Mashrur Chowdhury
Clemson University, CIVIL ENGINEERING, Faculty Member
- Dr. Chowdhury is the Eugene Douglas Mays Chair of Transportation in the Glenn Department of Civil Engineering at Clem... moreDr. Chowdhury is the Eugene Douglas Mays Chair of Transportation in the Glenn Department of Civil Engineering at Clemson University. He is also a professor in the Department of Automotive Engineering at Clemson University and a member of the Clemson University International Center of Automotive Research (CU ICAR). Dr. Chowdhury is a Co-Director of the Complex Systems, Data Analytics and Visualization Institute (CSAVI) at Clemson University.edit
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Dwindling revenue sources force transportation engineers to implement less durable solutions to distribute limited resources to the most critical and competing maintenance and development projects. However, implementing less durable... more
Dwindling revenue sources force transportation engineers to implement less durable solutions to distribute limited resources to the most critical and competing maintenance and development projects. However, implementing less durable solutions often increases the infrastructure life cycle costs. Several recent studies have found that a significant portion of truck traffic operates with weights above legal weight limits, which are not considered in current pavement design practices. These overweight trucks cause accelerated pavement deterioration. In this study, authors investigated the deterioration of pavements to quantify relative pavement damage attributed to overweight trucks compared to trucks within legal weight limits. In South Carolina, weigh-in-motion data revealed that 8.3% trucks were either axle overweight or gross vehicle overweight. To accommodate these 8.3% overweight trucks, which are not considered in the current equivalent single axle load (ESAL) based design method, the hot-mix asphalt (HMA) base layer thickness should be increased by 1% to 6% depending on the roadway functional class. The mechanistic-empirical pavement design guide (MEPDG)-based analysis showed that all types of pavement distress increase with increasing truck gross vehicle weight. Among all distress types, fatigue cracking (top-down and bottom-up) was more sensitive to overweight trucks (up to the typical overweight permit limit) compared to rutting and international roughness index (IRI). Similarly, cracking was more sensitive to trucks loaded above typical overweight permit limit (i.e., superload) compared to rutting or IRI. To maximize the infrastructure service life and minimize life cycle costs, transportation agencies should consider accelerated pavement deterioration due to overweight trucks in pavement design.
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AbstractOf all roadway vehicles, trucks inflict the greatest deterioration to pavements and bridges owing to their heavy gross weights and axle loads. States issue permits to trucks beyond legal weight limits and collect fees to... more
AbstractOf all roadway vehicles, trucks inflict the greatest deterioration to pavements and bridges owing to their heavy gross weights and axle loads. States issue permits to trucks beyond legal weight limits and collect fees to compensate for additional damage. To study the extent to which state departments of transportation (DOTs) have allowed passage of overweight loads, the first objective of this paper was to characterize overweight load permit practices among all U.S. states, and the second objective was to identify stakeholders’ perspectives on how to modernize current overweight permit practices. Through an analysis of existing fee policies, this research has characterized the state of the practice in permit fees for overweight loads on public roadways, and evaluated these practices. The subsequent data showed a wide array of policies on overweight permitting, such that a single interstate overweight freight trip might encounter several diverse overweight permitting policies. Although the range of...
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In this paper, we theoretically develop and numerically validate an asymmetric linear bilateral control model (LBCM), in which the motion information (e.g., position and speed) from the immediate leading and following vehicles are... more
In this paper, we theoretically develop and numerically validate an asymmetric linear bilateral control model (LBCM), in which the motion information (e.g., position and speed) from the immediate leading and following vehicles are weighted differently. The novelty of the asymmetric LBCM is that using this model all the follower vehicles in a platoon can adjust their acceleration and deceleration to closely follow a constant desired time gap to improve platoon operational efficiency while maintaining local and string stability. We theoretically analyze the local stability of the asymmetric LBCM using the condition for asymptotic stability of a linear time-invariant system and prove the string stability of the asymmetric LBCM using a space gap error attenuation approach. Then, we evaluate the efficacy of the asymmetric LBCM by simulating a closely coupled cooperative adaptive cruise control (CACC) platoon of fully automated trucks in various non-linear acceleration and deceleration st...
