3 The provision of accurate bus arrival information is critical to encourage more people to use 4 public transport and alleviate traffic congestion. Developing a prediction scheme for bus travel 5 times can provide such information. Prediction schemes can be data driven or may use a 6 mathematical model that is usually less data intensive. This paper compares the performance of 7 two methods – ...

Due to population growth in urban areas, especially in the capital cities in developing countries, the use of private vehicles are increasing, leading to many problems such as congestion, pollution, noise, long travel time, high travel cost and more side effects. In such circumstances government policy would encourage people to use public transportation. In the meantime, employing the Intellige...

Advanced Traveler Information Systems (ATIS) plays an important role in intelligent transportation systems; it assists travelers with pre-trip and en route travel information to improve the convenience, safety and efficiency of travel. In this paper we present a highway ATIS system which provides more decisive and valuable travel information than conventional ATIS systems by integrating it with...

The provision of accurate travel time information of public transport vehicles is valuable for both operators and passengers. It helps operators effectively implement their management strategies. It also allows passengers to schedule their departure to minimize waiting times. Public transport travel time is affected by several factors such as traffic flow, passenger demand, etc, which have to b...

Air ticket sales revenue is an important source of revenue for travel agencies, and if future air ticket sales revenue can be accurately forecast, travel agencies will be able to advance procurement to achieve a sufficient amount of cost-effective tickets. Therefore, this study applied the Artificial Neural Network (ANN) and Genetic Algorithms (GA) to establish a prediction model of travel agen...

A work zone bottleneck in a roadway network can cause traffic delays, emissions and safety issues. Accurate measurement and prediction of work zone travel time can help travelers make better routing decisions and therefore mitigate its impact. Historically, data used for travel time analyses comes from fixed loop detectors, which are expensive to install and maintain. With connected vehicle tec...

While vehicular flows on freeways are often treated as uninterrupted flows, flows on arterials are conceivably much more complicated since vehicles traveling on arterials are not only subject to queuing delay but also to signal delay. Prediction of travel time is potentially more challenging for arterials than for freeways. This paper proposes a simple approach for arterial travel time predicti...

Accuracy and robustness with respect to missing or corrupt input data are two key characteristics for any travel time prediction model that is to be applied in a real-time environment (e.g. for display on variable message signs on freeways). This article proposes a freeway travel time prediction framework that exhibits both qualities. The framework exploits a recurrent neural network topology, ...

In this work, we address the problem of online travel time prediction in the context of a bus journey. That is, a journey may be ongoing in the sense that journey events already indicated the progress of the bus on its route. For such an ongoing journey, we are interested in the current prediction of the traveling time from the current bus stop to some destination via a particular sequence of s...