
显示样式: 排序: IF: - GO 导出
-
Itineraries evaluated and ranked using fuzzy logic J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-03-03 Lizhi Wang; Vassilissa Lehoux; Marie-Laure Espinouse; Van-Dat Cung
Abstract In nowadays transportation networks, many multimodal itineraries are possible when traveling from an origin to a destination. Due to the plurality of alternatives, the choice of an option is difficult for the user. In this paper, we propose a novel decision support system to help users in that task. Our method ranks itineraries according to users’ preferences and trip profile based on a fuzzy
-
Estimating cycle-level real-time traffic movements at signalized intersections J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-02-23 Nada Mahmoud; Mohamed Abdel-Aty; Qing Cai; Jinghui Yuan
Abstract Real-time traffic movements at intersections is vital for transportation and traffic engineering. It helps in providing intersection traffic data and optimizing signal control plans. This study attempts to extend the data coverage by developing algorithms to estimate through and left-turn movements in real-time at signalized intersections. This study is the first attempt to estimate short-term
-
An integrated modeling framework for active traffic management and its applications in the Washington, DC area J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-02-21 Chenfeng Xiong; Xianfeng Terry Yang; Lei Zhang; Minha Lee; Weiyi Zhou; Mohammed Raqib
Abstract Developing appropriate modeling and simulation tools with the capability of analyzing traffic patterns, travel demand, and traveling/driving behavior responses at the regional level is important for the evaluation of active traffic management (ATM) and real-time transportation systems management and operations (TSM&O). In this paper, an integrated travel behavior and dynamic traffic assignment
-
Safety impacts and benefits of connected and automated vehicles: How real are they? J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-02-01 C. Y. David Yang; Donald L. Fisher
(2021). Safety impacts and benefits of connected and automated vehicles: How real are they? Journal of Intelligent Transportation Systems: Vol. 25, No. 2, pp. 135-138.
-
Estimation of lane-level travel time distributions under a connected environment J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-02-03 Lili Lu; Zhengbing He; Jian Wang; Jufeng Chen; Wei Wang
Abstract Travel time distribution estimation is fundamentally important for the evaluation of travel time variability and reliability. For urban roads, signal delays are key components of travel time. They are stochastic and differ for vehicular movements due to different signal timings for through, left-turning, and right-turning vehicles. To better assist travelers in making trip decisions under
-
Metaheuristic approach for designing robust traffic signal timings to effectively serve varying traffic demand J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-02-03 Chaitrali Shirke; Nasser Sabar; Edward Chung; Ashish Bhaskar
Abstract Traffic demands at intersections vary across various periods of a day and from day to day. Generally, fixed time traffic signals are designed considering the average traffic flows across multiple days over a predetermined time interval. This approach overlooks the day to day variability in traffic demand, leading to inefficient and unreliable signal control performance. A signal plan should
-
Correction J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-01-31
(2021). Correction. Journal of Intelligent Transportation Systems. Ahead of Print.
