Link travel time functions for traffic assignment

1991 ◽  
Vol 25 (2-3) ◽  
pp. 103-113 ◽  
Author(s):  
C.S. Fisk
Keyword(s):  
Travel Time ◽  
Traffic Assignment ◽  
Link Travel Time

scholarly journals System Optimum Fuzzy Traffic Assignment Problem

2019 ◽  
Vol 31 (6) ◽  
pp. 611-620
Author(s):  
Gizem Temelcan ◽  
Hale Gonce Kocken ◽  
Inci Albayrak
Keyword(s):  
Travel Time ◽  
Assignment Problem ◽  
Road Network ◽  
Traffic Assignment ◽  
Triangular Fuzzy Numbers ◽  
System Optimum ◽  
Average Speed ◽  
Traffic Assignment Problem ◽  
Path Lengths ◽  
Link Travel Time

This paper focuses on converting the system optimum traffic assignment problem (SO-TAP) to system optimum fuzzy traffic assignment problem (SO-FTAP). The SO-TAP aims to minimize the total system travel time on road network between the specified origin and destination points. Link travel time is taken as a linear function of fuzzy link flow; thus each link travel time is constructed as a triangular fuzzy number. The objective function is expressed in terms of link flows and link travel times in a non-linear form while satisfying the flow conservation constraints. The parameters of the problem are path lengths, number of lanes, average speed of a vehicle, vehicle length, clearance, spacing, link capacity and free flow travel time. Considering a road network, the path lengths and number of lanes are taken as crisp numbers. The average speed of a vehicle and vehicle length are imprecise in nature, so these are taken as triangular fuzzy numbers. Since the remaining parameters, that are clearance, spacing, link capacity and free flow travel time are determined by the average speed of a vehicle and vehicle length, they will be triangular fuzzy numbers. Finally, the original SO-TAP is converted to a fuzzy quadratic programming (FQP) problem, and it is solved using an existing approach from literature. A numerical experiment is illustrated.

Estimating Link Travel Time with Sparse GPS Data on Highway Corridors

2015 ◽  
Vol 2477 (1) ◽  
pp. 7-17 ◽  
Author(s):  
Qi Gong ◽  
Teresa M. Adams ◽  
Xiubin Bruce Wang
Keyword(s):  
Travel Time ◽  
Gps Data ◽  
Link Travel Time

Minimum Sampling Size of Floating Cars for Urban Link Travel Time Distribution Estimation

2019 ◽  
Vol 2673 (3) ◽  
pp. 24-43 ◽  
Author(s):  
Meiping Yun ◽  
Wenwen Qin
Keyword(s):  
Sample Size ◽  
Travel Time ◽  
Real Time ◽  
Time Distribution ◽  
Ground Truth ◽  
Sample Size Determination ◽  
Minimum Sample Size ◽  
Travel Time Distribution ◽  
Minimum Sample ◽  
Link Travel Time

Despite the wide application of floating car data (FCD) in urban link travel time estimation, limited efforts have been made to determine the minimum sample size of floating cars appropriate to the requirements for travel time distribution (TTD) estimation. This study develops a framework for seeking the required minimum number of travel time observations generated from FCD for urban link TTD estimation. The basic idea is to test how, with a decreasing the number of observations, the similarities between the distribution of estimated travel time from observations and those from the ground-truth vary. These are measured by employing the Hellinger Distance (HD) and Kolmogorov-Smirnov (KS) tests. Finally, the minimum sample size is determined by the HD value, ensuring that corresponding distribution passes the KS test. The proposed method is validated with the sources of FCD and Radio Frequency Identification Data (RFID) collected from an urban arterial in Nanjing, China. The results indicate that: (1) the average travel times derived from FCD give good estimation accuracy for real-time application; (2) the minimum required sample size range changes with the extent of time-varying fluctuations in traffic flows; (3) the minimum sample size determination is sensitive to whether observations are aggregated near each peak in the multistate distribution; (4) sparse and incomplete observations from FCD in most time periods cannot be used to achieve the minimum sample size. Moreover, this would produce a significant deviation from the ground-truth distributions. Finally, FCD is strongly recommended for better TTD estimation incorporating both historical trends and real-time observations.

scholarly journals A Dynamic Traffic Assignment Model for the Sustainability of Pavement Performance

2018 ◽  
Vol 11 (1) ◽  
pp. 170 ◽  
Author(s):  
Xinhua Mao ◽  
Jianwei Wang ◽  
Changwei Yuan ◽  
Wei Yu ◽  
Jiahua Gan
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Traffic Assignment ◽  
Dynamic Traffic Assignment ◽  
Heavy Traffic ◽  
Pollutant Emissions ◽  
Pavement Performance ◽  
Dynamic Traffic ◽  
Teaching Learning ◽  
Pavement Damage

Existing Dynamic Traffic Assignment (DTA) models assign traffic flow with the principle of travel time, which are easy to distribute most of the traffic flows on the shortest path. A serious unbalance of traffic flow in the network can speed up pavement deterioration of highways with heavy traffic, which influences the sustainability of pavement performance and increases maintenance expenditures. The purpose of this research is to obtain a more optimized traffic assignment for pavement damage reduction by establishing a multi-objective DTA model with the objectives of not only minimum travel time but minimum decline of Present Serviceability Index (PSI) for pavements. Then, teaching-learning-based optimization (TLBO) algorithm is utilized to solve the proposed model. Results of a case study indicate that a more balanced traffic flow assignment can be realized by the model, which can effectively reduce average PSI loss, save maintenance expenditures, extend pavement service life span, save fuel consumption and reduce pollutant emissions in spite of a little increase of average travel time. Additionally, sensitivity of weight factor for the two objective functions is analyzed. This research provides some insights on methods on sustainable pavement performance.

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