Journal of the Eastern Asia Society for Transportation Studies, 2013
To accommodate the heavy travel demand in high-density areas, Taipei Bus Station (TBS) is develop... more To accommodate the heavy travel demand in high-density areas, Taipei Bus Station (TBS) is developed as the first multi-level bus terminal in Taipei City. TBS also plays important roles in congestion mitigation, energy conservation and pollutant reduction. Unlike conventional single-level terminals, bus flow interruption while circulating in TBS could significantly impact the service quality and deteriorate environmental condition. Considering time-varying demand and existing Radio Frequency Identification (RFID) monitoring systems, this study constructed an adaptive signal control model combining an artificial neural network (ANN) demand forecasting model to manage bus traffic in TBS. In the case study, the self-retraining demand forecasting algorism is programmed in existing controller/computer to facilitate demand changes. The proposed model has demonstrated itself very efficient in reducing congestion within the terminal.
A shockwave-based speed harmonization algorithm for the longitudinal movement of automated vehicl... more A shockwave-based speed harmonization algorithm for the longitudinal movement of automated vehicles is presented in this paper. In the advent of Connected/Automated Vehicle (C/AV) environment, the proposed algorithm can be applied to capture instantaneous shockwaves constructed from vehicular speed profiles shared by individual equipped vehicles. With a continuous wavelet transform (CWT) method, the algorithm detects abnormal speed drops in real-time and optimizes speed to prevent the shockwave propagating to the upstream traffic. A traffic simulation model is calibrated to evaluate the applicability and efficiency of the proposed algorithm. Based on 100% C/AV market penetration, the simulation results show that the CWT-based algorithm accurately detects abnormal speed drops. With the improved accuracy of abnormal speed drop detection, the simulation results also demonstrate that the congestion can be mitigated by reducing travel time and delay up to approximately 9% and 18%, respectively. It is also found that the shockwave caused by nonrecurrent congestion is quickly dissipated even with low market penetration.
The Manual on Uniform Traffic Control Devices (MUTCD) predominantly addresses work performed alon... more The Manual on Uniform Traffic Control Devices (MUTCD) predominantly addresses work performed along the centerline of roadways and low-speed roads. This work does not apply to the majority of situations encountered by New Jersey Department of Transportation (NJDOT) employees who survey or inspect high-speed, high-volume roadways. Therefore, there is a need to review current practices being used by other state DOTs and develop guidance for using traffic control devices (TCD) on high-volume roads for this targeted group. This research project reviews the current practices employed by the other state DOTs, and new and emerging safety technologies that are consistent with the MUTCD guidelines. Two traffic control devices were selected after the review process: (1) Temporary portable rumble strips and (2) advance warning lights. The effectiveness of these devices was evaluated based on field tests with the land surveying crew of NJDOT. Recommendations on using the traffic control devices and guidelines for surveyors working on/nearby roadways were summarized. 9. Performing Organization Name and Address FHWA-NJ-2013-002 10. Work Unit No. 11. Contract or Grant No.
Evaluating bus transit performance periodically is a key step to improve service quality and syst... more Evaluating bus transit performance periodically is a key step to improve service quality and system efficiency. An extenics-based model is developed with the real-world data. e performance indices employed for the evaluation are identified. e dependent function applied for measuring the correlation between the bus transit and the system performance is formulated. e hybrid weights associated with the indices are determined by subjective weights through analytic hierarchy process (AHP) and objective weights through the entropy method. e proposed extenics model is applied for evaluating a bus transit system of a mediumsized city in China. e model outcomes are informative, while the suggestions corresponding to the identified weakness are concluded for future planning and operation.
