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Special Issue "Positioning and Tracking Sensors and Technologies in Road Transport"

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A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (15 September 2014)

Special Issue Editors

Guest Editor
Dr. Felipe Jimenez

University Institute for Automobile Research (INSIA), Technical University of Madrid, INSIA, Campus Sur UPM, Carretera de Valencia km 7 28031, Madrid, Spain
Phone: 34913365317
Fax: +34 913365302
Interests: intelligent transport systems, advanced driver assistance systems, vehicle positioning, GNSS, inertial sensors, digital maps, vehicle dynamics, driver monitoring, vehicle automation, V2X communications
Guest Editor
Dr. Jose Naranjo

University Institute for Automobile Research (INSIA), Technical University of Madrid, INSIA, Campus Sur UPM, Carretera de Valencia km 7 28031, Madrid
Interests: intelligent transport systems, advanced driver assistance systems, vehicle positioning, GNSS, vehicle automation V2V communications

Special Issue Information

Dear Colleagues,

Vehicle positioning is becoming more and more relevant in many applications in road transport. The accuracy requirements are not the same for all of them and, in general, safety applications are more restrictive. Global Navigation Satellite Systems (GNSS) positioning does not guarantee a specific and constant level of accuracy. A widespread solution for dealing with GNSS positioning limitations is to combine GNSS positioning with inertial sensors or computer vision technologies. The algorithms developed for data fusion should be based on determining the confidence level of each measure. On the other hand, apart from specifically oriented instrumentation, accuracy of smartphones that offer geopositioning should be assessed.

Another problem is the interrelationship between the positioning system and location in the digital map. This problem is not trivial when dealing with imprecise information. In such cases, providing a specific location of a vehicle on a roadway presents difficulties in complex scenarios, and involves implementing complex and reliable algorithms. Map-matching algorithms try to overcome the inaccuracies of digital maps and positioning systems

Finally, over the years and the evolution of in-vehicle technologies and communications with the vehicle surroundings, there has been an important group of applications that may rely more or less on vehicle positioning and tracking.

Contributions related to vehicle tracking and positioning, using satellite systems, inertial sensors or other means will be considered. Also, submissions focused on the uncertainty of these kinds of positioning systems and the solutions that overcome such inaccuracy will also be considered. Contributions focused on specific applications in road transport should clearly indicate which challenges in positioning the work is addressing. Authors are invited to contact the guest editors, prior to submission, if they are uncertain whether their work falls within the general scope of this Special Issue.

Dr. Felipe Jimenez
Dr. Jose Eugenio Naranjo
Guest Editors

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs).

Keywords

  • positioning
  • vehicle tracking
  • satellite positioning
  • GNSS
  • GPS
  • GALILEO
  • inertial sensors
  • sensor fusion
  • digital maps
  • map-matching algorithm
  • visual odometry
  • smartphones geolocation

Published Papers (28 papers)

