Multivariate Time Series (MTS) data capture temporal behaviors to provide invaluable insights into various physical dynamic phenomena. In smart mobility, MTS plays a crucial role in providing temporal dynamics of behaviors such as maneuver patterns, enabling early detection of anomalous behaviors while facilitating pro-activity in Prognostics and Health Management (PHM). In this work, we aim to address challenges associated with modeling MTS data collected from a vehicle using sensors. Our goal is to investigate the effectiveness of two distinct unsupervised representation learning approaches in identifying maneuvering states in smart mobility. Specifically, we focus on some bivariate accelerations extracted from 2.5 years of driving, where the dataset is non-stationary, long, noisy, and completely unlabeled, making manual labeling impractical. The approaches of interest are Temporal Neighborhood Coding for Maneuvering (TNC4Maneuvering) and Decoupled Local and Global Representation learner for Maneuvering (DLG4Maneuvering). The main advantage of these frameworks is that they capture transferable insights in a form of representations from the data that can be effectively applied in multiple subsequent tasks, such as time-series classification, clustering, and multi-linear regression, which are the quantitative measures and qualitative measures, including visualization of representations themselves and resulting reconstructed MTS, respectively. We compare their effectiveness, where possible, in order to gain insights into which approach is more effective in identifying maneuvering states in smart mobility.

Wejo Group Limited a global leader in Smart Mobility for Good cloud and software analytics for connected, electric and autonomous mobility, announced that it has entered into a definitive business combination agreement to combine with TKB Critical Technologies 1. The proposed business combination is subject to a number of closing conditions and the parties anticipate that the transaction will close in the second quarter of 2023. Upon closing of the business combination, the combined company will retain Wejo's ticker symbol and will continue to trade on the Nasdaq Stock Market LLC. Through a combination of an anticipated PIPE raise and funds from TKB's trust, Wejo believes that this transaction can raise up to $100 million to fund its growth initiatives and position the company to execute on its strategic goals, and potentially reach cash flow breakeven which is expected by mid-2025. Wejo will continue to work on additional short-term funding initiatives to provide bridge capital until the transaction closes.

Wejo, a global leader in Smart Mobility for Good and cloud and software solutions for connected, electric, and autonomous vehicles, announced it has joined the MONET Consortium, an organization actively promoting collaboration and innovation for mobility services in Japan. As part of the MONET Consortium, Wejo will have the opportunity to work with companies selected from the hundreds of diverse and industry-leading members to drive forward mobility innovation and the mobility-as-a-service (MaaS) market, which could be worth $61 billion in 2030, according to Yano Research Institute. Bringing its groundbreaking solutions to the table, Wejo will provide new perspectives and ideas to the collective conversation while extending its influence in Japan which has the 3rd largest economy in the world and a high level of urbanization, making it naturally incentivized to develop smart mobility innovations. Japan, according to Statista's "Automobile Sector in Japan" report, also produces 8.1 million vehicles per year, which aligns with Wejo's aim to make a more globalized impact with its connected vehicle data and Smart Mobility for Good technology. "With the anticipated growth of MaaS offerings in Japan, we see the potential for a nearly three-billion-dollar addressable market by 2030 for Wejo Smart Mobility for Good products and services," said Richard Barlow, founder and CEO at Wejo. "We're honored to be a part of the MONET Consortium and be part of the conversations that will help accelerate mobility innovation in Japan."

DUBAI: Six years after the Dubai Roads and Transportation Authority laid the roadmap for driverless vehicles by 2030, smart mobility has swept the landscape with intelligent concepts that are changing the region's social infrastructure. The move has already spurred sustainable cities into high gear with smart transportation such as autonomous shuttles, e-bikes and e-buggies set to own the roads. An excellent example of a fully-integrated residential project is Sharjah Sustainable City. This eco-friendly concept is powering a net-zero energy community with energy-efficient villas that promise to offer sustainable living at no extra cost. Developed by Sharjah Investment and Development Authority in partnership with Diamond Developers, the sustainable city will host the best green technology, including solar-powered smart homes, bio-domes for vertical farming, electric vehicle chargers, driverless shuttles and a biogas plant. "The UAE is the first country in the Gulf Cooperation Council to commit to net-zero by 2050; all growth and development must align with that commitment, which means we have to do our bit," Karim El-Jisr, chief sustainability officer, SSC, told Arab News.

