Pub Date : 2004-06-01DOI: 10.1109/ITSC.2002.1041332
Wei-Hua Lin, R. Bertini
Many existing algorithms for bus arrival time prediction assume that buses travel at free-flow speed in the absence of congestion. As a result, delay incurred at one stop would propagate to the downstream stops in the same magnitude. In reality, good bus operators often constantly adjust their speeds to keep the bus on schedule. This paper formulates a Markov chain model for bus arrival time prediction that explicitly captures the behavior of bus operators in pursuing schedule recovery. The model exhibits some desirable properties in capturing the schedule recovery process and guarantees provision of the schedule information if realtime information suddenly becomes unavailable. The proposed model can be embedded into a transit arrival time estimation model for transit information systems.
{"title":"Modeling schedule recovery processes in transit operations for bus arrival time prediction","authors":"Wei-Hua Lin, R. Bertini","doi":"10.1109/ITSC.2002.1041332","DOIUrl":"https://doi.org/10.1109/ITSC.2002.1041332","url":null,"abstract":"Many existing algorithms for bus arrival time prediction assume that buses travel at free-flow speed in the absence of congestion. As a result, delay incurred at one stop would propagate to the downstream stops in the same magnitude. In reality, good bus operators often constantly adjust their speeds to keep the bus on schedule. This paper formulates a Markov chain model for bus arrival time prediction that explicitly captures the behavior of bus operators in pursuing schedule recovery. The model exhibits some desirable properties in capturing the schedule recovery process and guarantees provision of the schedule information if realtime information suddenly becomes unavailable. The proposed model can be embedded into a transit arrival time estimation model for transit information systems.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125671573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-12-10DOI: 10.1109/ITSC.2002.1041224
D. Khosla
This paper describes a new model and method for accurate estimation of forward path geometry of an automobile. In this work, the forward geometry is modeled by two contiguous clothoid segments with different geometries, but continuous curvature across the transition between them. This results in a closed-form parametric expression of the same polynomial order as previous models. A recursive estimation method based on the new road model is also described. The performance evaluation of the proposed method on various simulated road geometries and comparisons with previous approaches demonstrate the feasibility and higher accuracy of the proposed method. This higher accuracy comes without a concomitant increase in computational cost or/and sensitivity to noise. The high accuracy estimation of forward path or road geometry is directly useful in applications that rely on detecting targets in the forward path of the host vehicle, e.g., adaptive cruise control and automotive collision warning.
{"title":"Accurate forward road geometry estimation for collision warning applications","authors":"D. Khosla","doi":"10.1109/ITSC.2002.1041224","DOIUrl":"https://doi.org/10.1109/ITSC.2002.1041224","url":null,"abstract":"This paper describes a new model and method for accurate estimation of forward path geometry of an automobile. In this work, the forward geometry is modeled by two contiguous clothoid segments with different geometries, but continuous curvature across the transition between them. This results in a closed-form parametric expression of the same polynomial order as previous models. A recursive estimation method based on the new road model is also described. The performance evaluation of the proposed method on various simulated road geometries and comparisons with previous approaches demonstrate the feasibility and higher accuracy of the proposed method. This higher accuracy comes without a concomitant increase in computational cost or/and sensitivity to noise. The high accuracy estimation of forward path or road geometry is directly useful in applications that rely on detecting targets in the forward path of the host vehicle, e.g., adaptive cruise control and automotive collision warning.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115308483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-30DOI: 10.1109/ITSC.2002.1041286
Stefano Stramigioli, V. Duindam
In this article, we describe a novel way to physically model the dynamics of the compliant contact between a tyre and the ground. We show how the use of a spatial spring results in an intuitive model and how screw bond graphs can be used to describe the various parts of the model in a power-consistent way.