-
Smartphone-based parking guidance algorithm and implementation J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-01-19 Hongyan Gao; Qian Yun; Rundong Ran; Jun Ma
Abstract To alleviate parking problem and offer convenient and efficient service for drivers in parking selection, a smartphone-based parking guidance algorithm and system implementation architecture are proposed. The algorithm describes parking selection as multi-criteria decision making. Dijkstra algorithm is used to suggest the shortest path for the candidate parking lots. Travel cost criteria for
-
Passenger satisfaction evaluation of public transport using alternative queuing method under hesitant linguistic environment J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-01-19 Qiang Li; Ran Liu; Jianshen Zhao; Hu-Chen Liu
Abstract Nowadays, public transport is considered as an alternative to private vehicles to reduce environmental and social problems in developing countries. Hence, assuring a high passenger satisfaction level in the public transport system is an important task for municipalities and governments. However, passenger satisfaction evaluation of public transport is difficult as the opinions of passengers
-
An analytical approach to real-time bus signal priority system for isolated intersections J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-01-19 Bilal Thonnam Thodi; Bhargava Rama Chilukuri; Lelitha Vanajakshi
Abstract Bus signal priority (BSP) is an active traffic management measure to reduce bus travel delay at signalized intersections and to improve the bus service reliability. In this paper, we present a real-time BSP system with a primary focus on its practical implementation. We tackle two inter-related issues of existing priority systems, namely, real-time computation and solution optimality, using
-
A computer vision algorithm for locating and recognizing traffic signal control light status and countdown time J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2021-01-14 Xiaofeng Chen; Yu Chen; Guohui Zhang
Abstract It is of practical importance for individual vehicles to automatically identify traffic signal light status to facilitate their decision makings for traffic safety performance enhancement and operation efficiency maximization when they are approaching intersections, especially in near-future fully-or semi-autonomous vehicle-penetrated traffic systems. Traditional methods aim to directly extract
-
Machine learning techniques to predict reactionary delays and other associated key performance indicators on British railway network J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-12-31 Panukorn Taleongpong; Simon Hu; Zhoutong Jiang; Chao Wu; Sunday Popo-Ola; Ke Han
Abstract Reactionary delays that propagate from a primary source throughout train journeys are an immediate concern for British railway systems. Complex non-linear interactions between various spatiotemporal variables govern the propagation of these delays which can avalanche throughout railway network causing further severe disruptions. This paper introduces several machine learning (ML) techniques
-
Worst-case scenarios identification approach for the evaluation of advanced driver assistance systems in intelligent/autonomous vehicles under multiple conditions J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-12-21 Nacer Eddine Chelbi; Denis Gingras; Claude Sauvageau
Abstract To demonstrate the expected performance of an advanced driver assistance system (ADAS) in an intelligent or a highly automated vehicle test approaches should include a combination of simulations, track tests, and road tests. The main objective of our work was to propose a new evaluation approach conducted by an external entity where the vehicle is treated as a black box. This approach allowed
-
Reinforcement learning-enabled genetic algorithm for school bus scheduling J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-12-08 Eda Köksal Ahmed; Zengxiang Li; Bharadwaj Veeravalli; Shen Ren
Abstract In this paper, we focus on a bi-objective school bus scheduling optimization problem, which is a subset of vehicle fleet scheduling problems to transport students distributed across a designated area to the relevant schools. The problem being proven as NP-hard in the literature, we propose an algorithm that seamlessly integrates a reinforcement learning approach with a genetic algorithm. Our
-
Controlling passenger flow to mitigate the effects of platform overcrowding on train dwell time J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-12-07 Sunhyung Yoo; Hyun Kim; Wongil Kim; Namsun Kim; Jinwoo (Brian) Lee
Abstract This paper presents a cost-effective strategy to reduce train delays by controlling passenger flow at the station entry. When a scheduled dwell time delay is likely to occur, the strategy reduces the number of passengers entering the platform by slowing down the opening speed of the automated fare collection (AFC) gates. The dwell time of the next train is predicted to enable proactive passenger
-
Optimization model for regional green wave coordinated control based on ring-and-barrier structure J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-12-07 Kai Lu; Xin Tian; Shuyan Jiang; Jianmin Xu; Yinhai Wang
