Bruce Hellinga - Academia.edu (original) (raw)
Papers by Bruce Hellinga
Advanced traveller information systems (ATIS) constitute one of the key elements of ITS. While a ... more Advanced traveller information systems (ATIS) constitute one of the key elements of ITS. While a great deal of research has been conducted to examine various aspects of ATIS, such as data fusion, estimating travel times, what mechanisms are most appropriate for disseminating travel information, and the effects of providing traveller information, currently the most significant factor limiting the wide spread deployment of ATIS is the lack of a cost effective method of obtaining data reflecting network travel conditions. It has been proposed that the ability to autonomously determine the location of wireless communication devices (e.g. cell phones) provide an opportunity to acquire large quantities of travel data without the need to deploy a large and costly network of traffic surveillance equipment. To date, such a system has not been deployed in North America. However, a number of projects have been initiated to examine the feasibility of such an approach. This paper explores the po...
Advanced traveller information systems (ATIS) constitute one of the key elements of ITS. While a ... more Advanced traveller information systems (ATIS) constitute one of the key elements of ITS. While a great deal of research has been conducted to examine various aspects of ATIS, such as data fusion, estimating travel times, what mechanisms are most appropriate for disseminating travel information, and the effects of providing traveller information, currently the most significant factor limiting the wide spread deployment of ATIS is the lack of a cost effective method of obtaining data reflecting network travel conditions. It has been proposed that the ability to autonomously determine the location of wireless communication devices (e.g. cell phones) provide an opportunity to acquire large quantities of travel data without the need to deploy a large and costly network of traffic surveillance equipment. To date, such a system has not been deployed in North America. However, a number of projects have been initiated to examine the feasibility of such an approach. This paper explores the po...
Transportation Research Part C: Emerging Technologies, 2008
Transportation Research Part C: Emerging Technologies, 2008
This paper describes the derivation of two analytical models for predicting the mean and variance... more This paper describes the derivation of two analytical models for predicting the mean and variance of delay that a vehicle will experience when traversing a fixed-time signalized intersection approach at a known future point of time. This delay, referred as to arrival time dependent delay in this paper, differs from the traditional average delay estimate used in intersection performance analysis in that it is a function of the time at which the vehicle transverse the link. Arrival time dependent estimates of the mean and variance of delay are important for the successful deployment of many Intelligent Transportation Systems such as in-vehicle route guidance systems and Advanced Traffic Management Systems. The models presented in this paper are developed on the basis of an analysis of delay under two extreme traffic conditions: highly undersaturated and highly oversaturated conditions. A discrete cycle-by-cycle simulation model is used to generate data for calibrating and validating the proposed models. The analysis indicates a remarkable agreement (R 2 > 0.99) between the proposed analytical models and the simulation results.
In large urban areas dedicated fixed traffic sensors are deployed on major freeways (e.g. COMPASS... more In large urban areas dedicated fixed traffic sensors are deployed on major freeways (e.g. COMPASS and RESCU systems in Ontario) enabling traffic operators to collect high quality road condition information in real time. However, almost no real time information is available for all other roadways and full instrumentation of all major highways and arterials is cost prohibitive. Consequently, travellers are unable to make informed decisions about the best travel mode, departure time, and route, and traffic managers are unable to predict or monitor the effect of management strategies for roadways outside of the instrumented freeway corridors. The lack of information causes frustration on the part of travellers and transportation system managers and often results in sub-optimal decisions. New developments within the wireless communication field (dedicated probe systems, cell phone based systems or Vehicle Infrastructure Integration) provide the opportunity to obtain traffic condition information over a wide spatial area in near real time without the deployment of dedicated traffic sensors. A limited number of commercial systems have emerged in the market and several evaluation studies in North America are currently underway or have been recently completed. Most research and commercial activity in the area of network wide traffic monitoring has focused on the estimation of speed or travel time; however, this technology may support a wide range of other traffic management activities. This paper (a) describes the techniques that can be utilized to obtain wireless network wide traffic monitoring; (b) explores the opportunities that wide area traffic monitoring provides; (c) identifies existing commercial systems; and (d) summaries the published results of North American evaluations of these systems.
