Travel time cognition: Exploring the impacts of travel information provision strategies

2019 ◽  
Vol 14 ◽  
pp. 92-106 ◽  
Author(s):  
Ramin Saedi ◽  
Navid Khademi
Keyword(s):  
Travel Time ◽  
Information Provision ◽  
Travel Information

Optimal Information Provision at Bottleneck Equilibrium with Risk-Averse Travelers

2018 ◽  
Vol 2672 (48) ◽  
pp. 69-78 ◽  
Author(s):  
Peng Liu ◽  
Yang Liu
Keyword(s):  
Risk Aversion ◽  
Travel Time ◽  
Information Quality ◽  
Information Provision ◽  
Travel Cost ◽  
Total System ◽  
Risk Averse ◽  
Travel Information ◽  
Optimal Information ◽  
The Individual

This paper aims to study the effects of travel information provision on risk-averse travelers when travel time is uncertain. A stochastic bottleneck model is examined with risk-averse commuters, in which the free-flow travel time is assumed to be uncertain and follows a uniform distribution. A mean-variance approach is adopted to measure the travel cost under risk. It is proven that the individual travel cost at bottleneck equilibrium monotonically increases with the risk-aversion level. With a higher risk-aversion level, the morning peak hour starts earlier, but the duration of the peak hour remains constant regardless of the risk-aversion level. If improvement in information quality can reduce the travel time uncertainty, risk-averse commuters will benefit from the higher quality of information. Nevertheless, when the cost of information provision is also considered, the optimal information provision strategy is derived to minimize the total system cost. The numerical examples demonstrate the information efficiency and provision strategy. The findings reveal the congestion patterns of a stochastic bottleneck with risk-averse travelers and will guide us to provide appropriate travel information.

Validation of a multimodal travel simulator with travel information provision

2007 ◽  
Vol 15 (3) ◽  
pp. 191-207 ◽  
Author(s):  
Caspar G. Chorus ◽  
Eric J.E. Molin ◽  
Theo A. Arentze ◽  
Serge P. Hoogendoorn ◽  
Harry J.P. Timmermans ◽  
...  
Keyword(s):  
Information Provision ◽  
Travel Information

Development of Estimating Methodology for Transit Accessibility Using Smart Card Data

2021 ◽  
pp. 036119812110275
Author(s):  
Hyunsoo Yun ◽  
Eun Hak Lee ◽  
Dong-Kyu Kim ◽  
Shin-Hyung Cho
Keyword(s):  
Spatial Distribution ◽  
Travel Time ◽  
Smart Card ◽  
Explanatory Variable ◽  
Travel Information ◽  
Transit Network ◽  
Important Index ◽  
Transit Accessibility ◽  
Smart Card Data ◽  
Two Factors

Transit accessibility is an explanatory variable evaluating the mobility of a region in consideration of the connectivity and demand among the regions, which has been used for an important index to determine transport policy on the transit network. This study aims to develop an accessibility index considering the two factors with a demand-weighted approach, that is, impedance and attraction level. Two variables, travel time and the ratio of trips, are employed to calculate the accessibility index, and comparative assessments between zones are conducted. The application of smart card data makes it possible to analyze travel information and reflect them empirically in the model. This study identifies zones with vulnerable accessibility and suggests criteria for transit investment plans with two aspects, that is, intensive transit area and spatial distribution of the accessibility index. These aspects contribute to transit planners by suggesting transit investment criteria and comprehensible statistics to evaluate accessibility. Since zones with low accessibility indexes are identified as being vulnerable to access from other zones, policymakers should focus on those zones to improve the overall transit network.