The technology of dynamic wireless power transfer (DWPT) has been recognized as an effective way ... more The technology of dynamic wireless power transfer (DWPT) has been recognized as an effective way to recharge battery electric bus and overcome some drawbacks (e.g. high battery cost and limited service range) with opportunity charging. This study develops a mixed integer non-linear model to optimize a feeder bus transit powered by DWPT. The decision variables consist of bus route networks, service frequency, locations of DWPT devices and battery capacity. The objective is to minimize total cost, including the costs of charging devices, battery, operation and travel time. A tangible nested genetic algorithm (NGA) is developed to find the optimal solution. The computational efficiency of NGA is demonstrated through numerical comparisons to the solutions founded by LINGO and GA. It was found that with NGA the solution converges to an acceptable level faster than using LINGO and GA. A real-world bus network is employed to explore the relation between the minimized costs and decision variables. The result suggested that DWPT outperforms terminal charging technology in terms of the least total cost, and that the yielded total infrastructure cost with DWPT is 16.6% less than that with terminal charging technology. INDEX TERMS Electric buses, mixed non-linear programming, wireless charging, route optimization.
Coordinating train arrivals at transfer stations by altering their departure times can reduce tra... more Coordinating train arrivals at transfer stations by altering their departure times can reduce transfer waiting time (TWT) and improve level of service. This paper develops a method to optimize train departure times from terminals that minimizes total TWT for an urban rail network with many transfer stations. To maintain service capacity and avoid operational complexity, dispatching headway is fixed. An integrated Simulated Annealing with parallel computing approach is applied to perform the optimization. To demonstrate model applicability and performance, the Shenzhen metro network is applied, where passenger flows (i.e., entry, transfer, and exit) at stations are approximated with the automatic fare collection system (AFCS) data. Results show that the total TWT can be significantly reduced.
Electrifying bus transit has been deemed as an effective way to reduce the emissions of transit v... more Electrifying bus transit has been deemed as an effective way to reduce the emissions of transit vehicles. However, some concerns about on-board battery hinder its further development. Recently, dynamic wireless power transfer (DWPT) technologies have been developed, which enable buses to charge in-motion and overcome the drawback (short service range) with opportunity charging. This paper proposes a mathematic model which optimizes the locations for DWPT devices deployed at stops and size of battery capacity for battery electric buses (BEB) in a multi-route network, which considers the battery's service life, depth of discharge and weight. A tangible solution algorithm based on a genetic algorithm (GA) is developed to find the optimal solution. A case study based on the bus network from Xi'an China is conducted to investigate the relationship among optimized costs, greenhouse gas (GHG) emissions, battery service life, size of the battery capacity and the number of DWPT devices. The results demonstrated that a bus network powered by DWPT shows better performance in both costs (a 43.3% reduction) and emissions (a 14.4% reduction) compared to that with stationary charging at bus terminals.
A hybrid machine-learning model, integrating an artificial neural network (ANN) and a support vec... more A hybrid machine-learning model, integrating an artificial neural network (ANN) and a support vector machine (SVM) model, is developed to predict spatiotemporal delays, subject to road geometry, number of lane closures, and work zone duration in different periods of a day and in the days of a week. The model is very user friendly, allowing the least inputs from the users. With that the delays caused by a work zone on any location of a New Jersey freeway can be predicted. To this end, tremendous amounts of data from different sources were collected to establish the relationship between the model inputs and outputs. A comparative analysis was conducted, and results indicate that the proposed model outperforms others in terms of the least root mean square error (RMSE). The proposed hybrid model can be used to calculate contractor penalty in terms of cost overruns as well as incentive reward schedule in case of early work competition. Additionally, it can assist work zone planners in determining the best start and end times of a work zone for developing and evaluating traffic mitigation and management plans.
Travel times have been traditionally estimated from data collected by roadway sensors. Recently, ... more Travel times have been traditionally estimated from data collected by roadway sensors. Recently, new technologies, such as cell phone tracking, license plate matching, automatic vehicle identifications and video detection, are employed for this purpose. In this study, the data collected by TRANSMIT readers, Bluetooth sensors, and INRIX are assessed by comparing each to the "ground truth" travel times collected by probe vehicles carrying GPS-based navigation devices. Travel times of probe vehicles traveling on the study segment of I-287 in New Jersey were collected in 2009. Statistical measures, such as standard deviation, average absolute speed error, and speed error bias, were used to make an in-depth analysis. The accuracy of each travel time estimation method is analyzed. The data collected by Bluetooth sensors and the TRANSMIT readers seem more consistent with the ground true data, and slightly outperform the data reported by INRIX. This study established a procedure for analyzing the accuracy of floating car data (FCD) collected by different technologies.
