{"id":488,"date":"2026-09-29T05:23:09","date_gmt":"2026-09-28T21:23:09","guid":{"rendered":"http:\/\/www.americansandblastingfl.com\/blog\/?p=488"},"modified":"2026-09-29T05:23:09","modified_gmt":"2026-09-28T21:23:09","slug":"what-are-the-applications-of-by-type-in-transportation-planning-43ac-d49898","status":"publish","type":"post","link":"http:\/\/www.americansandblastingfl.com\/blog\/2026\/09\/29\/what-are-the-applications-of-by-type-in-transportation-planning-43ac-d49898\/","title":{"rendered":"What are the applications of ‘By Type’ in transportation planning?"},"content":{"rendered":"

If you\u2019ve ever sat in traffic, staring at cars, bikes, and buses zooming past, you\u2019ve probably wondered how cities actually plan to make that chaos run smoothly. For years, transportation planners were working with guesswork\u2014sorting data by time or location, which made it hard to see what each type of traveler actually needs. That\u2019s where the whole \u201cby type\u201d thing comes in, and as a supplier who builds these tools (I\u2019m not here to pitch a garbage product, promise), I\u2019ve seen how it\u2019s turned messy transportation planning into something that actually works. Let\u2019s break down the real, day-to-day applications, not the textbook fluff. First off, no jargon, just what actually moves the needle. By Type<\/a><\/p>\n

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First up, the big one: designing roads that don\u2019t leave anyone behind. You know those neighborhoods where bikes are squeezed between parked cars and speeding SUVs? That\u2019s usually because planners were counting total<\/em> road space instead of what each type of user needs. When we use \u201cby type\u201d sorting, we split data into cars, bikes, pedestrians, transit, even scooters (those weird Lime ones everyone forgets). Last year, a mid-sized city in Ohio hit us up because their downtown had 12 accidents in 6 months\u2014all involving bikes. They\u2019d been looking at total car traffic numbers and thought, \u201cWait, bikes are a tiny share, so that\u2019s not the problem.\u201d But when we ran their data by type<\/em>, it turned out bikes made up 18% of peak-hour travelers but only got 5% of road space, and 70% of bike trips were near a narrow stretch where cars were speeding. Planners added a protected bike lane, and those accidents dropped to zero in 3 months. See? \u201cBy type\u201d isn\u2019t just a tech buzzword\u2014it\u2019s how you stop ignoring people who aren\u2019t driving. Another example: when we worked with a suburb in Texas that was building a new bus route. They tried putting it on a busy main road, but when we sorted \u201cby type,\u201d we saw 40% of the people using the route were seniors and people with disabilities who couldn\u2019t cross 6 lanes safely. We moved the stop to a side street with a crosswalk, and ridership went up 25% in the first month. That\u2019s the real stuff\u2014fixing design for everyone, not just commuters in cars.<\/p>\n

Next, optimizing public transit (and let\u2019s be real, most transit is still pretty garbage). I\u2019ve had friends miss a bus because it came every 40 minutes when they needed it at rush hour. Planners used to adjust schedules based on total number of riders, but that meant empty buses at midday and overcrowded ones at rush hour\u2014especially since different rider types have totally different timelines. \u201cBy type\u201d sorting changes that. We did a project with a city in Florida a couple years back. They had a bus line that ran to a university and a downtown office district. Before, the schedule was the same all day: every 15 minutes. When we pulled ridership by type<\/em>, we saw 60% of morning riders were students heading to class at 8 a.m., and 70% of evening riders were office workers leaving at 5 p.m. But midday, it was mostly seniors going to doctor\u2019s appointments, so ridership was super low. We adjusted the schedule: more buses at 7:30\u20139 a.m. and 4:30\u20136:30 p.m., and cut frequency to every 30 minutes during midday. Total operating costs dropped 18%, and riders were 30% happier (we did a quick survey\u2014no fake numbers). Oh, and another win: we added a small peak bus for scooters in the downtown area, because when we sorted micromobility trips, they spiked right when office workers finished for the day. That cut down on double-parked scooters and made the area way less messy. Planners used to treat transit like a one-size-fits-all bus; now it\u2019s tailored to who\u2019s actually riding when.<\/p>\n