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Annual Average Daily Traffic (AADT) is an important parameter used in traffic engineering analysis. Departments of Transportation (DOTs) continually collect traffic count using both permanent count stations (i.e., Automatic Traffic... more
Annual Average Daily Traffic (AADT) is an important parameter used in traffic engineering analysis. Departments of Transportation (DOTs) continually collect traffic count using both permanent count stations (i.e., Automatic Traffic Recorders or ATRs) and temporary short-term count stations. In South Carolina, 87% of the ATRs are located on interstates and arterial highways. For most secondary highways (i.e., collectors and local roads), AADT is estimated based on short-term counts. This paper develops AADT estimation models for different roadway functional classes with two machine learning techniques: Artificial Neural Network (ANN) and Support Vector Regression (SVR). The models aim to predict AADT from short-term counts. The results are first compared against each other to identify the best model. Then, the results of the best model are compared against a regression method and factor-based method. The comparison reveals the superiority of SVR for AADT estimation for different road...
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This research used microscopic simulation to evaluate operational performance and feasibility of signal priority for connected vehicles (CV) at a signalized intersection. CVs with signal priority were simulated with penetration levels... more
This research used microscopic simulation to evaluate operational performance and feasibility of signal priority for connected vehicles (CV) at a signalized intersection. CVs with signal priority were simulated with penetration levels ranging from 10% to 100% as well as with various combinations of directions being allowed to request priority. These scenarios were compared to optimized signal timings without any priority to determine the effectiveness of the system in terms of average delay. It was discovered that CV with signal priority experienced less delay than non-CV for all priority direction scenarios studied up to a certain penetration level. When all directions and major street movements in both directions are allowed to request priority, the advantage for CVs was statistically significant up to 20% CV penetration. When priority was only allowed to be requested in the direction of highest flow, CVs experienced lower delay at a statistically significant level up to 40% CV pe...
Research Interests: Engineering and Revenue
The prediction of high-resolution hourly traffic volumes of a given roadway is essential for transportation planning. Traditionally, automatic traffic recorders (ATR) are used to collect these hourly volume data. These large datasets are... more
The prediction of high-resolution hourly traffic volumes of a given roadway is essential for transportation planning. Traditionally, automatic traffic recorders (ATR) are used to collect these hourly volume data. These large datasets are time-series data characterized by long-term temporal dependencies and missing values. Regarding the temporal dependencies, all roadways are characterized by seasonal variations that can be weekly, monthly or yearly, depending on the cause of the variation. Traditional time-series forecasting models perform poorly when they encounter missing data in the dataset. To address this limitation, robust, recurrent neural network (RNN)-based, multi-step-ahead forecasting models are developed for time-series in this study. The simple RNN, the gated recurrent unit (GRU) and the long short-term memory (LSTM) units are used to develop the forecasting models and evaluate their performance. Two approaches are used to address the missing value issue: masking and im...
Research Interests: Engineering, Civil Engineering, Mathematics, Computer Science, Statistics, and 9 moreTime Series, Urban And Regional Planning, Recurrent Neural Network, Missing Data, Autoregressive Integrated Moving Average, Civil and Environmental Engineering, Artificial Neural Network, Mean Absolute Percentage Error, and Mean Squared Error
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The connected vehicle (CV) system promises unprecedented safety, mobility, environmental, economic, and social benefits, which can be unlocked using the enormous amount of data shared between vehicles and infrastructure (e.g., traffic... more
The connected vehicle (CV) system promises unprecedented safety, mobility, environmental, economic, and social benefits, which can be unlocked using the enormous amount of data shared between vehicles and infrastructure (e.g., traffic signals, centers). Real-world CV deployments, including pilot deployments, help solve technical issues and observe potential benefits, both of which support the broader adoption of the CV system. This study focused on the Clemson University Connected Vehicle Testbed (CU-CVT) with the goal of sharing the lessons learned from the CU-CVT deployment. The motivation of this study was to enhance early CV deployments with the objective of depicting the lessons learned from the CU-CVT testbed, which includes unique features to support multiple CV applications running simultaneously. The lessons learned in the CU-CVT testbed are described at three different levels: (i) the development of system architecture and prototyping in a controlled environment, (ii) the ...
