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Abstract

Modern transportation systems optimize traffic flows in road networks by allowing intersection-level traffic controllers to communicate and synchronize. Typically they are distributed systems, with multiple nodes (intersections) communicating with each other in real time....Lead moreModern transportation systems optimize traffic flows in road networks by allowing intersection-level traffic controllers to communicate and synchronize. Typically they are distributed systems, with multiple nodes (intersections) communicating with each other in real time. This paper proposes a design process for traffic coordination systems using model driven engineering (MDE), a paradigm used to design complex embedded systems in automotive and aerospace. The approach combines a conventional micro-simulator (AIMSUN) with a state of the art control modelling tool (Simulink) following a model-view-controller approach. The MDE approach allows for both micro-simulation (on a PC) and emulation (using embedded controllers). Once the model is validated, automatic code generation can be used to generate the implementation of the system on embedded devices. As a case study, we designed a SCATS-inspired coordinated intersection control system. To our knowledge, the proposed approach is the first, fully automated approach for the design of complex ITS systems.

Abstract

Sags are freeway sections along which gradient changes significantly from downwards to upwards.Sags are often bottlenecks in freeway networks.
Capacity decreases due to changes in car-following behavior. We present a microscopic traffic flow model that describes drivin...Lead moreSags are freeway sections along which gradient changes significantly from downwards to upwards.Sags are often bottlenecks in freeway networks.
Capacity decreases due to changes in car-following behavior. We present a microscopic traffic flow model that describes driving behavior and traffic flow dynamics at sags. The model includes a new longitudinal driving behavior model that accounts for the fact that drivers generally have a limited ability to compensate for the negative effect that an increase in slope has on vehicle acceleration. The face-validity of the microscopic model is tested by means of a simulation study. The study site is a sag of the Tomei Expressway (near Tokyo). The simulation results are compared to empirical findings presented in the literature. We show that the model is capable of reproducing all the relevant phenomena that cause the formation of congestion at sags.

Abstract

When considering the extreme difficulty of estimating accident likelihood, the most important potentially soluble factor in the development of congestion management strategies is to identify the factors affecting non-recurrent congestion caused by accidents. Most of all t...Lead moreWhen considering the extreme difficulty of estimating accident likelihood, the most important potentially soluble factor in the development of congestion management strategies is to identify the factors affecting non-recurrent congestion caused by accidents. Most of all the identification of such factors is required as a basic information for the purpose of accident management strategies as well as for the purpose of congestion management strategies. The objective of this paper is to identify causal factors affecting non-recurrent congestion. To perform this objective, a case study to quantify non-recurrent congestion caused by accidents in terms of total delay is demonstrated by using a previously developed method based on historical inductance loop detector data from six major freeways in Orange County, California. From the case study results, potential factors contributing to non-recurrent congestion are identified by using a Cox model.

Abstract

Image-based object detection is a fundamental technique for advanced driving assistance systems. We show that two types of our object detection method run on our automotive image recognition LSI. The one detects obstacles using depth information obtained by a stereo camer...Lead moreImage-based object detection is a fundamental technique for advanced driving assistance systems. We show that two types of our object detection method run on our automotive image recognition LSI. The one detects obstacles using depth information obtained by a stereo camera system, and further recognizes pedestrians by pattern recognition using original image feature, CoHOG. The other uses a single camera to detect four types of objects simultaneously based on the CoHOG image feature.

Abstract

This paper describes a traffic control strategy that builds upon ideas of queue management. It uses inputs from traffic sensors to estimate lane-by-lane queue lengths and delays. It predicates decisions about switching from one stage (movement combination) to another on m...Lead moreThis paper describes a traffic control strategy that builds upon ideas of queue management. It uses inputs from traffic sensors to estimate lane-by-lane queue lengths and delays. It predicates decisions about switching from one stage (movement combination) to another on metrics like the average delay. It can work with either fully-dynamic staging or a pre-defined stage sequence. It can operate at an isolated intersection or in a network. It relies on intersection-based detectors and/or connected vehicle communications for its inputs. Both dynamic and static markers can be used to create coordination with or without a common cycle length. The paper describes the control strategy and illustrates its application in a hypothetical setting.