Israel's traffic congestion ranks near the worst among developed economies, but an algorithm can help, says one of the country's IT firms engaged in the auto and mobility sector. ITC, or Intelligent Traffic Control, was one of the artificial intelligence players at Tel Aviv's recent EcoMotion showcase where high-tech and AI firms hope to make transport more efficient and cleaner. Its AI software collects real-time data from road cameras and then sends instructions to manipulate traffic lights based on vehicle flows. "ITC managed to prove mathematically that many traffic jams can be prevented –- if you intervene early enough," said its co-founder and chief technology officer Dvir Kenig, citing a 30 percent drop in traffic at the two junctions using their system. The company says road congestion is a global scourge, calculating that the average driver spends three days a year stuck in traffic, also pumping out greenhouse gas emissions.

Israel's traffic congestion ranks near the worst among developed economies but an algorithm can help, says one of the country's IT firms engaged in the auto and mobility sector. ITC, or Intelligent Traffic Control, was one of the artificial intelligence players at Tel Aviv's recent EcoMotion showcase where high-tech and AI firms hope to make transport more efficient and cleaner. Its AI software collects real-time data from road cameras and then sends instructions to manipulate traffic lights based on vehicle flows. "ITC managed to prove mathematically that many traffic jams can be prevented -- if you intervene early enough," said its co-founder and chief technology officer Dvir Kenig, citing a 30 percent drop in traffic at the two junctions using their system. The company says road congestion is a global scourge, calculating that the average driver spends three days a year stuck in traffic, also pumping out greenhouse gas emissions.

The Workshop on Machine Learning in Smart Mobility (MLSM), is co-located with the 21st International Conference on Intelligent Data Engineering and Automated Learning -- IDEAL 2020, to take place in Guimarães, Portugal, on November 4-6. The workshop's technical program will include a session hosted by the H2020 SIMUSAFE project, "New Training Modules to Increase Usage of'Soft' Modes of Transport". The workshop will gather both the ML community and transportation practitioners to discuss how cutting-edge ML technologies can be effectively applied to improve the performance of transportation and mobility systems on a sustainable basis, according to three important dimensions: economic, environmental, and social. This forum also aims to generate new ideas towards building innovative applications of machine learning into smarter, greener, and safer mobility systems, stimulating contributions that emphasize on how theory and practice are effectively coupled to solve real-life problems in contemporary transportation, naturally including all sorts of mobility modes and their intrinsic interactions. Indeed, contemporary transportation is evolving rapidly on a more intelligent basis, and the concept of Intelligent Transportation Systems (ITS) has become already a reality among us, supporting the infrastructure leading to the emergence of the so-called Smart Mobility, and to a whole bunch of Mobility-as-a-Service (MaaS) options as we witness today.

Artificial Intelligence (AI) helps the vehicle to take decision in complex environment. AI is utilized in automobiles industry for smart mobility. At present, automotive industry has employed advanced driver assistance system (ADAS) and with increase amount of embedded intelligent the industry is progressing towards semi-autonomous vehicle. AI enables real-time recognition of surroundings and automates the vehicle mobility, controls in-vehicle systems, and eventually prevents accident. The various applications of AI in automobile sector is road tracking, capturing driver's gesture and expression, passenger experience, fleet management, weather monitoring, predictive maintenance, location search, E-payment and in-vehicle system control.

Artificial Intelligence (AI) helps the vehicle to take decision in complex environment. AI is utilized in automobiles industry for smart mobility. At present, automotive industry has employed advanced driver assistance system (ADAS) and with increase amount of embedded intelligent the industry is progressing towards semi-autonomous vehicle. AI enables real-time recognition of surroundings and automates the vehicle mobility, controls in-vehicle systems, and eventually prevents accident. The various applications of AI in automobile sector is road tracking, capturing driver's gesture and expression, passenger experience, fleet management, weather monitoring, predictive maintenance, location search, E-payment and in-vehicle system control.

Click here to learn more about Gilad David Maayan. There are a significant number of investments in the automotive industry nowadays. The majority of these investments focus on artificial intelligence (AI) and the optimization of self-driving technology. Meanwhile, new mobility systems and players are making their way into the automotive market. Tesla is trying to improve its autopilot system, Uber is testing robo-taxis, and Google is developing self-driving cars.