{"title":"A novel lumped spatial model of tyre contact","authors":"Stefano Stramigioli, V. Duindam","doi":"10.1109/ITSC.2002.1041286","DOIUrl":"https://doi.org/10.1109/ITSC.2002.1041286","url":null,"abstract":"In this article, we describe a novel way to physically model the dynamics of the compliant contact between a tyre and the ground. We show how the use of a spatial spring results in an intuitive model and how screw bond graphs can be used to describe the various parts of the model in a power-consistent way.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121323207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-17DOI: 10.1109/ITSC.2002.1041322
A. Cappiello, I. Chabini, E. Nam, A. Lué, M. Abou Zeid
Many vehicle emission models am overly simple, such as the speed dependent models used widely, and other models are sufficiently complicated as to require excessive inputs and calculations, which can slow down computational time. We develop and implement an instantaneous statistical model of emissions (CO/sub 2/, CO, HC, and NOx) and fuel consumption for light duty vehicles, which is simplified from the physical load-based approaches that are gaining in popularity. The model is calibrated for a set of vehicles driven on standard as well as aggressive driving cycles. The model is validated on another driving cycle in order to, test its estimation capabilities. The preliminary results indicate that the model gives reasonable results compared to actual measurements as well as to results obtained with CMEM, a well-known load-based emission model. Furthermore, the results indicate that the model runs fast and is relatively simple to calibrate. The model presented can be integrated with a variety of traffic models to predict the spatial and temporal distribution of traffic emissions and assess the impact of ITS traffic management strategies on travel times, emissions, and fuel consumption.
{"title":"A statistical model of vehicle emissions and fuel consumption","authors":"A. Cappiello, I. Chabini, E. Nam, A. Lué, M. Abou Zeid","doi":"10.1109/ITSC.2002.1041322","DOIUrl":"https://doi.org/10.1109/ITSC.2002.1041322","url":null,"abstract":"Many vehicle emission models am overly simple, such as the speed dependent models used widely, and other models are sufficiently complicated as to require excessive inputs and calculations, which can slow down computational time. We develop and implement an instantaneous statistical model of emissions (CO/sub 2/, CO, HC, and NOx) and fuel consumption for light duty vehicles, which is simplified from the physical load-based approaches that are gaining in popularity. The model is calibrated for a set of vehicles driven on standard as well as aggressive driving cycles. The model is validated on another driving cycle in order to, test its estimation capabilities. The preliminary results indicate that the model gives reasonable results compared to actual measurements as well as to results obtained with CMEM, a well-known load-based emission model. Furthermore, the results indicate that the model runs fast and is relatively simple to calibrate. The model presented can be integrated with a variety of traffic models to predict the spatial and temporal distribution of traffic emissions and assess the impact of ITS traffic management strategies on travel times, emissions, and fuel consumption.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128389433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-03DOI: 10.1109/ITSC.2002.1041257
Jing Dong, Bing Xia, Jiang-tao Ren, Zuo Zhang, D. Yao
The study of dynamic route guidance model over a general road network has been deployed for some time in intelligent transportation systems (ITS) field. The paper presents the general formulation of the system optimal dynamic traffic assignment (DTA) problems, and enunciates the discrete form model. For the sake of computational convenience, the simplification of the model is explored according to the characteristics of realistic traffic system. Then the algorithm base on Lagrangian relaxation and quasi-Newton iteration is given to solve the simplified problem. Simulation is carried out to show the practicability and efficiency of the algorithm. Moreover some analysis on the simulation and guidance for future studies are presented at the end.
{"title":"An efficient solution to the system optimum dynamic traffic assignment problems based on Lagrangian relaxation","authors":"Jing Dong, Bing Xia, Jiang-tao Ren, Zuo Zhang, D. Yao","doi":"10.1109/ITSC.2002.1041257","DOIUrl":"https://doi.org/10.1109/ITSC.2002.1041257","url":null,"abstract":"The study of dynamic route guidance model over a general road network has been deployed for some time in intelligent transportation systems (ITS) field. The paper presents the general formulation of the system optimal dynamic traffic assignment (DTA) problems, and enunciates the discrete form model. For the sake of computational convenience, the simplification of the model is explored according to the characteristics of realistic traffic system. Then the algorithm base on Lagrangian relaxation and quasi-Newton iteration is given to solve the simplified problem. Simulation is carried out to show the practicability and efficiency of the algorithm. Moreover some analysis on the simulation and guidance for future studies are presented at the end.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116798961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-03DOI: 10.1109/ITSC.2002.1041266
S. Lam, T. Srikanthan
Intermodality in transportation systems is fast becoming a research topic of great interest. The computation of multiple paths in a multimodal network is desirable to identify efficient routes based on user preferences. This paper describes the clustering technique, which improves the performance of conventional k-shortest paths computations in multimodal transportation networks by first transforming the network into an acyclic representation through identification of cycles and clustering them into hypothetical nodes. The generalized Floyd algorithm is then applied on these clusters to compute the k-shortest paths. Simulation results show that the proposed technique significantly improves the performance of the conventional algorithm, particularly when the required number of k-shortest paths increases.
