The Visual Difference. See for yourself.

There are a lot of very good reasons to monitor local environmental conditions, especially as they pertain to climate change research and various ecological protection initiatives. But doing so in urban locales is a challenge, as simply mounting a device can be difficult. That’s why a team from MIT’s Senseable City Lab built Octopus, which […] The post MIT’s Octopus is a delightful environmental sensor for urban deployment appeared first on Arduino Blog.

I have an ongoing fascination with "interactive TV": a series of efforts, starting in the 1990s and continuing today, to drag the humble living room television into the world of the computer. One of the big appeals of interactive TV was adoption, the average household had a TV long before the average household had a computer. So, it seems like interactive TV services should have proliferated before personal computers, at least following the logic that many in the industry did at the time. This wasn't untrue! In the UK, for example, Ceefax was a widespread success by the 1980s. In general, TV-based teletext systems were pretty common in Europe. In North America, they never had much of an impact---but not for lack of trying. In fact, there were multiple competing efforts at teletext in the US and Canada, and it may very well have been the sheer number of independent efforts that sunk the whole idea. But let's start at the beginning. The BBC went live with Ceefax in 1974, the culmination of years of prototype development and test broadcasts over the BBC network. Ceefax was quickly joined by other teletext standards in Europe, and the concept enjoyed a high level of adoption. This must have caught the attention of many in the television industry on this side of the ocean, but it was Bonneville International that first bit [1]. Its premier holding, KSL-TV of Salt Lake City, has an influence larger than its name suggests: KSL was carried by an extensive repeater network and reached a large portion of the population throughout the Mountain States. Because of the wide reach of KSL and the even wider reach of the religion that relied on Bonneville for communications, Bonneville was also an early innovator in satellite distribution of television and data. These were ingredients that made for a promising teletext network, one that could quickly reach a large audience and expand to broader television networks through satellite distribution. KSL applied to the FCC for an experimental license to broadcast teletext in addition to its television signal, and received it in June of 1978. I am finding some confusion in the historical record over whether KSL adopted the BBC's Ceefax protocol or the competing ORACLE, used in the UK by the independent broadcasters. A 1982 paper on KSL's experiment confusingly says they used "the British CEEFAX/Oracle," but then in the next sentence the author gives the first years of service for Ceefax and ORACLE the wrong way around, so I think it's safe to say that they were just generally confused. I think I know the reason why: in the late '70s, the British broadcasters were developing something called World System Teletext (WST), a new common standard based on aspects of both Ceefax and ORACLE. Although WST wasn't quite final in 1978, I believe that what KSL adopted was actually a draft of WST. That actually hints at an interesting detail which becomes important to these proposals: in Europe, where teletext thrived, there were usually not very many TV channels. The US's highly competitive media landscape lead to a proliferation of different TV networks, and local operations in addition. It was a far cry from the UK, for example, where 1982 saw the introduction of a fourth channel called, well, Channel 4. By contrast, Salt Lake City viewers with cable were picking from over a dozen channels in 1982, and that wasn't an especially crowded media market. This difference in the industry, between a few major nationwide channels and a longer list of often local ones, has widespread ramifications on how UK and US television technology evolved. One of them is that, in the UK, space in the VBI to transmit data became a hotly contested commodity. By the '80s, obtaining a line of the VBI on any UK network to use for your new datacasting scheme involved a bidding war with your potential competitors, not unlike the way spectrum was allocated in the US. Teletext schemes were made and broken by the outcomes of these auctions. Over here, there was a long list of television channels and on most of them only a single line of the VBI was in use for data (line 21 for closed captions). You might think this would create fertile ground for VBI-based services, but it also posed a challenge: the market was extensively fractured. You could not win a BBC or IBA VBI allocation and then have nationwide coverage, you would have to negotiate such a deal with a long list of TV stations and then likely provide your own infrastructure for injecting the signal. In short, this seems to be one of the main reasons for the huge difference in teletext adoption between Europe and North America: throughout Europe, broadcasting tended to be quite centralized, which made it difficult to get your foot in the door but very easy to reach a large customer base once you had. In the US, it was easier to get started, but you had to fight for each market area. "Critical mass" was very hard to achieve [2]. Back at KSL, $40,000 (~$200,000 today) bought a General Automation computer and Tektronix NTSC signal generator that made up the broadcast system. The computer could manage as many as 800 pages of 20x32 teletext, but KSL launched with 120. Texas Instruments assisted KSL in modifying thirty television sets with a new decoder board and a wired remote control for page selection. This setup, very similar to teletext sets in Europe, nearly doubled the price of the TV set. This likely would have become a problem later on, but for the pilot stage, KSL provided the modified sets gratis to their 30 test households. One of the selling points of teletext in Europe was its ability to provide real-time data. Things like sports scores and stock quotations could be quickly updated in teletext, and news headlines could make it to teletext before the next TV news broadcast. Of course, collecting all that data and preparing it as teletext pages required either a substantial investment in automation or a staff of typists. At the pilot stage, KSL opted for neither, so much of the information that KSL provided was out-of-date. It was very much a prototype. Over time, KSL invested more in the system. In 1979, for example, KSL partnered with the National Weather Service to bring real-time weather updates to teletext---all automatically via the NWS's computerized system called AFOS. At that time, KSL was still operating under an experimental license, one that didn't allow them to onboard customers beyond their 30-set test market. The goal was to demonstrate the technology and its compatibility with the broader ecosystem. In 1980, the FCC granted a similar experimental license to CBS affiliated KMOX in St. Louis, who started a similar pilot effort using a French system called Antiope. Over the following few years, the FCC allowed expansion of this test to other CBS affiliates including KNXT in Los Angeles. To emphasize the educational and practical value of teletext (and no doubt attract another funding source), CBS partnered with Los Angeles PBS affiliate KCET who carried their own Teletext programming with a characteristic slant towards enrichment. Meanwhile, in Chicago, station WFLD introduced a teletext service called Keyfax, built on Ceefax technology as a joint venture with Honeywell and telecom company Centel. Despite the lack of consumer availability, teletext was becoming a crowded field---and for the sake of narrative simplicity I am leaving out a whole set of other North American ventures right now. In 1983, there were at least a half dozen stations broadcasting teletext based on British or French technology, and yet, there were zero teletext decoders on the US market. Besides their use of an experimental license, the teletext pilot projects were constrained by the need for largely custom prototype decoders integrated into customer's television sets. Broadcast executives promised the price could come down to $25, but the modifications actually available continued to cost in the hundreds. The director of public affairs at KSL, asked about this odd conundrum of a nearly five-year-old service that you could not buy, pointed