Abstract

This paper proposes a new logistic regression model to predict a vehicle's queue/platoon state based on data that can be collected from a single loop detector positioned at the stopline of signalised intersections. The study focuses on estimating the queue length at the e...Lead moreThis paper proposes a new logistic regression model to predict a vehicle's queue/platoon state based on data that can be collected from a single loop detector positioned at the stopline of signalised intersections. The study focuses on estimating the queue length at the end of each cycle by predicting whether a vehicle was queued or platooned prior to passing over the detector. Different model forms were explored using data from an enhanced NGSIM dataset. These data were filtered to mimic data from a stopline detector loop. The best six models from 13 resulted in an accuracy ranging from 74% to 89% of correctly predicting a discharging vehicle's queue/platoon state, during the preceding red phase. Combined with a logical filter to group sequential vehicles, it will enable a traffic controller to estimate the most likely queue length. The queue predictor model will form part of a new offset algorithm under development

Abstract

This research aims to develop a reliable density estimation method for signalized arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sink/source, CUPRITE is employ...Lead moreThis research aims to develop a reliable density estimation method for signalized arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sink/source, CUPRITE is employed for density estimation. The method, by utilizing probe vehicles' sample, reduces or cancels the counting inconsistencies when vehicles' conservation is not satisfied. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.

Abstract

Delay is an important measure widely used traffic engineering to measure the operational efficiency of traffic control systems as well as to optimize them. A reasonable number of literatures have claimed an increasing discharge rate observed at signalized intersections. T...Lead moreDelay is an important measure widely used traffic engineering to measure the operational efficiency of traffic control systems as well as to optimize them. A reasonable number of literatures have claimed an increasing discharge rate observed at signalized intersections. These results contradict with a widely accepted traditional concept of a constant saturation flow rate adopted in the most commonly used traffic signal design guidelines such as HCM (2010) and ARR 123 by Akcelik (1981). This paper proposes an empirical model incorporating an increasing queue discharge rate based on what observed in the field data collected from Auckland, New Zealand. The model is implemented to estimate delay at signalized intersections and then compared with the existing methods of delay estimation. The results revealed some prospects for this model to improve delay estimation at signalized intersections.

Abstract

Global Navigation Satellite System (GNSS) suffers from invisible problem and multiple-path problem of the signal in urban canyons. Many researches have been performed to exclude multiple-path signals to reduce the positioning errors. Among them, ideas become popular to co...Lead moreGlobal Navigation Satellite System (GNSS) suffers from invisible problem and multiple-path problem of the signal in urban canyons. Many researches have been performed to exclude multiple-path signals to reduce the positioning errors. Among them, ideas become popular to consider the geometry of the surrounding constructions in order to improve the evaluation of possible multiple-path signals. Although those related works were so successful, they require many satellites for the positioning after discarding the multiple-path signals. In this paper, an idea is proposed to make use of the multiple-path signals themselves for the positioning error correction. The algorithm evaluates the pseudoranges of the possible multiple-path signals by referring to the building geometry. The assumed position is estimated by using the pseudoranges, and evaluated by the likelihood of the possible error for the positioning. The proposed method was proved successful by the field experiments in the deep urban canyons in Tokyo.

Abstract

We conducted an experiment with 22 participants to investigate the effect of secondary task presentation style on driving-related performance. Participants performed a 1-D tracking task with a foot pedal while performing a secondary task (list monitoring) under 12 conditi...Lead moreWe conducted an experiment with 22 participants to investigate the effect of secondary task presentation style on driving-related performance. Participants performed a 1-D tracking task with a foot pedal while performing a secondary task (list monitoring) under 12 conditions using different presentation styles (sequential-audio; sequential-visual; simultaneous-visual), task complexity (the number of distractors), and time dependency (list length). In four additional conditions list length was changed based on performance, and modality was selectable. Primary task performance was better with audio presentation when the task was short and simple, but there was no advantage for audio presentation when the secondary task was longer and more complex. We also found that participants changed their modality preferences and selections depending on presentation style (sequential or simultaneous).

Abstract

We describe in this paper the recent results of experiments using the double articulation analyzer to analyze and predict the driving behavior data. Upon the observations by previous researches that the prediction of actual value of driving behavior is difficult, we focus...Lead moreWe describe in this paper the recent results of experiments using the double articulation analyzer to analyze and predict the driving behavior data. Upon the observations by previous researches that the prediction of actual value of driving behavior is difficult, we focus on predicting discrete symbols of driving behavior modeled probabilistically. Incorporating longer temporal context of driving behavior using unsupervised learning algorithm of variable order n-gram model which was developed in Natural Language Processing field and extending it, our proposed prediction method based on the assumption of the double articulation structure in driving behavior data has shown to be effective by the experiment using real driving data.

