scholarly journals Forecasting travel time reliability in urban road transpo

2017 ◽  
Vol 43 (3) ◽  
pp. 53-67 ◽  
Author(s):  
Mattias Juhász ◽  
Tamás Mátrai ◽  
Csaba Koren

Assessment of travel time reliability as a fundamental factor in travel behaviour has become a very important aspect in both transport modelling and economic appraisal. Improved reliability could provide a significant economic benefit if it is adequately calculated in cost-benefit analyses for which the theoretical background has already been set. However, methods to forecast travel time reliability as well as travel behaviour models including its effects are rather scarce and there is a need for development in this field. Another important aspect could be the influencing factor of reliability in travel demand management and related policy-making. Therefore, this paper intends to further analyse reliability focusing exclusively on urban road transport based on automatic measurements of journey times and traffic volumes from a dataset of the city of Budapest. The main finding and the novelty of the study is a model which can forecast the standard deviation of travel times based on the volume-capacity ratio and the free-flow travel time. The paper also provides a real-life numerical experiment in which the proposed model has been compared with other, existing ones. It proves that besides existing mean-delay-based models, travel time reliability can be forecasted based on the volume-capacity ratio with an adequate accuracy.

Author(s):  
Fatemeh Fakhrmoosavi ◽  
Ali Zockaie ◽  
Khaled Abdelghany

Congestion pricing is proposed as an effective travel demand management strategy to circumvent the problem of congestion and generate revenue to finance developmental projects. There are several studies focusing on optimal pricing strategies to minimize the congestion level or maximize the revenue of the system. However, with regard to equity issues, benefiting only users with higher value of time is claimed to be the main factor that prevents implementation of such policies in practice. While many studies aimed to tackle the equity issues by certain welfare analyses, most of these studies fail to fully consider realistic features of users’ behavior and the uncertainty in link travel times. Given the variability of travel time in real-world networks and the impacts of pricing policies on path travel time distributions, it is important to consider the users’ reliability valuations, in addition to their travel time valuations. Thus, the goal in this study is to find an equitable pricing scheme that minimizes the total travel time of auto users in a general bimodal network considering heterogeneous users with different values of time and reliability. A particle swarm optimization algorithm is proposed to find self-funded and Pareto-improving optimal toll values. A reliability-based user equilibrium algorithm is embedded into this optimization algorithm to assign travelers to the equilibrated paths for different user classes given toll values. The proposed approach is successfully applied to a modified Sioux Falls network to explore impacts of subsidization, congestion level, and considering travel time reliability on the pricing strategy and its effectiveness.


Author(s):  
Malvika Dixit ◽  
Ties Brands ◽  
Niels van Oort ◽  
Oded Cats ◽  
Serge Hoogendoorn

Urban transit networks typically consist of multiple modes and the journeys may involve a transfer within or across modes. Therefore, the passenger experience of travel time reliability is based on the whole journey experience including the transfers. Although the impact of transfers on reliability has been highlighted in the literature, the existing indicators either focus on unimodal transfers only or fail to include all components of travel time in reliability measurement. This study extends the existing “reliability buffer time” metric to transit journeys with multimodal transfers and develops a methodology to calculate it using a combination of smartcard and automatic vehicle location data. The developed methodology is applied to a real-life case study for the Amsterdam transit network consisting of bus, metro, and tram lines. By using a consistent method for all journeys in the network, reliability can be compared between different transit modes or between multiple routes for the same origin–destination pair. The developed metric can be used to study the reliability impacts of policies affecting multiple transit modes. It can also be used as an input to behavioral models such as mode, route, or departure time choice models.


2011 ◽  
Vol 38 (4) ◽  
pp. 433-443 ◽  
Author(s):  
Hamid Zaman ◽  
Khandker M. Nurul Habib

Travel demand management (TDM) for achieving sustainability is now considered one of the most important aspects of transportation planning and operation. It is now a well known fact that excessive use of private car results inefficient travel behaviour. So, from the TDM perspective, it is of great importance to analyze travel behaviour for improving our understanding on how to influence people to reduce car use and choose more sustainable modes such as  carpool, public transit, park & ride, walk, bike etc. This study attempts an in-depth analysis of commuting mode choice behaviour using a week-long commuter survey data set collected in the City of Edmonton. Using error correlated nested logit model for panel data, this study investigates sensitivities of various factors including some specific TDM policies such as flexible office hours, compressed work week etc. Results of the investigation provide profound understanding and guidelines for designing effective TDM policies.


2018 ◽  
Vol 46 (2) ◽  
pp. 21-32 ◽  
Author(s):  
Devika Babu ◽  
Sreelakshmi Balan ◽  
M.V.L.R. Anjaneyulu

Travel behaviour studies in activity-based perspective treat travel as a result of individual’s desire to participate in different activities. This approach is more significant in the context of developing countries, as the transportation problems are more severe here. Since, commuters contribute to a major share in the travel, understanding their travel behaviour is essential. This paper aims to explore the travel behaviour of commuters in Calicut city, Kerala State, India and thereby model their activity-travel patterns. Household, personal and activity-travel information from 12920 working people and 9684 students formed the database for this study. The data collection was performed by means of home-interview survey by face-to-face interview technique. From preliminary analysis, several simple and complex tours were identified for the study area. Working people’s work participation and students’ education activity participation decision are modelled as mandatory activity participation choice in a binary logit modelling framework. Results of this mandatory activity participation model revealed that male workers are more likely to engage in work compared to females. Presence of elderly persons is found to negatively influence the work participation decisions of workers. This may be due to the fact that, work activity may be partially or completely replaced with the medical requirements of the elderly. The chances for work activity participation increase with increase in number of two-wheelers at home. In the case of students, as the education level increases, they are found to be less likely to participate in education activities. Students are observed to follow simple activity-travel pattern. Complex tours are found to be performed by males, compared to females. Activity-travel pattern of the study group are predicted using the developed models. The percentages correctly predicted indicate reasonably good predictability for the models. These kind of studies are expected to help the town planners to better understand city’s travel behaviour and thus to formulate well-organised travel demand management policies.


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