out that electronics manufacturers were hesitant to mass produce an inexpensive teletext decoder as long as it was unclear which of several standards would prevail. The reason that no one used teletext, then, was in part the sheer number of different teletext efforts underway. And, of course, things were looking pretty evenly split: CBS had fully endorsed the French-derived system, and was a major nationwide TV network. But most non-network stations with teletext projects had gone the British route. In terms of broadcast channels, it was looking about 50/50. Further complicating things, teletext proper was not the only contender. There was also videotex. The terminology has become somewhat confused, but I will stick to the nomenclature used in the 1980s: teletext services used a continuous one-way broadcast of every page and decoders simply displayed the requested page when it came around in the loop. Videotex systems were two-way, with the customer using a phone line to request a specific page which was then sent on-demand. Videotex systems tended to operate over telephone lines rather than television cable, but were frequently integrated into television sets. Videotex is not as well remembered as teletext because it was a massive commercial failure, with the very notable exception of the French Minitel. But in the '80s they didn't know that yet, and the UK had its own videotex venture called Prestel. Prestel had the backing of the Post Office, because they ran the telephones and thus stood to make a lot of money off of it. For the exact same reason, US telephone company GTE bought the rights to the system in the US. Videotex is significantly closer to "the internet" in its concept than teletext, and GTE was entering a competitive market. In 1981, Radio Shack had introduced a videotex terminal for several years already, a machine originally developed as the "AgVision" for use with an experimental Kentucky agricultural videotex service and then offered nationwide. This creates an amusing irony: teletext services existed but it was very difficult to obtain a decoder to use them. Radio Shack was selling a videotex client nationwide, but what service would you use it with? In practice, the "TRS-80 Videotex" as the AgVision came to be known was used mostly as a client for CompuServe and Dow Jones. Neither of these were actually videotex services, using neither the videotex UX model nor the videotex-specific features of the machine. The TRS-80 Videotex was reduced to just a slightly weird terminal with a telephone modem, and never sold well until Radio Shack beefed it up into a complete microcomputer and relaunched it as the TRS-80 Color Computer. Radio Shack also sold a backend videotex system, and apparently some newspapers bought it in an effort to launch a "digital edition." The only one to achieve long-term success seems to have been StarText, a service of the Fort Worth Star-Telegram. It was popular enough to be remembered by many from the Fort Worth area, but there was little national impact. It was clearly not enough to float sales of the TRS-80 Videotex and the whole thing has been forgotten. Well, with such a promising market, GTE brought its US Prestel service to market in 1982. As the TRS-80 dropped its Videotex ambitions, Zenith launched a US television set with a built-in Prestel client. Prestel wasn't the only videotex operation, and GTE wasn't the only company marketing videotex in the US. If the British Post Office and GTE thought they could make money off of something, you know AT&T was somewhere around. They were, and in classic AT&T fashion. During the 1970s, the Canadian Communications Research Center developed a vector-based drawing system. Ontario manufacturer Norpak developed a consumer terminal that could request full-color pages from this system using a videotex-like protocol. Based on the model of Ceefax, the CRC designed a system called Telidon that worked over television (in a more teletext-like fashion) or phone lines (like videotex), with the capability of publishing far more detailed graphics than the simple box drawings of teletext. Telidon had several cool aspects, like the use of a pretty complicated vector-drawing terminal and a flexible protocol designed for interoperability between different communications media. That's the kind of thing AT&T loved, so they joined the effort. With CRC, AT&T developed NABTS, the North American Broadcast Teletext Specification---based on Telidon and intended for one-way broadcast over TV networks. NABTS was complex and expensive compared to Ceefax/ORACLE/WST based systems. A review of KSL's pilot notes how the $40,000 budget for their origination system compared to the cost quoted by AT&T for an NABTS headend: as much as $2 million. While KSL's estimates of $25 for a teletext decoder had not been achieved, the prototypes were still running cheaper than NABTS clients that ran into the hundreds. Still, the graphical capabilities of NABTS were immediately impressive compared to text-only services. Besides, the extensibility of NABTS onto telephone systems, where pages could be delivered on-demand, made it capable of far larger databases. When KSL first introduced teletext, they spoke of a scheme where a customer could call a phone number and, via DTMF menus, request an "extended" page beyond the 120 normally transmitted. They could then request that page on their teletext decoder and, at the end of the normal 120 page loop, it would be sent just for them. I'm not sure if that was ever implemented or just a concept. In any case, videotex systems could function this way natively, with pages requested and retrieved entirely by telephone modem, or using hybrid approaches. NABTS won the support of NBC, who launched a pilot NABTS service (confusingly called NBC Teletext) in 1981 and went into full service in 1983. CBS wasn't going to be left behind, and trialed and launched NABTS (as CBS ExtraVision) at the same time. That was an ignominious end for CBS's actual teletext pilot, which quietly shut down without ever having gone into full service. ExtraVision and NBC Teletext are probably the first US interactive TV services that consumers could actually buy and use. Teletext was not dead, though. In 1982, Cincinnati station WKRC ran test broadcasts for a WST-based teletext service called Electra. WKRC's parent company, Taft, partnered with Zenith to develop a real US-market consumer WST decoder for use with the Electra service. In 1983, the same year that ExtraVision and CBS Teletext went live, Zenith teletext decoders appeared on the shelves of Cincinnati stores. They were plug-in modules for recent Zenith televisions, meaning that customers would likely also need to buy a whole new TV to use the service... but it was the only option, and seems to have remained that way for the life of US teletext. I believe that Taft's Electra was the first teletext service to achieve a regular broadcast license. Through the mid 1980s, Electra would expand to more television stations, reaching similar penetration to the videotex services. In 1982, KeyFax (remember KeyFax? it was the one on WFLD in Chicago) had made the pivot from teletext to videotex as well, adopting the Prestel-derived technology from GTE. In 1984, KeyFax gave up on their broadcast television component and became a telephone modem service only. Electra jumped on the now-free VBI lines of WFLD and launched in Chicago. WTBS in Atlanta carried Electra, and then in the biggest expansion of teletext, Electra appeared on SPN---a satellite network that would later become CNBC. While major networks, and major companies like GTE and AT&T, pushed for the videotex NABTS, teletext continued to have its supporters among independent stations. Los Angeles's KTTV started its own teletext service in 1984, which combined locally-developed pages with national news syndicated from Electra. This seemed like the start of a promising model for teletext across independent stations, but it wasn't often repeated. Oh, and KSL? at some point, uncertain to me but before 1984, they switched to NABTS. Let's stop for a moment and recap the situation. Between about 1978 and 1984, over a dozen major US television stations launched interactive TV offerings using four major protocols that fell into two general categories. One of those categories was one-way over television while the other was two-way over telephone or one-way over television with some operators offering both. Several TV stations switched between types. The largest telcos and TV networks favored one option, but it was