Abstract

According to the research on principle of mobile phone' signaling events, a travel route identification algorithm of subway passenger was proposed based on NORMAL LOCATION UPDATE of the passengers' mobile phone. Meanwhile, in order to mend travel route when the signaling ...Lead moreAccording to the research on principle of mobile phone' signaling events, a travel route identification algorithm of subway passenger was proposed based on NORMAL LOCATION UPDATE of the passengers' mobile phone. Meanwhile, in order to mend travel route when the signaling data was missed, a repair algorithm was also proposed based on the normal communication events, such as phone calling and called, message receiving and sending. Finally, two typical subway stations of Beijing subway system were selected to validate the travel route identification algorithm. The application result showed that the algorithm could identify the subway passenger travel route accurately with Mobile Phone Location Data.

Abstract

Based on mechanical energy measurement, theoretical model of train movement is established. Then Hamiltonian function jointly expressed by state variables, adjoint variables and control variables are put forward, which led to the acquisition of necessary condition of opti...Lead moreBased on mechanical energy measurement, theoretical model of train movement is established. Then Hamiltonian function jointly expressed by state variables, adjoint variables and control variables are put forward, which led to the acquisition of necessary condition of optimal control strategy. While train encounters with steep-gradient section, new creative functional is introduced accordingly. By pursuing its extreme value, we can define new simplified discriminant to judge local optimal control strategy. Further global optimal control strategy emerge with the obtain of the precise phase sequence and phase transformation position, which combined with the comprehension of practical train movement environment.

Abstract

A significant proportion of bus travel time is contributed by bus dwell time for passenger boarding and alighting. This paper reports an investigation conducted on approximation and short-term prediction of bus dwell time based on historical AVL data collected from select...Lead moreA significant proportion of bus travel time is contributed by bus dwell time for passenger boarding and alighting. This paper reports an investigation conducted on approximation and short-term prediction of bus dwell time based on historical AVL data collected from selected bus routes in Auckland, New Zealand. Three distribution functions were assessed to approximate the distribution of bus dwell time including normal, lognormal and Wakeby distribution functions. For the first time, Autoregressive Integrated Moving Average (ARIMA) a time series based method, is assessed to make a short-term prediction of bus dwell time. Wakeby distribution, which is also assessed for the first time for this purpose outperformed the most commonly used distribution function namely lognormal distribution to approximate the dwell time for both peak and off-peak periods while ARIMA performed reasonably well for a short-term prediction of the dwell time.

Abstract

Given their larger capacity, faster velocity and higher reliability, Mass Rapid Transit systems (MRT) is becoming the most important public transport mode in major cities globally. On one hand, a demand sensitive timetable can reduce both waiting time and crowdedness on t...Lead moreGiven their larger capacity, faster velocity and higher reliability, Mass Rapid Transit systems (MRT) is becoming the most important public transport mode in major cities globally. On one hand, a demand sensitive timetable can reduce both waiting time and crowdedness on trains for passengers. On the other hand, it will improve operation stability and hence reliability for transit operators as well. However, understanding and obtaining the dynamic demand patterns is difficult. With the help of smart card data, here we propose an optimization model to solve timetable scheduling problem by minimizing total waiting time.

Abstract

Ramp metering (RM) and variable speed limits (VSL) are two important ITS tools aimed at improving performance of motorway systems. The former is widely used all around the world to regulate on-ramp traffic while the latter is an emerging technology that can be deployed in...Lead moreRamp metering (RM) and variable speed limits (VSL) are two important ITS tools aimed at improving performance of motorway systems. The former is widely used all around the world to regulate on-ramp traffic while the latter is an emerging technology that can be deployed in the mainline immediately upstream side of on-ramps to create some merging space for entering traffic. This paper assesses the performance of two ramp metering algorithms namely ALINEA and HERO individually and in combination with VSL strategies for a critical bottleneck section of Auckland Motorway using AIMSUN micro-simulation. ALINEA is the most prominent local RM algorithm while HERO is a rule-based coordinated RM algorithm. The performance was evaluated based on two important performance indicators namely total time spent and Gini coefficient representing the efficiency and equity of the motorway system respectively. Results show a potential to improve the motorway performance using a combination of these tools.