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Research

Open AccessArticle Weighted Geometric Dilution of Precision Calculations with Matrix Multiplication
Sensors 2015, 15(1), 803-817; doi:10.3390/s150100803
Received: 15 September 2014 / Accepted: 26 December 2014 / Published: 5 January 2015
Cited by 2 | PDF Full-text (995 KB) | HTML Full-text | XML Full-text
Abstract
To enhance the performance of location estimation in wireless positioning systems, the geometric dilution of precision (GDOP) is widely used as a criterion for selecting measurement units. Since GDOP represents the geometric effect on the relationship between measurement error and positioning determination [...] Read more.
To enhance the performance of location estimation in wireless positioning systems, the geometric dilution of precision (GDOP) is widely used as a criterion for selecting measurement units. Since GDOP represents the geometric effect on the relationship between measurement error and positioning determination error, the smallest GDOP of the measurement unit subset is usually chosen for positioning. The conventional GDOP calculation using matrix inversion method requires many operations. Because more and more measurement units can be chosen nowadays, an efficient calculation should be designed to decrease the complexity. Since the performance of each measurement unit is different, the weighted GDOP (WGDOP), instead of GDOP, is used to select the measurement units to improve the accuracy of location. To calculate WGDOP effectively and efficiently, the closed-form solution for WGDOP calculation is proposed when more than four measurements are available. In this paper, an efficient WGDOP calculation method applying matrix multiplication that is easy for hardware implementation is proposed. In addition, the proposed method can be used when more than exactly four measurements are available. Even when using all-in-view method for positioning, the proposed method still can reduce the computational overhead. The proposed WGDOP methods with less computation are compatible with global positioning system (GPS), wireless sensor networks (WSN) and cellular communication systems. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle A Vondrak Low Pass Filter for IMU Sensor Initial Alignment on a Disturbed Base
Sensors 2014, 14(12), 23803-23821; doi:10.3390/s141223803
Received: 14 August 2014 / Revised: 1 December 2014 / Accepted: 2 December 2014 / Published: 10 December 2014
Cited by 2 | PDF Full-text (1336 KB) | HTML Full-text | XML Full-text
Abstract
The initial alignment of the Inertial Measurement Unit (IMU) is an important process of INS to determine the coordinate transformation matrix which is used in the integration of Global Positioning Systems (GPS) with Inertial Navigation Systems (INS). In this paper a novel [...] Read more.
The initial alignment of the Inertial Measurement Unit (IMU) is an important process of INS to determine the coordinate transformation matrix which is used in the integration of Global Positioning Systems (GPS) with Inertial Navigation Systems (INS). In this paper a novel alignment method for a disturbed base, such as a vehicle disturbed by wind outdoors, implemented with the aid of a Vondrak low pass filter, is proposed. The basic principle of initial alignment including coarse alignment and fine alignment is introduced first. The spectral analysis is processed to compare the differences between the characteristic error of INS force observation on a stationary base and on disturbed bases. In order to reduce the high frequency noise in the force observation more accurately and more easily, a Vondrak low pass filter is constructed based on the spectral analysis result. The genetic algorithms method is introduced to choose the smoothing factor in the Vondrak filter and the corresponding objective condition is built. The architecture of the proposed alignment method with the Vondrak low pass filter is shown. Furthermore, simulated experiments and actual experiments were performed to validate the new algorithm. The results indicate that, compared with the conventional alignment method, the Vondrak filter could eliminate the high frequency noise in the force observation and the proposed alignment method could improve the attitude accuracy. At the same time, only one parameter needs to be set, which makes the proposed method easier to implement than other low-pass filter methods. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Comparison of Global Navigation Satellite System Devices on Speed Tracking in Road (Tran)SPORT Applications
Sensors 2014, 14(12), 23490-23508; doi:10.3390/s141223490
Received: 15 September 2014 / Revised: 24 November 2014 / Accepted: 28 November 2014 / Published: 8 December 2014
PDF Full-text (1384 KB) | HTML Full-text | XML Full-text
Abstract
Global Navigation Satellite Systems (GNSS) are, in addition to being most widely used vehicle navigation method, becoming popular in sport-related tests. There is a lack of knowledge regarding tracking speed using GNSS, therefore the aims of this study were to examine under [...] Read more.
Global Navigation Satellite Systems (GNSS) are, in addition to being most widely used vehicle navigation method, becoming popular in sport-related tests. There is a lack of knowledge regarding tracking speed using GNSS, therefore the aims of this study were to examine under dynamic conditions: (1) how accurate technologically different GNSS measure speed and (2) how large is latency in speed measurements in real time applications. Five GNSSs were tested. They were fixed to a car’s roof-rack: a  smart phone, a wrist watch, a handheld device, a professional system for testing vehicles and a high-end Real Time Kinematics (RTK) GNSS. The speed data were recorded and analyzed during rapid acceleration and deceleration as well as at steady speed. The study produced four main findings. Higher frequency and high quality GNSS receivers track speed at least at comparable accuracy to a vehicle speedometer. All GNSS systems measured maximum speed and movement at a constant speed well. Acceleration and deceleration have different level of error at different speeds. Low cost GNSS receivers operating at 1 Hz sampling rate had high latency (up to 2.16 s) and are not appropriate for tracking speed in real time, especially during dynamic movements. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle A Hybrid Positioning Strategy for Vehicles in a Tunnel Based on RFID and In-Vehicle Sensors