significantly more expensive than the other, leading smaller operators to choose differently. The hardware situation was surprisingly straightforward in that, within teletext and videotex, consumers only had one option and it was very expensive. Oh, and that's just the technical aspects. The business arrangements could get even stranger. Teletext services were generally free, but videotex services often charged a service fee. This was universally true for videotex services offered over telephone and often, but not always, true for videotex services over cable. Were the videotex services over cable even videotex? doesn't that contradict the definition I gave earlier? is that why NBC called their videotex service teletext? And isn't videotex over telephone barely differentiated from computer-based services like CompuServe and The Source that were gaining traction at the same time? I think this all explains the failure of interactive TV in the 1980s. As you've seen, it's not that no one tried. It's that everyone tried, and they were all tripping over each other the entire time. Even in Canada, where the government had sponsored development of the Telidon system ground-up to be a nationwide standard, the influence of US teletext services created similar confusion. For consumers, there were so many options that they didn't know what to buy, and besides, the price of the hardware was difficult to justify with the few stations that offered teletext. The fact that teletext had been hyped as the "next big thing" by newspapers since 1978, and only reached the market in 1983 as a shambled mess, surely did little for consumer confidence. You might wonder: where was the FCC during this whole thing? In the US, we do not have a state broadcaster, but we do have state regulation of broadcast media that is really quite strict as to content and form. During the late '70s, under those first experimental licenses, the general perception seemed to be that the FCC was waiting for broadcasters to evaluate the different options before selecting a nationwide standard. Given that the FCC had previously dictated standards for television receivers, it didn't seem like that far of a stretch to think that a national-standard teletext decoder might become mandatory equipment on new televisions. Well, it was political. The long, odd experimental period from 1978 to 1983 was basically a result of FCC indecision. The commission wasn't prepared to approve anything as a national standard, but the lack of approval meant that broadcasters weren't really allowed to use anything outside of limited experimental programs. One assumes that they were being aggressively lobbied by every side of the debate, which no doubt factored into the FCC's 1981 decision that teletext content would be unregulated, and 1982 statements from commissioners suggesting that the FCC would not, in fact, adopt any technical standards for teletext. There is another factor wrapped up in this whole story, another tumultuous effort to deliver text over television: closed captioning. PBS introduced closed captioning in 1980, transmitting text over line 21 of the VBI for decoding by a set-top box. There are meaningful technical similarities between closed captioning and teletext, to the extent that the two became competitors. Some broadcasters that added NABTS dropped closed captioning because of incompatibility between the equipment in use. This doesn't seem to have been a real technical constraint, and was perhaps more likely cover for a cost-savings decision, but it generated considerable controversy that lead to the National Association for the Deaf organizing for closed captioning and against teletext. The topic of closed captioning continued to haunt interactive TV. TV networks tended to view teletext or videotex as the obvious replacements for line 21 closed captioning, due to their more sophisticated technical features. Of course, the problems that limited interactive TV adoption in general, high cost and fragmentation, made it unappealing to the deaf. Closed captioning had only just barely become well-standardized in the mid-1980s and its users were not keen to give it up for another decade of frustration. While some deaf groups did support NABTS, the industry still set up a conflict between closed captioning and interactive TV that must have contributed to the FCC's cold feet. In April of 1983, at the dawn of US broadcast teletext, the FCC voted 6-1 to allow television networks and equipment manufacturers to support any teletext or videotex protocol of their choice. At the same time, they declined to require cable networks to carry teletext content from broadcast television stations, making it more difficult for any TV network to achieve widespread adoption [3]. The FCC adopted what was often termed a "market-based" solution to the question of interactive TV. The market would not provide that solution. It had already failed. In November of 1983, Time ended their teletext service. That's right, Time used to have a TV network and it used to have teletext; it was actually one of the first on the market. It was also the first to fall, but they had company. CBS and NBC had significantly scaled back their NABTS programs, which were failing to make any money because of the lack of hardware that could decode the service. On the WST side of the industry, Taft reported poor adoption of Electra and Zenith reported that they had sold very few decoders, so few that they were considering ending the product line. Taft was having a hard time anyway, going through a rough reorganization in 1986 that seems to have eliminated most of the budget for Electra. Electra actually seems to have still been operational in 1992, an impressive lifespan, but it says something about the level of adoption that we have to speculate as to the time of death. Interactive TV services had so little adoption that they ended unnoticed, and by 1990, almost none remained. Conflict with closed captioning still haunted teletext. There had been some efforts towards integrating teletext decoders into TV sets, by Zenith for example, but in 1990 line 21 closed caption decoding became mandatory. The added cost of a closed captioning decoder, and the similarity to teletext, seems to have been enough for the manufacturing industry to decide that teletext had lost the fight. Few, possibly no teletext decoders were commercially available after that date. In Canada, Telidon met a similar fate. Most Telidon services were gone by 1986, and it seems likely that none were ever profitable. On the other hand, the government-sponsored, open-standards nature of Telidon mean that it and descendants like NABTS saw a number of enduring niche uses. Environment Canada distributed weather data via a dedicated Telidon network, and Transport Canada installed Telidon terminals in airports to distribute real-time advisories. Overall, the Telidon project is widely considered a failure, but it has had enduring impact. The original drawing vector drawing language, the idea that had started the whole thing, came to be known as NAPLPS, the North American Presentation Layer Protocol Syntax. NAPLPS had some conceptual similarities to HTML, as Telidon's concept of interlinking did to the World Wide Web. That similarity wasn't just theoretical: Prodigy, the second largest information service after CompuServe and first to introduce a GUI, ran on NAPLPS. Prodigy is now viewed as an important precursor to the internet, but seen in a different light, it was just another videotex---but one that actually found success. I know that there are entire branches of North American teletext and videotex and interactive TV services that I did not address in this article, and I've become confused enough in the timeline and details that I'm sure at least one thing above is outright wrong. But that kind of makes the point, doesn't it? The thing about teletext here is that we tried, we really tried, but we badly fumbled it. Even if the internet hadn't happened, I'm skeptical that interactive television efforts would have gotten anywhere without a complete fresh start. And the internet did happen, so abruptly that it nearly killed the whole concept while television carriers were still tossing it around. Nearly killed... but not quite. Even at the beginning of the internet age, televisions were still more widespread than computers. In fact, from a TV point of view, wasn't the internet a tremendous opportunity? Internet technology and more compact computers could enable more sophisticated interactive television services at lower