Abstract

It is essential input of dynamic Origin-Destination (OD) for on-line traffic control, dynamic traffic-assignment simulation and management systems. Two kinds of dynamic OD estimation models have been presented and in-depth researched, which are assignment-based and non-as...Lead moreIt is essential input of dynamic Origin-Destination (OD) for on-line traffic control, dynamic traffic-assignment simulation and management systems. Two kinds of dynamic OD estimation models have been presented and in-depth researched, which are assignment-based and non-assignment-based approaches. However, estimation error of models will rapidly increase as scale of road networks expand. To deal with the above difficulty, the article puts forward a new idea to combine functions of geographic information system (GIS) freely to select network size for dynamic OD estimation, which decease the network size and the number of nodes thereby to improve estimated accuracy. Depending on multi-source information such as floating car data and section traffic volume, the proposed model employ the non-assignment-based approach. The model by combining dynamic traffic-assignment models will be embedded in advance traffic management system (ATMS) to equilibrium traffic flow, which have important use value and application prospect

Abstract

Drivers who make wrong-way entries onto motorways or other access-controlled highways pose a serious risk to the safety of other motorists and themselves. Wrong-way driving often leads to severe head-on crashes on motorways. Wrong-way crashes are relatively infrequent, bu...Lead moreDrivers who make wrong-way entries onto motorways or other access-controlled highways pose a serious risk to the safety of other motorists and themselves. Wrong-way driving often leads to severe head-on crashes on motorways. Wrong-way crashes are relatively infrequent, but they are more likely to cause serious injuries and fatalities compared to other types of motorway crashes. The characteristics of both wrong-way incidents and crashes that occurred on the whole motorway network in Japan are analyzed in this study with an emphasis on wrong-way crashes. The characteristics of several typical factors resulting in wrong-way crashes are briefly identified and then directions of countermeasures for each factor are suggested. Finally some applications of recent ITS technologies to prevent wrong-way driving are briefly introduced that have been successfully implemented on motorways in Japan.

Abstract

This paper proposes a connected vehicle (CV) based dynamic all-red extension (DARE) framework for adaptive signalized intersections to avoid potential crashes caused by red-light running (RLR) behaviors. The conceptual structure consists of three components, i.e. CVs, roa...Lead moreThis paper proposes a connected vehicle (CV) based dynamic all-red extension (DARE) framework for adaptive signalized intersections to avoid potential crashes caused by red-light running (RLR) behaviors. The conceptual structure consists of three components, i.e. CVs, road-side equipment (RSE), traffic control devices. Under the CV environment, vehicle trajectories and continuous vehicle running information could be obtained via vehicle-to-infrastructure and vehicle-to-vehicle communications. A mathematic model is built to predict the potential of RLR. As a comparison, the current approach of DARE at adaptive signalized intersections based on inductive loop detectors is presented as well. In the field experiments, vehicle trajectories collected by radar sensors were used to simulate the CV environment. Based on empirical measurements, results in terms of prediction rate, missing rate and false alarm rate show the merits of CV continuous trajectories in RLR prediction accuracy improvement, and thus to improve intersection safety.

Abstract

The license plate recognition (LPR) is one of the important research subjects in machine vision of ITS. To improve LPR accuracy under poor illumination conditions, a new algorithm including license plate detection, characters segmentation and characters recognition is pro...Lead moreThe license plate recognition (LPR) is one of the important research subjects in machine vision of ITS. To improve LPR accuracy under poor illumination conditions, a new algorithm including license plate detection, characters segmentation and characters recognition is proposed. In the license plate detection phase, adaboost algorithm using extended Haar-like feature is adopted to enhance detecting robustness. In the characters segmentation and
recognition phase, we employ multi-candidate segmentation method for adhering and broken characters. A probabilistic graphical model is proposed to integrate recognition results of neural network and the optimum solution is obtained by belief propagation. The experiments indicate that the system achieves 91% recognition rate under complex illumination.

Abstract

The collision avoidance system has a potential to reduce traffic accidents and expected to become widely used. From the driver's point of view, it is important to present a collision warning which does not disturb driver's concentration on driving. This paper describes th...Lead moreThe collision avoidance system has a potential to reduce traffic accidents and expected to become widely used. From the driver's point of view, it is important to present a collision warning which does not disturb driver's concentration on driving. This paper describes the effectiveness of the collision avoidance system which uses the information displayed in driver's peripheral vision in right turn at an intersection. In order to analyze the effectiveness of the peripheral vision information, we evaluated the collision avoidance ratio and the effect of over-trust behavior when the information was missed. The analysis was conducted through the driving simulator experiment and the numerical simulation by the Time Series Reliability Model, which is a driver-model the authors proposed. The result showed that the peripheral vision information is effective to avoid the collision and the over-trust behavior did not appear even when the information is missed.