Abstract It’s often hard for existing mathematical models to unify and optimize all control variables including phase time, signal phase sequence, offset and signal cycle at the same time. An optimization model for regional green wave coordinated control based on Ring-and-Barrier structure under unsaturated signalized network is proposed in this study. The constraints of signal timing parameters, such
-
New England merge: a novel cooperative merge control method for improving highway work zone mobility and safety J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-09-23 Tianzhu Ren; Yuanchang Xie; Liming Jiang
Abstract Given the aging infrastructure and the anticipated growing number of highway work zones in the United States, it is important to investigate methods to improve work zone mobility and safety. Data suggests that inappropriate merge maneuvers are a major contributing factor to highway work zone crashes that often lead to severe congestion and delay. This research proposes a New England Merge
-
A queue length estimation and prediction model for long freeway off-ramps J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-11-17 Seiran Heshami; Lina Kattan
Abstract Real-time queue length estimation and prediction provides useful information for proactively managing transportation networks. Queue spillback from off-ramps onto main lanes of freeways is one of the traffic issues caused by vehicular queues that can be efficiently managed using dynamic queue information. In this paper, a case-based reasoning algorithm combined with a Kalman filter is developed
-
Driver’s black box: a system for driver risk assessment using machine learning and fuzzy logic J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-12-02 A. S. Yuksel; S. Atmaca
Abstract Risky driving behaviors can cause accidents, which may result in major material and moral damages. Due to the increase in road accidents, it has become an important issue to identify risky driving behaviors and reward people who drive safely. With the development of technology, it is now possible to model driving behavior through advanced sensors integrated into embedded systems. In this study
-
Identifying traffic conditions from non-traffic related sources J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-11-29 Jorge C. Chamby-Diaz; Rhuam Sena Estevam; Ana L. C. Bazzan
Abstract Mobile devices and Internet-based applications are producing a significant volume of data that may be used to, at least partially, replace some of the hardware necessary to sense traffic systems. However, there are several issues related to such an agenda: data are heterogeneous, unstructured, may appear in natural language, are normally not geolocated, and there are balancing issues related
-
Solving urban electric transit network problem by integrating Pareto artificial fish swarm algorithm and genetic algorithm J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-11-24 Yi Liu; Xuesong Feng; Yan Yang; Zejing Ruan; Lukai Zhang; Kemeng Li
Abstract This study presents a multi-objective optimization model for the urban electric transit network problem with the aim of simultaneously designing the layout of bus routes, the frequency and the location and size of charging stations by making a tradeoff between two inconsistent objectives from the perspectives of passengers and operators. A Pareto artificial fish swarm algorithm (PAFSA) embedded
-
Mapping of bus travel time to traffic stream travel time using econometric modeling J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-11-18 Sharmili Banik; Lelitha Vanajakshi; Darcy M. Bullock
Abstract Travel time is one of the most important traffic parameters for travelers, traffic managers, planners, and operators alike. Travel time estimation is a significant component of any intelligent transportation systems (ITS) operations. In countries like India, which are at a nascent stage of ITS deployment, one of the main hurdles is the lack of accurate and automated systems for travel time
-
A multistudy investigation of drivers and passengers’ gesture and voice input preferences for in-vehicle interactions J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-11-18 Laura-Bianca Bilius; Radu-Daniel Vatavu
Abstract We conduct an examination of the preferences of drivers and passengers alike for in-vehicle interactions with a multistudy approach consisting of (1) a targeted literature survey of applications and user interfaces designed to support interactions with in-vehicle controls and systems based on gesture and voice input; (2) a large-scale survey (N = 160 participants) to understand drivers and
-
The potential impacts of automated vehicles on pedestrian safety in a four-season country J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-11-12 R. Utriainen
Abstract Automated vehicles (AVs, level 4) are coming on the market in forthcoming years, but it is unsure what is the operational capability of these vehicles in the first place. Especially in four-season countries, winter conditions, such as snowfall and minor amount of daylight hours, increase the operational requirements of AVs. In this study, the potential impacts of AVs on pedestrian safety are
-
Traffic and granular flow: the role of data and technology in the understanding of particle dynamics J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-10-30 Samer Hamdar; Alireza Talebpour; Robert Bertini
(2020). Traffic and granular flow: the role of data and technology in the understanding of particle dynamics. Journal of Intelligent Transportation Systems: Vol. 24, Traffic and Granular Flow, pp. 535-538.