{"title":"Accelerating the k-shortest paths computation in multimodal transportation networks","authors":"S. Lam, T. Srikanthan","doi":"10.1109/ITSC.2002.1041266","DOIUrl":"https://doi.org/10.1109/ITSC.2002.1041266","url":null,"abstract":"Intermodality in transportation systems is fast becoming a research topic of great interest. The computation of multiple paths in a multimodal network is desirable to identify efficient routes based on user preferences. This paper describes the clustering technique, which improves the performance of conventional k-shortest paths computations in multimodal transportation networks by first transforming the network into an acyclic representation through identification of cycles and clustering them into hypothetical nodes. The generalized Floyd algorithm is then applied on these clusters to compute the k-shortest paths. Simulation results show that the proposed technique significantly improves the performance of the conventional algorithm, particularly when the required number of k-shortest paths increases.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127365214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-03DOI: 10.1109/ITSC.2002.1041300
P. Chandrasekar, W. Chan, Der-Horng Lee, S. Wee, R. Cheu
The Internet has enabled travelers to be kept updated with traffic and related travel information on their computer screens, PDAs (Personal Digital Assistant), and hand phones. The information can be either real-time or predictive. It has long been the interest of researchers to develop suitable methodologies and algorithms to obtain accurate predictive information about traffic conditions based on historical and/or current data. In this paper, the possibility of employing microscopic simulation to generate traffic and travel information that can be made available through the Internet is demonstrated The predictive information includes traffic speed, travel time and route guidance. PARAMICS, a sophisticated microscopic simulation program is used as the simulation engine behind the information generation process. The role of PARAMICS is to create a comprehensive database consisting of predictive information which is kept updated at pre-specified time intervals. The Application Programming Interface (API) of PARAMICS has been used to control and manage the whole process of information generation. The paper focuses on describing this process in detail.
{"title":"A simulation-driven internet-based predictive traffic information hub","authors":"P. Chandrasekar, W. Chan, Der-Horng Lee, S. Wee, R. Cheu","doi":"10.1109/ITSC.2002.1041300","DOIUrl":"https://doi.org/10.1109/ITSC.2002.1041300","url":null,"abstract":"The Internet has enabled travelers to be kept updated with traffic and related travel information on their computer screens, PDAs (Personal Digital Assistant), and hand phones. The information can be either real-time or predictive. It has long been the interest of researchers to develop suitable methodologies and algorithms to obtain accurate predictive information about traffic conditions based on historical and/or current data. In this paper, the possibility of employing microscopic simulation to generate traffic and travel information that can be made available through the Internet is demonstrated The predictive information includes traffic speed, travel time and route guidance. PARAMICS, a sophisticated microscopic simulation program is used as the simulation engine behind the information generation process. The role of PARAMICS is to create a comprehensive database consisting of predictive information which is kept updated at pre-specified time intervals. The Application Programming Interface (API) of PARAMICS has been used to control and manage the whole process of information generation. The paper focuses on describing this process in detail.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123658162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-03DOI: 10.1109/ITSC.2002.1041313
Jin-Tae Kim, Myung-soon Chang
The Highway Capacity Manual (HCM) suggests estimating the average green time for performance evaluation of vehicle-gap based traffic operation and provides an average green time estimation model. This paper proposes a new model that overcomes the shortcomings of the HCM model. Through a comparison study based on 1,196 pieces of hypothetical test data, it was found that the average green times estimated by the proposed method yields a much better one-to-one linear relationship to the simulation data representing field data than that from the HCM method in both exclusive-only and shared-permitted cases. The R/sup 2/ values of the proposed and HCM methods with these cases are 0.90 and 0.86, and 0.56 and 0.57, respectively.