This paper describes a new methodology proposed for real-time travel time prediction utilizing ve... more This paper describes a new methodology proposed for real-time travel time prediction utilizing vehicle trajectory data and shockwave information. The main idea behind this methodology is that average speed on a section of roadway is constant unless a shockwave is created due to change in flow or traffic density. In the proposed methodology first the route is discretized into a number of smaller road sections and the average speed of each section is calculated based on the available information obtained from vehicles trajectories during the current time interval. The travel times obtained from average speed of each road section are modified if any shockwaves are identified in the traffic stream. The proposed model was evaluated using the vehicle trajectory data from global positioning system (GPS) data loggers on a freeway section in Toronto, Ontario. It is shown that the prediction accuracy of the proposed model is superior to the travel times obtained from traditional loop detectors. Moreover, this paper shows that alternative sources of data which use the existing infrastructure (e.g. cell phone network) can potentially be used to acquire traffic information. This is especially important for rural freeways which do not have full Freeway Traffic Management System (FTMS) infrastructure.
Knowledge of the location and speed of shockwaves in a traffic stream provides insight into the f... more Knowledge of the location and speed of shockwaves in a traffic stream provides insight into the formation and dissipation of congestion-information which is important for system managers. Furthermore, this information can be used to estimate and predict travel time for a section of a roadway. Most of the past efforts at identifying shockwaves have been focused on performing shockwave analysis based on fixed sensors such as loop detectors which are commonly used in many jurisdictions. However, latest advances in wireless communications have provided an opportunity to obtain vehicle trajectory data that potentially could be used to derive traffic conditions over a wide spatial area. This paper proposes a new methodology to detect and analyze shockwaves based on vehicle trajectory data. In the proposed methodology first the points that correspond to the intersection of shockwaves and trajectories of probe vehicles are identified and then a linear clustering algorithm is employed to group different shockwaves. Finally, a linear regression model is used to find propagation speed and spatial and temporal extent of each shockwave. The framework is evaluated using data obtained from a simulation of a signalized intersection and also real trajectory data from freeway US-101 near Los Angeles and shows promising results.
The ability to estimate the status of current traffic congestion of a road network is of signific... more The ability to estimate the status of current traffic congestion of a road network is of significant importance for many Intelligent Transportation Systems (ITS) applications such as in-vehicle route guidance systems (RGS) and advanced traffic management systems (ATMS). Substantial research effort has been dedicated to developing accurate and reliable techniques for estimation of various congestion measures such as link travel time and average travel speed. Few reliable models have however been reported, especially for congested arterials. This paper presents a model that can be used to estimate one of the congestion measures, namely real-time overflow queue at signalized arterial approaches. The model is developed on the basis of the principle of flow conservation, assuming that time-varying traffic arrivals can be obtained from loop detectors located at signalized approaches and signal control information is available online. A conventional microscopic simulation model is used to ...
Transportation Research Record: Journal of the Transportation Research Board, 2013
Road agencies typically collect travel time information from their network to identify traffic bo... more Road agencies typically collect travel time information from their network to identify traffic bottlenecks and to quantify the effects of road improvement investments in terms of travel time improvements. Road agencies can benefit from newly emerging automated data collection technologies that acquire travel time information for a large geographical area at lower costs. The objective of the study presented in this paper was to evaluate travel time data obtained from three technologies (i.e., Bluetooth, in-vehicle navigation systems, and mobile phone probes) compared with travel time obtained from probe vehicles equipped with Global Positioning Systems (GPSs). Traffic data were obtained for road types (e.g., freeways, arterials, ramps) in the study area from commercial data providers for a relatively large study area in the Province of Ontario, Canada. A multicriteria methodology was developed to evaluate data from each data provider on the basis of accuracy, coverage, number of obse...
