INTELLIGENT TRANSPORTATION
S.NO | TITLES | ABSTARCTS | Year |
IT 1 | An Improved Exact ε-Constraint and Cut-and-Solve Combined Method for Biobjective Robust Lane Reservation | This study investigates a new biobjective lanereservation problem, which is to exclusively reserve lanes from an existing transportation network for special transport tasks with given deadlines. The objectives are to minimize the total negative impact on normal traffic due to the reduction of available lanes for general-purpose vehicles and to maximize the robustness of the lane-reservation solution against the uncertainty in link travel times. We first define the robustness for the lanereservation problem and formulate a biobjective mixed-integer linear program. Then, we develop an improved exact ε-constraint and a cut-and-solve combined method to generate its Pareto front. Computational results for an instance based on a real network topology and 220 randomly generated instances with up to 150 nodes, 600 arcs, and 50 tasks demonstrate that the proposed method is able to find the Pareto front and that the proposed cut-and-solve method is more efficient than the direct use of
optimization software CPLEX. |
2015 |
IT 3 | A Video-Analysis-Based Railway–Road Safety System for Detecting Hazard Situations at Level Crossings | Safety and security are the most discussed topics in the road and railway transportation field. Latest security initiatives in the field of railway transportation propose to implement
video surveillance at level crossing (LC) environments. In this paper we explore the possibility of implementing a smart video surveillance security system that is tuned toward detecting and evaluating abnormal situations induced by users (pedestrians, vehicle drivers, and unattended objects) in LCs. This intelligent security system starts by detecting, separating, and tracking moving objects shot in the LC. Then, a hiddenMarkov model is developed to estimate ideal trajectories, allowing the detected targets to discard dangerous situations. After that, the level of risk of each target is instantly estimated by using the Dempster–Shafer data fusion technique. The proposed analysis allows for also recognizing hazard scenarios. The video surveillance system is connected to a communication system (the Wireless Access for Vehicular Environment), which takes the information on the dynamic status of the LC (safe or presence of a dangerous situation) and sends it to users approaching the LC. Four hazard scenarios are tested and evaluated with different real video image sequences: presence of the obstacle in the LC, presence of the stopped vehicles line, vehicle zigzagging between two closed half barriers, and pedestrian crossing the LC area. |
2015 |
IT 4 | Advanced Modeling of a 2-kW Series–Series Resonating Inductive Charger for Real Electric Vehicle | This paper focuses on the design of a contactless charging system for electric vehicles (EVs) using inductive loops
connected to a resonance converter. The study carries out the system operation, electromagnetic radiation, and testing. It is shown that the presence of the chassis leads to a double resonance and has a strong influence on the radiated fields. |
2015 |
IT 5 | Online Prediction of Driver Distraction Based on Brain Activity Patterns | This paper presents a new computational framework for early detection of driver distractions (map viewing) using
brain activity measured by electroencephalographic (EEG) signals. Compared with most studies in the literature, which are mainly focused on the classification of distracted and nondistracted periods, this study proposes a new framework to prospectively predict the start and end of a distraction period, defined by map viewing. The proposed prediction algorithm was tested on a data set of continuous EEG signals recorded from 24 subjects. During the EEG recordings, the subjects were asked to drive from an initial position to a destination using a city map in a simulated driving environment. The overall accuracy values for the prediction of the start and the end of map viewing were 81% and 70%, respectively. The experimental results demonstrated that the proposed algorithm can predict the start and end of map viewing with relatively high accuracy and can be generalized to individual subjects. The outcome of this study has a high potential to improve the design of future intelligent navigation systems. Prediction of the start of map viewing can be used to provide route information based on a driver’s needs and consequently avoid map-viewing activities. Prediction of the end of map viewing can be used to provide warnings for potential long map-viewing durations. Further development of the proposed framework and its applications in driver-distraction predictions are also discussed. |
2015 |
IT 6 | Deduction of Passengers’ Route Choices From Smart Card Data | Deducing passengers’ route choices from smart card data provides public transport operators the opportunity to evaluate
and improve their passenger service. Particularly in the case of disruptions, when traditional route choice models may not be valid, this is an advantage. This paper proposes a method for deducing the chosen route of passengers based on smart card data and validates this method on a real-life data set. The method deduces the correct route for about 95% of the journeys per day in our validation sample, and also in the case of disruptions. Moreover, it is shown how this method can be used to analyze and evaluate passenger service by a case study based on a real-life data set of Netherlands Railways, which is the largest passenger railway operator in the Netherlands. |
2015 |
IT 7 | Recognition of Highway Workzones for Reliable Autonomous Driving | In order to be deployed in real-world driving environments, self-driving cars must be able to recognize and respond
to exceptional road conditions, such as highway workzones, because such unusual events can alter previously known traffic rules and road geometry. In this paper, we present a set of computer vision methods that recognize, through identification of workzone signs, the bounds of a highway workzone and temporary changes in highway driving environments. Through testing using video data about highway workzones recorded under various weather conditions, our approach was able to perfectly identify the boundaries of workzones and robustly detect a majority of driving condition changes. In addition to these tests, we evaluated, using a mock workzone setup, the usefulness of our workzone recognition systems’ outputs for safe-guarding a self-driving car. |