{"title":"Development of an average green time estimation model for vehicle-gap based traffic operation","authors":"Jin-Tae Kim, Myung-soon Chang","doi":"10.1109/ITSC.2002.1041313","DOIUrl":"https://doi.org/10.1109/ITSC.2002.1041313","url":null,"abstract":"The Highway Capacity Manual (HCM) suggests estimating the average green time for performance evaluation of vehicle-gap based traffic operation and provides an average green time estimation model. This paper proposes a new model that overcomes the shortcomings of the HCM model. Through a comparison study based on 1,196 pieces of hypothetical test data, it was found that the average green times estimated by the proposed method yields a much better one-to-one linear relationship to the simulation data representing field data than that from the HCM method in both exclusive-only and shared-permitted cases. The R/sup 2/ values of the proposed and HCM methods with these cases are 0.90 and 0.86, and 0.56 and 0.57, respectively.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125266582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-03DOI: 10.1109/ITSC.2002.1041334
L. Weigang, W. Koendjbiharie, R.C. de M Juca, Y. Yamashita, A. MacIver
This paper presents a method to estimate bus arrival times at bus stops using GPS information, which was implemented in the SITCUO-Information System for Urban Bus Transportation, in Brasilia. The model consists of a main algorithm and two sub algorithms to determine the position and the speed of the bus en route. When using the speed information from the GPS, the arrival time at the stop point will be infinite if the vehicle is stationary. With the improved method and empirical calibration, the results from the developed model were found to be satisfactory in the implementation and experiment.
{"title":"Algorithms for estimating bus arrival times using GPS data","authors":"L. Weigang, W. Koendjbiharie, R.C. de M Juca, Y. Yamashita, A. MacIver","doi":"10.1109/ITSC.2002.1041334","DOIUrl":"https://doi.org/10.1109/ITSC.2002.1041334","url":null,"abstract":"This paper presents a method to estimate bus arrival times at bus stops using GPS information, which was implemented in the SITCUO-Information System for Urban Bus Transportation, in Brasilia. The model consists of a main algorithm and two sub algorithms to determine the position and the speed of the bus en route. When using the speed information from the GPS, the arrival time at the stop point will be infinite if the vehicle is stationary. With the improved method and empirical calibration, the results from the developed model were found to be satisfactory in the implementation and experiment.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126735218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-03DOI: 10.1109/ITSC.2002.1041258
M. Florian, M. Mahut, N. Tremblay
The evaluation of on-line intelligent transportation system (ITS) measures, such as adaptive route-guidance and traffic management systems, depend heavily on the use of faster than real time traffic simulation models. Fast-running traffic models are needed off-line for use in iterative approaches that imitate drivers' adaptation to changes to the network topology. The paper describes a simulation-based dynamic-equilibrium traffic assignment model. The determination of time-dependent path flows is modeled as a master problem that is solved using the method of successive averages (MSA). The determination of path travel times for a given set of path flows is the network-loading sub-problem, which is solved using the space-time queueing approach of Mahut (2000). This loading method has been shown to provide reasonably accurate results with very little computational effort. The model was applied to the Stockholm road network, which consists of 4342 links, 1980 nodes and 250 zones, representing over 11,000 turns. The results show that this model is applicable to medium-size networks with a very reasonable computation time.
{"title":"Application of a simulation-based dynamic traffic assignment model","authors":"M. Florian, M. Mahut, N. Tremblay","doi":"10.1109/ITSC.2002.1041258","DOIUrl":"https://doi.org/10.1109/ITSC.2002.1041258","url":null,"abstract":"The evaluation of on-line intelligent transportation system (ITS) measures, such as adaptive route-guidance and traffic management systems, depend heavily on the use of faster than real time traffic simulation models. Fast-running traffic models are needed off-line for use in iterative approaches that imitate drivers' adaptation to changes to the network topology. The paper describes a simulation-based dynamic-equilibrium traffic assignment model. The determination of time-dependent path flows is modeled as a master problem that is solved using the method of successive averages (MSA). The determination of path travel times for a given set of path flows is the network-loading sub-problem, which is solved using the space-time queueing approach of Mahut (2000). This loading method has been shown to provide reasonably accurate results with very little computational effort. The model was applied to the Stockholm road network, which consists of 4342 links, 1980 nodes and 250 zones, representing over 11,000 turns. The results show that this model is applicable to medium-size networks with a very reasonable computation time.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122837411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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