Abstract

Position information plays an important role in support system for safe driving, where
inter-vehicle distance is used to prevent collision accidents from happening. In urban areas,
however, multipath propagation degrades the accuracy of absolute positions and the de...Lead morePosition information plays an important role in support system for safe driving, where
inter-vehicle distance is used to prevent collision accidents from happening. In urban areas,
however, multipath propagation degrades the accuracy of absolute positions and the deduced
relative position. On the other hand, simply removing reflected signals might lead to a
shortage of satellites in fixing positions. In our previous work, we suggested a cooperative
relative positioning scheme to exploit correlated information, including reflected signals, in
computing relative position. In this paper, we use a 3-D electronic map and a ray-tracing tool
to analyze reflected signals in detail. More specifically, we evaluate the distribution of
pseudo-range errors due to reflection and analyze their correlation. We find that reflected
signals received by adjacent vehicles tend to be highly correlated and can be used to improve
accuracy of relative positions.

Abstract

We propose a method for detecting and stabilizing shaky frames of omnidirectional videos captured by omnidirectional camera systems mounted on top a car. We introduce a technique to detect frames where the video has unwanted shakes and jitters. This enables us to avoid st...Lead moreWe propose a method for detecting and stabilizing shaky frames of omnidirectional videos captured by omnidirectional camera systems mounted on top a car. We introduce a technique to detect frames where the video has unwanted shakes and jitters. This enables us to avoid stabilizing all frames of the video that can be very time-consuming in long videos. The main difference between two consecutive frames, specially when the video is shaky, is caused by camera rotation. We decouple rotation and translation and compensate only for rotation. We use a fast and robust method to estimate the camera rotation between two consecutive spherical frames. Our method uses only two pairs of corresponding points as seeds in RANSAC that makes the computation faster than other methods. Our experiments show that our results are comparable to those methods that compensate for both rotation and translation but our method is faster and more robust.

Abstract

Recently, a number of researches are conducted to construct the actual city into the computer for the purpose of Web services, ITS, disaster analysis, landscape simulation and so on. Further, with the spread of on-vehicle video camera, it becomes common to share the on-ve...Lead moreRecently, a number of researches are conducted to construct the actual city into the computer for the purpose of Web services, ITS, disaster analysis, landscape simulation and so on. Further, with the spread of on-vehicle video camera, it becomes common to share the on-vehicle video on website. If the locations of the videos are available, the data can be efficiently used for virtual city construction.In this paper, we propose a method to realize localization of anonymous on-vehicle video uploaded on the Web by using video matching technique utilizing Temporal Height Image, Affine SIFT and Bag of Feature. THI retains information of relative building height from temporal image sequence and the Affine SIFT realizes a robust matching for variance of both camera speed and driving lane. Finally, BoF representation allows us to realize stable matching with less computational cost. We conducted several experiments using real image sequences.

Abstract

Acceleration is an integral part of driving and consumes a significant portion of a vehicle's fuel. The research presented in this paper develops a dynamic programming and path-finding algorithm to compute the fuel-optimal throttle level input for acceleration maneuvers. ...Lead moreAcceleration is an integral part of driving and consumes a significant portion of a vehicle's fuel. The research presented in this paper develops a dynamic programming and path-finding algorithm to compute the fuel-optimal throttle level input for acceleration maneuvers. A constant throttle model is compared with two variable throttle models that are based on state-of-the-art path-finding algorithms: namely, the Dijkstra and the A-star algorithms. These methods were compared using two measures of effectiveness – model accuracy and computational efficiency. The results demonstrate that a variable throttle model minimizes the fuel consumed relative to a constant throttle model, but is computationally complex. The optimum solution computed using a constant throttle model is up to 10 percent fuel saving than the way we normally drive.

Abstract

Dynamax is a road side based system using the SPECIALIST control algorithm and inductive loops. Dynamax field tests showed that moving jams can be effectively resolved by dynamic speed measures. This paper focuses on Dynamax In Car, which extends the road side infrastruct...Lead moreDynamax is a road side based system using the SPECIALIST control algorithm and inductive loops. Dynamax field tests showed that moving jams can be effectively resolved by dynamic speed measures. This paper focuses on Dynamax In Car, which extends the road side infrastructure with a V2I cooperative approach. V2I cooperation is used to detect an emerging jam earlier and more accurately, so that a smaller speed measure can be set to resolve it and more moving jams can be resolved within the available road length. The detection performance is analyzed through simulation and found to improve already with a very low penetration rate. An additional road side detection system is also analyzed that is independent of the penetration rate and provides the best detection performance.