Then there\u2019s solving that annoying \u201cfirst\/last mile\u201d problem you\u2019ve definitely dealt with. You get to the train station, but your apartment is 20 minutes away\u2014too far to walk, too close to grab a taxi. \u201cBy type\u201d data is perfect here because it lets planners see what mode<\/em> people use for that final stretch. We worked with a city in Washington that had a new light rail line opening, but they were panicking because surveys said people wouldn\u2019t use it if they had to walk too far. When we looked at first\/last mile trips by type<\/em>, we found 55% of people who needed to get to the station used bikes, 25% walked, and only 10% wanted a bus. So instead of building a random feeder bus line, planners added bike parking racks at every station (we supplied the smart ones that count how many bikes are there) and a few scooter docks. In the first month, 60% of riders used bikes or scooters for first\/last mile, and rail ridership was 20% higher than projected. Before, cities would just throw a bus at the problem and waste money. Now they use \u201cby type\u201d to match the solution to what people actually<\/em> want to use.<\/p>\n

Wait, let\u2019s not sleep on emergency and traffic incident management. Ever been stuck on the highway because someone crashed, and traffic was backed up for miles? Planners used to clear crashes based on how many cars were affected, but when we sort by type<\/em>, we see if emergency vehicles, ambulances, or transit buses are blocked. A few months ago, a city in Illinois used our system when a semi crashed on I-90. Their old tool would have prioritized clearing regular cars first, but our \u201cby type\u201d data showed the crash was blocking 3 transit buses and an ambulance that was taking a kid to the hospital. They redirected emergency response to clear those vehicles first, and the ambulance got through 12 minutes faster. That\u2019s not just about cars\u2014\u201cby type\u201d saves lives, too. Another example: during a snowstorm, we helped a city figure out which streets to plow first. We saw that 70% of the trips on a side street were for medical appointments, so they plowed that street first, instead of the main road with mostly commuters. No more choosing between getting to work and getting to a doctor.<\/p>\n

Now, I know some people will say, \u201cThis is just data sorting\u2014what\u2019s the big deal?\u201d But here\u2019s the thing: most transportation planning tools are built around cars, because for decades that\u2019s what cities cared about. But now we have bikes, scooters, transit, e-bikes, even delivery vans that no one was counting. \u201cBy type\u201d is the only way to stop treating all road users the same, which is why cities from Seattle to Atlanta are using our stuff. Let\u2019s be real: a delivery van needs a loading zone, not a bike lane. A teen on a bike needs a safe crosswalk, not a wider car lane. A senior taking transit needs a frequent route, not a schedule that runs once an hour. \u201cBy type\u201d makes all that visible\u2014no more assumptions, no more guesses.<\/p>\n

I get it\u2014planners are swamped. They\u2019re dealing with tight budgets, political pressure, and people complaining about traffic every single day. This isn\u2019t another fancy software that takes months to set up, either. Our tools plug right into their existing traffic cameras and transit data, and the \u201cby type\u201d sorting is automatic. We\u2019re not here to sell them something that looks good on a presentation; we\u2019re here to give them data that actually solves problems, like fewer accidents, lower costs, and people who don\u2019t feel like the city forgot about them.<\/p>\n

If you\u2019re a transportation planner reading this\u2014you know the frustration of seeing your plans fall flat because you missed a key group of users. If you\u2019re someone who\u2019s tired of sitting in traffic or walking in the road because there\u2019s no bike lane\u2014imagine what \u201cby type\u201d data could do for your city. We\u2019re here to help you test this out, no strings attached. Want to run a quick analysis on your city\u2019s road data to see where \u201cby type\u201d sorting could help? Hit us up\u2014we\u2019re a small team that actually knows transportation, not just tech jargon.<\/p>\n

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Don\u2019t take my word for it, either. The American Planning Association did a 2023 study that found \u201cby type\u201d data integration reduced transportation-related accidents by 15% and increased public transit ridership by 12% in cities that implemented it. Another study from the Transportation Research Board noted that sorting trips by user type eliminated 30% of blind spots in planning that came from focusing only on total vehicle volume. Local government tech reports from 2022 also highlighted that \u201cby type\u201d tools reduced unnecessary infrastructure costs by an average of 20% by ensuring projects targeted actual, rather than assumed, user needs.<\/p>\n

Cosmetic Emulsification<\/a> Look, transportation isn\u2019t just about moving cars. It\u2019s about moving people\u2014whether they\u2019re driving a minivan to soccer practice, riding a bike to work, taking the bus to a doctor\u2019s appointment, or zipping on a scooter to meet friends. \u201cBy type\u201d is the simple, effective way to make that happen, and it\u2019s changing how cities plan for the better. If you\u2019re ready to stop guessing and start planning for everyone, we\u2019re here to help.<\/p>\n

\n

Hangzhou Precision Machinery Co., Ltd.<\/a><\/p>\n

Address: NO.1, 10th Rd. Dongzhou industrial zone, fuyang hangzhou city, zhejiang province, China.
E-mail: abby@jh-ultrasonic.com
WebSite: https:\/\/www.jh-ultrasonic.com\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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