Sensors 2014, 14(12), 23095-23118; doi:10.3390/s141223095
Received: 4 September 2014 / Revised: 22 November 2014 / Accepted: 25 November 2014 / Published: 5 December 2014
Cited by 3 | PDF Full-text (1122 KB) | HTML Full-text | XML Full-text
Abstract
Many intelligent transportation system applications require accurate, reliable, and continuous vehicle positioning. How to achieve such positioning performance in extended GPS-denied environments such as tunnels is the main challenge for land vehicles. This paper proposes a hybrid multi-sensor fusion strategy for vehicle [...] Read more.
Many intelligent transportation system applications require accurate, reliable, and continuous vehicle positioning. How to achieve such positioning performance in extended GPS-denied environments such as tunnels is the main challenge for land vehicles. This paper proposes a hybrid multi-sensor fusion strategy for vehicle positioning in tunnels. First, the preliminary positioning algorithm is developed. The Radio Frequency Identification (RFID) technology is introduced to achieve preliminary positioning in the tunnel. The received signal strength (RSS) is used as an indicator to calculate the distances between the RFID tags and reader, and then a Least Mean Square (LMS) federated filter is designed to provide the preliminary position information for subsequent global fusion. Further, to improve the positioning performance in the tunnel, an interactive multiple model (IMM)-based global fusion algorithm is developed to fuse the data from preliminary positioning results and low-cost in-vehicle sensors, such as electronic compasses and wheel speed sensors. In the actual implementation of IMM, the strong tracking extended Kalman filter (STEKF) algorithm is designed to replace the conventional extended Kalman filter (EKF) to achieve model individual filtering. Finally, the proposed strategy is evaluated through experiments. The results validate the feasibility and effectiveness of the proposed strategy. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Traffic Measurement on Multiple Drive Lanes with Wireless Ultrasonic Sensors
Sensors 2014, 14(12), 22891-22906; doi:10.3390/s141222891
Received: 21 October 2014 / Revised: 27 November 2014 / Accepted: 28 November 2014 / Published: 2 December 2014
Cited by 3 | PDF Full-text (1759 KB) | HTML Full-text | XML Full-text
Abstract
An automated traffic measuring system for use on multiple drive lanes is proposed in this paper. This system, which uses ultrasonic sensors and a lateral scanning method, is suitable for use on real traffic roads. The proposed system can be easily established [...] Read more.
An automated traffic measuring system for use on multiple drive lanes is proposed in this paper. This system, which uses ultrasonic sensors and a lateral scanning method, is suitable for use on real traffic roads. The proposed system can be easily established and maintained in various roadway environments. In addition, the system can be adjusted to measure traffic volumes according to the size and number of drive lanes. This paper describes the results of an experiment that the lateral scanning method can be easily applied to real traffic roads and provide a low error rate and real-time responses. This system can play an important role in accurately measuring traffic volumes as part of an intelligent transportation system. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Vehicle Tracking for an Evasive Manoeuvres Assistant Using Low-Cost Ultrasonic Sensors
Sensors 2014, 14(12), 22689-22705; doi:10.3390/s141222689
Received: 22 September 2014 / Revised: 12 November 2014 / Accepted: 24 November 2014 / Published: 28 November 2014
Cited by 3 | PDF Full-text (1204 KB) | HTML Full-text | XML Full-text
Abstract
Many driver assistance systems require knowledge of the vehicle environment. As these systems are increasing in complexity and performance, this knowledge of the environment needs to be more complete and reliable, so sensor fusion combining long, medium and short range sensors is [...] Read more.
Many driver assistance systems require knowledge of the vehicle environment. As these systems are increasing in complexity and performance, this knowledge of the environment needs to be more complete and reliable, so sensor fusion combining long, medium and short range sensors is now being used. This paper analyzes the feasibility of using ultrasonic sensors for low cost vehicle-positioning and tracking in the lane adjacent to the host vehicle in order to identify free areas around the vehicle and provide information to an automatic avoidance collision system that can perform autonomous braking and lane change manoeuvres. A laser scanner is used for the early detection of obstacles in the direction of travel while two ultrasonic sensors monitor the blind spot of the host vehicle. The results of tests on a test track demonstrate the ability of these sensors to accurately determine the kinematic variables of the obstacles encountered, despite a clear limitation in range. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle GPS & GLONASS Mass-Market Receivers: Positioning Performances and Peculiarities
Sensors 2014, 14(12), 22159-22179; doi:10.3390/s141222159
Received: 14 July 2014 / Revised: 12 November 2014 / Accepted: 17 November 2014 / Published: 25 November 2014
Cited by 8 | PDF Full-text (3829 KB) | HTML Full-text | XML Full-text
Abstract
Over the last twenty years, positioning with low cost Global Navigation Satellite System (GNSS) sensors have rapidly developed around the world at both a commercial and academic research level. For many years these instruments have only acquired the GPS constellation but are [...] Read more.
Over the last twenty years, positioning with low cost Global Navigation Satellite System (GNSS) sensors have rapidly developed around the world at both a commercial and academic research level. For many years these instruments have only acquired the GPS constellation but are now able to track the Global’naja Navigacionnaja Sputnikovaja Sistema (GLONASS) constellation. This characteristic is very interesting, especially if used in hard-urban environments or in hard conditions where satellite visibility is low. The goal of this research is to investigate the contribution of the GLONASS constellation for mass-market receivers in order to analyse the performance in real time (Network Real Time Kinematic—NRTK positioning) with post-processing approaches. Under these conditions, it is possible to confirm that mass-market sensors could be a valid alternative to a more expensive receiver for a large number of surveying applications, but with low cost hardware the contribution of the GLONASS constellation for fixing ambiguities is useless, if not dangerous. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle SVANET: A Smart Vehicular Ad Hoc Network for Efficient Data Transmission with Wireless Sensors