Transportation Research Part C: Emerging Technologies, 2002
The use of probe vehicles to provide estimates of link travel times has been suggested as a means... more The use of probe vehicles to provide estimates of link travel times has been suggested as a means of obtaining travel times within signalized networks for use in advanced traveler information systems. Previous research has shown that bias in arrival time distributions of probe vehicles will lead to a systematic bias in the sample estimate of the mean. This paper proposes a methodology for reducing the effect of this bias. The method, based on stratified sampling techniques, requires that vehicle count data be obtained from an inroad loop detector or other traffic surveillance method. The effectiveness of the methodology is illustrated using simulation results for a single intersection approach and for an arterial corridor. The results for the single intersection approach indicate a correlation (R 2) between the biased estimate and the population mean of 0.61, and an improved correlation between the proposed estimation method and the population mean of 0.81. Application of the proposed method to the arterial corridor resulted in a reduction in the mean travel time error of approximately 50%, further indicating that the proposed estimation method provides improved accuracy over the typical method of computing the arithmetic mean of the probe reports.
Transportation Research Part C: Emerging Technologies, 2008
In probe-based traffic monitoring systems, traffic conditions can be inferred based on the positi... more In probe-based traffic monitoring systems, traffic conditions can be inferred based on the position data of a set of periodically polled probe vehicles. In such systems, the two consecutive polled positions do not necessarily correspond to the end points of individual links. Obtaining estimates of travel time at the individual link level requires the total traversal time (which is equal to the polling interval duration) be decomposed. This paper presents an algorithm for solving the problem of decomposing the traversal time to times taken to traverse individual road segments on the route. The proposed algorithm assumes minimal information about the network, namely network topography (i.e. links and nodes) and the free flow speed of each link. Unlike existing deterministic methods, the proposed solution algorithm defines a likelihood function that is maximized to solve for the most likely travel time for each road segment on the traversed route. The proposed scheme is evaluated using simulated data and compared to a benchmark deterministic method. The evaluation results suggest that the proposed method outperforms the bench mark method and on average improves the accuracy of the estimated link travel times by up to 90%.
Advanced traveller information systems (ATIS) constitute one of the key elements of ITS. While a ... more Advanced traveller information systems (ATIS) constitute one of the key elements of ITS. While a great deal of research has been conducted to examine various aspects of ATIS, such as data fusion, estimating travel times, what mechanisms are most appropriate for disseminating travel information, and the effects of providing traveller information, currently the most significant factor limiting the wide spread deployment of ATIS is the lack of a cost effective method of obtaining data reflecting network travel conditions. It has been proposed that the ability to autonomously determine the location of wireless communication devices (e.g. cell phones) provide an opportunity to acquire large quantities of travel data without the need to deploy a large and costly network of traffic surveillance equipment. To date, such a system has not been deployed in North America. However, a number of projects have been initiated to examine the feasibility of such an approach. This paper explores the po...
Advanced traveller information systems (ATIS) constitute one of the key elements of ITS. While a ... more Advanced traveller information systems (ATIS) constitute one of the key elements of ITS. While a great deal of research has been conducted to examine various aspects of ATIS, such as data fusion, estimating travel times, what mechanisms are most appropriate for disseminating travel information, and the effects of providing traveller information, currently the most significant factor limiting the wide spread deployment of ATIS is the lack of a cost effective method of obtaining data reflecting network travel conditions. It has been proposed that the ability to autonomously determine the location of wireless communication devices (e.g. cell phones) provide an opportunity to acquire large quantities of travel data without the need to deploy a large and costly network of traffic surveillance equipment. To date, such a system has not been deployed in North America. However, a number of projects have been initiated to examine the feasibility of such an approach. This paper explores the po...