Abstract

For online traffic control at traffic control centers there is a need for predictions
of traffic flow over a short horizon to evaluate the impact of different scenario for
the purpose of on-line scenarios selection. Fast computation is needed for the
online decis...Lead moreFor online traffic control at traffic control centers there is a need for predictions
of traffic flow over a short horizon to evaluate the impact of different scenario for
the purpose of on-line scenarios selection. Fast computation is needed for the
online decision support system. However, the common approach of a parallel sim-
ulation has several drawbacks. In this paper, a novel approach by an asynchronous
iterative algorithm is presented to predict the traffic flow in a large-scale traffic net-
work in a parallel and distributed way with a reasonably small computation time.
By a proper selection of the number of distributed subsystems one can reduce the
time complexity of the prediction to a value satisfactory for traffic control centers.
The experience with the computations is that after two or three iterations the ob-
tained predictions for the prediction horizon are quite satisfactory for practical use.

Abstract

This paper describes a green control unit (GCU) for eco-driving of electric vehicles through the use of information and communication technology. The GCU can provide the most energy-efficient driving strategy for the EV driver based on the road information obtained via wi...Lead moreThis paper describes a green control unit (GCU) for eco-driving of electric vehicles through the use of information and communication technology. The GCU can provide the most energy-efficient driving strategy for the EV driver based on the road information obtained via wireless communication, EV models and the measurements from on-board sensors and the EV propulsion system. The Model Predictive Control (MPC) technique is adopted for developing the GCU algorithms. Two different energy cost functions and different assumptions for the driver model and the availability of road information are used to develop five different MPC-based GCU algorithms. Computer simulations were performed to compare the performance of the five EV driving strategies against the other two scenarios which simply follow the upper and lower speed limits, respectively. Simulation results show that the MPC-based GCU algorithm using the road information and a good driver model outperforms the other four schemes of GCU algorithms.

Abstract

This paper demonstrates the use of a set of computer vision techniques
for the automated collection of pedestrian data. The paper addresses
three distinct issues in data collection. The first issue deals with
the identification of gender attribute using informat...Lead moreThis paper demonstrates the use of a set of computer vision techniques
for the automated collection of pedestrian data. The paper addresses
three distinct issues in data collection. The first issue deals with
the identification of gender attribute using information extracted on
the walking characteristics of the pedestrians. The demonstrated case
study reported correct classification rates (CCR) of 78%. The second
issue is related to the conformance of pedestrian crossings. Automated
spatial violation detection is demonstrated with accuracy greater than
90% is reported on the data set. The last data collection problem
addressed in this paper is the automated classification of road-users.
A classification approach relying on the movement characteristics of
the road users is proposed. The approach is validated on real world
data collected in Oakland California. The application of the
classifier has shown a correct classification rate of around 90%.

Abstract

Incidents can significantly impact freeway operations and deteriorate mobility and safety. This study quantified their safety impacts through inspecting queue properties. Specifically, end-of-queue (EOQ), where severe rear-end collisions commonly occur, is employed for as...Lead moreIncidents can significantly impact freeway operations and deteriorate mobility and safety. This study quantified their safety impacts through inspecting queue properties. Specifically, end-of-queue (EOQ), where severe rear-end collisions commonly occur, is employed for assessment based on vehicles' trajectories. Since detector data is typically available, this paper applied such data for EOQ identification, as opposed to vehicle trajectories that are difficult to collect and process. Three measures related to queue duration, impact area and vehicle number exposed to the EOQ are presented as surrogates. To understand the applicability of these measures, a systematic set of incident scenarios are replicated with VISSIM. Quantitative results are used to estimate regression models, and significant variables are identified. The proposed methods can be used to evaluate safety impact of traffic incident management programs such as freeway service patrol, as well as to determine optimal plans for prearranged incidents such as pothole repair.