This report presents research performed analyzing crashes in work zones in the state of New Jerse... more This report presents research performed analyzing crashes in work zones in the state of New Jersey so as to identify critical areas in work zones susceptible to crashes and key factors that contribute to these crashes. A field data collection on New Jersey roadways was performed for a select number of work zones to provide a better understanding of driver behavior in New Jersey work zones. The research also sought to identify where data needs are limited in evaluating work zone crashes in New Jersey and make recommendations on how the gaps in these needs can be addressed. Innovative strategies that hold potential for reducing work zone crashes were also identified. Crash frequency and crash severity models were developed to identify factors that contribute to number and severity of crashes in work zones. Negative binomial models were used to estimate: total number of crashes; frequency of injury crashes; and frequency of property damage only crashes. Binary logistic regression models were used to estimate severity for crashes where the driver is at fault, for drivers and for occupants in crashes at work zones. Recommendations on the operation and design of the work zone to reduce crash frequency and severity are presented based on the findings of the study.
Recent advance in VMS technology has made it viable to ease traffic congestion and improve road t... more Recent advance in VMS technology has made it viable to ease traffic congestion and improve road traffic efficiency. However, the drivers' low compliance with the posted information may limit its performance to ease traffic congestion and improve traffic safety. This paper explores drivers' attitude to the service quality of VMS system resulted from the identified predominant influencing factors. A questionnaire is developed and used for surveying 9,600 drivers in Beijing, China. The collected data are analyzed with a multiple indicators and multiple causes (MIMIC) model considering different driver categories (e.g., private car driver, office car driver, taxi driver). The results show that the causal relationships between latent variables and socio-demographic characteristic is significant. Driving frequency, attitude towards contents of VMS, drivers' decision-making and the effectiveness of VMS message can directly and indirectly affect driver's perceived quality of service. The attitude towards formats of VMS indirectly affect their QoS resulting from the effectiveness of VMS message, while there is no indirect impact for taxi drivers. Besides, the drivers' decisionmaking directly affects the perceived quality of service for private car drivers and office car drivers, but there is no impact for taxi drivers. The findings of this study can provide guidance and reference for urban authorities to perform the relevant actions required to meet user expectations.
Facing unprecedented increases in operational expenses, rail operators are seeking new methods to... more Facing unprecedented increases in operational expenses, rail operators are seeking new methods to reduce costs. Traction is their largest expense and despite their low energy intensities, the scale of operations causes large overall energy consumptions. This, coupled with the environmental impact of fossil fuel consumption is cause for concern. Modern railcars are equipped with the regenerative braking feature allowing them to generate electrical energy on braking. The energy can be stored for later use or transmitted directly to an accelerating train to reduce the energy used for acceleration. This study presents an intelligent method for harvesting the kinetic energy of an electric train through coasting and regenerative braking, and optimal positioning of the wayside energy storage system (WESS) units on a multi-segment rail line. Coasting saves energy by maintaining motion with propulsion disabled, and regenerative braking converts the kinetic energy of the train into electrical energy for the powering of subsequent acceleration cycles. The study entails the design of a model that simulates the movement of the train over an existing alignment section while considering alignment topography, speed limits, and train schedule. The main contribution of this research is the optimization of the number and locations of the WESS units using optimized speed profiles to maximize the net present value (NPV) of the energy recovery project. In this study, the optimized speed profiles are obtained with and without WESS installation and used as inputs to a linear programming (LP) simulation model. Hence, the model begins with inputs that are already optimized, ensuring a greater degree of processing speed and accuracy. The decision variables are the number and locations of the WESS units, and the output of the simulator is the optimized NPV. The results can be used for the planning of smart infrastructural
The road weather information system (RWIS), which collects and monitors weather and pavement surf... more The road weather information system (RWIS), which collects and monitors weather and pavement surface conditions, has been proven effective to support winter road maintenance by improving safety, mobility, and efficiency. Although the geographic information systems are being widely applied for facility siting, traditional practices of sitting RWIS stations still heavily rely on the experiences of maintenance and operation personnel, which is time-consuming and subjective. This study develops a linear model to determine the optimal RWIS locations subject to three selection criteria: weather, traffic condition, and distance to existing RWIS sites, while considering practical constraints to satisfy specific requirements of various agencies (e.g., different weights of weather/traffic factors, various available budgets, etc.).
