Impact of para-transit travel time reliability on urban mobility: a case study

2017 ◽  
Vol 6 (2) ◽  
pp. 93 ◽  
Author(s):  
Fatima Electricwala ◽  
Rakesh Kumar
Keyword(s):  
Travel Time ◽  
Travel Time Reliability ◽  
Urban Mobility

Analyzing Travel Time Reliability from Sparse Probe Vehicle Data: A Case Study on the Effects of Spatial and Temporal Aggregation

2021 ◽  
pp. 036119812110315
Author(s):  
Markus Steinmaßl ◽  
Stefan Kranzinger ◽  
Karl Rehrl
Keyword(s):  
Travel Time ◽  
Time Of Day ◽  
Temporal Aggregation ◽  
Travel Time Reliability ◽  
Probe Vehicle ◽  
Vehicle Data ◽  
Depth Analysis ◽  
Data Source ◽  
Travel Time Index

Travel time reliability (TTR) indices have gained considerable attention for evaluating the quality of traffic infrastructure. Whereas TTR measures have been widely explored using data from stationary sensors with high penetration rates, there is a lack of research on calculating TTR from mobile sensors such as probe vehicle data (PVD) which is characterized by low penetration rates. PVD is a relevant data source for analyzing non-highway routes, as they are often not sufficiently covered by stationary sensors. The paper presents a methodology for analyzing TTR on (sub-)urban and rural routes with sparse PVD as the only data source that could be used by road authorities or traffic planners. Especially in the case of sparse data, spatial and temporal aggregations could have great impact, which are investigated on two levels: first, the width of time of day (TOD) intervals and second, the length of road segments. The spatial and temporal aggregation effects on travel time index (TTI) as prominent TTR measure are analyzed within an exemplary case study including three different routes. TTI patterns are calculated from data of one year grouped by different days-of-week (DOW) groups and the TOD. The case study shows that using well-chosen temporal and spatial aggregations, even with sparse PVD, an in-depth analysis of traffic patterns is possible.

scholarly journals Metro Train Operation Plan Analysis Based on Station Travel Time Reliability

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Ruihua Xu ◽  
Fangsheng Wang ◽  
Feng Zhou
Keyword(s):  
Travel Time ◽  
Clustering Algorithm ◽  
Algorithm Design ◽  
Service Level ◽  
Travel Time Reliability ◽  
Plan Analysis ◽  
Train Operation ◽  
Metro Systems ◽  
Transportation Organization

The train operation plan plays an essential role in metro systems and directly affects transportation organization efficiency and passenger service level. In metro systems, passengers have paid more attention to the travel time reliability (TTR), reflecting the reliability of metro operation management. This article proposes an analysis method of train operation plan based on TTR in the station dimension. First, an automated fare collection (AFC) data-driven framework is established to calculate the station travel time reliability (STTR) and analyze the train operation plan at different periods. The framework structure consists of four steps: AFC data preprocessing, STTR calculation and assignment, clustering algorithm design based on SOM neural network, and train operation plan analysis and optimization. Second, the proposed method is applied to the Beijing metro network as a case study. Several promising results are analyzed that allow the optimization of the existing train operation plan. Our research shows that STTR is a good supplement for the existing metro operation assignment studies, which can help analyze and optimize the train operation plan effectively. This study is also applicable to other metro networks with AFC systems.

Comparative approach for predicting travel time reliability (a case study of Virginia interstate)

2021 ◽  
Vol 6 (4) ◽  
Author(s):  
Shahriar Afandizadeh Zargari ◽  
Navid Amoei Khorshidi ◽  
Hamid Mirzahossein ◽  
Navid Kalantari
Keyword(s):  
Travel Time ◽  
Comparative Approach ◽  
Travel Time Reliability
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