-
Safety evaluation of connected and automated vehicles in mixed traffic with conventional vehicles at intersections J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-10-28 Ramin Arvin; Asad J. Khattak; Mohsen Kamrani; Jackeline Rio-Torres
Abstract Connected and Automated Vehicles (CAVs) can potentially improve the performance of the transportation system by reducing human errors. This paper investigates the safety impact of CAVs in a mixed traffic with conventional vehicles at intersections. Analyzing real-world AV crashes in California revealed that rear-end crashes at intersections are the dominant crash type. Therefore, to enhance
-
Impact of lane keeping assist system camera misalignment on driver behavior J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-10-14 Richard Romano; Davide Maggi; Toshiya Hirose; Zara Broadhead; Oliver Carsten
Abstract This research investigated the impact of sensor camera misalignment on the quality of the lane keeping assistance, end user experience and driving performance. Testing was performed with 16 participants, both males and females, with an age range from 25 to 35. The Lane Keeping Assist System (LKAS) errors in lateral offset ranged from −0.66 m to 0.66 m and testing was performed on two roads
-
A motion planner enabling cooperative lane changing: Reducing congestion under partially connected and automated environment J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-09-24 Yu Bai; Yu Zhang; Jia Hu
A cooperative lane-changing (CLC) motion planning algorithm for partially connected and automated environment is proposed in this study. Unlike conventional motion planner whose goal is merely enabling driving maneuver, this proposed algorithm takes one step further in terms of reducing oscillation and shockwave caused by lane change, hence improves transport mobility. The proposed motion planner is
-
Assessing potential safety benefits of advanced pedestrian technologies through a Pedestrian Technology Test Bed J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-08-30 Mafruhatul Jannat; Stephanie M. Roldan; Stacy A. Balk; Karen Timpone
Abstract This research, funded by the United States Department of Transportation Federal Highway Administration, is one of the early initiatives to investigate the potential of advanced technologies to improve pedestrian safety through vehicle automation and user notification. The research identified the need to develop standardized strategies with which to investigate the effectiveness and applicability
-
Towards application of light detection and ranging sensor to traffic detection: an investigation of its built-in features and installation techniques J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-08-24 Junxuan Zhao; Hao Xu; Yuan Tian; Hongchao Liu
In transportation, LiDAR sensors have been primarily used in surveying and autonomous driving as a major onboard sensing device to detect field objects. Recently, with reduced price and increased demand from real-time and trajectory-level traffic detection, LiDAR technology sees great potential for becoming a mainstream means of infrastructure-based traffic detection other than only being used onboard
-
Correction J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-08-21
(2020). Correction. Journal of Intelligent Transportation Systems. Ahead of Print.
-
Model-free speed management for a heterogeneous platoon of connected ground vehicles J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-08-06 Yifan Weng; Rasoul Salehi; Xinyi Ge; Denise Rizzo; Matthew P. Castanier; Scott Heim; Tulga Ersal
Motivated by military applications, this work considers connected platoons of ground vehicles of potentially different sizes and presents a model-free approach for optimizing the speed of the platoon to adjust the tradeoff between fuel economy and mobility as measured by travel speed. The motivation to seek a model-free solution is twofold: (1) vehicle models that are typically assumed to be available
-
An alternative design for traffic intersections with work zones by using pre-signals J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-08-05 Jing Zhao; Kevin Kiptoo Kigen; Xiaomei Xia
The lane closures caused by the work zone at the approaches create a negative impact on the operational effectiveness of the signalized intersections. This paper presents an innovative design for intersections with work zones to improve the intersection’s practical capacity. In this design, the lanes in the leg with work zone can be used dynamically as approach and exit lanes during different periods
-
Crowd logistics: Understanding auction-based pricing and couriers’ strategies in crowdsourcing package delivery J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-08-04 Amit Rechavi; Eran Toch
The growth of electronic commerce generates significant demand for the delivery of personal goods. Crowdsourcing applications have the potential to create more flexible alternatives to existing package-delivery services. However, the success of these applications is strongly related to the strategies of the crowd couriers, which are not well-understood in the current literature. In this paper, we analyzed
-
Integrated mainline and ramp signal control for expressway on-ramp bottleneck with unequal lane-setting J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-07-30 Xiaoyun Chen; Tienan Li; Zian Ma; Jian Sun
Ramp metering is a major measure to reduce traffic congestion and prevent traffic breakdown at on-ramp bottlenecks. However, its efficiency is often limited by the excessive traffic demands on either the mainline or the on-ramp. Meanwhile, unequal lane-setting, in which the number of mainline lanes is more than on-ramp, is a common infrastructure setup in urban expressway system. In this paper, a novel
-
Analysis of global positioning system based bus travel time data and its use for advanced public transportation system applications J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-07-30 Abdhul Khadhir; B. Anil Kumar; Lelitha Devi Vanajakshi
Abstract The rapid advancements in sensor technologies has resulted in the increased use of Automatic Vehicle Location (AVL) systems for traffic data collection. Global Position System (GPS) sensors are the most commonly used AVL system, majorly because of it being a time-tested technology and being relatively cheap. Also, many of the transportation agencies have their vehicles equipped with GPS sensors