Congestion is always a serious problem in many transportation commuting corridors. The need to im... more Congestion is always a serious problem in many transportation commuting corridors. The need to implement effective control in the corridors has long been recognized by transportation professionals. Ramp metering has been discussed as a viable control strategy on freeways in many places of the US, which may alleviate or at least reduce the delay. In this study, a dynamic ramp metering control model is developed to maximize the total throughput with simultaneous perturbation stochastic approximation (SPSA), subject to the constraints of link densities, capacities, and feasible range of metering rates. A case study for a segment of US I-80 in New Jersey is conducted, while the impact of the proposed ramp metering control on traffic behavior is simulated with CORSIM.
Ramp metering has been recognized as one of viable strategies of freeway traffic management, whic... more Ramp metering has been recognized as one of viable strategies of freeway traffic management, which may improve travel speed as well as reduce delay. In this study, a dynamic model is developed to optimize metering rates of a series of on-ramps which maximize the total throughput subject to vehicle density, roadway capacity, and queue length constraints with simultaneous perturbation stochastic approximation (SPSA). A calibrated microscopic traffic simulation model is used to evaluate the performance of the developed model. Results show that the total throughput of the studied freeway can be increased without increasing the total delay after implementing optimal metering rates. The developed SPSA has demonstrated itself as an efficient algorithm to search for the optimal solution of a dynamic, multivariate, and non-linear problem.
Accurate real-time traffic information is essential for the development of efficient traffic cont... more Accurate real-time traffic information is essential for the development of efficient traffic control and management. In recent years, private probe vehicle data has been employed by many public transportation agencies. However, most of those agencies have been unable to validate the accuracy of the purchased private probe data. This paper describes a sound methodology to evaluate the accuracy of estimated link travel speed by three probe data providers, which are INRIX, NAVTEQ, and TrafficCast, by using the ground truth travel speed of TRANSCOM‘s System for Managing Incidents & Traffic (TRANSMIT). The study route segments are on interstate 287 (I-287) and 78 (I-78) in New Jersey.
Although it is clear that adverse weather has an impact on roadway operating conditions, New Jers... more Although it is clear that adverse weather has an impact on roadway operating conditions, New Jersey had not performed research to quantify these impacts. To investigate the impact of adverse weather on New Jersey roadways, data on traffic parameters were collected under a variety of weather and light conditions. Speed, flow and density data were collected under no adverse weather, as well as under rain, snow, darkness and sun glare conditions. Comparisons were then made between traffic parameters under no adverse weather conditions, and under each weather and light condition. The study found that under rain conditions speeds decreased between 0.82 mi/hr (11%, 1.3 km/hr) and 37 mi/hr (61%, 59.2 km/hr). Under snow conditions speeds decrease between 5.8 mi/hr (15%, 9.3 km/hr) to 33.8 mi/hr (50%, 54 km/hr). Under rain and darkness conditions speeds were observed to both decrease from 0.71 mi/hr (1%, 1.1 km/hr) to 5.2 mi/hr (7%, 8.3 km/hr) and to also increase. Under snow and darkness co...