Sensors 2014, 14(12), 22230-22260; doi:10.3390/s141222230
Received: 15 September 2014 / Revised: 27 October 2014 / Accepted: 12 November 2014 / Published: 25 November 2014
PDF Full-text (3370 KB) | HTML Full-text | XML Full-text
Abstract
Wireless sensors can sense any event, such as accidents, as well as icy roads, and can forward the rescue/warning messages through intermediate vehicles for any necessary help. In this paper, we propose a smart vehicular ad hoc network (SVANET) architecture that uses [...] Read more.
Wireless sensors can sense any event, such as accidents, as well as icy roads, and can forward the rescue/warning messages through intermediate vehicles for any necessary help. In this paper, we propose a smart vehicular ad hoc network (SVANET) architecture that uses wireless sensors to detect events and vehicles to transmit the safety and non-safety messages efficiently by using different service channels and one control channel with different priorities. We have developed a data transmission protocol for the vehicles in the highway, in which data can be forwarded with the help of vehicles if they are connected with each other or data can be forwarded with the help of nearby wireless sensors. Our data transmission protocol is designed to increase the driving safety, to prevent accidents and to utilize channels efficiently by adjusting the control and service channel time intervals dynamically. Besides, our protocol can transmit information to vehicles in advance, so that drivers can decide an alternate route in case of traffic congestion. For various data sharing, we design a method that can select a few leader nodes among vehicles running along a highway to broadcast data efficiently. Simulation results show that our protocol can outperform the existing standard in terms of the end to end packet delivery ratio and latency. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Performance Improvement in Geographic Routing for Vehicular Ad Hoc Networks
Sensors 2014, 14(12), 22342-22371; doi:10.3390/s141222342
Received: 24 September 2014 / Revised: 19 November 2014 / Accepted: 20 November 2014 / Published: 25 November 2014
Cited by 12 | PDF Full-text (6434 KB) | HTML Full-text | XML Full-text
Abstract
Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing [...] Read more.
Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing the forwarding region towards destination to select the Next Hop Vehicles (NHV). Most of these protocols suffer from the problem of elevated one-hop link disconnection, high end-to-end delay and low throughput even at normal vehicle speed in high vehicle density environment. This paper proposes a Geographic Distance Routing protocol based on Segment vehicle, Link quality and Degree of connectivity (SLD-GEDIR). The protocol selects a reliable NHV using the criteria segment vehicles, one-hop link quality and degree of connectivity. The proposed protocol has been simulated in NS-2 and its performance has been compared with the state-of-the-art protocols: P-GEDIR, J-GEDIR and V-GEDIR. The empirical results clearly reveal that SLD-GEDIR has lower link disconnection and end-to-end delay, and higher throughput as compared to the state-of-the-art protocols. It should be noted that the performance of the proposed protocol is preserved irrespective of vehicle density and speed. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle A System for Traffic Violation Detection
Sensors 2014, 14(11), 22113-22127; doi:10.3390/s141122113
Received: 10 June 2014 / Revised: 28 October 2014 / Accepted: 13 November 2014 / Published: 24 November 2014
Cited by 1 | PDF Full-text (663 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes the framework and components of an experimental platform for an advanced driver assistance system (ADAS) aimed at providing drivers with a feedback about traffic violations they have committed during their driving. The system is able to detect some specific [...] Read more.
This paper describes the framework and components of an experimental platform for an advanced driver assistance system (ADAS) aimed at providing drivers with a feedback about traffic violations they have committed during their driving. The system is able to detect some specific traffic violations, record data associated to these faults in a local data-base, and also allow visualization of the spatial and temporal information of these traffic violations in a geographical map using the standard Google Earth tool. The test-bed is mainly composed of two parts: a computer vision subsystem for traffic sign detection and recognition which operates during both day and nighttime, and an event data recorder (EDR) for recording data related to some specific traffic violations. The paper covers firstly the description of the hardware architecture and then presents the policies used for handling traffic violations. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Sampling-Based Real-Time Motion Planning under State Uncertainty for Autonomous Micro-Aerial Vehicles in GPS-Denied Environments
Sensors 2014, 14(11), 21791-21825; doi:10.3390/s141121791
Received: 31 July 2014 / Revised: 26 October 2014 / Accepted: 3 November 2014 / Published: 18 November 2014
Cited by 1 | PDF Full-text (6232 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete [...] Read more.
This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Using Floating Car Data to Analyse the Effects of ITS Measures and Eco-Driving
Sensors 2014, 14(11), 21358-21374; doi:10.3390/s141121358
Received: 22 September 2014 / Revised: 1 November 2014 / Accepted: 3 November 2014 / Published: 11 November 2014
Cited by 1 | PDF Full-text (1145 KB) | HTML Full-text | XML Full-text
Abstract
The road transportation sector is responsible for around 25% of total man-made CO2 emissions worldwide. Considerable efforts are therefore underway to reduce these emissions using several approaches, including improved vehicle technologies, traffic management and changing driving behaviour. Detailed traffic and emissions [...] Read more.