prices. At least, that's what a lot of people thought. I've written before about (Cablesoft)[https://computer.rip/2024-11-23-cablesoft.html] and it is just one small part of an entire 1990s renaissance of interactive TV. There's a few major 1980s-era services that I didn't get to here either. Stick around and you'll hear more. You know what's sort of funny? Remember the AgVision, the first form of the TRS-80? It was built as a client for AGTEXT, a joint project of Kentucky Educational Television (who carried it on the VBI of their television network) and the Kentucky College of Agriculture. At some point, AGTEXT switched over the line 21 closed captioning protocol and operated until 1998. It was almost the first teletext service, and it may very well have been the last. [1] There's this weird thing going on where I keep tangentially bringing up Bonnevilles. I think it's just a coincidence of what order I picked topics off of my list but maybe it reflects some underlying truth about the way my brain works. This Bonneville, Bonneville International, is a subsidiary of the LDS Church that owns television and radio stations. It is unrelated, except by being indirectly named after the same person, to the Bonneville Power Administration that operated an early large-area microwave communications network. [2] There were of course large TV networks in the US, and they will factor into the story later, but they still relied on a network of independent but affiliated stations to reach their actual audience---which meant a degree of technical inconsistency that made it hard to rollout nationwide VBI services. Providing another hint at how centralization vs. decentralization affected these datacasting services, adoption of new datacasting technologies in the US has often been highest among PBS and NPR affiliates, our closest equivalents to something like the BBC or ITV. [3] The regulatory relationship between broadcast TV stations, cable network TV stations, and cable carriers is a complex one. The FCC's role in refereeing the competition between these different parts of the television industry, which are all generally trying to kill each other off, has lead to many odd details of US television regulation and some of the everyday weirdness of the American TV experience. It's also another area where the US television industry stands in contrast to the European television industry, where state-owned or state-chartered broadcasting meant that the slate of channels available to a consumer was generally the same regardless of how they physically received them. Not so in the US! This whole thing will probably get its own article one day.

other irredeemably nerdy habit is roadgeeking, exploring and mapping highways both old and new, and it turns out that 8-bit roadgeeking on ordinary home computers was absolutely possible. For computers of this class, devising an optimal highway route becomes an exercise not only in how to encode sufficient map data to a floppy disk, but also performing efficient graph traversal with limited hardware. Today we'll explore Roadsearch-Plus, one of the (if not the) earliest such software — primarily on the Commodore 64, but originating on the Apple II — and at the end "drive" all the way from southern California to British Columbia along US Highway 395, my first long haul expedition, but as it was in 1985. Buckle up while we crack the program's runtime library, extract its database, and (working code included) dive deeply into the quickest ways to go from A to B using a contemporary home computer. Although this article assumes a little bit of familiarity with the United States highway system, I'll provide a 30-second version. The top-tier national highway network is the 1956 Eisenhower Interstate System (abbreviated I-, such as I-95), named for president Dwight D. Eisenhower who promulgated it, signed with red, white and blue shields. Nearly all of its alignments, which is to say the physical roads composing it, are grade-separated full freeway. It has come to eclipse the 1926 United States Numbered Highway System (abbreviated US, such as US 395), a nationally-numbered grid system of highways maintained by the states, albeit frequently with federal funding. Signed using a horned white shield, these roads vary from two-lane highway all the way to full freeway and may be multiplexed (i.e., multiply signed) with other US highways or Interstates in many areas. While they are no longer the highest class of U.S. national road, they nevertheless remain very important for regional links especially in those areas that Interstates don't service. States and counties maintain their own locally allocated highway systems in parallel. Here is a glossary of these and other roadgeek terms. Geographic information systems (GIS) started appearing in the 1960s, after Waldo Tobler's 1959 "Automation and Cartography" paper about his experience with the military Semi-Autographic Ground Environment system. SAGE OA-1008 displays relied on map transparencies developed manually but printed with computers like the IBM 704. Initially such systems contained only geographic features like terrain and coastlines and specific points of interest, but support for highways as a layer or integral component was rapidly implemented for land use applications, and such support became part of most, if not all, mainframe and minicomputer GIS systems by the late 1970s. However, these systems generally only handled highways as one of many resource or entity types; rarely were there specific means of using them for navigational purposes. Honda Electro-Gyrocator. Because Global Positioning System (GPS) satellite data was not then available for civilian applications and other radio navigational systems like LoRAN were hard to reliably receive in canyons or tunnels, it relied on its own internal gas gyroscope to detect rotation and movement aided by a servo in the car's transmission. The Electro-Gyrocator used a Texas Instruments TMS9980 (a derivative of the 16-bit TMS9900 in the TI-99/4A but with an 8-bit data bus) as its CPU and a sidecar TMS9901 for I/O. It had 10K of ROM, 1K of SRAM and 16K of DRAM, hopeless for storing map data of any consequence, so the actual maps were transparencies too; the 9980 integrated sensor data provided by the 9901 from the gyroscope and servo to plot the car's course on a small 6" CRT behind the map overlay. The user was expected to set the starting location on the map before driving and there was likewise no provision for routing. It was only made available that year for ¥300,000 (about US$2900 in 2025 dollars at current exchange rates) on the JDM Honda Accord and Honda Vigor, and discontinued by 1982. There were also a few early roadgeek-oriented computer and console games, which I distinguish from more typical circuit or cross-country racers by an attempt to base them on real (not fictional) roads with actual geography. One I remember vividly was Imagic's Truckin', a Mattel Intellivision-exclusive game from 1983 which we played on our Tandyvision One. Juggernaut for the ZX Spectrum by at least two years, and Juggernaut uses a completely fictitious game world instead. you're expected to do that! an easter egg. Besides very terse prompts and a heavily compressed internal routing table, the game makes all highway numbers unique and has no multiplexes or three-digit auxiliary Interstates, and while you can drive into Canada you can't drive into Mexico (admittedly it was pre-NAFTA). Additionally, for gameplay reasons every highway junction is a named "city," introducing irregularities like Interstate 70 ending in Provo, UT when it really ends about 130 miles south, or Interstate 15 ending in El Cajon, CA, and many cities and various two-digit primary Interstates are simply not included (e.g., I-12, I-19, I-30, I-85, I-93, etc.). As a result of these constraints, among other inaccuracies Interstate 90 terminates in Madison, WI at I-94 (not Boston), I-94 terminates in Milwaukee at I-55 (not Port Huron, MI), and I-40 is extended west from its true terminus in Barstow, CA along real-world California State Highway 58 to intersect I-5 "in Bakersfield" (real Interstate 5 is around twenty miles away). Still, it contains an extensive network of real highways with their lengths and control cities, managing it all on an early console platform with limited memory, while simultaneously supporting full 1983-level gameplay. The 8-bit home computer was ascendant during the same time and at least one company perceived a market for computer-computed routes with vacations and business trips. I