Journal of the Eastern Asia Society for Transportation Studies, 2013
To accommodate the heavy travel demand in high-density areas, Taipei Bus Station (TBS) is develop... more To accommodate the heavy travel demand in high-density areas, Taipei Bus Station (TBS) is developed as the first multi-level bus terminal in Taipei City. TBS also plays important roles in congestion mitigation, energy conservation and pollutant reduction. Unlike conventional single-level terminals, bus flow interruption while circulating in TBS could significantly impact the service quality and deteriorate environmental condition. Considering time-varying demand and existing Radio Frequency Identification (RFID) monitoring systems, this study constructed an adaptive signal control model combining an artificial neural network (ANN) demand forecasting model to manage bus traffic in TBS. In the case study, the self-retraining demand forecasting algorism is programmed in existing controller/computer to facilitate demand changes. The proposed model has demonstrated itself very efficient in reducing congestion within the terminal.
A shockwave-based speed harmonization algorithm for the longitudinal movement of automated vehicl... more A shockwave-based speed harmonization algorithm for the longitudinal movement of automated vehicles is presented in this paper. In the advent of Connected/Automated Vehicle (C/AV) environment, the proposed algorithm can be applied to capture instantaneous shockwaves constructed from vehicular speed profiles shared by individual equipped vehicles. With a continuous wavelet transform (CWT) method, the algorithm detects abnormal speed drops in real-time and optimizes speed to prevent the shockwave propagating to the upstream traffic. A traffic simulation model is calibrated to evaluate the applicability and efficiency of the proposed algorithm. Based on 100% C/AV market penetration, the simulation results show that the CWT-based algorithm accurately detects abnormal speed drops. With the improved accuracy of abnormal speed drop detection, the simulation results also demonstrate that the congestion can be mitigated by reducing travel time and delay up to approximately 9% and 18%, respectively. It is also found that the shockwave caused by nonrecurrent congestion is quickly dissipated even with low market penetration.
The Manual on Uniform Traffic Control Devices (MUTCD) predominantly addresses work performed alon... more The Manual on Uniform Traffic Control Devices (MUTCD) predominantly addresses work performed along the centerline of roadways and low-speed roads. This work does not apply to the majority of situations encountered by New Jersey Department of Transportation (NJDOT) employees who survey or inspect high-speed, high-volume roadways. Therefore, there is a need to review current practices being used by other state DOTs and develop guidance for using traffic control devices (TCD) on high-volume roads for this targeted group. This research project reviews the current practices employed by the other state DOTs, and new and emerging safety technologies that are consistent with the MUTCD guidelines. Two traffic control devices were selected after the review process: (1) Temporary portable rumble strips and (2) advance warning lights. The effectiveness of these devices was evaluated based on field tests with the land surveying crew of NJDOT. Recommendations on using the traffic control devices and guidelines for surveyors working on/nearby roadways were summarized. 9. Performing Organization Name and Address FHWA-NJ-2013-002 10. Work Unit No. 11. Contract or Grant No.
Evaluating bus transit performance periodically is a key step to improve service quality and syst... more Evaluating bus transit performance periodically is a key step to improve service quality and system efficiency. An extenics-based model is developed with the real-world data. e performance indices employed for the evaluation are identified. e dependent function applied for measuring the correlation between the bus transit and the system performance is formulated. e hybrid weights associated with the indices are determined by subjective weights through analytic hierarchy process (AHP) and objective weights through the entropy method. e proposed extenics model is applied for evaluating a bus transit system of a mediumsized city in China. e model outcomes are informative, while the suggestions corresponding to the identified weakness are concluded for future planning and operation.