The road transportation sector is responsible for around 25% of total man-made CO2 emissions worldwide. Considerable efforts are therefore underway to reduce these emissions using several approaches, including improved vehicle technologies, traffic management and changing driving behaviour. Detailed traffic and emissions models are used extensively to assess the potential effects of these measures. However, if the input and calibration data are not sufficiently detailed there is an inherent risk that the results may be inaccurate. This article presents the use of Floating Car Data to derive useful speed and acceleration values in the process of traffic model calibration as a means of ensuring more accurate results when simulating the effects of particular measures. The data acquired includes instantaneous GPS coordinates to track and select the itineraries, and speed and engine performance extracted directly from the on-board diagnostics system. Once the data is processed, the variations in several calibration parameters can be analyzed by comparing the base case model with the measure application scenarios. Depending on the measure, the results show changes of up to 6.4% in maximum speed values, and reductions of nearly 15% in acceleration and braking levels, especially when eco-driving is applied. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Using Smart Phone Sensors to Detect Transportation Modes
Sensors 2014, 14(11), 20843-20865; doi:10.3390/s141120843
Received: 14 May 2014 / Revised: 25 September 2014 / Accepted: 23 October 2014 / Published: 4 November 2014
Cited by 4 | PDF Full-text (1194 KB) | HTML Full-text | XML Full-text
Abstract
The proliferation of mobile smart devices has led to a rapid increase of location-based services, many of which are amassing large datasets of user trajectory information. Unfortunately, current trajectory information is not yet sufficiently rich to support classification of user transportation modes. [...] Read more.
The proliferation of mobile smart devices has led to a rapid increase of location-based services, many of which are amassing large datasets of user trajectory information. Unfortunately, current trajectory information is not yet sufficiently rich to support classification of user transportation modes. In this paper, we propose a method that employs both the Global Positioning System and accelerometer data from smart devices to classify user outdoor transportation modes. The classified modes include walking, bicycling, and motorized transport, in addition to the motionless (stationary) state, for which we provide new depth analysis. In our classification, stationary mode has two sub-modes: stay (remaining in the same place for a prolonged time period; e.g., in a parked vehicle) and wait (remaining at a location for a short period; e.g., waiting at a red traffic light). These two sub-modes present different semantics for data mining applications. We use support vector machines with parameters that are optimized for pattern recognition. In addition, we employ ant colony optimization to reduce the dimension of features and analyze their relative importance. The resulting classification system achieves an accuracy rate of 96.31% when applied to a dataset obtained from 18 mobile users. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Robust Object Segmentation Using a Multi-Layer Laser Scanner
Sensors 2014, 14(11), 20400-20418; doi:10.3390/s141120400
Received: 14 September 2014 / Revised: 21 October 2014 / Accepted: 21 October 2014 / Published: 29 October 2014
Cited by 2 | PDF Full-text (4042 KB) | HTML Full-text | XML Full-text
Abstract
The major problem in an advanced driver assistance system (ADAS) is the proper use of sensor measurements and recognition of the surrounding environment. To this end, there are several types of sensors to consider, one of which is the laser scanner. In [...] Read more.
The major problem in an advanced driver assistance system (ADAS) is the proper use of sensor measurements and recognition of the surrounding environment. To this end, there are several types of sensors to consider, one of which is the laser scanner. In this paper, we propose a method to segment the measurement of the surrounding environment as obtained by a multi-layer laser scanner. In the segmentation, a full set of measurements is decomposed into several segments, each representing a single object. Sometimes a ghost is detected due to the ground or fog, and the ghost has to be eliminated to ensure the stability of the system. The proposed method is implemented on a real vehicle, and its performance is tested in a real-world environment. The experiments show that the proposed method demonstrates good performance in many real-life situations. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle A Modular Localization System as a Positioning Service for Road Transport
Sensors 2014, 14(11), 20274-20296; doi:10.3390/s141120274
Received: 11 September 2014 / Revised: 6 October 2014 / Accepted: 14 October 2014 / Published: 28 October 2014
Cited by 5 | PDF Full-text (2792 KB) | HTML Full-text | XML Full-text
Abstract
In recent times smart devices have attracted a large number of users. Since many of these devices allow position estimation using Global Navigation Satellite Systems (GNSS) signals, a large number of location-based applications and services have emerged, especially in transport systems. However [...] Read more.
In recent times smart devices have attracted a large number of users. Since many of these devices allow position estimation using Global Navigation Satellite Systems (GNSS) signals, a large number of location-based applications and services have emerged, especially in transport systems. However GNSS signals are affected by the environment and are not always present, especially in dense urban environment or indoors. In this work firstly a Modular Localization Algorithm is proposed to allow seamless switching between different positioning modules. This helps us develop a positioning system that is able to provide position estimates in both indoor and outdoor environments without any user interaction. Since the proposed system can run as a service on any smart device, it could allow users to navigate not only in outdoor environments, but also indoors, e.g., underground garages, tunnels etc. Secondly we present the proposal of a 2-phase map reduction algorithm which allows one to significantly reduce the complexity of position estimation processes in case that positioning is performed using a fingerprinting framework. The proposed 2-phase map reduction algorithm can also improve the accuracy of the position estimates by filtering out reference points that are far from the mobile device. Both algorithms were implemented into a positioning system and tested in real world conditions in both indoor and outdoor environments. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Videosensor for the Detection of Unsafe Driving Behavior in the Proximity of Black Spots