can't find any references to an earlier software package of this kind for this class of computer, at least in the United States, so we'll call it the first. The Software Writer's Marketplace from 1984. If this is the same person, he later appears in a 2001 document as the Ground and Mission Systems Manager at the NASA Goddard Space Flight Center in Greenbelt, Maryland, about a half hour's drive away. Columbia Software does not appear in any magazines prior to 1982 nor does it appear after 1985, though no business record under that name is known to either the state of Maryland or the state of Delaware. T%(), N%() and B%() which sound like Applesoft BASIC integer arrays. (The file MPH just contains the MPG and MPH targets in text.) In fact, there are actually two compiled programs present, ROADSEARCH (the main executable) and DBA (the distance editor), and using these "variable" files allows both programs to keep the memory image of the arrays, no doubt the representation of its map database, consistent between them. You can start either compiled program by BRUNning them, as HELLO does. Exactly which compiler we can also make a fairly educated guess about: there were only a few practical choices in 1981-82 when it was probably written, and most of them we can immediately eliminate due to what they (don't) support or what they (don't) generate. For example, being almost certainly Applesoft BASIC would obviously eliminate any Integer BASIC compiler. It also can't be On-Line Systems' Expediter II because that generates "Applesoft BASIC" programs with a single CALL statement instead of binaries that are BRUN, and it probably isn't Southwestern Data Systems' Speed Star because of the apparent length of the program and that particular compiler's limited capacity. That leaves the two major compilers of this era, Microsoft's TASC ("The Applesoft Compiler"), which was famously compiled with itself, and Hayden Book Company's Applesoft Compiler. TASC uses a separate runtime that must be BLOADed before BRUNning the main executable, which HELLO doesn't do. Hayden's compiler is thus the most likely tool, and this theory is buoyed by the fact that this compiler does support variable sharing between modules. If we run strings on the DOS 3.3 .dsk image, we see things like Accounting for the fact that the disk interleave will not necessarily put lines in sequential order, you can pick out the strings of the program as well as a number of DOS 3.3 file manager commands, sometimes in pieces, such as B%(),A30733,L5448 which is probably part of a BSAVE command, or BLOAD B%(),A30733. The disk also has examples of both kinds of DOS 3.3 text files, both sequentially accessed (such as OPEN T%(), READ T%() and CLOSE T%()) but also the less commonly encountered random access (with explicitly specified record numbers and lengths such as OPEN ROADS,L12 and OPEN ROADMAP CITIES,L19, then READ ROADS,R and READ ROADMAP CITIES,R which would be followed by the record number). For these random access files, given a record length and record number, the DOS track-and-sector list is walked to where that record would be and only the necessary sector(s) are read to construct and return the record. We can see the contents with a quick Perl one-liner to strip off the high bit and feeding that to strings: Again note that the order is affected by the disk interleave, but the file is stored alphabetically (we'll extract this file properly in a moment). Another interesting string I found this way was "TIABSRAB WS AIBMULOC" which is COLUMBIA SW BARSBAIT backwards. Perhaps someone can explain this reference. In a hex editor the city database looks like this, where you can see the regularly repeating 19-byte record format for the names. Remember that the characters are stored with the high bit set. This is not a very efficient means of storage especially considering DOS 3.3 only had 124K free per disk side (after DOS itself and filesystem overhead), but it would be a lot easier for an Applesoft BASIC program to handle since the record lookup work could be shunted off to DOS 3.3 and performed quickly. Also, while you can list the cities and junctions from the menu, they are not indexed by state, only by first letter: ROADMAP CITIES to the emulator's virtual printer. We know its record length because it was stored as a string in the compiled BASIC text we scanned previously. That, in turn, gives us a text file we can read on the Mac side. It is, as expected, 406 lines long. The same process gets us the ROADS list, which is 171 lines long. Keep in mind that's just a list of the names of the roads; it does not contain information on the actual highway segments between points. T%()), where for each letter index 1-26, the value is the first record number for all cities starting with that letter. As we saw previously, the cities are already sorted on disk to facilitate. There are no cities starting with Z, so that letter just goes to the end of the file (non-existent record 407) and terminates. B%() and N%(), but we'll solve that problem a little later on. and updated routing information. However, this release appears to be specific to the Commodore port — if there were a 1985 map update for the Apple II, it has yet to surface — and I can find no subsequent release of Roadsearch after 1985 on any platform. Both C64 versions came in the same Roadsearch and Roadsearch-Plus variants for the same prices, so the iteration we'll explore here is Roadsearch-Plus with the presumed final 1985 database. For purposes of emulation we'll use VICE's SuperCPU spin with the 65816 enabled as some number crunching is involved, but I also tested it on my real Commodore SX-64 and 128DCR for veracity. (Running xscpu64 in warp mode will absolutely tear through any routing task, but I strongly recommend setting location 650 to 64 in the VICE monitor to disable key repeat.) It's worth noting that the various circulating 1541 disk images of the 1984 and 1985 editions were modified to add entries by their previous owners, though we'll point out how these can be detected and reversed. For much of this article I'll be running a 1985 disk that I manually cleared in a hex editor to what I believe was its original contents. ROADSEARCH+), the editor (IDBA) and two RELative files for the CITIES and ROADS. RELative files are functionally equivalent to DOS 3.3 random access files, being a record-based file format with a fixed size and an index (made up of "side sectors"). They are an uncommon sight on commercial software due to their idiosyncracies and a few outright bugs, and they don't work well for binary data or support variable record sizes which is why Berkeley Softworks came up with VLIR for GEOS instead. On the other hand, they do just fine for text strings and the lookup can be very fast. The cities file looks like this when dumping the raw sectors from the .d64 disk image: The directory entry indicates a file with 31-byte records, the first side sector at track 19 sector 10 and the first data sector (shown in part below) at track 19 sector 0. Other than the obvious typo in Abilene, TX, it is the same basic format as the Apple version and also sorted, ending each string with a carriage return. As a method of what I assume prevents trivially dumping its contents, a naive read of each record won't yield anything useful because every record starts with an $ff and a whole bunch of nulls, which Commodore DOS interprets as the end. The actual string doesn't start until offset 12. The same basic idea holds for the roads file: The same offset trick is used, but here the records are 24-byte since route names are shorter. Again, this isn't a particularly efficient storage mechanism, but we have over 165K available on a formatted disk, and RELative file access to any arbitrary record is quite quick. Despite the presence of side sectors, the actual records of a RELative file are still sequentially stored on disk with the usual forward track and sector pointers. As such, we don't need to grab the side sectors to simply extract its contents. For some period of time the c1541 tool from the VICE suite would not copy REL files and this was only recently fixed, so here is a Perl script I threw together to iterate over a D64 disk image and transfer a file to standard output, either by name or if you specify a starting track and sector. Because this yanks the files "raw," we will then need to strip them down. Feed the extracted REL records to this and you'll get a text file: You'll notice that both the cities and roads lists are, or at least start out, sorted. All C64 