The technology of dynamic wireless power transfer (DWPT) has been recognized as an effective way ... more The technology of dynamic wireless power transfer (DWPT) has been recognized as an effective way to recharge battery electric bus and overcome some drawbacks (e.g. high battery cost and limited service range) with opportunity charging. This study develops a mixed integer non-linear model to optimize a feeder bus transit powered by DWPT. The decision variables consist of bus route networks, service frequency, locations of DWPT devices and battery capacity. The objective is to minimize total cost, including the costs of charging devices, battery, operation and travel time. A tangible nested genetic algorithm (NGA) is developed to find the optimal solution. The computational efficiency of NGA is demonstrated through numerical comparisons to the solutions founded by LINGO and GA. It was found that with NGA the solution converges to an acceptable level faster than using LINGO and GA. A real-world bus network is employed to explore the relation between the minimized costs and decision variables. The result suggested that DWPT outperforms terminal charging technology in terms of the least total cost, and that the yielded total infrastructure cost with DWPT is 16.6% less than that with terminal charging technology. INDEX TERMS Electric buses, mixed non-linear programming, wireless charging, route optimization.
Coordinating train arrivals at transfer stations by altering their departure times can reduce tra... more Coordinating train arrivals at transfer stations by altering their departure times can reduce transfer waiting time (TWT) and improve level of service. This paper develops a method to optimize train departure times from terminals that minimizes total TWT for an urban rail network with many transfer stations. To maintain service capacity and avoid operational complexity, dispatching headway is fixed. An integrated Simulated Annealing with parallel computing approach is applied to perform the optimization. To demonstrate model applicability and performance, the Shenzhen metro network is applied, where passenger flows (i.e., entry, transfer, and exit) at stations are approximated with the automatic fare collection system (AFCS) data. Results show that the total TWT can be significantly reduced.
Electrifying bus transit has been deemed as an effective way to reduce the emissions of transit v... more Electrifying bus transit has been deemed as an effective way to reduce the emissions of transit vehicles. However, some concerns about on-board battery hinder its further development. Recently, dynamic wireless power transfer (DWPT) technologies have been developed, which enable buses to charge in-motion and overcome the drawback (short service range) with opportunity charging. This paper proposes a mathematic model which optimizes the locations for DWPT devices deployed at stops and size of battery capacity for battery electric buses (BEB) in a multi-route network, which considers the battery's service life, depth of discharge and weight. A tangible solution algorithm based on a genetic algorithm (GA) is developed to find the optimal solution. A case study based on the bus network from Xi'an China is conducted to investigate the relationship among optimized costs, greenhouse gas (GHG) emissions, battery service life, size of the battery capacity and the number of DWPT devices. The results demonstrated that a bus network powered by DWPT shows better performance in both costs (a 43.3% reduction) and emissions (a 14.4% reduction) compared to that with stationary charging at bus terminals.
A hybrid machine-learning model, integrating an artificial neural network (ANN) and a support vec... more A hybrid machine-learning model, integrating an artificial neural network (ANN) and a support vector machine (SVM) model, is developed to predict spatiotemporal delays, subject to road geometry, number of lane closures, and work zone duration in different periods of a day and in the days of a week. The model is very user friendly, allowing the least inputs from the users. With that the delays caused by a work zone on any location of a New Jersey freeway can be predicted. To this end, tremendous amounts of data from different sources were collected to establish the relationship between the model inputs and outputs. A comparative analysis was conducted, and results indicate that the proposed model outperforms others in terms of the least root mean square error (RMSE). The proposed hybrid model can be used to calculate contractor penalty in terms of cost overruns as well as incentive reward schedule in case of early work competition. Additionally, it can assist work zone planners in determining the best start and end times of a work zone for developing and evaluating traffic mitigation and management plans.
Travel times have been traditionally estimated from data collected by roadway sensors. Recently, ... more Travel times have been traditionally estimated from data collected by roadway sensors. Recently, new technologies, such as cell phone tracking, license plate matching, automatic vehicle identifications and video detection, are employed for this purpose. In this study, the data collected by TRANSMIT readers, Bluetooth sensors, and INRIX are assessed by comparing each to the "ground truth" travel times collected by probe vehicles carrying GPS-based navigation devices. Travel times of probe vehicles traveling on the study segment of I-287 in New Jersey were collected in 2009. Statistical measures, such as standard deviation, average absolute speed error, and speed error bias, were used to make an in-depth analysis. The accuracy of each travel time estimation method is analyzed. The data collected by Bluetooth sensors and the TRANSMIT readers seem more consistent with the ground true data, and slightly outperform the data reported by INRIX. This study established a procedure for analyzing the accuracy of floating car data (FCD) collected by different technologies.