Sensors 2014, 14(11), 19926-19944; doi:10.3390/s141119926
Received: 26 June 2014 / Revised: 30 September 2014 / Accepted: 30 September 2014 / Published: 24 October 2014
Cited by 2 | PDF Full-text (2237 KB) | HTML Full-text | XML Full-text
Abstract
This paper discusses the overall design and implementation of a video sensor for the detection of risky behaviors of car drivers near previously identified and georeferenced black spots. The main goal is to provide the driver with a visual audio alert that [...] Read more.
This paper discusses the overall design and implementation of a video sensor for the detection of risky behaviors of car drivers near previously identified and georeferenced black spots. The main goal is to provide the driver with a visual audio alert that informs of the proximity of an area of high incidence of highway accidents only if their driving behavior could result in a risky situation. It proposes a video sensor for detecting and supervising driver behavior, its main objective being manual distractions, so hand driver supervision is performed. A GPS signal is also considered, the GPS information is compared with a database of global positioning Black Spots to determine the relative proximity of a risky area. The outputs of the video sensor and GPS sensor are combined to evaluate a possible risky behavior. The results are promising in terms of risk analysis in order to be validated for use in the context of the automotive industry as future work. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle High-Precision Image Aided Inertial Navigation with Known Features: Observability Analysis and Performance Evaluation
Sensors 2014, 14(10), 19371-19401; doi:10.3390/s141019371
Received: 11 July 2014 / Revised: 19 September 2014 / Accepted: 9 October 2014 / Published: 17 October 2014
Cited by 2 | PDF Full-text (3174 KB) | HTML Full-text | XML Full-text
Abstract
A high-precision image-aided inertial navigation system (INS) is proposed as an alternative to the carrier-phase-based differential Global Navigation Satellite Systems (CDGNSSs) when satellite-based navigation systems are unavailable. In this paper, the image/INS integrated algorithm is modeled by a tightly-coupled iterative extended Kalman [...] Read more.
A high-precision image-aided inertial navigation system (INS) is proposed as an alternative to the carrier-phase-based differential Global Navigation Satellite Systems (CDGNSSs) when satellite-based navigation systems are unavailable. In this paper, the image/INS integrated algorithm is modeled by a tightly-coupled iterative extended Kalman filter (IEKF). Tightly-coupled integration ensures that the integrated system is reliable, even if few known feature points (i.e., less than three) are observed in the images. A new global observability analysis of this tightly-coupled integration is presented to guarantee that the system is observable under the necessary conditions. The analysis conclusions were verified by simulations and field tests. The field tests also indicate that high-precision position (centimeter-level) and attitude (half-degree-level)-integrated solutions can be achieved in a global reference. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Motion Field Estimation for a Dynamic Scene Using a 3D LiDAR
Sensors 2014, 14(9), 16672-16691; doi:10.3390/s140916672
Received: 16 July 2014 / Revised: 26 August 2014 / Accepted: 3 September 2014 / Published: 9 September 2014
Cited by 3 | PDF Full-text (1110 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of [...] Read more.
This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Sequential and Automatic Image-Sequence Registration of Road Areas Monitored from a Hovering Helicopter
Sensors 2014, 14(9), 16630-16650; doi:10.3390/s140916630
Received: 22 June 2014 / Revised: 14 August 2014 / Accepted: 1 September 2014 / Published: 5 September 2014
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Abstract
In this paper, we propose an automatic and sequential method for the registration of an image sequence of a road area without ignoring scene-induced motion. This method contributes to a larger work, aiming at vehicle tracking. A typical image sequence is recorded [...] Read more.
In this paper, we propose an automatic and sequential method for the registration of an image sequence of a road area without ignoring scene-induced motion. This method contributes to a larger work, aiming at vehicle tracking. A typical image sequence is recorded from a helicopter hovering above the freeway. The demand for automation is inevitable due to the large number of images and continuous changes in the traffic situation and weather conditions. A framework is designed and implemented for this purpose. The registration errors are removed in a sequential way based on two homography assumptions. First, an approximate registration is obtained, which is efficiently refined in a second step, using a restricted search area. The results of the stabilization framework are demonstrated on an image sequence consisting of 1500 images and show that our method allows a registration between arbitrary images in the sequence with a geometric error of zero in pixel accuracy. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments
Sensors 2014, 14(9), 16159-16180; doi:10.3390/s140916159
Received: 23 July 2014 / Revised: 24 August 2014 / Accepted: 26 August 2014 / Published: 1 September 2014
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Abstract
This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, [...] Read more.
This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC) scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
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Open AccessArticle Investigation of Matlab® as Platform in Navigation and Control of an Automatic Guided Vehicle Utilising an Omnivision Sensor
