EVALUATION OF TRADE-OFFS BETWEEN TWO DATA SOURCES FOR THE ACCURATE ESTIMATION OF OD MATRICES
In this paper, we evaluate the trade-offs between loop detector data and floating car data (FCD) for the real-time estimation of origin–destination (OD) matrices in small networks. The proposed methodology is based on a bi-level optimisation using fuzzy logic theory. Here we demonstrate that it provides accurate results with low computational cost, while presenting several advantages over other existing algorithms (especially in terms of data requirements, computational complexity, and quality of adjustment). The methodology is illustrated with three examples covering two different locations in the city of Zurich, Switzerland. Results are used to evaluate the trade-offs between loop detector coverage and the penetration rate of FCD, and to determine minimum values for ensuring a given accuracy level on the estimated OD matrices. In general, the resulting error in OD estimation is affected by the data redundancy in the network.
ADJUSTMENT BOARDING AND ALIGHTING PASSENGERS ON A BUS TRANSIT LINE USING QUALITATIVE INFORMATION
Obtaining data to use in an urban public transport operation planning and analysis is problematic, particularly in urban bus transit lines. In an urban environment and for bus services, most ticketing methods can be used to record passengers getting on board but not getting off, and current methods are unable to make a proper adjustment of boardings and alightings based on the available data unless they do alighting counts. This paper presents a method whereby counts are made at fewer stops and qualitative information on alightings and/or vehicle loads between consecutive stops is used to make the boarding and alighting adjustment as a previous step to obtain the real origin and destination (O/ D) of passengers allowing the O/D matrix calibration by using the loads between stops. Qualitative information can be obtained by the vehicle’s driver or an on board observer, avoiding the necessity of counting many stops in planning period. The method is applied to a real bus transit line in Malaga (Spain) and to a set of 50 different bus transit lines with number of stops ranging from 10 to 75. The results show that the proposed method reduces the adjustment errors with regard to traditional methods, such as Least Square Method, even in the situation where no qualitative information is used. When qualitative data is used on alightings and loadings, the reduction of the average error is over 50%.
METHOD TO DETECT MALFUNCTIONING TRAFFIC COUNT STATIONS
This study presents a method for the automatic detection of malfunctioning traffic count stations (TCS) in a transport system. First, double linear optimisation is used to detect inadmissible errors in the recordings of a series of TCS and next, the TCS that are most likely to be failing are identified. The method has been applied to an urban traffic network showing success rates up to 93% in identifying the TCS that are failing.
BILEVEL FUZZY OPTIMIZATION TO PRE-PROCESS TRAFFIC DATA TO SATISFY THE LAW OF FLOW CONSERVATION
Traffic data obtained in the field usually have some errors. For instance, traffic volume data on the various links of a network must be consistent and satisfy flow conservation, but this rarely occurs. This paper presents a method for using fuzzy optimization to adjust observed values so they meet flow conservation equations and any consistency requirements. The novelty lies in the possibility of obtaining the best combination of adjusted values, thereby preserving data integrity as much as possible. The proposed method allows analysts to manage field data reliability by assigning different ranges to each observed value. The paper is divided into two sections: the first section explains the theory through a simple example of a case in which the data is equally reliable and a case in which the observed data comes from more or less reliable sources, and the second one is an actual application of the method in a freeway network in southern Spain where data were available but some data were missing.
El papel del ingeniero de Caminos en las Smart Cities futuras
This paper presents the five acting domains within the concept of Smart City that are focused on transforming our cities into future cities, pursuing them to be able to compete themselves as a turism attraction. Among these domains, special mention to be made to those where civil engineers, thanks to their skills, have more presence. The paper is organized in five sections; firstly, the introduction about cities transformation and the change of concept they are suffering. Secondly, challenges that actual cities offer nowadays are presented, in the third section, windows of opportunity where to act on are detected, to focus in the fourth part, on those fields where the civil engineer performs the main roll, to end in the last section with a reflection about the need of acting on some other fields to reach the real city transformation.
Las ciudades en el centro de la pandemia
This article shows how cities are at the center of the pandemic, how it has affected citizen behavior and the consequences that this entails in the new conception of the city to be able to adapt to similar situations in the future. It has been structured in three large sections, one where the three capital action points are presented, a second where a diagnosis of the strategic solutions is made, both those that have been carried out to date and those that are expected in the short term future. In a last section, the objectives of sustainable development with a 2030 horizon are pointed out, where the concept of “sustainable development” includes the need to consider the relationship between nature and society as well as the social, environmental and economic dimension. Finally, the article ends with some conclusions on how to transform cities and a final reflection.