| contributor author | Golshan Khavas Reza;Hellinga Bruce | |
| date accessioned | 2019-02-26T07:55:03Z | |
| date available | 2019-02-26T07:55:03Z | |
| date issued | 2018 | |
| identifier other | JTEPBS.0000124.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4250262 | |
| description abstract | Travel time reliability refers to the day-to-day variability of trip travel times. There is a belief that there is a cost associated with unreliability and this cost can be quantified as a function of the difference between the travel time that was experienced and the travel time that was anticipated. In the realm of public transport systems, the anticipated travel time is essentially the scheduled travel time and is therefore easy to compute. However, for personal auto modes, it is not clear how the anticipated travel time should be computed. This paper focuses on addressing the following two questions: What is the relationship between the distribution of the travel times that travelers experience and the travel times that travelers anticipate for a future trip? What effect do unusually long travel times have on this anticipated travel time? The authors explored both questions through a stated preference survey that was distributed to over 3, individuals. Just over 3 valid responses were received, and on the basis of the survey results, a two-stage model for estimating the anticipated travel time as a function of the experienced travel time distribution was formulated and calibrated. The proposed model can be applied to travel times obtained from simulation models or from field observations. | |
| publisher | American Society of Civil Engineers | |
| title | Examining the Relationship between Drivers’ Anticipated Travel Time and Previous Experienced Travel Times | |
| type | Journal Paper | |
| journal volume | 144 | |
| journal issue | 3 | |
| journal title | Journal of Transportation Engineering, Part A: Systems | |
| identifier doi | 10.1061/JTEPBS.0000124 | |
| page | 4018004 | |
| tree | Journal of Transportation Engineering, Part A: Systems:;2018:;Volume ( 144 ):;issue: 003 | |
| contenttype | Fulltext | |