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A connected vehicle (CV) environment is comprised of diverse computing infrastructure, data communication and dissemination, and data collection systems that are vulnerable to the same cyberattacks as all traditional computing... more
A connected vehicle (CV) environment is comprised of diverse computing infrastructure, data communication and dissemination, and data collection systems that are vulnerable to the same cyberattacks as all traditional computing environments. Cyberattacks can jeopardize the expected safety, mobility, energy, and environmental benefits from CV applications. As cyberattacks can lead to severe consequences such as traffic incidents, it has become one of the primary concerns in CV applications. In this paper, we evaluate the impact of cyberattacks on the vehicle-to-infrastructure (V2I) network from a V2I application point of view. Then, we develop a novel V2I cybersecurity architecture, named CVGuard, which can detect and prevent cyberattacks on the V2I applications. In designing CVGuard, key challenges, such as scalability, resiliency and future usability were considered. A case study using a distributed denial of service (DDoS) attack on a V2I application, “Stop Sign Gap Assist (SSGA)” ...
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Urban arterials are characterised by high traffic volume, and driveway densities which cause congestion and crashes. In urban arterials, safety and operational issues can be improved by access management strategies. One such strategy is... more
Urban arterials are characterised by high traffic volume, and driveway densities which cause congestion and crashes. In urban arterials, safety and operational issues can be improved by access management strategies. One such strategy is to restrict traffic entering the urban arterial to ‘right-in–right-out’ through implementing a raised median. While past research has shown the operational benefits of this strategy, it has not been evaluated in the context of dynamic access control. This study investigates the effectiveness of the connected vehicle (CV)-supported dynamic access control. The analysis is applied to an urban corridor under four scenarios: (i) the existing condition with direct left turns (DLTs) permitted at all driveways, (ii) a raised median restricting all driveway traffic to right-in–right-out and U-turns permitted at signallised intersections, (iii) a peak-hour DLT restriction at all driveways, and (iv) dynamic restriction (i.e. a restriction enforced during the time intervals in which traffic flow rates exceed given thresholds) of driveways to right-in–right-out in a CV environment. On the basis of the simulation analysis, it was found that converting driveway access from fully open to right-in–right-out based on prevailing traffic conditions in a CV environment can improve traffic operations.
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Annual Average Daily Traffic (AADT) is an important parameter for traffic engineering analysis. Departments of Transportation continually collect traffic count using both permanent count stations (i.e., Automatic Traffic Recorders or... more
Annual Average Daily Traffic (AADT) is an important parameter for traffic engineering analysis. Departments of Transportation continually collect traffic count using both permanent count stations (i.e., Automatic Traffic Recorders or ATRs) and temporary short-term count stations. In South Carolina, 87% of the ATRs are located on interstates and arterial highways. For most secondary highways (i.e., collectors and local roads), AADT is estimated based on short-term counts. This paper develops AADT estimation models for different roadway functional classes with two machine learning techniques: Support Vector Regression (SVR) and Artificial Neural Network (ANN). The models predict AADT from short-term counts. The results are first compared against each other, using the 2011 ATR data, to identify the best models. Then, the results of the best models are compared against both the regression-based model and factor-based model. The comparison reveals the superiority of the SVR model for AAD...
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The introduction of autonomous vehicles in the surface transportation system could improve traffic safety and reduce traffic congestion and negative environmental effects. Although the continuous evolution in computing, sensing, and... more
The introduction of autonomous vehicles in the surface transportation system could improve traffic safety and reduce traffic congestion and negative environmental effects. Although the continuous evolution in computing, sensing, and communication technologies can improve the performance of autonomous vehicles, the new combination of autonomous automotive and electronic communication technologies will present new challenges, such as interaction with other nonautonomous vehicles, which must be addressed before implementation. The objective of this study was to identify the risks associated with the failure of an autonomous vehicle in mixed traffic streams. To identify the risks, the autonomous vehicle system was first disassembled into vehicular components and transportation infrastructure components, and then a fault tree model was developed for each system. The failure probabilities of each component were estimated by reviewing the published literature and publicly available data so...