-
Feedback perimeter control with online estimation of maximum throughput for an incident-affected road network J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-07-27 Jiawen Wang; Xiaozheng He; Srinivas Peeta; Xiaoguang Yang
This study develops a feedback perimeter control strategy to maximize the throughput of an incident-affected network. The proposed perimeter control strategy is innovative in two aspects. First, the control variables, i.e., the inflow rates to the controlled subnetwork within the incident-affected network, are adjusted based on the online estimation of maximum network throughput that is updated dynamically
-
Geographical window based structural similarity index for origin-destination matrices comparison J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-07-22 Krishna N. S. Behara; Ashish Bhaskar; Edward Chung
Most traditional metrics compare origin-destination (OD) matrices based on the deviations of individual OD flows and often neglect OD matrix structural information within their formulations. Limited metrics exist in literature for the structural comparison of OD matrices. One such metric is mean structural similarity index (MSSIM) that computes statistics on groups of OD pairs defined by local sliding
-
Spatial-temporal traffic congestion identification and correlation extraction using floating car data J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-07-22 Yanyan Chen; Cong Chen; Qiong Wu; Jianming Ma; Guohui Zhang; John Milton
Traffic congestion induces significant economic loss each year, and identifying traffic congestion patterns is necessary for better traffic control and management. Floating car data (FCD) provides a cost-effective alternative for assessing traffic status and detecting congestion on a large scale. Recently, a new speed performance index (SPI) has been proposed to evaluate traffic status considering
-
Safety margins – a novel approach from risk homeostasis theory for evaluating the impact of advanced driver assistance systems on driving behavior in near-crash events J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-07-23 Nengchao Lyu; Zhicheng Duan; Changxi Ma; Chaozhong Wu
Abstract Whereas the development of ADAS seeks to improve driver’s overall performance with a particular focus on traffic safety improvement; with it comes the requirement and opportunity to objectively evaluate the effectiveness of the technology in improving safety and overall road traffic efficiency. This study evaluates the effectiveness of ADAS in improving driver’s risk perception in near-crash
-
Road surface friction prediction using long short-term memory neural network based on historical data J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-07-08 Ziyuan Pu; Chenglong Liu; Xianming Shi; Zhiyong Cui; Yinhai Wang
Road surface friction significantly impacts traffic safety and mobility. A precise road surface friction prediction model can help to alleviate the influence of inclement road conditions on traffic safety, Level of Service, traffic mobility, fuel efficiency, and sustained economic productivity. Laboratory-based methods were used in most previous studies related to road surface friction prediction model
-
A two-sided lateral gap continuum model and its numerical simulation for non-lane based heterogeneous traffic environment J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-06-10 Hari Krishna Gaddam; K. Ramachandra Rao
Abstract The objective of this study is to model the complex behavior of non-lane based heterogeneous traffic which is predominantly occupied by vehicles with varying physical and dynamical characteristics and their staggered car following behavior. This study proposes a new continuum model by considering the properties of two-sided lateral gap in a non-lane based heterogeneous traffic stream. The
-
A two-sided lateral gap continuum model and its numerical simulation for non-lane based heterogeneous traffic environment J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-06-10 Hari Krishna Gaddam; K. Ramachandra Rao
The objective of this study is to model the complex behavior of non-lane based heterogeneous traffic which is predominantly occupied by vehicles with varying physical and dynamical characteristics and their staggered car following behavior. This study proposes a new continuum model by considering the properties of two-sided lateral gap in a non-lane based heterogeneous traffic stream. The model is
-
A proof-of-concept field experiment on cooperative lane change maneuvers using a prototype connected automated vehicle testing platform J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-06-09 Kelli Raboy; Jiaqi Ma; Edward Leslie; Fang Zhou
Abstract Connected automation systems coordinate vehicle communications and automated vehicle control to improve transportation system mobility, safety, and sustainability. Real-world deployment of connected automated vehicle (CAV) applications and related traffic management technologies will require automation of all vehicle and traffic movements, including platooning, lane change, and merge maneuvers
-
Adaptive traffic signal control algorithms based on probe vehicle data J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-05-18 Fushi Lian; Bokui Chen; Kai Zhang; Lixin Miao; Jinchao Wu; Shichao Luan
Abstract In this paper, two new adaptive traffic signal control algorithms are proposed based on data from probe vehicles to realize the coordinated signal control of arterial roads. One is an iterative signal control algorithm, and the other is an optimized signal control algorithm. The proportion of vehicles in the nonstop group is selected as the indicator of the traffic state. The value for this
-
Special issue on dense surveillance systems for urban traffic J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-05-07 Gwanggil Jeon; Marco Anisetti; Yong Fang
(2020). Special issue on dense surveillance systems for urban traffic. Journal of Intelligent Transportation Systems: Vol. 24, Dense Surveillance Systems for Urban Traffic, pp. 217-220.