Transportation Research Part C: Emerging Technologies, 2008
Transportation Research Part C: Emerging Technologies, 2008
This paper describes the derivation of two analytical models for predicting the mean and variance... more This paper describes the derivation of two analytical models for predicting the mean and variance of delay that a vehicle will experience when traversing a fixed-time signalized intersection approach at a known future point of time. This delay, referred as to arrival time dependent delay in this paper, differs from the traditional average delay estimate used in intersection performance analysis in that it is a function of the time at which the vehicle transverse the link. Arrival time dependent estimates of the mean and variance of delay are important for the successful deployment of many Intelligent Transportation Systems such as in-vehicle route guidance systems and Advanced Traffic Management Systems. The models presented in this paper are developed on the basis of an analysis of delay under two extreme traffic conditions: highly undersaturated and highly oversaturated conditions. A discrete cycle-by-cycle simulation model is used to generate data for calibrating and validating the proposed models. The analysis indicates a remarkable agreement (R 2 > 0.99) between the proposed analytical models and the simulation results.
In large urban areas dedicated fixed traffic sensors are deployed on major freeways (e.g. COMPASS... more In large urban areas dedicated fixed traffic sensors are deployed on major freeways (e.g. COMPASS and RESCU systems in Ontario) enabling traffic operators to collect high quality road condition information in real time. However, almost no real time information is available for all other roadways and full instrumentation of all major highways and arterials is cost prohibitive. Consequently, travellers are unable to make informed decisions about the best travel mode, departure time, and route, and traffic managers are unable to predict or monitor the effect of management strategies for roadways outside of the instrumented freeway corridors. The lack of information causes frustration on the part of travellers and transportation system managers and often results in sub-optimal decisions. New developments within the wireless communication field (dedicated probe systems, cell phone based systems or Vehicle Infrastructure Integration) provide the opportunity to obtain traffic condition information over a wide spatial area in near real time without the deployment of dedicated traffic sensors. A limited number of commercial systems have emerged in the market and several evaluation studies in North America are currently underway or have been recently completed. Most research and commercial activity in the area of network wide traffic monitoring has focused on the estimation of speed or travel time; however, this technology may support a wide range of other traffic management activities. This paper (a) describes the techniques that can be utilized to obtain wireless network wide traffic monitoring; (b) explores the opportunities that wide area traffic monitoring provides; (c) identifies existing commercial systems; and (d) summaries the published results of North American evaluations of these systems.
This paper describes a new methodology proposed for real-time travel time prediction utilizing ve... more This paper describes a new methodology proposed for real-time travel time prediction utilizing vehicle trajectory data and shockwave information. The main idea behind this methodology is that average speed on a section of roadway is constant unless a shockwave is created due to change in flow or traffic density. In the proposed methodology first the route is discretized into a number of smaller road sections and the average speed of each section is calculated based on the available information obtained from vehicles trajectories during the current time interval. The travel times obtained from average speed of each road section are modified if any shockwaves are identified in the traffic stream. The proposed model was evaluated using the vehicle trajectory data from global positioning system (GPS) data loggers on a freeway section in Toronto, Ontario. It is shown that the prediction accuracy of the proposed model is superior to the travel times obtained from traditional loop detectors. Moreover, this paper shows that alternative sources of data which use the existing infrastructure (e.g. cell phone network) can potentially be used to acquire traffic information. This is especially important for rural freeways which do not have full Freeway Traffic Management System (FTMS) infrastructure.
Knowledge of the location and speed of shockwaves in a traffic stream provides insight into the f... more Knowledge of the location and speed of shockwaves in a traffic stream provides insight into the formation and dissipation of congestion-information which is important for system managers. Furthermore, this information can be used to estimate and predict travel time for a section of a roadway. Most of the past efforts at identifying shockwaves have been focused on performing shockwave analysis based on fixed sensors such as loop detectors which are commonly used in many jurisdictions. However, latest advances in wireless communications have provided an opportunity to obtain vehicle trajectory data that potentially could be used to derive traffic conditions over a wide spatial area. This paper proposes a new methodology to detect and analyze shockwaves based on vehicle trajectory data. In the proposed methodology first the points that correspond to the intersection of shockwaves and trajectories of probe vehicles are identified and then a linear clustering algorithm is employed to group different shockwaves. Finally, a linear regression model is used to find propagation speed and spatial and temporal extent of each shockwave. The framework is evaluated using data obtained from a simulation of a signalized intersection and also real trajectory data from freeway US-101 near Los Angeles and shows promising results.