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A complex and vast amount of data will be collected from on-board sensors of operational connected vehicles (CVs), infrastructure data sources such as roadway sensors and traffic signals, mobile data sources such as cell phones, social... more
A complex and vast amount of data will be collected from on-board sensors of operational connected vehicles (CVs), infrastructure data sources such as roadway sensors and traffic signals, mobile data sources such as cell phones, social media sources such as Twitter, and news and weather data services. Unfortunately, these data will create a bottleneck at data centers for processing and retrievals of collected data, and will require the deployment of additional message transfer infrastructure between data producers and consumers to support diverse CV applications. In this paper, we present a strategy for creating an efficient and low-latency distributed message delivery system for CV applications using a distributed message delivery platform. This strategy enables large-scale ingestion, curation, and transformation of unstructured data (roadway traffic-related and roadway non-traffic-related data) into labeled and customized topics for a large number of subscribers or consumers, such as CVs, mobile devices, and data centers. We evaluate the performance of this strategy by developing a prototype infrastructure using Apache Kafka, an open source message delivery system, and compared its performance with the latency requirements of CV applications. We present experimental results of the message delivery infrastructure on two different distributed computing testbeds at Clemson University: the Holocron cluster and the Palmetto cluster. Experiments were performed to measure the latency of the message delivery system for a variety of testing scenarios. These experiments reveal that measured latencies are less than the U.S. Department of Transportation recommended latency requirements for CV applications, which prove the efficacy of the system for CV related data distribution and management tasks.
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This study examined the current state of the incident management industry in the US by reviewing the available published literature, and by launching a nationwide survey of multiple incident management agencies. The study also evaluated... more
This study examined the current state of the incident management industry in the US by reviewing the available published literature, and by launching a nationwide survey of multiple incident management agencies. The study also evaluated the specific impact of traffic incidents on both motorists and the environment on South Carolina freeways by using traffic simulation and benefit-cost analysis. Survey responses revealed that technologies such as traffic cameras, dispatched personnel, and freeway service patrols were the most successful in detecting and verifying incidents. Responses also emphasized the importance of effective institutional coordination, and communication to both the public and decision makers for a successful incident management program. Through traffic simulation analysis, researchers examined the effectiveness of traffic sensors, traffic cameras, freeway service patrols, a multiple-strategy approach, a Steer-it Clear-it law, and route diversion. Results of the benefit-cost analysis indicated that using traffic sensors, traffic cameras, freeway service patrols, and a combination of these strategies with an incident report hot line, produced $7, $12, $11, and $8 of benefit for each dollar invested, respectively. The Steer-it Clear-it scenario produced approximately $22 for each dollar invested if all drivers were aware of and obeyed the law. The route diversion strategy, evaluated for severe crashes, produced approximately $55 for every dollar invested with 100 percent compliance rate.
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Intelligent Transportation System (ITS) enhances the performance of modern transportation systems by improving the reliability of travel times and reducing the risk of collisions. Because of these benefits, state departments of... more
Intelligent Transportation System (ITS) enhances the performance of modern transportation systems by improving the reliability of travel times and reducing the risk of collisions. Because of these benefits, state departments of transportation (DOTs) and other transportation agencies have been increasingly deploying these tools since the mid 1990’s. Recently, many public agencies have expressed a need to manage their ITS systems more effectively and efficiently. ITS asset management tools can help state DOTs meet their requirements of managing ITS-associated resources, which often includes technologically sophisticated devices, computer hardware and software, and communications infrastructure. Because ITS asset management is new to many DOTs, there is a need to evaluate different asset management systems for their potential efficacy for supporting public agency’s ITS needs. Establishing the requirements to evaluate such systems is the primary contribution of this paper. The requirements presented were identified through a nationwide survey of public transportation agencies.