This report presents research performed analyzing crashes in work zones in the state of New Jerse... more This report presents research performed analyzing crashes in work zones in the state of New Jersey so as to identify critical areas in work zones susceptible to crashes and key factors that contribute to these crashes. A field data collection on New Jersey roadways was performed for a select number of work zones to provide a better understanding of driver behavior in New Jersey work zones. The research also sought to identify where data needs are limited in evaluating work zone crashes in New Jersey and make recommendations on how the gaps in these needs can be addressed. Innovative strategies that hold potential for reducing work zone crashes were also identified. Crash frequency and crash severity models were developed to identify factors that contribute to number and severity of crashes in work zones. Negative binomial models were used to estimate: total number of crashes; frequency of injury crashes; and frequency of property damage only crashes. Binary logistic regression models were used to estimate severity for crashes where the driver is at fault, for drivers and for occupants in crashes at work zones. Recommendations on the operation and design of the work zone to reduce crash frequency and severity are presented based on the findings of the study.
Recent advance in VMS technology has made it viable to ease traffic congestion and improve road t... more Recent advance in VMS technology has made it viable to ease traffic congestion and improve road traffic efficiency. However, the drivers' low compliance with the posted information may limit its performance to ease traffic congestion and improve traffic safety. This paper explores drivers' attitude to the service quality of VMS system resulted from the identified predominant influencing factors. A questionnaire is developed and used for surveying 9,600 drivers in Beijing, China. The collected data are analyzed with a multiple indicators and multiple causes (MIMIC) model considering different driver categories (e.g., private car driver, office car driver, taxi driver). The results show that the causal relationships between latent variables and socio-demographic characteristic is significant. Driving frequency, attitude towards contents of VMS, drivers' decision-making and the effectiveness of VMS message can directly and indirectly affect driver's perceived quality of service. The attitude towards formats of VMS indirectly affect their QoS resulting from the effectiveness of VMS message, while there is no indirect impact for taxi drivers. Besides, the drivers' decisionmaking directly affects the perceived quality of service for private car drivers and office car drivers, but there is no impact for taxi drivers. The findings of this study can provide guidance and reference for urban authorities to perform the relevant actions required to meet user expectations.
Facing unprecedented increases in operational expenses, rail operators are seeking new methods to... more Facing unprecedented increases in operational expenses, rail operators are seeking new methods to reduce costs. Traction is their largest expense and despite their low energy intensities, the scale of operations causes large overall energy consumptions. This, coupled with the environmental impact of fossil fuel consumption is cause for concern. Modern railcars are equipped with the regenerative braking feature allowing them to generate electrical energy on braking. The energy can be stored for later use or transmitted directly to an accelerating train to reduce the energy used for acceleration. This study presents an intelligent method for harvesting the kinetic energy of an electric train through coasting and regenerative braking, and optimal positioning of the wayside energy storage system (WESS) units on a multi-segment rail line. Coasting saves energy by maintaining motion with propulsion disabled, and regenerative braking converts the kinetic energy of the train into electrical energy for the powering of subsequent acceleration cycles. The study entails the design of a model that simulates the movement of the train over an existing alignment section while considering alignment topography, speed limits, and train schedule. The main contribution of this research is the optimization of the number and locations of the WESS units using optimized speed profiles to maximize the net present value (NPV) of the energy recovery project. In this study, the optimized speed profiles are obtained with and without WESS installation and used as inputs to a linear programming (LP) simulation model. Hence, the model begins with inputs that are already optimized, ensuring a greater degree of processing speed and accuracy. The decision variables are the number and locations of the WESS units, and the output of the simulator is the optimized NPV. The results can be used for the planning of smart infrastructural
The road weather information system (RWIS), which collects and monitors weather and pavement surf... more The road weather information system (RWIS), which collects and monitors weather and pavement surface conditions, has been proven effective to support winter road maintenance by improving safety, mobility, and efficiency. Although the geographic information systems are being widely applied for facility siting, traditional practices of sitting RWIS stations still heavily rely on the experiences of maintenance and operation personnel, which is time-consuming and subjective. This study develops a linear model to determine the optimal RWIS locations subject to three selection criteria: weather, traffic condition, and distance to existing RWIS sites, while considering practical constraints to satisfy specific requirements of various agencies (e.g., different weights of weather/traffic factors, various available budgets, etc.).
