated human-machine interface that was presented during the 2016 Grand Cooperative Driving Challenge. It was demonstrated by the Chalmers Truck Team as the envisioned interface to their open source software framework OpenDLV, which is used to power Chalmers' fleet of self-driving vehicles. The design originates from the postulate that the veh... View full abstract»

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead... View full abstract»

Road detection from the perspective of moving vehicles is a challenging issue in autonomous driving. Recently, many deep learning methods spring up for this task, because they can extract high-level local features to find road regions from raw RGB data, such as convolutional neural networks and fully convolutional networks (FCNs). However, how to detect the boundary of road accurately is still an ... View full abstract»

Under the Connected Vehicles (CV) environment, it is possible to create a Cooperative Vehicle Intersection Control (CVIC) system that enables cooperation between vehicles and infrastructure for effective intersection operations and management when all vehicles are fully automated. Assuming such a CVIC environment, this paper proposed a CVIC algorithm that does not require a traffic signal. The CVI... View full abstract»

The smart city embraces gradual adoption of autonomous vehicles (AVs) into the intelligent transportation system. Contributed by their full-fledged controllability, AVs can respond to instantaneous situations with high efficiency and flexibility. In this paper, we propose a novel AV logistic system (AVLS) to accommodate logistic demands for smart cities. We focus on determining the optimal routes ... View full abstract»

Although traffic sign recognition has been studied for many years, most existing works are focused on the symbol-based traffic signs. This paper proposes a new data-driven system to recognize all categories of traffic signs, which include both symbol-based and text-based signs, in video sequences captured by a camera mounted on a car. The system consists of three stages, traffic sign regions of in... View full abstract»

Connected and automated vehicles (CAVs) have the potential to improve safety by reducing and mitigating traffic accidents. They can also provide opportunities to reduce transportation energy consumption and emissions by improving traffic flow. Vehicle communication with traffic structures and traffic lights can allow individual vehicles to optimize their operation and account for unpredictable cha... View full abstract»

The validity of any traffic simulation model depends on its ability to generate representative driver acceleration profiles. This paper studies the effectiveness of recurrent neural networks in predicting the acceleration distributions for car following on highways. The long short-term memory recurrent networks are trained and used to propagate the simulated vehicle trajectories over 10-s horizons... View full abstract»

By considering a lane change maneuver as primarily a longitudinal motion planning problem, this paper presents a lane change maneuver algorithm with a pragmatic approach to determine an inter-vehicle traffic gap and time instance to perform the maneuver. The proposed approach selects an appropriate inter-vehicle traffic gap and time instance to perform the lane change maneuver by simply estimating... View full abstract»

Activity-based travel demand models are becoming essential tools used in transportation planning and regional development scenario evaluation. They describe travel itineraries of individual travelers, namely, what activities they are participating in, when they perform these activities, and how they choose to travel to the activity locales. However, data collection for activity-based models is per... View full abstract»

Parking in major cities, particularly with dense traffic, directly effects the traffic flow and people's life. In this paper, we introduce a new smart parking system that is based on intelligent resource allocation, reservation, and pricing. The proposed system solves the current parking problems by offering guaranteed parking reservations with the lowest possible cost and searching time for drive... View full abstract»

Automotive electronics is a rapidly expanding area with an increasing number of safety, driver assistance, and infotainment devices becoming standard in new vehicles. Current vehicles generally employ a number of different networking protocols to integrate these systems into the vehicle. The introduction of large numbers of sensors to provide driver assistance applications and the associated high-... View full abstract»

Dynamic wireless charging (DWC) technology, a novel way of supplying vehicles with electric energy, allows the vehicle battery to be recharged remotely while it is moving over power tracks, which are charging infrastructures installed beneath the road. DWC systems mitigate the range limitation of electric vehicles by using power tracks as additional sources of electric energy. This paper proposes ... View full abstract»

As the number of vehicles continues to grow, parking spaces are at a premium in city streets. In addition, due to the lack of knowledge about street parking spaces, heuristic circling in the streets not only costs drivers' time and fuel, but also increases city congestion. In the wake of the recent trend to build convenient, green, and energy-efficient smart cities, common techniques adopted by hi... View full abstract»

