Approach to estimate travel time using sparsely sampled GPS data in urban networks

2013 ◽  
Vol 49 (15) ◽  
pp. 957-958 ◽  
Author(s):  
A. Hadachi ◽  
S. Mousset ◽  
A. Bensrhair
Author(s):  
Qi Gong ◽  
Teresa M. Adams ◽  
Xiubin Bruce Wang

2014 ◽  
Vol 8 (1) ◽  
pp. 130-135
Author(s):  
S. Nithya ◽  
D. Senthurkumar ◽  
K. .Gunasekaran

The travel time studies are one of the most important measures used for evaluating the performance of road networks. The Global Positioning System (GPS) is a space-based system that provides position and time information in all weather conditions. GPS data could be used to obtain the values of traffic control delay, vehicle queue, average travel time and vehicle acceleration and deceleration at intersections.The task of estimation of delay becomes complex if it is performed for intersections carrying heterogeneous traffic and that to for over saturated conditions. Most of the urban signalized intersections are manually controlled during peak hours. GPS device fitted in a vehicle was run repeatedly during morning peak period and the period during which vehicles were allowed to cross the intersection was recorded with video graphic camera. The attempt to identify the control delay with the GPS data from the test vehicle while crossing manually operated major intersection is presented in this paper.


2020 ◽  
Vol 202 ◽  
pp. 106790 ◽  
Author(s):  
Xing Wu ◽  
Uttara Roy ◽  
Maryam Hamidi ◽  
Brian N. Craig

Computation ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 51
Author(s):  
Alireza Sahebgharani ◽  
Mahmoud Mohammadi ◽  
Hossein Haghshenas

Space-time prism (STP) is a comprehensive and powerful model for computing accessibility to urban opportunities. Despite other types of accessibility measures, STP models capture spatial and temporal dimensions in a unified framework. Classical STPs assume that travel time in street networks is a deterministic and fixed variable. However, this assumption is in contradiction with the uncertain nature of travel time taking place due to fluctuations and traffic congestion. In addition, travel time in street networks mostly follows non-normal probability distributions which are not modeled in the structure of classical STPs. Neglecting travel time uncertainty and disregarding different types of probability distributions cause unrealistic accessibility values in STP-based metrics. In this way, this paper proposes a spatiotemporal accessibility model by extending classical STPs to non-normal stochastic urban networks and blending this modified STP with the attractiveness of urban opportunities. The elaborated model was applied on the city of Isfahan to assess the accessibility of its traffic analysis zones (TAZs) to Kowsar discount retail markets. A significant difference was found between the results of accessibility values in normally and non-normally distributed networks. In addition, the results show that the northern TAZs had larger accessibility level compared to the southern ones.


2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Jian Wang ◽  
Yang Cao

Bus travel time is an important source of data for time of day partition of the bus route. However, in practice, a bus driver may deliberately speed up or slow down on route so as to follow the predetermined timetable. The raw GPS data collected by the GPS device equipped on the bus, as a result, cannot reflect its real operating conditions. To address this concern, this study first develops a method to identify whether there is deliberate speed-up or slow-down movement of a bus. Building upon the relationships between the intersection delay, link travel time, and traffic flow, a recovery method is established for calculating the real bus travel time. Using the dwell time at each stop and the recovered travel time between each of them as the division indexes, a sequential clustering-based time of day partition method is proposed. The effectiveness of the developed method is demonstrated using the data of bus route 63 in Harbin, China. Results show that the partition method can help bus enterprises to design reasonable time of day intervals and significantly improve their level of service.


Author(s):  
Kelvin Lee ◽  
Anatolii Prokhorchuk ◽  
Justin Dauwels ◽  
Patrick Jaillet
Keyword(s):  

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