Congestion is always a serious problem in many transportation commuting corridors. The need to im... more Congestion is always a serious problem in many transportation commuting corridors. The need to implement effective control in the corridors has long been recognized by transportation professionals. Ramp metering has been discussed as a viable control strategy on freeways in many places of the US, which may alleviate or at least reduce the delay. In this study, a dynamic ramp metering control model is developed to maximize the total throughput with simultaneous perturbation stochastic approximation (SPSA), subject to the constraints of link densities, capacities, and feasible range of metering rates. A case study for a segment of US I-80 in New Jersey is conducted, while the impact of the proposed ramp metering control on traffic behavior is simulated with CORSIM.
Ramp metering has been recognized as one of viable strategies of freeway traffic management, whic... more Ramp metering has been recognized as one of viable strategies of freeway traffic management, which may improve travel speed as well as reduce delay. In this study, a dynamic model is developed to optimize metering rates of a series of on-ramps which maximize the total throughput subject to vehicle density, roadway capacity, and queue length constraints with simultaneous perturbation stochastic approximation (SPSA). A calibrated microscopic traffic simulation model is used to evaluate the performance of the developed model. Results show that the total throughput of the studied freeway can be increased without increasing the total delay after implementing optimal metering rates. The developed SPSA has demonstrated itself as an efficient algorithm to search for the optimal solution of a dynamic, multivariate, and non-linear problem.
Accurate real-time traffic information is essential for the development of efficient traffic cont... more Accurate real-time traffic information is essential for the development of efficient traffic control and management. In recent years, private probe vehicle data has been employed by many public transportation agencies. However, most of those agencies have been unable to validate the accuracy of the purchased private probe data. This paper describes a sound methodology to evaluate the accuracy of estimated link travel speed by three probe data providers, which are INRIX, NAVTEQ, and TrafficCast, by using the ground truth travel speed of TRANSCOM‘s System for Managing Incidents & Traffic (TRANSMIT). The study route segments are on interstate 287 (I-287) and 78 (I-78) in New Jersey.
Although it is clear that adverse weather has an impact on roadway operating conditions, New Jers... more Although it is clear that adverse weather has an impact on roadway operating conditions, New Jersey had not performed research to quantify these impacts. To investigate the impact of adverse weather on New Jersey roadways, data on traffic parameters were collected under a variety of weather and light conditions. Speed, flow and density data were collected under no adverse weather, as well as under rain, snow, darkness and sun glare conditions. Comparisons were then made between traffic parameters under no adverse weather conditions, and under each weather and light condition. The study found that under rain conditions speeds decreased between 0.82 mi/hr (11%, 1.3 km/hr) and 37 mi/hr (61%, 59.2 km/hr). Under snow conditions speeds decrease between 5.8 mi/hr (15%, 9.3 km/hr) to 33.8 mi/hr (50%, 54 km/hr). Under rain and darkness conditions speeds were observed to both decrease from 0.71 mi/hr (1%, 1.1 km/hr) to 5.2 mi/hr (7%, 8.3 km/hr) and to also increase. Under snow and darkness co...
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