Roadsearch images I've seen circulating so far have been altered by their previous owners to add their own local roads and cities, and their changes can be easily distinguished at the point where the lists abruptly go out of alphabetical order. There is also a pair of SEQuential files, one named MPH and serving the same function to store the preferred speed and fuel economy, and a second one simply named M. This file contains four ASCII numbers, one obviously recognizeable as our serial number, though this is only one of the two places the program checks. The others are the number of cities (406, or 487 in the 1985 version), number of roads (215 in 1985), and a third we don't yet know the purpose of. You can confirm the first two by checking it against the number of lines in the files you extracted. What we don't see are files for the arrays we spotted on the Apple disk. The only file left big enough to account for those is MATS. To figure out how that works, we should start digging into the program. RTL-64, a runtime library and the telltale sign of a program compiled with DTL BASIC. DTL BASIC, formally DTL-BASIC 64 Jetpack, became extremely popular with developers not just due to its good performance and compatibility but also requiring no royalties to sell programs compiled with it as long as credit was given. An optional "protector" version can obfuscate the program and/or require a hardware dongle, though this version is rarer due to its expense (and fortunately was not used here). The runtime library slots into the RAM under the BASIC ROM, so there is no obvious loss of free memory. DTL stood for "Drive Technology Ltd." and was written by David Hughes in the UK, first for the PET; the compiler is notable for being compiled with itself, like Microsoft TASC, and using the same "RTL" runtime library and protection system (and, obnoxiously, a dongle) as the object code it generates. The 64 tape version is substantially less capable than the disk one. DTL BASIC compiles to its own bespoke P-code which is executed by the RTL. It achieves its speed through a greater degree of precalculation and preparsing (e.g., pre-resolving values and line numbers, removal of comments, etc.), a custom garbage collection routine, and also, where possible, the use of true signed 16-bit integer math. This is a substantial speed-up over most Microsoft-derived BASICs, in which Microsoft Binary Format floating point is the native system for all calculations to the point where integer variables must first be converted to floating point, the computation performed, and then converted back. Ordinarily this would only make them useful for smaller arrays in memory because the double conversion will make them slower than regular floating point variables. However, DTL BASIC does perform true integer math without conversion, first for all variables explicitly declared as integer, and even autoconverting other variables at compile time with a directive (pragma). Although some private work on a decompiler reportedly exists, to the best of my knowledge that decompiler remains unfinished and unavailable. Interestingly, what I presume is the earlier 1984 disk image has some ghost directory entries, two each for the source BASIC programs and their "symbol tables" used by ERROR LOCATE for runtime errors: Sadly these source files were overwritten and cannot be resurrected, and even the ghost entries were purged on the second 1984 image. However, two aspects of the compiler make it possible to recover at least a portion of the original program text by hand. The first is that not all statements of the original program are fully converted to P-code: in particular, READ/DATA, OPEN, INPUT/INPUT#, DIM, PRINT/PRINT# and possibly others will be preserved nearly in their original BASIC form, including literal strings and most usefully variable names. For example, if we pull the compiled ROADSEARCH+ off the disk image and run it through strings, we see text not unlike a BASIC program: DTL-compiled programs always start with an SYS 2073 to jump into a small machine-code subroutine linked into the object. This section of code loads the RTL (the filename follows) and has other minor housekeeping functions, including one we'll explain shortly when we break into the program while it's running. It resides here so that it can bank BASIC ROM in or out as necessary without crashing the computer. Following that is an incomplete machine language subroutine in a consolidated DATA statement. Disassembly of the fragment shows it's clearly intended to run from $c000, but at least part of it is missing. Of the portion we can see here, however, there are calls for what appears to be a Kernal load, so if we drop a breakpoint on $ffba in VICE (e.g., the Kernal SETLFS routine) we can run the 6502's call stack back to see the full routine and the filename (at $c0e1) it's trying to access: MATS. It loads it straight into memory in the middle of the available BASIC range. After that, now we see the arrays we saw in the Apple II version, but more importantly they're clearly part of DIM statements, so we can also see their dimensions. We already knew T%() was likely to be only 26 (27 counting the zero index) integers long from dumping the Apple version's contents, but the N%() array has up to 757 entries of five fields each, and B%() is even bigger, with 1081 records of four fields each. This is obviously where our map data is stored, and MATS is the file it seems to be loading to populate them. This brings us to the second aspect of DTL Jetpack that helps to partially decipher the program: to facilitate some reuse of the BASIC ROM, the generated code will still create and maintain BASIC-compatible variables which we can locate in RAM. So that we know what we're dealing with, we need to figure out some way to stop the program while it's running to examine its state. Naturally the compiler offers a means to defeat this. ; warm start (2061) .C:080d 20 52 08 JSR $0852 .C:0810 4C 2B A9 JMP $A92B ; not called? .C:0813 20 52 08 JSR $0852 .C:0816 4C 11 A9 JMP $A911 ; cold start (2073) ; load the RTL if flag not set, then start P-code execution .C:0819 20 52 08 JSR $0852 .C:081c AD FF 02 LDA $02FF .C:081f C9 64 CMP #$64 .C:0821 F0 17 BEQ $083A .C:0823 A9 3F LDA #$3F .C:0825 85 BB STA $BB .C:0827 A9 08 LDA #$08 .C:0829 85 BC STA $BC .C:082b A9 06 LDA #$06 .C:082d 85 B7 STA $B7 .C:082f A9 00 LDA #$00 .C:0831 85 B9 STA $B9 .C:0833 A2 00 LDX #$00 .C:0835 A0 A0 LDY #$A0 .C:0837 20 D5 FF JSR $FFD5 .C:083a 68 PLA .C:083b 68 PLA .C:083c 4C 48 A0 JMP $A048 .C:083f .asc "RTL-64" ; seems to get called on a crash or error .C:0845 20 52 08 JSR $0852 .C:0848 20 2F A0 JSR $A02F ; jumps to $a948 .C:084b 20 5F 08 JSR $085F .C:084e 60 RTS ; dummy STOP routine .C:084f A2 01 LDX #$01 .C:0851 60 RTS ; bank out BASIC ROM .C:0852 A9 03 LDA #$03 .C:0854 05 00 ORA $00 .C:0856 85 00 STA $00 .C:0858 A9 FE LDA #$FE .C:085a 25 01 AND $01 .C:085c 85 01 STA $01 .C:085e 60 RTS ; bank in BASIC ROM .C:085f 48 PHA .C:0860 A9 03 LDA #$03 .C:0862 05 00 ORA $00 .C:0864 85 00 STA $00 .C:0866 A5 01 LDA $01 .C:0868 09 01 ORA #$01 .C:086a 85 01 STA $01 .C:086c 68 PLA .C:086d 60 RTS ; execute next statement (using BASIC ROM) .C:086e 20 5F 08 JSR $085F .C:0871 20 ED A7 JSR $A7ED .C:0874 20 52 08 JSR $0852 .C:0877 60 RTS DS and ES compiler directives which disable and enable RUN/STOP respectively. If we scan the RTL for code that modifies $0328 and $0329 where the STOP routine is vectored, we find this segment: $f6ed is the normal value for the STOP vector, so we can assume that the routine at $b7c9 (which calls the routine at $b7da to set it) enables RUN/STOP, and thus the routine at $b7e5 disables it. Both routines twiddle a byte at $a822, part of this section: By default the byte at $a822 is $ea, a 6502 NOP. This falls through to checking $91 for the state of the STOP key at the last time the keyboard matrix was scanned and branching accordingly. When the STOP routine is revectored, at the same time the byte at $a822 is changed to $60 RTS so that the STOP key check is never performed. (The RTL further achieves additional speed here by only doing this check on NEXT and IF statements even if the check is enabled.) The simplest way to deal with this is to alter RTL-64 with a hex editor and turn everything from $b7e5 to $b7ec inclusive into NOPs. This turns the DS directive into a no-op as well, and now we can break out of the program by mashing RUN/STOP, though we'll do this after MATS is loaded. Parenthetically, instead of using CONT, the compiled program can be continued with SYS 2061 