Social Networks, Big Data and Transport Planning

[EN] The characteristics of people who are related or tied to each individual affects her activity-travel behavior. That influence is especially associated to social and recreational activities, which are increasingly important. Collecting high quality data from those social networks is very difficult using traditional travel surveys, because respondents are asked about their general social life, which is most demanding to remember that specific facts. On the other hand, currently there are different potential sources of transport data, which is characterized by the huge amount of information available, the velocity with it is obtained and the variety of format in which is presented. This sort of information is commonly known as Big Data. To use this data on Transport Planning application is a challenge, which require employing complex data mining techniques. In this paper, we identify potential sources of social network related big data that can be used in Transport Planning, discussing their advantages and limitations. Then, a review of current applications in Transport Planning is presented. Finally, some future prospects of using social network related big data that are included in the MINERVA project are highlighted.Cost Action TU1305 Social Networks and Travel Behaviour, MINECORuiz Sánchez, T.; Mars Aicart, MDL.; Arroyo-López, MR.; Serna, A. (2016). Social Networks, Big Data and Transport Planning. Transportation Research Procedia. 18:446-452. doi:10.1016/j.trpro.2017.01.122S4464521

Social Networks, Big Data and Transport Planning

The characteristics of people who are related or tied to each individual affects her activity-travel behavior. That influence is especially associated to social and recreational activities, which are increasingly important. Collecting high quality data from those social networks is very difficult using traditional travel surveys, because respondents are asked about their general social life, which is most demanding to remember that specific facts. On the other hand, currently there are different potential sources of transport data, which is characterized by the huge amount of information available, the velocity with it is obtained and the variety of format in which is presented. This sort of information is commonly known as Big Data. To use this data on Transport Planning application is a challenge, which require employing complex data mining techniques. In this paper, we identify potential sources of social network related big data that can be used in Transport Planning, discussing their advantages and limitations. Then, a review of current applications in Transport Planning is presented. Finally, some future prospects of using social network related big data that are included in the MINERVA project are highlighted

Measurement and analysis of extra propagation loss of tunnel curve

Wave propagation experiences extra loss in curved tunnels, which is highly desired for network planning. Extensive narrow-band propagation measurements are made in two types of Madrid subway tunnels (different cross sections and curvatures) with various configurations (different frequencies and polarizations). A ray tracer validated by the straight and curved parts of the measuring tunnels is employed to simulate the reference received signal power by assuming the curved tunnel to be straight. By subtracting the measured received power in the curved tunnels from the simulated reference power, the extra loss resulting from the tunnel curve is extracted. Finally, this paper presents the figures and tables quantitatively reflecting the correlations between the extra loss and radius of curvature, frequency, polarization, and cross section, respectively. The results are valuable for statistical modeling and the involvement of the extra loss in the design and network planning of communication systems in subway tunnels

OPTIMALISASI KETERSEDIAAN TEMPAT DUDUK (SEAT CAPACITY) ANGKUTAN UDARA PADA MASA LEBARAN DENGAN PENDEKATAN POTENTIAL DEMAND BERBASIS BIG DATA

Trend permintaan angkutan udara menunjukkan kecenderungan meningkat secara signifikan, namun ketersediaan tempat duduk sering tidak terpenuhi terutama pada masa lebaran H-7 s.d H+7. Disisi lain terdapat permasalahan beban angkutan jalan yang sangat tinggi pada masa lebaran khususnya di Pulau Jawa yang berdampak pada lamanya waktu tempuh arus mudik-balik masa lebaran. Moda angkutan udara dapat dimaksimalkan pada koridor tertentu untuk mengurangi beban jalan pada masa arus mudik balik lebaran. Potential demand dengan pendekatan Big Data melalui Maskapai Penerbangan dan Travel Agent Online dapat dimanfaatkan untuk mengoptimalkan ketersediaan tempat duduk (seat capacity) pesawat yang sesuai dengan kebutuhan masyarakat. Optimalisasi melalaui pendekatan Big Data bersinergi dengan para stakeholders diharapkan dapat memetakan potential demand, sehingga dapat tercapai pemenuhan kebutuhan ketersediaan tempat duduk (seat capacity) pada masa lebaran. Hasil penelitian menunjukan dari 12 rute penerbangan yang diduga merupakan rute terpadat, terdapat 6 rute yang perlu dilakukan penambahan seat capacity mengingat potensi permintaan penumpang angkutan udara yang cukup tinggi. Sementara pengamatan terhadap kemampuan bandar udara, dari enam (6) bandara pengamatan diperoleh hasil bahwa bandara “mampu” melayani lonjakan arus mudik balik lebaran. Penilaian didasari atas variabel yang dijadikan indikator untuk menentukan kesiapan, variabel tersebut adalah fasilitas dan personil sisi udara, sisi darat, ground handling dan ketersediaan slot time. Dari ke-6 bandara tersebut 5 (lima) bandara siap melayani penerbangan extra flight maupun penggantian pesawat menjadi wide body (bigger size), sementara hanya 1 bandara yaitu Bandara Adi Sucipto yang tidak memungkinkan untuk melakukan penambahan kapasitas melalui perubahan type pesawat yang lebih besar (bigger Size), dengan demikian penambahan kapasitas dilakukan melalui penambahan frekwensi penerbangan (extra flight). Sementara berdasarkan capturing terhadap potential demand berbasis big data diperoleh hasil terdapat 64 % hingga 89,5 % penumpang yang tidak dapat memperoleh tiket pada 12 rute pengamatan selama rentang masa lebaran tahun 2018. Selanjutnya hasil penelitian ini diharapkan dapat menjadi pertimbangan kebijakan para stakeholders dan memberikan impact terhadap ketersediaan kursi (seat capacity) angkutan udara pada masa lebaran sesuai dengan kebutuhan masyarakat serta diharapkan pula pada koridor tertentu angkutan udara dapat mengurangi beban jalan sehingga tidak terjadi kemacetan panjang selama masa arus mudik balik lebaran

A new analytical approach to evaluate the critical-event probability due to wireless communication errors in train control systems

Wireless communication links tend to be employed more and more in safety-critical railway applications. Their safe use in an advanced train control system (TCS) is an issue that is addressed in this paper by characterizing the TCS service inter- ruption due to communication errors. More precisely, occurrence probabilities of single errors are first discussed. Then, we obtain probabilistic analytical expressions of several temporal conditions that lead to a TCS service interruption, here a train emergency braking (the critical event). The accuracy of this analytical ap- proach is proved when the results are compared with those given by a simulation approach with a Petri net model. Additionally, as the use case related to the “trains’ separation” is considered in this paper, an analytical evaluation process is proposed to discuss the tolerated time margins that can be fixed to limit the critical-event occurrence probability due to the wireless communication errors