-
Fusion of weigh-in-motion and global positioning system data to estimate truck weight distributions at traffic count sites J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2019-09-05 Sarah Hernandez; Kyung (Kate) Hyun
Truck weight data is needed for a wide range of applications including but not limited to pavement design, weight enforcement, traffic monitoring, and freight transportation planning. Unfortunately, the low spatial resolution of weight sensors along the transportation network can limit these and other potential applications. The main contribution of this paper is a methodology to estimate gross vehicle
-
A dynamic optimization method for adaptive signal control in a connected vehicle environment J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2019-08-01 Zhihong Yao; Yangsheng Jiang; Bin Zhao; Xiaoling Luo; Bo Peng
In a connected vehicle environment, vehicle location, speed, and other traffic information are readily available; hence, such environments provide new data sources for traffic signal control optimization. Existing adaptive signal control systems based on fixed detectors cannot directly obtain vehicle location and speed information, and thus, cannot provide accurate information about real-time traffic
-
A new and efficient authentication scheme for vehicular ad hoc networks J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2019-07-04 Majid Bayat; Mostafa Barmshoory; S. Morteza Pournaghi; Majid Rahimi; Yaghoub Farjami; Mohammad Reza Aref
In the past decades, Vehicular Ad hoc Networks (VANETs) have been increasingly developed. Providing secure and efficient communication is essential in VANETs. One of most important challenges in the secure and efficient communications is proposing an appropriate authentication scheme. In this paper, we suggest an efficient and novel authentication scheme for VANETs. In the proposed scheme, vehicles
-
Operational performance evaluation of adaptive traffic control systems: A Bayesian modeling approach using real-world GPS and private sector PROBE data J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2019-05-20 Zulqarnain H. Khattak; Mark J. Magalotti; Michael D. Fontaine
This evaluation ascertained the operational impacts of the SUTRAC (Scalable Urban Traffic Control) Adaptive Signal Control Technology (ASCT) in an urban corridor consisting of 23 intersections in Pittsburgh, Pennsylvania. A combination of real-world GPS floating car runs and private sector probe data from INRIX was used to assess the impact of the ASCT. Data were collected with the ASCT active and
-
A vehicle routing model based on large-scale radio frequency identification data J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2019-04-23 Chengcheng Wang; Zhongzhi Xu; Ronghua Du; Haifeng Li; Pu Wang
The rapid development of sensing, computing, and wireless communication techniques has given rise to an increasing number and increasing availability of high-resolution data that record real-time traffic information. In this study, radio frequency identification (RFID) data collected in Nanjing (a major city in southern China) were used to estimate dynamic travel demands and develop an RFID data-based
-
Multi-step-ahead traffic speed forecasting using multi-output gradient boosting regression tree J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2019-03-18 Xingbin Zhan; Shuaichao Zhang; Wai Yuen Szeto; Xiqun (Michael) Chen
Short-term traffic speed forecasting is an important component of Intelligent Transportation Systems (ITS). Multi-step-ahead prediction can provide more information and predict the longer trend of traffic speed than single-step-ahead prediction. This paper presents a multi-step-ahead traffic speed prediction approach by improving the gradient boosting regression tree (GBRT). The traditional multiple
-
Long-term travel time prediction using gradient boosting J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2019-01-03 Che-Ming Chen; Chia-Ching Liang; Chih-Peng Chu
Reliable long-term travel time prediction would be effective support to traffic management, for example, traffic flow control or the pricing of tolls. Gradient boosting (GB) has been suggested as an excellent tool for short-term travel time prediction problems. This paper shows that GB with modifications can also work for long-term prediction. We introduce key variables, regarded as multiple factors