instead of SYS 2073. T%(), since we've assumed it has the same purpose in the Commodore port, and it does (once again there are no cities starting with Z, so the final letter points to non-existent record 488 beyond Yuma, AZ as record 487). We then use the BASIC routine at $b08b (SYS 45195) to look up the address of the first variable in the array — note no comma between the SYS and the variable reference — which is deposited as a 16-bit address in location $47 (71). In this case the pointer is to $6b8a (27530), the actual zeroth data element, so if we rewind a few bytes we'll also get the array descriptor as well as its entire contents: C:6b83 d4 80 3d 00 01 00 1b 00 01 00 01 00 0f 00 2d 00 >C:6b93 52 00 60 00 69 00 7c 00 8b 00 97 00 ed 00 f6 00 >C:6ba3 fe 01 16 01 36 01 43 01 4e 01 62 01 63 01 70 01 >C:6bb3 a3 01 b6 01 c8 01 cf 01 e4 01 e4 01 e8 big-endian: the dimensions themselves (a single big-endian short specified as 27, i.e. 26 plus the zeroth element), and then each value. In multidimensional arrays, each dimension is run out fully before moving to the next. We can easily pick out the values we saw for T%() in the above dump, but more importantly we now have a long unambiguous 61-byte key we can search for. The entire sequence shows up in MATS, demonstrating that the file is in fact nothing more than an in-place memory dump of the program arrays' contents. Rather than manually dump the other two arrays from BASIC, we can simply walk MATS and pull the array values directly. This Perl script walks a memory dump of arrays (currently only two-dimensional integer arrays are implemented because that's all we need for this project). It skips the starting address and then writes out tab-separated values into files named by the arrays it finds. Unlike their storage in memory, where values go (0,0), (1,0), (2,0) ... (0,1), (1,1) and so on, this pivots the arrays horizontally so you get (0,0), (0,1), (0,2), etc., grouped into lines as "rows." B%() is the easiest to grok. Ignoring index 0, here is an extract from the file: B%() is referenced directly in one PRINT statement when displaying outgoing roads from a particular city: Let's take city record number 1, which is the misspelled (but only in the 1985 version) ABILINE TX (that is, Abilene, Texas). The develop-a-route feature will list all connected cities. For Abilene, there are five in the database. PRINTed. PRINTs above that B%(I,3) represents the mile length of the current connecting segment indexed by I (here 39), which would make B%() the array containing the connecting roads between cities and junctions. We also know it gets R$ and C$ from the RELative files ROADS and CITIES on each row. Helpfully, it tells us that FORT WORTH TX is city number 115 (it is), which we can see is B%(I,1). B%(I,2) is 1, which must be us, leaving B%(I,0) as the route number which must be the record number for Interstate 20 in ROADS. If we grab line 39 from out-B% (the value of index I), we do indeed see these same values. However, we can now do the search ourselves by just hunting for any record containing city 1 in columns 1 or 2 of our dumped array file (^I is a TAB character): Or, to show the correspondence more plainly: B%(). N%(), on the other hand, is a little harder to crack. Other than its apparent DIM statement at the beginning (as shown above), it is never displayed directly to the user and never appears again in plaintext in the compiled object. Here are the first few entries of the array: The first record (index 0) is the second place where the serial number is stored, though only the map editor references it. Not counting index 0 the file has exactly one record for every city or junction, so it must correspond to them somehow. Otherwise, column 3 (except for index 0) is always an unusual value 32,766, near the positive maximum for a 16-bit integer variable, and columns 4 and 5 are always zero (note from the future: this is not always true for routes which are added in the editor). Additionally, columns 1 and 2 have an odd statistical distribution where the first is always between 4499 and 8915 and the second between 11839 and 21522. There are no negative values anywhere in the file, and the first three columns are never zero (other than index 0). Whatever they are, they are certainly not random. The meaning of the values in this array managed to successfully evade my understanding for awhile, so in the meantime I turned to figuring out how Roadsearch does its routing. The theorists reading this have already internalized this part as an exercise in graph traversal, specifically finding the shortest path. Abstractly the cities and junctions can be considered as the nodes or vertices of a graph. These nodes are enumerated by name in CITIES with additional, currently opaque, metadata in N%(). The nodes are then connected with edges, which are weighted by their mile length. These edges are the highway alignments listed with termini and length in B%() and their names in ROADS. The program appears to universally treat all edges as bi-directional, going both to and from a destination, which also makes the graph generally undirected. Because of the way the database (and indeed the nature of the American highway network) is constructed, all nodes are eventually reachable from any other node. For a first analysis I presented Roadsearch with a drive I know well, having done it as part of longer trips many times in both directions: Bishop, California (city number 31) to Pendleton, Oregon (city number 338). This run can be traveled on a single highway number, namely US Highway 395, and it is also the shortest route. I have not indicated any roads that should be removed, so it will use everything in its database. five seconds. No, warp mode was not on. Take note of the progress display showing miles traveled. This is the first milepoint that appears. If we compare the edges (highway alignments) directly leaving from Bishop and Pendleton, an edge with a weight (length) of 198 miles only shows up leaving Pendleton, suggesting the program works the routing backwards: Edsger Dijkstra's algorithm, conceived in 1956 and published in 1959, an independent reimplementation of Vojtěch Jarník's 1930 minimum spanning tree algorithm that was also separately rediscovered and published by Robert C. Prim in 1957. In broad strokes, the algorithm works by building a tree out of the available nodes, putting them all into a queue. It keeps an array of costs for each node, initially set to an "infinite" value for all nodes except for the first node to be examined, traditionally the start point. It then repeatedly iterates over the queue: of all current nodes in the queue the lowest cost node is pulled out (so, first out, this will be the start point) and its edges are examined, selecting and marking any edges where the sum of the current node's cost and the cost of the edge (the mile length) are less than the current cost of the node it connects to (which, first out, will be "infinite"). The nodes connected by these marked edges take the current node as their parent, constructing the tree, and store the new lower cost value. Once the queue is empty, the algorithm halts and the tree is walked backwards from the target back to the start point, accumulating the optimal route using the parent pointers. This Perl script accepts two city numbers and will generate the optimal route between them using the Roadsearch database with Dijkstra's algorithm. It expects cities, roads (both converted to text, not the raw RELative files) and out-B% to be in the same directory. We build arrays of @cities and @roads, and turn B%() into @edges and @a (for arcs) for expedience. We then walk down the nodes and build the tree in @s, noting which arc/edge was used in @prou so that we can look it up later, and then at the end walk the parent pointers back and do all the dereferencing to generate a human-readable route. As a check we also dump @s, which indexes @edges. Here's what it computes for Bishop to Pendleton, forward and reverse: This is the same answer, and Dijkstra's algorithm further gives us a clue about one of the columns in N%() — the one which is invariably 32766. We already know from the plaintext portion of the compiled program that there are no other arrays, so the routing must be built in-place in the arrays that are present. We need an starting "infinite" value for each node within the range of a 16-bit signed integer, and no optimal path in continental North America would ever exceed that mileage, so this is the "infinite" value used to build the route into