Pub Date : 2000-01-01DOI: 10.1080/10248070008903774
M. A. Do
This paper describes the design and evaluation of an electronic road pricing (ERP) system for use in a multi-lane city road environment. The system is formed by an automatic vehicle identification-debiting (AVID) system, a vehicle position detector (VPD), and an enforcement camera system (ECS). The evaluation covered various aspects, including the design, the performance of subsystems, and of the integrated system, the system reliability, and the system qualification tests (SQT) prior to the production and implementation. The SQT result shows an unprecedented performance of the AVID system with one communication error in the first 1.3 million transactions and no communication errors in the second 1.3 million transactions. All violations were successfully detected by the enforcement camera system with about 12% of redundant images.
{"title":"An Electronic Road Pricing System Designed for the Busy Multi-lane Road Environment","authors":"M. A. Do","doi":"10.1080/10248070008903774","DOIUrl":"https://doi.org/10.1080/10248070008903774","url":null,"abstract":"This paper describes the design and evaluation of an electronic road pricing (ERP) system for use in a multi-lane city road environment. The system is formed by an automatic vehicle identification-debiting (AVID) system, a vehicle position detector (VPD), and an enforcement camera system (ECS). The evaluation covered various aspects, including the design, the performance of subsystems, and of the integrated system, the system reliability, and the system qualification tests (SQT) prior to the production and implementation. The SQT result shows an unprecedented performance of the AVID system with one communication error in the first 1.3 million transactions and no communication errors in the second 1.3 million transactions. All violations were successfully detected by the enforcement camera system with about 12% of redundant images.","PeriodicalId":273303,"journal":{"name":"ITS Journal - Intelligent Transportation Systems Journal","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125232244","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 : 2000-01-01DOI: 10.1080/10248070008903772
E. Bekiaris, M. Dangelmaier
This paper describes the conceptualisation of the in-car HMI of a driver monitoring and emergency handling system within the European Union Transport Telematics project SAVE (TR 1047). An integrated Rapid Prototyping approach using product scenarios and computer demonstration/simulation of the HMI has been applied. Expert and user tests with the demonstrator/simulator have been performed and valuable hints for the optimisation of the HMI concept have been derived. Principle problems of the HMI design of SAVE type systems have been identified. The approach has proved to be useful in the conceptualisation of the HMI of in-car telematic systems. Due to a restricted correspondence of computer simulation and reality, additional testing in driving simulators and demonstrator cars is required.
{"title":"Conceptualisation of the Human-Machine Interface of an Integrated Driver Monitoring and Emergency Handling System","authors":"E. Bekiaris, M. Dangelmaier","doi":"10.1080/10248070008903772","DOIUrl":"https://doi.org/10.1080/10248070008903772","url":null,"abstract":"This paper describes the conceptualisation of the in-car HMI of a driver monitoring and emergency handling system within the European Union Transport Telematics project SAVE (TR 1047). An integrated Rapid Prototyping approach using product scenarios and computer demonstration/simulation of the HMI has been applied. Expert and user tests with the demonstrator/simulator have been performed and valuable hints for the optimisation of the HMI concept have been derived. Principle problems of the HMI design of SAVE type systems have been identified. The approach has proved to be useful in the conceptualisation of the HMI of in-car telematic systems. Due to a restricted correspondence of computer simulation and reality, additional testing in driving simulators and demonstrator cars is required.","PeriodicalId":273303,"journal":{"name":"ITS Journal - Intelligent Transportation Systems Journal","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126418453","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 : 2000-01-01DOI: 10.1080/10248070008903775
C. Grant, Bret Gillis, R. Guensler
Advanced traffic management systems allow video image detection to supplement and improve data inputs in transportation modeling efforts. Video detection systems use machine vision technology, the interaction of video cameras, and specialty computer hardware and software to measure traffic. Traffic parameters such as hourly flows, density, vehicle speed, level of service, and other parameters derived from measured and default values are automatically computed. However, the accuracy of video image detection systems is dependent upon factors such as the camera height, location, and angle above the roadway. Environmental factors such as rain, sun intensity, and day/night also affect vehicle detection accuracy. Existing transportation models can benefit from video image detection technology and improved travel demand models can be developed from such data, providing video detection is accurate. This paper examines how transportation models can benefit from video data. A commercially available system is used to collect data from freeway segments in Atlanta, Georgia. The detected vehicle counts, classifications, and average speeds are compared to true counts obtained over the same interval. Differences in these traffic parameters are determined as a function of camera location and site conditions that constrain the accuracy of video detection. The analytical results lead to recommendations on use of video detected traffic parameters in model improvement.
{"title":"Collection of Vehicle Activity Data by Video Detection for Use in Transportation Planning","authors":"C. Grant, Bret Gillis, R. Guensler","doi":"10.1080/10248070008903775","DOIUrl":"https://doi.org/10.1080/10248070008903775","url":null,"abstract":"Advanced traffic management systems allow video image detection to supplement and improve data inputs in transportation modeling efforts. Video detection systems use machine vision technology, the interaction of video cameras, and specialty computer hardware and software to measure traffic. Traffic parameters such as hourly flows, density, vehicle speed, level of service, and other parameters derived from measured and default values are automatically computed. However, the accuracy of video image detection systems is dependent upon factors such as the camera height, location, and angle above the roadway. Environmental factors such as rain, sun intensity, and day/night also affect vehicle detection accuracy. Existing transportation models can benefit from video image detection technology and improved travel demand models can be developed from such data, providing video detection is accurate. This paper examines how transportation models can benefit from video data. A commercially available system is used to collect data from freeway segments in Atlanta, Georgia. The detected vehicle counts, classifications, and average speeds are compared to true counts obtained over the same interval. Differences in these traffic parameters are determined as a function of camera location and site conditions that constrain the accuracy of video detection. The analytical results lead to recommendations on use of video detected traffic parameters in model improvement.","PeriodicalId":273303,"journal":{"name":"ITS Journal - Intelligent Transportation Systems Journal","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131049432","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 : 2000-01-01DOI: 10.1080/10248070008903681
R. Holland
In this paper, emerging technologies and applications are identified that could be used to present travellers with higher quality information about public transport services. The concept of real-time information is introduced and the means of delivering such information are compared to the methods that can be used for disseminating trip planning information.
{"title":"Future Directions for Passenger Information: A Review of the Potential Application to Public Transport in the UK","authors":"R. Holland","doi":"10.1080/10248070008903681","DOIUrl":"https://doi.org/10.1080/10248070008903681","url":null,"abstract":"In this paper, emerging technologies and applications are identified that could be used to present travellers with higher quality information about public transport services. The concept of real-time information is introduced and the means of delivering such information are compared to the methods that can be used for disseminating trip planning information.","PeriodicalId":273303,"journal":{"name":"ITS Journal - Intelligent Transportation Systems Journal","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133314207","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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