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ABSTRACT
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This chapter contains sections titled: IntroductionElements of Computer Network SecurityImportance of Computer Network SecurityApproach to Computer Network SecurityComputer Network Security in ITSNetwork Security ObjectivesFuture of... more
This chapter contains sections titled: IntroductionElements of Computer Network SecurityImportance of Computer Network SecurityApproach to Computer Network SecurityComputer Network Security in ITSNetwork Security ObjectivesFuture of Network Security and Its Impacts on Securing ITS NetworkReferencesReview QuestionsIntroductionElements of Computer Network SecurityImportance of Computer Network SecurityApproach to Computer Network SecurityComputer Network Security in ITSNetwork Security ObjectivesFuture of Network Security and Its Impacts on Securing ITS NetworkReferencesReview Questions
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This appendix contains sections titled: PrefaceSummaryElectronic Access and FilingBackgroundThe National ITS ArchitectureTransportation Equity Act for the 21st CenturyITS Architecture and Standards NPRM Discussion of CommentsSummary of... more
This appendix contains sections titled: PrefaceSummaryElectronic Access and FilingBackgroundThe National ITS ArchitectureTransportation Equity Act for the 21st CenturyITS Architecture and Standards NPRM Discussion of CommentsSummary of RequirementsRulemaking Analyses and NoticesPart 940—Intelligent Transportation System Architecture and StandardsPrefaceSummaryElectronic Access and FilingBackgroundThe National ITS ArchitectureTransportation Equity Act for the 21st CenturyITS Architecture and Standards NPRM Discussion of CommentsSummary of RequirementsRulemaking Analyses and NoticesPart 940—Intelligent Transportation System Architecture and Standards
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Motivated by Title 23 Code of Federal Regulation 511, the U.S. Department of Transportation has recently established real-time systems management information programs to improve the consistency of traveler information provided to the... more
Motivated by Title 23 Code of Federal Regulation 511, the U.S. Department of Transportation has recently established real-time systems management information programs to improve the consistency of traveler information provided to the public. Part of these requirements is to review the quality of the information provided to the public. Because limited information is available about current practices for meeting this new regulation, this article presents a method of evaluating real-time travel time information along metropolitan interstate freeways in the context of 23 CFR (Code of Federal Regulations) 511. This article presents a method and a case study of collecting travel time information from multiple sources (such as Google Maps and TravelMidwest.com ) and comparing them to measure accuracy. The findings suggested that the travel time information in the Chicago, Illinois, metropolitan area meets the accuracy requirements of 23 CFR 511, and this study has identified areas for futu...
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Research Interests: Psychology, Mathematics, Econometrics, Statistics, Medicine, and 12 moreLogistic Regression, Safety, Crash, Probit, Accident analysis and prevention, Public health systems and services research, Akaike Information Criterion, Civil and Environmental Engineering, Logit, Probit Model, Crash Severity, and Ordered probit
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A modern vehicle contains many electronic control units (ECUs), which communicate with each other through the in-vehicle network to ensure vehicle safety and performance. Emerging Connected and Automated Vehicles (CAVs) will have more... more
A modern vehicle contains many electronic control units (ECUs), which communicate with each other through the in-vehicle network to ensure vehicle safety and performance. Emerging Connected and Automated Vehicles (CAVs) will have more ECUs and coupling between them due to the vast array of additional sensors, advanced driving features and Vehicle-to-Everything (V2X) connectivity. Due to the connectivity, CAVs will be more vulnerable to remote attackers. In this study, we developed a software-defined in-vehicle Ethernet networking system that provides security against false information attacks. We then created an attack model and attack datasets for false information attacks on brake-related ECUs. After analyzing the attack dataset, we found that the features of the dataset are time-series that have sequential variation patterns. Therefore, we subsequently developed a long short term memory (LSTM) neural network based false information attack/anomaly detection model for the real-time...
