In the modern transportation industry, accurate prediction of travelers' next destinations brings multiple benefits to companies, such as customer satisfaction and targeted marketing. This study focuses on developing a precise model that captures the sequential patterns and dependencies in travel data, enabling accurate predictions of individual travelers' future destinations. To achieve this, a novel model architecture with a sliding window approach based on Long Short-Term Memory (LSTM) is proposed for destination prediction in the transportation industry. The experimental results highlight satisfactory performance and high scores achieved by the proposed model across different data sizes and performance metrics. This research contributes to advancing destination prediction methods, empowering companies to deliver personalized recommendations and optimize customer experiences in the dynamic travel landscape.

For residents of Kosuge, an idyllic village nestled in a valley deep in the mountains of Yamanashi Prefecture, fast food is a luxury. There aren't any convenience stores or supermarkets in the tiny community, let alone a McDonald's. So when Aeronext Inc. celebrated its 100th on-demand drone delivery in Kosuge in July, the startup treated villagers to fast food chain Yoshinoya Co.'s signature gyūdon beef bowls -- steamed rice topped with thinly sliced beef and simmered onions. Amid a small crowd of curious onlookers, hot meals prepared in a Yoshinoya kitchen car were hauled onto spider-like drones that took off in regular intervals to several drop-off stations dotted around the village. For those who got to savor the dish, it was a taste of the city delivered by air, and a glimpse of a future in which these flying devices could become an essential part of rural life.

Some experts suspect they won't circulate widely for another decade. But earlier this month, the state of California adopted new rules governing how ride-hail services without a driver behind the wheel might work. There are separate rules for autonomous vehicles with safety drivers, and those without. But operators of both types of services will have to hand over lots of information to the government: data on where robotaxi riders are picked up and dropped off; how many miles the vehicles travel; whether the vehicles are powered by gas or electricity; whether rides are available in underserved communities; and a safety plan, which Californians will be able to comment on. The rules contrast sharply with the first-of-their kind ride-hail rules that the state adopted in 2013.

Every major tech company is dedicating resources to breakthroughs in artificial intelligence. Personal assistants like Siri and Alexa have made AI a part of our daily lives. Meanwhile, revolutionary breakthroughs like self-driving cars may not be the norm, but are certainly within reach. As the big guys scramble to infuse their products with artificial intelligence, other companies are hard at work developing their own intelligent technology and services. Here are 30 artificial intelligence companies, according to Forbes, you should know.

With each passing day, the transportation and logistics industry grows more and more complex. Customer expectations are changing constantly, workforces are shifting, and technology is advancing. In response, successful transportation companies are relying on intelligence to provide them with the tools and tactics they need to create security during uncertain times. If you've already undergone a digital transformation, it's likely that you have already integrated some form of intelligent technology. Now is the time to take it a step further – when you embed intelligence into your business processes across the enterprise, you gain the vision and ability you need to withstand change.

The analysis in this report draws on the results of a global online survey of 289 senior IT executives working in the transportation industry. They include CIOs, CTOs, and other C‑level roles, as well as IT directors, network managers, and other direct reports into the C‑suite. The survey was conducted in August 2018 on behalf of AT&T Business by Longitude, a Financial Times company that has world-class expertise in quantitative and qualitative research. Respondents were based in 3 territories: North America (47%), EMEA (42%), and Asia Pacific (11%), and all work in large organizations that have annual revenues of USD1 billion or more. Up to now, the transportation industry has dealt pretty well with potentially disruptive technologies. For example, airlines, trucking companies, and railways have vast experience in using sensor-based tracking systems such as RFID and GPS, or automated equipment tracking, to make sure their asset utilization and operating efficiency are on-point.

McLeod Software has created the AI Truck Racing League (AITRL), a new organization focused on advancing the understanding of Machine Learning technology in the transportation industry. "Machine Learning is not yet widely understood by many, but to help companies gain a better understanding, we have set up a fun racing simulation as a way for companies to learn and participate. At McLeod Software, we realize Machine Learning is the future happening now. That is why we have created the AI Truck Racing League and the McLeod Software Racing Team," said Vice President of Special Projects Ken Craig. AITRL's open platform enables member-racing teams to use industry standard cutting edge AI technologies.

Ever wonder how your Amazon Prime packages show up at your door mere hours after you place an order? A complex series of operations connects suppliers to manufacturers to wholesalers to retailers to you, the end consumer. Oversight of this process is called supply chain management (SCM). Within SCM, logistics is the portion that handles the movement of goods. Ecommerce giants like Amazon specialize in logistics, while consumer packaged goods leaders like Unilever provide full-spectrum supply chain management services.

Otto developed technology to allow big-rig trucks to drive themselves. Uber, another transportation company working on self-driving technology, acquired Otto in August. Otto developed technology to allow big-rig trucks to drive themselves. Uber, another transportation company working on self-driving technology, acquired Otto in August. Self-driving cars have been getting a lot of attention lately: Uber's self-driving taxis in Pittsburgh, Tesla's semi-autonomous Model S and the driverless Google rides that look like a cross between a Cozy Coupe and a golf cart.