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»

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»

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»

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»

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»

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»

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»

Cooperative adaptive cruise control (CACC) is an extension of ACC. In addition to measuring the distance to a predecessor, a vehicle can also exchange information with a predecessor by wireless communication. This enables a vehicle to follow its predecessor at a closer distance under tighter control. This paper focuses on the impact of CACC on traffic-flow characteristics. It uses the traffic-flow... 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»

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»

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»

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»

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»

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»

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»

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»

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»

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»

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»

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»

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»

In this paper, the practical string stability of both homogeneous and heterogeneous platoons of adaptive cruise control (ACC) vehicles, which apply the constant time headway spacing policy, is investigated by considering the parasitic time delays and lags of the actuators and sensors when building the vehicle longitudinal dynamics model. The proposed control law based on the sliding-mode controlle... 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»

This paper presents real-time obstacles detection and their status classification method for collision warning in the vehicle active safety system. Specifically, stereo cameras and millimeter wave (mmw)-radar are fused to help the driving ego-vehicle to find “Danger” or “Potential Danger” in a timely way through combining with the vehicle kinematic model. The proposed method makes full use of the ... 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»

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»

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»

This paper looks into recent developments and research trends in collision avoidance/warning systems and automation of vehicle longitudinal/lateral control tasks. It is an attempt to provide a bigger picture of the very diverse, detailed and highly multidisciplinary research in this area. Based on diversely selected research, this paper explains the initiatives for automation in different levels o... View full abstract»

Automated license plate recognition (ALPR) is essential in several roadway imaging applications. For ALPR systems deployed in the United States, variation between jurisdictions on character width, spacing, and the existence of noise sources (e.g., heavy shadows, non-uniform illumination, various optical geometries, poor contrast, and so on) present in LP images makes it challenging for the recogni... View full abstract»

Over the past decade, vision-based vehicle detection techniques for road safety improvement have gained an increasing amount of attention. Unfortunately, the techniques suffer from robustness due to huge variability in vehicle shape (particularly for motorcycles), cluttered environment, various illumination conditions, and driving behavior. In this paper, we provide a comprehensive survey in a sys... View full abstract»

This paper proposes a cooperative intersection control strategy, which aims to decrease the number of accidents and to increase the traffic flow at intersections. Existing high-level automation methodologies mainly focus on the determination of a safe crossing sequence of the involved vehicles, typically ignoring realistic vehicle dynamics aspects. The solution proposed in this paper, referred to ... View full abstract»

Intersection management is one of the most challenging problems within the transport system. Traffic light-based methods have been efficient but are not able to deal with the growing mobility and social challenges. On the other hand, the advancements of automation and communications have enabled cooperative intersection management, where road users, infrastructure, and traffic control centers are ... 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»

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»

The introduction of wirelessly charged electric buses (WCEBs) into current public transportation system attracts many attentions in recent years. As the wireless charging technology enables energy transfer from power transmitters to electric vehicles (EVs) on road, it provides a promising solution to reduce the huge cost of battery with large size and long charging time, which are two critical imp... View full abstract»

This paper adopts different supervised learning methods from the field of machine learning to develop multiclass classifiers that identify the transportation mode, including driving a car, riding a bicycle, riding a bus, walking, and running. Methods that were considered include K-nearest neighbor, support vector machines (SVMs), and tree-based models that comprise a single decision tree, bagging,... View full abstract»

Real-time traffic surveillance is essential in today's intelligent transportation systems and will surely play a vital role in tomorrow's smart cities. The work detailed in this paper reports on the development and implementation of a novel smart wireless sensor for traffic monitoring. Computationally efficient and reliable algorithms for vehicle detection, speed and length estimation, classificat... 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»

Automatic license plate recognition (LPR) plays an important role in numerous applications and a number of techniques have been proposed. However, most of them worked under restricted conditions, such as fixed illumination, limited vehicle speed, designated routes, and stationary backgrounds. In this study, as few constraints as possible on the working environment are considered. The proposed LPR ... View full abstract»

In this paper, we propose a visualization method for driving behavior that helps people to recognize distinctive driving behavior patterns in continuous driving behavior data. Driving behavior can be measured using various types of sensors connected to a control area network. The measured multi-dimensional time series data are called driving behavior data. In many cases, each dimension of the time... View full abstract»

This paper presents a comprehensive literature review on environment perception for intelligent vehicles. The state-of-the-art algorithms and modeling methods for intelligent vehicles are given, with a summary of their pros and cons. A special attention is paid to methods for lane and road detection, traffic sign recognition, vehicle tracking, behavior analysis, and scene understanding. In additio... 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»

Automatic video analysis from urban surveillance cameras is a fast-emerging field based on computer vision techniques. We present here a comprehensive review of the state-of-the-art computer vision for traffic video with a critical analysis and an outlook to future research directions. This field is of increasing relevance for intelligent transport systems (ITSs). The decreasing hardware cost and,... View full abstract»

Driver drowsiness and distraction are two main reasons for traffic accidents and the related financial losses. Therefore, researchers have been working for more than a decade on designing driver inattention monitoring systems. As a result, several detection techniques for the detection of both drowsiness and distraction have been proposed in the literature. Some of these techniques were successful... View full abstract»

Driven by the expeditious evolution of the Internet of Things, the conventional vehicular ad hoc networks will progress toward the Internet of Vehicles (IoV). With the rapid development of computation and communication technologies, IoV promises huge commercial interest and research value, thereby attracting a large number of companies and researchers. In an effort to satisfy the driver's well-bei... View full abstract»

Obtaining accurate information about current and near-term future traffic flows of all links in a traffic network has a wide range of applications, including traffic forecasting, vehicle navigation devices, vehicle routing, and congestion management. A major problem in getting traffic flow information in real time is that the vast majority of links is not equipped with traffic sensors. Another pro... View full abstract»

This paper presents an algorithm for overapproximating the drivable area of road vehicles in the presence of time-varying obstacles. The drivable area can be used to detect whether a feasible trajectory exists and in which area one can limit the search of drivable trajectories. For this purpose, we abstract the considered road vehicle by a point mass with bounded velocity and acceleration. Our alg... 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»