Show simple item record

dc.contributor.author Pilanavithana, US
dc.contributor.author Bandara, JMSJ
dc.contributor.editor Pasindu, HR
dc.date.accessioned 2022-06-09T06:29:03Z
dc.date.available 2022-06-09T06:29:03Z
dc.date.issued 2011
dc.identifier.citation Pilanavithana, U.S., & Bandara, J.M.S.J. (2011). Dynamic travel time estimation model for real time travelers [Abstract]. In H.R. Pasindu (Ed.), Proceedings of the Transportation Research Forum 2011 (pp.13-14). Department of Civil Engineering, University of Moratuwa. https://uom.lk/sites/default/files/civil/files/TRF%202011_0.pdf en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/18226
dc.description.abstract A broad range of diverse technologies, known collectively as intelligent transportation systems (ITS), holds the answer to many of our society's transportation problems. ITS are comprised of existing and new technologies, including information processing, sensors, communications, control, and electronics. Combining these technologies in innovative ways and integrating them into our multimodal transportation system will save lives, time, and resources. Transportation is the backbone of our society—the movement of people and goods provides the foundation of our quality of life and economic prosperity. Various methodologies have been developed for dynamic travel time prediction. With the development of the Advanced Travelers Information Systems (ATIS), short-term travel time prediction is becoming increasingly important. As a key input for the dynamic route guidance system, travel time information enables the generation of the shortest path (or alternative paths) connecting the origins (or current locations) and destinations. Traffic estimation and prediction system (TrEPS) have the potential to improve traffic conditions and reduce travel delays by facilitating better utilization of available capacity. Moreover, a Short-term travel time prediction is incredibly significant to the real time travelers' information and route guidance system to hang on to the finest path during their route to the desired destination. In this research, to fulfill the first objective a model for estimating path flows and modifying O-D flows simultaneously is proposed based on probabilistic information (Route selection behaviour of drivers) and traffic counts. The probabilistic information is accumulated to obtain prior information on path proportions. The link traffic counts are used as sectional volume information of links. The proposed model is constructed as a two stage model. The first stage model is estimation model of path flows and the second stage model is modification model of O-D flows. Moreover, it was clarified that the proposed two stage model had enough ability to estimate path flows and to modify O-D flows accurately even when prior O-D flows had inconsistency with the current traffic conditions. By satisfying the Second objective, improved speed flow relationship employed which was focused on refining the speed estimates of network assignment models by using the modified Akçelik speed-flow model along with the literature findings. This Akçelik model produces significantly improved traffic assignment run times and provides more accurate speed estimates which lead accurate travel times to assure the last objective of identify the best path based on travel time using minimum real time information available. In Conclusion, the estimation of link flows and modifying the O - D flows can be performed by two stages modal and travel time will be projected by the improved speed flow relationship. Projected travel time facilitates the selecting best path or the alternative for the user destination. Furthermore, integrate a method which will automatically update the system data base with the latest traffic data corresponding to road links and give the most up-to-date best travel time path to the road user is proposed as future development. en_US
dc.language.iso en en_US
dc.publisher Department of Civil Engineering, University of Moratuwa en_US
dc.relation.uri https://uom.lk/sites/default/files/civil/files/TRF%202011_0.pdf en_US
dc.subject Intelligent transportation System en_US
dc.subject O – D flow en_US
dc.subject Link traffic flow en_US
dc.subject Travel time en_US
dc.title Dynamic travel time estimation model for real time travelers en_US
dc.type Conference-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Department of Civil Engineering en_US
dc.identifier.year 2011 en_US
dc.identifier.conference Transport Research Forum 2011 en_US
dc.identifier.place Colombo en_US
dc.identifier.pgnos pp. 13-14 en_US
dc.identifier.proceeding Proceedings of the Transport Research Forum 2011 en_US
dc.identifier.email pilanavithanage@gmail.com en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record