Abstract
In populated cities with high traffic congestion, traffic information may play a key role in choosing the fastest route between origins and destinations, thus saving travel time. Several research studies investigated the effect of traffic information on travel time. However, little attention has been given to the effect of traffic information on travel time according to trip distance. This paper aims to investigate the relation between real-time traffic information dissemination and travel time reduction for medium-distance trips. To examine this relation, a methodology is applied to compare travel times of two types of vehicle, with and without traffic information, travelling between an origin and a destination employing probe vehicles. A real case study in the metropolitan city of Tehran, the capital of Iran, is applied to test the methodology. There is no significant statistical evidence to prove that traffic information would have a significant impact on travel time reduction in a medium-distance trip according to the case study.
Highlights
Routing is a decision support system that guides a traveler from a certain origin to a specific destination across a network
The results showed that GPS technology was more accurate than those based on Base Transceiver Station (BTS) signals for routing and collecting traffic conditions
Data exploration was executed through computing descriptive statistics for speeds and travel times of the informed and uninformed vehicles over different time slots and origin-destination pairs
Summary
Routing is a decision support system that guides a traveler from a certain origin to a specific destination across a network This system can be different in many aspects, its main goal is to provide travelers with an optimal solution, i.e., to identify the shortest or fastest path to travel from an origin to a destination. Routing methods can be classified into four categories: static and dynamic routing, deterministic and stochastic routing, reflective and forecasting routing, centralized and non-centralized routing. Historical traffic data is utilized, while in dynamic routing real-time traffic data is used as the system input. Stochastic routing considers the random nature of traffic data, whilst the deterministic approach treats traffic data as fixed variables. Forecasting routing applies models to predict traffic data, while reflective routing employs the current state of a network.
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