Realised pedestrian accessibility of an informal settlement in Jakarta, Indonesia

To date, little is known about the interplay between transport, land use and the social systems that influence potential and realised accessibility in Southeast Asia. This paper aims to understand these relationships in an informal settlement – a kampong – at the edge of the upscale Menteng district, Jakarta. We applied a mixed-methods approach of (1) a computational street network analysis using space syntax, (2) video analysis to understand travel behaviour and land use and (3) an analysis of street users’ experiences collected through interviews. Our findings indicated that the pedestrian accessibility was not fully realised due to unsupportive land uses and negative perceptions of walking experienced by kampong inhabitants. Marginalised groups became captive pedestrians limited in their mobility choices. This study provides insights into Jakarta’s informal settlements and how urban planning can contribute to sustainable development for inclusive, safe, and resilient cities

Smart streetlights: a feasibility study

The world's cities are growing. The effects of population growth and urbanisation mean that more people are living in cities than ever before, a trend set to continue. This urbanisation poses problems for the future. With a growing population comes more strain on local resources, increased traffic and congestion, and environmental decline, including more pollution, loss of green spaces, and the formation of urban heat islands. Thankfully, many of these stressors can be alleviated with better management and procedures, particularly in the context of road infrastructure. For example, with better traffic data, signalling can be smoothed to reduce congestion, parking can be made easier, and streetlights can be dimmed in real time to match real-world road usage. However, obtaining this information on a citywide scale is prohibitively expensive due to the high costs of labour and materials associated with installing sensor hardware. This study investigated the viability of a streetlight-integrated sensor system to affordably obtain traffic and environmental information. This investigation was conducted in two stages: 1) the development of a hardware prototype, and 2) evaluation of an evolved prototype system. In Stage 1 of the study, the development of the prototype sensor system was conducted over three design iterations. These iterations involved, in iteration 1, the live deployment of the prototype system in an urban setting to select and evaluate sensors for environmental monitoring, and in iterations 2 and 3, deployments on roads with live and controlled traffic to develop and test sensors for remote traffic detection. In the final iteration, which involved controlled passes of over 600 vehicle, 600 pedestrian, and 400 cyclist passes, the developed system that comprised passive-infrared motion detectors, lidar, and thermal sensors, could detect and count traffic from a streetlight-integrated configuration with 99%, 84%, and 70% accuracy, respectively. With the finalised sensor system design, Stage 1 showed that traffic and environmental sensing from a streetlight-integrated configuration was feasible and effective using on-board processing with commercially available and inexpensive components. In Stage 2, financial and social assessments of the developed sensor system were conducted to evaluate its viability and value in a community. An evaluation tool for simulating streetlight installations was created to measure the effects of implementing the smart streetlight system. The evaluation showed that the on-demand traffic-adaptive dimming enabled by the smart streetlight system was able to reduce the electrical and maintenance costs of lighting installations. As a result, a 'smart' LED streetlight system was shown to outperform conventional always-on streetlight configurations in terms of financial value within a period of five to 12 years, depending on the installation's local traffic characteristics. A survey regarding the public acceptance of smart streetlight systems was also conducted and assessed the factors that influenced support of its applications. In particular, the Australia-wide survey investigated applications around road traffic improvement, streetlight dimming, and walkability, and quantified participants' support through willingness-to-pay assessments to enable each application. Community support of smart road applications was generally found to be positive and welcomed, especially in areas with a high dependence on personal road transport, and from participants adversely affected by spill light in their homes. Overall, the findings of this study indicate that our cities, and roads in particular, can and should be made smarter. The technology currently exists and is becoming more affordable to allow communities of all sizes to implement smart streetlight systems for the betterment of city services, resource management, and civilian health and wellbeing. The sooner that these technologies are embraced, the sooner they can be adapted to the specific needs of the community and environment for a more sustainable and innovative future

Group-In: Group Inference from Wireless Traces of Mobile Devices

This paper proposes Group-In, a wireless scanning system to detect static or mobile people groups in indoor or outdoor environments. Group-In collects only wireless traces from the Bluetooth-enabled mobile devices for group inference. The key problem addressed in this work is to detect not only static groups but also moving groups with a multi-phased approach based only noisy wireless Received Signal Strength Indicator (RSSIs) observed by multiple wireless scanners without localization support. We propose new centralized and decentralized schemes to process the sparse and noisy wireless data, and leverage graph-based clustering techniques for group detection from short-term and long-term aspects. Group-In provides two outcomes: 1) group detection in short time intervals such as two minutes and 2) long-term linkages such as a month. To verify the performance, we conduct two experimental studies. One consists of 27 controlled scenarios in the lab environments. The other is a real-world scenario where we place Bluetooth scanners in an office environment, and employees carry beacons for more than one month. Both the controlled and real-world experiments result in high accuracy group detection in short time intervals and sampling liberties in terms of the Jaccard index and pairwise similarity coefficient.Comment: This work has been funded by the EU Horizon 2020 Programme under Grant Agreements No. 731993 AUTOPILOT and No.871249 LOCUS projects. The content of this paper does not reflect the official opinion of the EU. Responsibility for the information and views expressed therein lies entirely with the authors. Proc. of ACM/IEEE IPSN'20, 202

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

Computational Challenges in Cooperative Intelligent Urban Transport

This report documents the talks and group work of Dagstuhl Seminar 16091 “Computational Challenges in Cooperative Intelligent Urban Transport”. This interdisciplinary seminar brought researchers together from many fields including computer science, transportation, operations research, mathematics, machine learning and artificial intelligence. The seminar included two formats of talks: several minute research statements and longer overview talks. The talks given are documented here with abstracts. Furthermore, this seminar consisted of significant amounts of group work that is also documented with short abstracts detailing group discussions and planned outcomes

北九州市における低炭素都市モビリティデザインのための歩行者のプロフィール・活動・環境に関する研究

By understanding the walking experience, the importance of walking in sustainable urban development could be comprehended. A tool for urban planning was proposed so that an urban area could be improved to become a walk-able area.北九州市立大