-
A decentralized model predictive traffic signal control method with fixed phase sequence for urban networks J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-04-15 Dongfang Ma; Jiawang Xiao; Xiaolong Ma
Traffic congestion has become a significant issue in urban road networks. There have been massive works about traffic signal optimization to improve the efficiency of traffic flow operation, and the so-called back-pressure control policy has proven to be excellent for oversaturated conditions. Most of the existing works with back-pressure are based on an adaptive phase sequence, and research with cyclic
-
Multi-view crowd congestion monitoring system based on an ensemble of convolutional neural network classifiers J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-04-13 Yan Li; Majid Sarvi; Kourosh Khoshelham; Milad Haghani
Multi-view video surveillance is a highly valuable tool to ensure the safety of the crowd in large public space. By utilizing complementary information captured by multiple cameras, the issue of limited views and occlusion in single views can be addressed to gain better insight into the whole monitored space. However, multi-view surveillance has been widely applied to microscopic crowd analysis, for
-
Convolutional neural network for recognizing highway traffic congestion J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-04-13 Hua Cui; Gege Yuan; Ni Liu; Mingyuan Xu; Huansheng Song
We investigates the performance of deep Convolutional Neural Network (CNN) for recognizing highway traffic congestion state in surveillance camera images. Different from the usual images in ImageNet, images generated by highway surveillance cameras usually have much more extensive range of perspective and thus larger area of background. Therefore the objective road and vehicles are not as prominent
-
A taxonomy of validation strategies to ensure the safe operation of highly automated vehicles J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-03-20 Felix Batsch; Stratis Kanarachos; Madeline Cheah; Roberto Ponticelli; Mike Blundell
Self-driving cars are on the horizon, making it necessary to consider safety assurance and homologation of these autonomously operating vehicles. In this study, we systematically review literature that proposes new methods for these areas. The available methods were categorized into a novel taxonomy, dividing them into the strategies of combinatorial testing, robustness testing and search-based testing
-
Driving with and without automation on the motorway – an observational study J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-03-13 András Várhelyi; Clemens Kaufmann; Carl Johnsson; Sverker Almqvist
Abstract User-related assessment of a level 3 automated driving system, providing functions such as lane- and distance-keeping, stop & go driving, lane change and overtaking, was carried out on a motorway in Germany with the aim to assess user-related issues of automated driving, i.e., behavior when driving with automation on motorways, user experiences, reactions and acceptance. Twenty-one persons
-
Methods for classification of truck trailers using side-fire light detection and ranging (LiDAR) Data J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-03-06 Olcay Sahin; Reza Vatani Nezafat; Mecit Cetin
Classification of vehicles into distinct groups is critical for a number of applications including freight and commodity flow modeling, pavement management and design, tolling, air quality monitoring, and intelligent transportation systems. The main goal of this paper is to demonstrate how data from Light Detection and Ranging (LiDAR) sensors could be leveraged to distinguish between specific types
-
Pore acceptance predictions of motorised Two-Wheelers during filtering at urban Mid-Block sections J. Intell. Transp. Syst. (IF 3.269) Pub Date : 2020-03-03 Sanhita Das; Akhilesh Kumar Maurya
Filtering of motorized two-wheelers (MTWs) is a common practice in dense urban heterogeneous traffic environments where they often tend to navigate through the available lateral spaces (commonly termed as ‘pore’ in the literature) described by the vehicles in-front. Considering the increased vulnerability of MTW riders in dense urban systems, proper evaluation and modeling of pore acceptance/rejection