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Cooperative Adaptive Cruise Control (CACC) is a pivotal vehicular application that would allow transportation field to achieve its goals of increased traffic throughput and roadway capacity. This application is of paramount interest to... more
Cooperative Adaptive Cruise Control (CACC) is a pivotal vehicular application that would allow transportation field to achieve its goals of increased traffic throughput and roadway capacity. This application is of paramount interest to the vehicular technology community with a large body of literature dedicated to research within different aspects of CACC, including but not limited to security with CACC. Of all available literature, the overwhelming focus in on CACC utilizing vehicle-to-vehicle (V2V) communication. In this work, we assert that a qualitative increase in vehicle-to-infrastructure (V2I) and infrastructure-to-vehicle (I2V) involvement has the potential to add greater value to CACC. In this study, we developed a strategy for detection of a denial-of-service (DoS) attack on a CACC platoon where the system edge in the vehicular network plays a central role in attack detection. The proposed security strategy is substantiated with a simulation-based evaluation using the ns-3...
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The transportation system is rapidly evolving with new connected and automated vehicle (CAV) technologies that integrate CAVs with other vehicles and roadside infrastructure in a cyberphysical system (CPS). Through connectivity, CAVs... more
The transportation system is rapidly evolving with new connected and automated vehicle (CAV) technologies that integrate CAVs with other vehicles and roadside infrastructure in a cyberphysical system (CPS). Through connectivity, CAVs affect their environments and vice versa, increasing the size of the cyberattack surface and the risk of exploitation of security vulnerabilities by malicious actors. Thus, greater understanding of potential CAV-CPS cyberattacks and of ways to prevent them is a high priority. In this article we describe CAV-CPS cyberattack surfaces and security vulnerabilities, and outline potential cyberattack detection and mitigation strategies. We examine emerging technologies - artificial intelligence, software-defined networks, network function virtualization, edge computing, information-centric and virtual dispersive networking, fifth generation (5G) cellular networks, blockchain technology, and quantum and postquantum cryptography - as potential solutions aiding ...
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Identification of influential nodes is an important step in understanding and controlling the dynamics of information, traffic, and spreading processes in networks. As a result, a number of centrality measures have been proposed and used... more
Identification of influential nodes is an important step in understanding and controlling the dynamics of information, traffic, and spreading processes in networks. As a result, a number of centrality measures have been proposed and used across different application domains. At the heart of many of these measures lies an assumption describing the manner in which traffic (of information, social actors, particles, etc.) flows through the network. For example, some measures only count shortest paths while others consider random walks. This paper considers a spreading process in which a resource necessary for transit is partially consumed along the way while being refilled at special nodes on the network. Examples include fuel consumption of vehicles together with refueling stations, information loss during dissemination with error-correcting nodes, and consumption of ammunition of military troops while moving. We propose generalizations of the well-known measures of betweenness, random...
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A modern vehicle contains many electronic control units (ECUs), which communicate with each other through the in-vehicle network to ensure vehicle safety and performance. Emerging Connected and Automated Vehicles (CAVs) will have more... more
A modern vehicle contains many electronic control units (ECUs), which communicate with each other through the in-vehicle network to ensure vehicle safety and performance. Emerging Connected and Automated Vehicles (CAVs) will have more ECUs and coupling between them due to the vast array of additional sensors, advanced driving features and Vehicle-to-Everything (V2X) connectivity. Due to the connectivity, CAVs will be more vulnerable to remote attackers. In this study, we developed a software-defined in-vehicle Ethernet networking system that provides security against false information attacks. We then created an attack model and attack datasets for false information attacks on brake-related ECUs. After analyzing the attack dataset, we found that the features of the dataset are time-series that have sequential variation patterns. Therefore, we subsequently developed a long short term memory (LSTM) neural network based false information attack/anomaly detection model for the real-time detection of anomalies within the in-vehicle network. This attack detection model can detect false information with an accuracy, precision and recall of 95%, 95% and 87%, respectively, while satisfying the real-time communication and computational requirements. Index Terms-Anomaly detection, automotive Ethernet, controller area network (CAN), information security, in-vehicle network, long short term memory, software-defined networking (SDN).