Abstract

The development of mobile phone technology caused a rupture in the telecommunications industry service model. To fill the gaps created by the technological breakthrough in the service availability architecture the 3GPP (an ITU-T group) has developed a model that resulted ...Lead moreThe development of mobile phone technology caused a rupture in the telecommunications industry service model. To fill the gaps created by the technological breakthrough in the service availability architecture the 3GPP (an ITU-T group) has developed a model that resulted in an architecture called IMS - IP Multimedia Subsystem. The IMS architecture became the basis of the session control architecture for third-generation networks (3G) and their evolution (4G), where the focus is no longer the increase in capacity or bandwidth, but the interoperability between heterogeneous access networks. Based on the premise that increasing ITS services will be available on mobile devices (embedded or portable), IMS can be extended to cover the ITS applications. The IMS can be used to implement the ITS sub architectures because it has the ability to provide multiple ITS services on the same session, regardless the different types of mobile devices used to access these services.

Abstract

With the addition of a new roadway in Maryland, the availability of GPS panel data before and after the opening of a toll road was explored for the first time in value of time calculation. Using a GPS dataset spanning 70 days including 218 participants, toll costs per tri...Lead moreWith the addition of a new roadway in Maryland, the availability of GPS panel data before and after the opening of a toll road was explored for the first time in value of time calculation. Using a GPS dataset spanning 70 days including 218 participants, toll costs per trip, duration, distance, and accurate origin/destinations are observed. A novel approach for directly computing value of time is developed based on before-and-after GPS data; using the cost and travel time of previous trips. The method iteratively estimates the bounds for individual values of time from day to day, and derives individuals' values of time based upon their recurrent route, and therefore cost, decisions. Both the variation of VOT across individuals and the temporal variation of VOT within the same person are considered and measured with this new method. The proposed VOT estimation method takes full advantage of detailed GPS travel behavior information.

Abstract

This paper proposes a method to detect traffic congestion recovery, which is a point in time where demand has dropped below maximum capacity and traffic starts to recover from congestion to free-flow state. The proposed method captures transient patterns when traffic star...Lead moreThis paper proposes a method to detect traffic congestion recovery, which is a point in time where demand has dropped below maximum capacity and traffic starts to recover from congestion to free-flow state. The proposed method captures transient patterns when traffic starts to recover from congestion to free-flow state by assessing individual traffic variables called congestion recovery indicators. In this paper, the proposed method is implemented by adopting the previously proposed dynamic time warping algorithm []. Performance evaluation is conducted using a real-world traffic data set where the effectiveness and efficiency of individual congestion recovery indicators are assessed. It is shown that using the statistics of speed enables rapid detection while using flow and occupancy can reduce false detections.

Abstract

The approval of GNSS devices for safety-relevant applications demands an independent test laboratory that provides a measurement standard for vehicle localisation and standardised methods for carrying out test runs and data analysis. A literature review has shown that suc...Lead moreThe approval of GNSS devices for safety-relevant applications demands an independent test laboratory that provides a measurement standard for vehicle localisation and standardised methods for carrying out test runs and data analysis. A literature review has shown that such test laboratory does not exist yet. For this reason, a mobile reference system for assessing the measurement quality of the coming Galileo system is currently developed within the scope of the new European project QualiSaR. This paper introduces the objectives of QualiSaR. As a first result, a technology review regarding suitable reference localisation technologies is presented. Finally, the design of the reference system for road transport vehicles to be developed is illustrated.

Abstract

The research presented in this paper analyzes responses from a public opinion survey of 434 drivers. The results indicate that over 89 percent of the respondents support advanced in-vehicle technologies whereas only 26 percent support intelligent highway systems that intr...Lead moreThe research presented in this paper analyzes responses from a public opinion survey of 434 drivers. The results indicate that over 89 percent of the respondents support advanced in-vehicle technologies whereas only 26 percent support intelligent highway systems that intrude driver-independence. Only 20 percent of the respondents indicated that cruise control systems make driving more distractive whereas nearly 31 percent of the respondents indicated that a smart-phone based driving assistance device would be distractive. As far as trustworthiness of advanced cruise control systems such as adaptive cruise control and cooperative adaptive cruise control systems are concerned, up to 60 percent of the respondents felt that they would need to get acquainted with these systems before making a judgment. The results from this paper are especially important as the connected vehicle program is being introduced to the research arena.