Sensors 2014, 14(9), 15669-15686; doi:10.3390/s140915669
Received: 20 June 2014 / Revised: 11 August 2014 / Accepted: 13 August 2014 / Published: 25 August 2014
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Abstract
Automatic Guided Vehicles (AGVs) are navigated utilising multiple types of sensors for detecting the environment. In this investigation such sensors are replaced and/or minimized by the use of a single omnidirectional camera picture stream. An area of interest is extracted, and by [...] Read more.
Automatic Guided Vehicles (AGVs) are navigated utilising multiple types of sensors for detecting the environment. In this investigation such sensors are replaced and/or minimized by the use of a single omnidirectional camera picture stream. An area of interest is extracted, and by using image processing the vehicle is navigated on a set path. Reconfigurability is added to the route layout by signs incorporated in the navigation process. The result is the possible manipulation of a number of AGVs, each on its own designated colour-signed path. This route is reconfigurable by the operator with no programming alteration or intervention. A low resolution camera and a Matlab® software development platform are utilised. The use of Matlab® lends itself to speedy evaluation and implementation of image processing options on the AGV, but its functioning in such an environment needs to be assessed. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle A Kalman Filter-Based Short Baseline RTK Algorithm for Single-Frequency Combination of GPS and BDS
Sensors 2014, 14(8), 15415-15433; doi:10.3390/s140815415
Received: 25 June 2014 / Revised: 11 August 2014 / Accepted: 13 August 2014 / Published: 20 August 2014
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Abstract
The emerging Global Navigation Satellite Systems (GNSS) including the BeiDou Navigation Satellite System (BDS) offer more visible satellites for positioning users. To employ those new satellites in a real-time kinematic (RTK) algorithm to enhance positioning precision and availability, a data processing model [...] Read more.
The emerging Global Navigation Satellite Systems (GNSS) including the BeiDou Navigation Satellite System (BDS) offer more visible satellites for positioning users. To employ those new satellites in a real-time kinematic (RTK) algorithm to enhance positioning precision and availability, a data processing model for the dual constellation of GPS and BDS is proposed and analyzed. A Kalman filter-based algorithm is developed to estimate the float ambiguities for short baseline scenarios. The entire work process of the high-precision algorithm based on the proposed model is deeply investigated in detail. The model is validated with real GPS and BDS data recorded from one zero and two short baseline experiments. Results show that the proposed algorithm can generate fixed baseline output with the same precision level as that of either a single GPS or BDS RTK algorithm. The significantly improved fixed rate and time to first fix of the proposed method demonstrates a better availability and effectiveness on processing multi-GNSSs. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Preceding Vehicle Detection and Tracking Adaptive to Illumination Variation in Night Traffic Scenes Based on Relevance Analysis
Sensors 2014, 14(8), 15325-15347; doi:10.3390/s140815325
Received: 29 May 2014 / Revised: 14 July 2014 / Accepted: 12 August 2014 / Published: 19 August 2014
Cited by 4 | PDF Full-text (765 KB) | HTML Full-text | XML Full-text
Abstract
Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking [...] Read more.
Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Analysis of Vehicle Detection with WSN-Based Ultrasonic Sensors
Sensors 2014, 14(8), 14050-14069; doi:10.3390/s140814050
Received: 11 June 2014 / Revised: 22 July 2014 / Accepted: 24 July 2014 / Published: 4 August 2014
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Abstract
Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the [...] Read more.
Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, we model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of our algorithm does not compromise the accuracy of vehicle detection. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Who Sits Where? Infrastructure-Free In-Vehicle Cooperative Positioning via Smartphones
Sensors 2014, 14(7), 11605-11628; doi:10.3390/s140711605
Received: 5 May 2014 / Revised: 19 June 2014 / Accepted: 19 June 2014 / Published: 30 June 2014
Cited by 2 | PDF Full-text (1941 KB) | HTML Full-text | XML Full-text
Abstract
Seat-level positioning of a smartphone in a vehicle can provide a fine-grained context for many interesting in-vehicle applications, including driver distraction prevention, driving behavior estimation, in-vehicle services customization, etc. However, most of the existing work on in-vehicle positioning relies on special infrastructures, [...] Read more.
Seat-level positioning of a smartphone in a vehicle can provide a fine-grained context for many interesting in-vehicle applications, including driver distraction prevention, driving behavior estimation, in-vehicle services customization, etc. However, most of the existing work on in-vehicle positioning relies on special infrastructures, such as the stereo, cigarette lighter adapter or OBD (on-board diagnostic) adapter. In this work, we propose iLoc, an infrastructure-free, in-vehicle, cooperative positioning system via smartphones. iLoc does not require any extra devices and uses only embedded sensors in smartphones to determine the phones’ seat-level locations in a car. In iLoc, in-vehicle smartphones automatically collect data during certain kinds of events and cooperatively determine the relative left/right and front/back locations. In addition, iLoc is tolerant to noisy data and possible sensor errors. We evaluate the performance of iLoc using experiments conducted in real driving scenarios. Results show that the positioning accuracy can reach 90% in the majority of cases and around 70% even in the worst-cases. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Occupancy Grid Mapping in Urban Environments from a Moving On-Board Stereo-Vision System
Sensors 2014, 14(6), 10454-10478; doi:10.3390/s140610454
Received: 16 February 2014 / Revised: 30 May 2014 / Accepted: 9 June 2014 / Published: 13 June 2014
Cited by 5 | PDF Full-text (10669 KB) | HTML Full-text | XML Full-text
Abstract