The ability to estimate the status of current traffic congestion of a road network is of signific... more The ability to estimate the status of current traffic congestion of a road network is of significant importance for many Intelligent Transportation Systems (ITS) applications such as in-vehicle route guidance systems (RGS) and advanced traffic management systems (ATMS). Substantial research effort has been dedicated to developing accurate and reliable techniques for estimation of various congestion measures such as link travel time and average travel speed. Few reliable models have however been reported, especially for congested arterials. This paper presents a model that can be used to estimate one of the congestion measures, namely real-time overflow queue at signalized arterial approaches. The model is developed on the basis of the principle of flow conservation, assuming that time-varying traffic arrivals can be obtained from loop detectors located at signalized approaches and signal control information is available online. A conventional microscopic simulation model is used to ...
Transportation Research Record: Journal of the Transportation Research Board, 2013
Road agencies typically collect travel time information from their network to identify traffic bo... more Road agencies typically collect travel time information from their network to identify traffic bottlenecks and to quantify the effects of road improvement investments in terms of travel time improvements. Road agencies can benefit from newly emerging automated data collection technologies that acquire travel time information for a large geographical area at lower costs. The objective of the study presented in this paper was to evaluate travel time data obtained from three technologies (i.e., Bluetooth, in-vehicle navigation systems, and mobile phone probes) compared with travel time obtained from probe vehicles equipped with Global Positioning Systems (GPSs). Traffic data were obtained for road types (e.g., freeways, arterials, ramps) in the study area from commercial data providers for a relatively large study area in the Province of Ontario, Canada. A multicriteria methodology was developed to evaluate data from each data provider on the basis of accuracy, coverage, number of obse...
Transportation Research Part C: Emerging Technologies, 2002
The use of probe vehicles to provide estimates of link travel times has been suggested as a means... more The use of probe vehicles to provide estimates of link travel times has been suggested as a means of obtaining travel times within signalized networks for use in advanced traveler information systems. Previous research has shown that bias in arrival time distributions of probe vehicles will lead to a systematic bias in the sample estimate of the mean. This paper proposes a methodology for reducing the effect of this bias. The method, based on stratified sampling techniques, requires that vehicle count data be obtained from an inroad loop detector or other traffic surveillance method. The effectiveness of the methodology is illustrated using simulation results for a single intersection approach and for an arterial corridor. The results for the single intersection approach indicate a correlation (R 2) between the biased estimate and the population mean of 0.61, and an improved correlation between the proposed estimation method and the population mean of 0.81. Application of the proposed method to the arterial corridor resulted in a reduction in the mean travel time error of approximately 50%, further indicating that the proposed estimation method provides improved accuracy over the typical method of computing the arithmetic mean of the probe reports.
Transportation Research Part C: Emerging Technologies, 2008
In probe-based traffic monitoring systems, traffic conditions can be inferred based on the positi... more In probe-based traffic monitoring systems, traffic conditions can be inferred based on the position data of a set of periodically polled probe vehicles. In such systems, the two consecutive polled positions do not necessarily correspond to the end points of individual links. Obtaining estimates of travel time at the individual link level requires the total traversal time (which is equal to the polling interval duration) be decomposed. This paper presents an algorithm for solving the problem of decomposing the traversal time to times taken to traverse individual road segments on the route. The proposed algorithm assumes minimal information about the network, namely network topography (i.e. links and nodes) and the free flow speed of each link. Unlike existing deterministic methods, the proposed solution algorithm defines a likelihood function that is maximized to solve for the most likely travel time for each road segment on the traversed route. The proposed scheme is evaluated using simulated data and compared to a benchmark deterministic method. The evaluation results suggest that the proposed method outperforms the bench mark method and on average improves the accuracy of the estimated link travel times by up to 90%.