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EN
All the available modes of travel and their respective travel parameters must be known to the commuters before their trip. Otherwise they may either spend more money or more time for the trip. In addition to this, recent pandemic, rapidly spreading novel corona virus is demanding a smart solution for contactless commuting. This paper suggests a practical solution to make both the above possible and it emphasizes the applicability of two developed android applications, one for travel data collection and another to predict travel time for a multimodal trip within the study area. If the whole trip is by a single mode, the user can get the corresponding travel time estimate from “Google maps”. But, if the trip is by multiple modes, it is not possible to get the total travel time estimate for the whole trip at a time from “Google maps”. A separate travel mode for “auto” is unavailable in “Google maps” alongside drive, two-wheeler, train or bus and walk alternatives. It is also observed that the travel time estimate of “Google maps” for the city buses is inaccurate. Hence, the two modes (Buses and Autos) were chosen for the study. Unless and until the travel times and stopping times of the two modes are known, it is not possible to predict their trip times. Hence, the mobility analysis was performed for the two modes in the study area to find their respective average travel rate at peak hours, across 15 corridors and the results were presented.
EN
Understanding the needs of ferry service commuters cannot be overemphasis, considering the fact that the survival of any business largely depends on the volume of its customer base, and how well they are satisfied with the level of services received. More so, owing to the high population of Lagos state and usual traffic congestion across main roads during the peak periods, water transportation via ferries undoubtedly becomes a viable alternative to ensure stakeholders satisfaction in urban planning for a city majorly surrounded by water providers. Thus, this study employs the analytical hierarchy process (AHP) to prioritise the ferry services needs of commuters to make effective managerial decisions that will aid efficiency in their operations, thereby, increasing the market penetration, competitive edge and commuter satisfaction. A sample size of two hundred and four was computed through purposive sampling procedure. The data retrieved were analysed using pairwise comparison in line with AHP methodology. The study found out that among the criteria measured, comfort was perceived more important to commuters compared to its pairs. In addition, recreational facilities, ease of online payment, regular maintenance of waterways and seating with good legroom were ranked high by the commuters. Therefore, to ensure a sustainable competitive advantage over other modes of transportation, these indicators need to be effectively considered in water transportation policy.
EN
The purpose of this paper is to examine the rule compliance behavior of pedestrians at signalized intersections located in two different urban contexts in Italy, a tourist context and a typical working urban context, and to highlight if there is any influence, of the specific urban context, on the non-compliance behavior of pedestrians. Digital video camera images are gathered in two different urban contexts and data are processed using automated software, self-written in MatLab. Both test places are located in Tuscany (Italy) and they are only 20 km apart. The tourist, or recreational, context is the beach town of Viareggio. The typical working, or commuter, urban context is the historical city of Lucca. Factors such as age, sex and group size are analyzed. Pearson’s chi-square test has been applied to investigate whether the difference between observed values and expected values of variables is statistically significant. The average crossing speed in tourists is found to be 1.50 m/s and the average 15th percentile is 1.09 m/s, whereas in commuters, the average crossing speed is found to be 1.78 m/s and the average 15th percentile is 1.42 m/s. The obtained results highlight that pedestrians in a tourist urban context are generally more compliant to traffic lights than in a commuter urban context. Moreover, the results point out that pedestrian behavior is highly linked to the urban context, and the obtained results of this exploratory study on pedestrians, in a recreational context as compared to a working one, raise some interesting questions that deserve further research work.
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