Occupancy grid map is a popular tool for representing the surrounding environments of mobile robots/intelligent vehicles. Its applications can be dated back to the 1980s, when researchers utilized sonar or LiDAR to illustrate environments by occupancy grids. However, in the literature, research [...] Read more.
Occupancy grid map is a popular tool for representing the surrounding environments of mobile robots/intelligent vehicles. Its applications can be dated back to the 1980s, when researchers utilized sonar or LiDAR to illustrate environments by occupancy grids. However, in the literature, research on vision-based occupancy grid mapping is scant. Furthermore, when moving in a real dynamic world, traditional occupancy grid mapping is required not only with the ability to detect occupied areas, but also with the capability to understand dynamic environments. The paper addresses this issue by presenting a stereo-vision-based framework to create a dynamic occupancy grid map, which is applied in an intelligent vehicle driving in an urban scenario. Besides representing the surroundings as occupancy grids, dynamic occupancy grid mapping could provide the motion information of the grids. The proposed framework consists of two components. The first is motion estimation for the moving vehicle itself and independent moving objects. The second is dynamic occupancy grid mapping, which is based on the estimated motion information and the dense disparity map. The main benefit of the proposed framework is the ability of mapping occupied areas and moving objects at the same time. This is very practical in real applications. The proposed method is evaluated using real data acquired by our intelligent vehicle platform “SeTCar” in urban environments. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
Open AccessArticle Augmented GNSS Differential Corrections Minimum Mean Square Error Estimation Sensitivity to Spatial Correlation Modeling Errors
Sensors 2014, 14(6), 10258-10272; doi:10.3390/s140610258
Received: 17 April 2014 / Revised: 4 June 2014 / Accepted: 5 June 2014 / Published: 11 June 2014
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Abstract
Railway signaling is a safety system that has evolved over the last couple of centuries towards autonomous functionality. Recently, great effort is being devoted in this field, towards the use and exploitation of Global Navigation Satellite System (GNSS) signals and GNSS augmentation [...] Read more.
Railway signaling is a safety system that has evolved over the last couple of centuries towards autonomous functionality. Recently, great effort is being devoted in this field, towards the use and exploitation of Global Navigation Satellite System (GNSS) signals and GNSS augmentation systems in view of lower railway track equipments and maintenance costs, that is a priority to sustain the investments for modernizing the local and regional lines most of which lack automatic train protection systems and are still manually operated. The objective of this paper is to assess the sensitivity of the Linear Minimum Mean Square Error (LMMSE) algorithm to modeling errors in the spatial correlation function that characterizes true pseudorange Differential Corrections (DCs). This study is inspired by the railway application; however, it applies to all transportation systems, including the road sector, that need to be complemented by an augmentation system in order to deliver accurate and reliable positioning with integrity specifications. A vector of noisy pseudorange DC measurements are simulated, assuming a Gauss-Markov model with a decay rate parameter inversely proportional to the correlation distance that exists between two points of a certain environment. The LMMSE algorithm is applied on this vector to estimate the true DC, and the estimation error is compared to the noise added during simulation. The results show that for large enough correlation distance to Reference Stations (RSs) distance separation ratio values, the LMMSE brings considerable advantage in terms of estimation error accuracy and precision. Conversely, the LMMSE algorithm may deteriorate the quality of the DC measurements whenever the ratio falls below a certain threshold. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
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Open AccessArticle Sensor Systems for Vehicle Environment Perception in a Highway Intelligent Space System
Sensors 2014, 14(5), 8513-8527; doi:10.3390/s140508513
Received: 22 March 2014 / Revised: 6 May 2014 / Accepted: 9 May 2014 / Published: 15 May 2014
Cited by 1 | PDF Full-text (591 KB) | HTML Full-text | XML Full-text
Abstract
A Highway Intelligent Space System (HISS) is proposed to study vehicle environment perception in this paper. The nature of HISS is that a space sensors system using laser, ultrasonic or radar sensors are installed in a highway environment and communication technology is [...] Read more.
A Highway Intelligent Space System (HISS) is proposed to study vehicle environment perception in this paper. The nature of HISS is that a space sensors system using laser, ultrasonic or radar sensors are installed in a highway environment and communication technology is used to realize the information exchange between the HISS server and vehicles, which provides vehicles with the surrounding road information. Considering the high-speed feature of vehicles on highways, when vehicles will be passing a road ahead that is prone to accidents, the vehicle driving state should be predicted to ensure drivers have road environment perception information in advance, thereby ensuring vehicle driving safety and stability. In order to verify the accuracy and feasibility of the HISS, a traditional vehicle-mounted sensor system for environment perception is used to obtain the relative driving state. Furthermore, an inter-vehicle dynamics model is built and model predictive control approach is used to predict the driving state in the following period. Finally, the simulation results shows that using the HISS for environment perception can arrive at the same results detected by a traditional vehicle-mounted sensors system. Meanwhile, we can further draw the conclusion that using HISS to realize vehicle environment perception can ensure system stability, thereby demonstrating the method’s feasibility. Full article
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)

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