2015 |
IT 8 | Design of a Mobile Charging Service for Electric Vehicles in an Urban Environment | This paper presents a novel approach to providing a service for electric-vehicle (EV) battery charge replenishment. This is an alternate system in which the charge replenishment is provided by mobile chargers (MCs). These chargers could have two possible configurations: a mobile plug-in charger (MP) or a mobile battery-swapping station (MS). A queuing-based analytical approach is used to determine the appropriate range of design parameters for such a mobile charging system. An analytical analysis is first developed for an idealized system with a nearest-job-next (NJN) service strategy explored for such a system. In a NJN service strategy, the MC services the next spatially closest EV
when it is finished with its current request. An urban environment approximated by Singapore is then analyzed through simulation. Charging requests are simulated through a trip generation model based on Singapore. In such a realistic environment, an updated practical NJN service strategy is proposed. For an MP system in an urban environment such as Singapore, there exists an optimal battery capacity with a threshold battery charge rate. Similarly, the battery swap capacity of an MS system does not need to be large for the system to perform. |
2015 |
IT 9 | A Train Localization Algorithm for Train Protection Systems of the Future | This paper describes an algorithm that enables a railway vehicle to determine its position in a track network. The system is based solely on onboard sensors such as a velocity sensor and a Global Navigation Satellite System (GNSS) sensor and does not require trackside infrastructure such as axle counters or balises. The paper derives a probabilistic modeling of the localization task and develops a sensor fusion approach to fuse the inputs of the GNSS sensor and the velocity sensor with the digital track map. We describe how we can treat ambiguities and stochastic uncertainty adequately. Moreover, we introduce the concept of virtual balises that can be used to replace balises on the track and evaluate the approach experimentally. This paper focuses on an accurate modeling of sensor and estimation uncertainties, which is relevant for safety critical applications. | 2015 |
IT 10 | A Prototype Integrated Monitoring System for Pavement and Traffic Based on an Embedded Sensing Network | In the past half-century, the monitoring systems for traffic or infrastructure have been developed a lot. Because of
the interdependency between traffic and infrastructure, significant advantages can be expected if the monitoring system for traffic can be integrated with that for infrastructure. In October 2011, a wireless sensing network (WSN) was installed on Virginia State Route 114. Since then, Virginia Polytechnic Institute and State University (Blacksburg, VA, USA) has been developing an integrated monitoring system of pavements and traffic. This paper presents the achievement of this study: a prototype system that can monitor pavement conditions and collect traffic information simultaneously using the same embedded sensing network. In the sensing network, the sensors are ranged in longitudinal and transverse groups, and the compositions, characteristics, and functionalities of the two arrangements are introduced. The two monitoring patterns of the system, i.e., continuous monitoring and periodic testing, are explained, and the data processing methods in the two patterns are illustrated. The whole system is presented combining hardware and software, and a flowchart is used to clarify its component and function modules. This system has the potential to achieve comprehensive monitoring functions for both traffic and infrastructure based on the embedded sensing network. This system is still under study, and needs to be consummated with various loading and environmental conditions taken into consideration. Once finished, this system will be valuable for the Intelligent Transportation System in the future. |
2015 |
IT 11 | Wireless Sensor Networks for Condition Monitoring in the Railway Industry: A Survey | 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 integrate devices.Wireless sensor networks (WSNs) can be used for monitoring the railway infrastructure
such as bridges, rail tracks, track beds, and track equipment along with vehicle health monitoring such as chassis, bogies, wheels, and wagons. Condition monitoring reduces human inspection requirements through automated monitoring, reduces maintenance through detecting faults before they escalate, and improves safety and reliability. This is vital for the development, upgrading, and expansion of railway networks. This paper surveys these wireless sensors network technology for monitoring in the railway industry for analyzing systems, structures, vehicles, and machinery. This paper focuses on practical engineering solutions, principally, which sensor devices are used and what they are used for; and the identification of sensor configurations and network topologies. It identifies their respective motivations and distinguishes their advantages and disadvantages in a comparative review. |
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IT 12 | Sustainable Transportation Management System for a
Fleet of Electric Vehicles |
In the last few years, significant efforts have been devoted to developing intelligent and sustainable transportation
to address pollution problems and fuel shortages. Transportation agencies in various countries, along with several standardization organizations, have proposed different types of energy sources (such as hydrogen, biodiesel, electric, and hybrid technologies) as alternatives to fossil fuel to achieve a more ecofriendly and sustainable environment. However, to achieve this goal, there are significant challenges that still need to be addressed. We present a survey on sustainable transportation systems that aim to reduce pollution and greenhouse gas emissions. We describe the architectural components of a future sustainable means of transportation, and we review current solutions, projects, and standardization fforts related to green transportation with particular focus on electric vehicles.We also highlight the main issues that still need to be addressed to achieve a green transportation management system. To address these issues, we present an integrated architecture for sustainable transportation management systems. |
2015 |