Influence Mechanism of Travel Information Service Level for Drivers' Travel Time Prediction Error

2014 ◽  
Vol 505-506 ◽  
pp. 1183-1188
Author(s):  
Neng Wan ◽  
Jian Xiong ◽  
Feng Xiang Guo
Keyword(s):  
Travel Time ◽  
Prediction Error ◽  
Influence Factors ◽  
Information Service ◽  
Service Level ◽  
Travel Time Prediction ◽  
Travel Information ◽  
The Road ◽  
Time Prediction ◽  
Planning And Construction

In order to reveal the effect mechanism of travel information service level for drivers travel time prediction error, defined the concept of travel information service level and travel time prediction error. Utilize the conceptual model, described the various influence factors of travel information service level and interaction relations. Discussed the relationship between the drivers travel information receiving preference habits and the road selection, analyzed the effect of the influence factors on drivers' road selection and travel time prediction, based on Bayesian methods analyzed the effect of different travel information service level for travel time prediction error. The calculation shows that the higher travel information service level can improve the drivers travel time prediction, increase the travel information service level play an important role for the efficiency of drivers travel, and provide theoretical support for planning and construction of travel information system on the future.

Modeling Urban Link Travel Time with Inductive Loop Detector Data by Using the k-NN Method

2005 ◽  
Vol 1935 (1) ◽  
pp. 47-56 ◽  
Author(s):  
Steve Robinson ◽  
John W. Polak
Keyword(s):  
Travel Time ◽  
Estimation Method ◽  
Information Provision ◽  
Accurate Estimate ◽  
Design Parameters ◽  
Real World Data ◽  
Inductive Loop ◽  
Loop Detector ◽  
Inductive Loop Detector ◽  
Link Travel Time

The need to measure urban link travel time (ULTT) is becoming increasingly important for network management and traveler information provision. This paper proposes the use of the k nearest neighbors ( k-NN) technique to estimate ULTT with the use of single loop inductive loop detector (ILD) data. Real-world data from London is used. This paper explores the sensitivity of travel time estimates to various k-NN design parameters. It finds that the k-NN method is not particularly sensitive to the distance metric, although care must be taken in selecting the right combination of local estimation method (LEM) and value of k. A robust LEM should be used. The optimized k-NN model is found to provide more accurate estimates than other ULTT methods. To obtain a more accurate estimate of ULTT, a potential application of this approach could be to aggregate GPS probe vehicle ULTT records from different times but the same underlying travel time distribution.

Modeling the Impact of Travel Information on Activity–Travel Rescheduling Decisions under Conditions of Travel Time Uncertainty

2005 ◽  
Vol 1926 (1) ◽  
pp. 79-87 ◽  
Author(s):  
Zhongwei Sun ◽  
Theo Arentze ◽  
Harry J. P. Timmermans
Keyword(s):  
Travel Time ◽  
Information Gain ◽  
Information Source ◽  
Perceived Value ◽  
Travel Information ◽  
Context Learning ◽  
Expected Information ◽  
Expected Information Gain ◽  
The Individual ◽  
The Impact

This study elaborates on a model system developed in earlier papers to predict the perceived value and use of travel information. The value of travel information is conceptualized as the extent to which the information allows the individual to make better activity–travel scheduling decisions at the beginning of the day and during execution of the schedule. By taking the broader schedule context into account, the model is sensitive to the impact of information and decisions on the full activity–travel pattern. Furthermore, the model includes Bayesian mechanisms to make sure that beliefs about travel times, and other uncertain events, and the credibility of the information source are updated each time information is received and the real travel time is experienced. This paper describes the results of numerical simulations conducted to illustrate the system and to derive theoretical implications from the model. The simulations show that the schedule context, learning, and expected information gain in combination determine the perceived value of information and that none of these factors can be ignored in the derivation of estimates of these values. A theoretical analysis further shows how decision trees can be pruned to reduce a potential problem of combinatorics.

Optimal travel information provision strategies: an agent-based approach under uncertainty

2017 ◽  
Vol 6 (2) ◽  
pp. 129-150 ◽  
Author(s):  
Chenfeng Xiong ◽  
Zheng Zhu ◽  
Xiqun Chen ◽  
Lei Zhang
Keyword(s):  
Information Provision ◽  
Travel Information ◽  
Agent Based
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