This paper presents a novel convolutional neural network (CNN) -based method for high-accuracy real-time car license plate detection. Many contemporary methods for car license plate detection are reasonably effective under the specific conditions or strong assumptions only. However, they exhibit poor performance when the assessed car license plate images have a degree of rotation, as a result of m... View full abstract»

Real-time object tracking on a drone under a dynamic environment has been a challenging issue for many years, with existing approaches using off-line calculation or powerful computation units on board. This paper presents a new lightweight real-time onboard object tracking approach with multi-inertial sensing data, wherein a highly energy-efficient drone is built based on the Snapdragon flight boa... View full abstract»

Vehicle-IT convergence technology is a rapidly rising paradigm of modern vehicles, in which an electronic control unit (ECU) is used to control the vehicle electrical systems, and the controller area network (CAN), an in-vehicle network, is commonly used to construct an efficient network of ECUs. Unfortunately, security issues have not been treated properly in CAN, although CAN control messages co... View full abstract»

In a recent paper, Ghazizadeh et al. have studied vehicular clouds running on top of the vehicles in the parking lot of a major airport. The defining difference between vehicular clouds and their conventional counterparts is the unpredictable availability of computational resources. Indeed, as vehicles enter the parking lot, fresh compute resources become available; when vehicles depart, their com... View full abstract»

This paper summarizes the state of the art in connected vehicles-from the need for vehicle data and applications thereof, to enabling technologies, challenges, and identified opportunities. Connectivity is increasing around the world and its expansion to vehicles is no exception. With improvements in connectivity, sensing, and computation, the future will see vehicles used as development platforms... View full abstract»

Recently, Vijayakumar et al. proposed a dual authentication and key management scheme for secure data transmission in vehicular ad-hoc networks. As described by Vijayakumar et al., a dual authentication scheme and the corresponding group key management mechanism are illustrated successively. The authors claimed that the proposed scheme is resistant to replay attack and masquerade attack. However, ... View full abstract»

Efficient data dissemination is critical for enabling emerging applications in vehicular ad hoc networks. As a typical traffic scenario, the bidirectional road scenario of highways bring unique challenges on well exploiting the benefit of vehicle-to-vehicle (V2V) communication for data sharing among vehicles driving in opposite directions. This paper is dedicated to investigating the characteristi... View full abstract»

Smart card data gathered by automated fare collection (AFC) systems are valuable resources for studying urban mobility. In this paper, we propose two approaches to cluster smart card data, which can be used to extract mobility patterns in a public transportation system. Two complementary standpoints are considered: a station-oriented operational point of view and a passenger-focused one. The first... View full abstract»

The U.S. Department of Transportation (USDOT) issued a proposed rule on January 12, 2017 to mandate vehicle-to-vehicle safety communications in light vehicles in the U.S. Cybersecurity and privacy are major challenges for such a deployment. We present a Security Credential Management System (SCMS) for vehicle-to-everything (V2X) communications in this paper, which has been developed by the Crash A... View full abstract»

It is very difficult to establish and maintain end-to-end connections in a vehicle ad hoc network (VANET) as a result of high vehicle speed, long inter-vehicle distance, and varying vehicle density. Instead, a store-and-forward strategy has been considered for vehicle communications. The success of this strategy, however, depends heavily on the cooperation among nodes. Different from exiting store... View full abstract»

Railroad tracks need to be periodically inspected and monitored to ensure safe transportation. Automated track inspection using computer vision and pattern recognition methods has recently shown the potential to improve safety by allowing for more frequent inspections while reducing human errors. Achieving full automation is still very challenging due to the number of different possible failure mo... View full abstract»

Vehicles are currently being developed and sold with increasing levels of connectivity and automation. As with all networked computing devices, increased connectivity often results in a heightened risk of a cyber security attack. Furthermore, increased automation exacerbates any risk by increasing the opportunities for the adversary to implement a successful attack. In this paper, a large volume o... View full abstract»

Driver-assistance systems that monitor driver intent, warn drivers of lane departures, or assist in vehicle guidance are all being actively considered. It is therefore important to take a critical look at key aspects of these systems, one of which is lane-position tracking. It is for these driver-assistance objectives that motivate the development of the novel "video-based lane estimation and trac... View full abstract»