Abstract

This study proposes a dynamic travel time prediction algorithm that matches current traffic patterns to historical data. Unlike previous approaches that use travel time as the control variable, the approach uses the temporal-spatial traffic state evolution to match traffi...Lead moreThis study proposes a dynamic travel time prediction algorithm that matches current traffic patterns to historical data. Unlike previous approaches that use travel time as the control variable, the approach uses the temporal-spatial traffic state evolution to match traffic states and predict travel times. The approach first identifies candidate historical time intervals by matching real-time traffic state data against historical data for use in prediction purposes. Subsequently, the selected candidates are used to predict the temporal-spatial evolution of traffic. Lastly, dynamic travel times are constructed using the identified candidate historical data. The proposed algorithm is tested on a 37-mile freeway segment from Newport News to Virginia Beach along the I-64 and I-264 freeways using historical INRIX data. The prediction results indicate that the proposed method produces predictions that are more accurate than the state-of-the-art K-Nearest Neighbor methods reducing the error by 15 percent, within 3 minutes on a 50-minute trip.

Abstract

Recently mass-produced electric vehicles have become commercially available both at home and abroad.The purpose of this paper is to clarify purchase preferences based on two conditions, mileage and the cost of EVs, as well as their determinant factors. The purchase prefer...Lead moreRecently mass-produced electric vehicles have become commercially available both at home and abroad.The purpose of this paper is to clarify purchase preferences based on two conditions, mileage and the cost of EVs, as well as their determinant factors. The purchase preference for mileage as well as the purchase preference for the total cost were set as the objective variables, whereas the basic attributes and psychological attributes, as well as the usage status of the vehicles and residential area characteristics, were set as explanatory variables in order to perform an order logistic regression analysis. As a result, it was revealed that the age and consumer propensity determine both the purchase preference for mileage and the purchase preference for the total cost. It was also revealed that the maximum kilometrage strongly affected the purchase preference for mileage and the kilometrage per year for the purchase preference for the total cost of possession.

Abstract

Focusing on the individualized dynamic traffic information, this study applies a stated preference (SP) survey and a data mining technique called Exhaustive CHAID to evaluate the heterogeneous effects of the information on drivers' adaptation behavior to the occurrence of...Lead moreFocusing on the individualized dynamic traffic information, this study applies a stated preference (SP) survey and a data mining technique called Exhaustive CHAID to evaluate the heterogeneous effects of the information on drivers' adaptation behavior to the occurrence of traffic accidents in the context of expressway. Three decision scenes are targeted: before departure, on the way to expressway and on expressway. SP survey is designed to reflect the influence of each respondent's different driving experience and preference for travel information on the SP responses. Different from existing studies, several new types of traffic information are additionally examined. Taking the expressway of West NEXCO, Japan as an example, 10,000 SP responses were collected for each scene. Analyses identified about 30 adaptation patterns with considerably different influencing information contents. The importance of developing individualized traffic safety information systems is confirmed.

Abstract

The constantly growing amount of vehicles in urban areas leads to a more saturated condition at signalized intersections. Microscopic traffic flow optimization offers a probate solution to reducing queue length and lost time, thus increasing overall traffic flow. Gatherin...Lead moreThe constantly growing amount of vehicles in urban areas leads to a more saturated condition at signalized intersections. Microscopic traffic flow optimization offers a probate solution to reducing queue length and lost time, thus increasing overall traffic flow. Gathering sufficient input data for the optimization process is dependent on the available hardware and the used mode of transport. In this paper we suggest the usage of inexpensive 802.15.4-based wireless sensor networks (WSN) as a technology to be applicable to a broad variety of modes of transport in urban traffic environments. The WSN-nodes are capable of transmitting traffic telematics information as well as achieving a distance measurement between two equally equipped nodes. We present testing data that shows the performance of the positioning using the proposed hardware while still maintaining a communication link and transmitting data from the traffic light system to the vehicle.

Abstract

In Japan, a new project for reducing CO2, called "Energy ITS project" has started since 2008 by New Energy and Industrial Technology Development Organization (NEDO) for reducing CO2 emissions. This project aims to develop techniques for the autonomous platooning of heavy-...Lead moreIn Japan, a new project for reducing CO2, called "Energy ITS project" has started since 2008 by New Energy and Industrial Technology Development Organization (NEDO) for reducing CO2 emissions. This project aims to develop techniques for the autonomous platooning of heavy-duty trucks to reduce their air resistance in expressway driving. Platooning needs lateral and longitudinal control. This paper describes novel lateral and longitudinal control. Lateral control method is based on path following. Longitudinal control method uses information acquired from the front and rear trucks by inter-vehicle communication. And a steering control methods using feedfoward control to deal with a road cant and a deviation from a target course by a disturbance are proposed. The experimental results of autonomous platooning are provided to evaluate the effectiveness of the method. In this experiment, the platoon is composed of four trucks, and two kind trucks are used.