N%(). (It gets reset by reloading MATS if you select the option to start over after route generation.) That said, it's almost certain that the program is not using an implementation of Dijkstra's algorithm. The queue starts out with all (in this case 487) nodes in it, making finding the lowest cost node in the queue on each iteration quite expensive on a little ~1.02MHz 6502. The usual solution in later implementations is a min-priority queue to speed up the search, but we already know there are no other arrays in memory to construct a faster heap or tree, so any efficiency gained would likely be unimpressive. Furthermore, it's not clear the author would have known about this approach (the earliest work on it dates to the late 1970s, such as Johnson [1977]), and even if he did, it still doesn't explain the meaning of the first two columns in N%() which aren't even used by this algorithm. After all, they're not there for nothing. E(x) specific to the problem being examined to walk from a source to a target node, terminating when the target was reached. In the process it created a set of partial trees from the source to the target from which the lowest cumulative value of E(x) would ultimately be selected, starting with individual nodes where E(x) to some next immediate destination was locally smaller. Additionally, since it was now no longer required to construct a complete tree touching every possible node, the initial set of nodes considered could simply be the starting point. How the evaluation function was to be implemented was not specified, but a simple straight-line distance to the goal node would have been one logical means. Raphael instead suggested that the function to be minimized be the sum of the distance to the goal node and the evaluation function, which was reworked as a heuristic. The heuristic thus provided a hint to the algorithm, ideally attracting it to the solution sooner by considering a smaller set of nodes. If the heuristic function was properly admissible — what Hart defined as never overstating the actual cost to get to the target — then this new algorithm could be proven to always find the lowest-cost path and greatly reduce comparisons if the solution converged quickly. Considering Graph Traverser as algorithm "A," this more informed goal-directed algorithm was dubbed "A*" (say it A-star). If Roadsearch really is using A-star, at this point we don't know what the heuristic function is. (Note from the future: stay tuned.) Fortunately, a heuristic function that returns zero for all values is absolutely admissible because it will never overstate the actual cost. Although as a degenerate case doing so effectively becomes Dijkstra's algorithm, we'll still observe the runtime benefit of not having an initial queue potentially containing all possible nodes and being able to terminate early if the target is reached (which is always possible with Roadsearch's database). To make the number of nodes more manageable for study, since we will also want to observe how the program behaves for comparison, we'll now consider a smaller routing problem that will be easier to reason about. #!/usr/bin/perl die("usage: $0 point_no_1 point_no_2\n") if (scalar(@ARGV) != 2); $p1 = $ARGV[0]; $p2 = $ARGV[1]; die("wherever you go there you are\n") if ($p1 == $p2); open(K, "cities") || open(K, "cities.txt") || die("cities: $!\n"); @cities = ( undef ); while(<K>) { $ln++; if ($ln==$p1) { $v1=$p1; print; } if ($ln==$p2) { $v2=$p2; print; } chomp; push(@cities, $_); # default gscore and fscore $gscore[$ln] = 99999; $fscore[$ln] = 99999; } die("both cities must be valid\n") if (!$v1 || !$v2); close(K); open(R, "roads") || open(R, "roads.txt") || die("roads: $!\n"); open(B, "out-B%") || die("out-B%: $!\n"); @roads = ( undef ); while(<R>) { chomp; push(@roads, $_); } close(R); $ee = 0; while(<B>) { chomp; ($rn, $c1, $c2, $d) = split(/\t/, $_); $rn += 0; $c1 += 0; $c2 += 0; $d += 0; next if (!$d || !$c1 || !$c2 || !$rn); push(@edges, [ $rn, $c1, $c2, $d ]); push(@{ $a[$c1] }, [ $rn, $c2, $d, $ee ]); push(@{ $a[$c2] }, [ $rn, $c1, $d, $ee++ ]); } close(B); @camefrom = (); @openset = ( $v1 ); $gscore[$v1] = 0; $fscore[$v1] = 0; # heuristic of distance is 0 for the start while(scalar(@openset)) { @openset = sort { $fscore[$a] <=> $fscore[$b] } @openset; print join(", ", @openset), "\n"; $current = shift(@openset); last if ($current == $v2); foreach $n (@{ $a[$current] }) { $ni = $n->[1]; $tgscore = $gscore[$current] + $n->[2]; if ($tgscore < $gscore[$ni]) { $camefrom[$ni] = $current; $routefrom[$ni] = $n->[3]; $gscore[$ni] = $tgscore; $fscore[$ni] = $tgscore + 0; # "heuristic" unless (scalar(grep { $_ == $ni } @openset)) { push(@openset, $ni); } } } } @s = ( ); while(defined($camefrom[$current])) { $route = $routefrom[$current]; $current = $camefrom[$current]; unshift(@s, $route); } print join(' - ', @s), "\n"; $miles = 0; foreach(@s) { print $roads[$edges[$_]->[0]], "($edges[$_]->[0]) - ", $cities[$edges[$_]->[2]], "($edges[$_]->[2]) - ", $cities[$edges[$_]->[1]], "($edges[$_]->[1]) ", $edges[$_]->[3], " miles\n"; $miles += $edges[$_]->[3]; } print "total $miles miles\n"; f(x) (realized here as @fscore) and g(x) (@gscore). The G-score for a given node is the currently known cost of the cheapest path from the start to that node, which we build from the mile length of each edge. The node's F-score is its G-score plus the value of the heuristic function for that node, representing our best guess as to how cheap the overall path could be if the path from start to finish goes through it. In this case, the F-score and G-score will be identical because the heuristic function in this implementation always equals zero. Also, because we're interested in knowing how many fewer nodes we've considered, we dump the open set on every iteration. % route-dij 375 311 NEEDLES CA SAN BERNARDINO CA 237 - 236 - 63 - 719 I 15 - SAN BERNARDINO CA - US395/I15 CA 27 miles I 15 - US395/I15 CA - BARSTOW CA 44 miles I 40 - BARSTOW CA - I40/US95 CA 134 miles I 40 - I40/US95 CA - NEEDLES CA 12 miles total 217 miles % route-astar 375 311 NEEDLES CA SAN BERNARDINO CA 375 443, 335, 274, 376 335, 274, 442, 18, 376 274, 442, 18, 376, 34 442, 18, 376, 171, 380, 34 18, 376, 171, 380, 15, 34, 31 376, 171, 380, 15, 34, 169, 262, 31 424, 171, 380, 15, 34, 169, 262, 31, 487 171, 380, 15, 34, 169, 262, 31, 487 380, 15, 34, 169, 275, 262, 31, 487 15, 34, 169, 275, 262, 31, 379, 487 34, 45, 169, 275, 262, 31, 379, 487 45, 169, 275, 262, 31, 379, 311, 487, 342 169, 275, 262, 31, 379, 311, 119, 487, 342 275, 311, 262, 31, 379, 119, 487, 342 311, 262, 31, 379, 336, 119, 487, 170, 342 237 - 236 - 63 - 719 I 15 (31) - SAN BERNARDINO CA (375) - US395/I15 CA (443) 27 miles I 15 (31) - US395/I15 CA (443) - BARSTOW CA (18) 44 miles I 40 (60) - BARSTOW CA (18) - I40/US95 CA (169) 134 miles I 40 (60) - I40/US95 CA (169) - NEEDLES CA (311) 12 miles total 217 miles % route-astar 311 375 NEEDLES CA SAN BERNARDINO CA 311 169, 251, 34 251, 34, 262, 18 168, 34, 262, 18 34, 262, 18, 475, 110 262, 18, 475, 110, 335, 342 454, 18, 475, 110, 335, 342, 427 18, 475, 110, 335, 342, 53, 427, 446 442, 443, 475, 110, 335, 342, 53, 427, 446 443, 475, 110, 335, 342, 15, 53, 427, 31, 446 475, 110, 375, 335, 342, 15, 53, 427, 31, 446 110, 375, 335, 342, 15, 53, 427, 31, 446 375, 335, 342, 15, 53, 427, 31, 446, 124, 247 719 - 63 - 236 - 237 I 40 (60) - I40/US95 CA (169) - NEEDLES CA (311) 12 miles I 40 (60) - BARSTOW CA (18) - I40/US95 CA (169) 134 miles I 15 (31) - US395/I15 CA (443) - BARSTOW CA (18) 44 miles I 15 (31) - SAN BERNARDINO CA (375) - US395/I15 CA (443) 27 miles total 217 miles N%(), we'll instruct VICE to trap each integer array write to the range covered by MATS. (Trapping reads would also be handy but we'd go mad with the amount of data this generates.) We can get the value being written from $64/$65 (using the BASIC #1 floating point accumulator as temporary space) based on this code in the RTL: On each store we'll duly log the value in $64/$65 (remember it's big-endian) and the address it's being stored to. I wrote a one-off script to turn this string of writes into array offsets so we can understand how they relate to N%(), and then look them up in the tables so that we know which node and edge is under consideration. Remember, Roadsearch works this problem backwards starting with Needles. From the above you can see where the program marks the order of each node and the accumulated mileage. Our running totals, most likely the F-score and G-score, for a given node x are in N%(x,1) and N%(x,2), the length of the candidate edge is in N%(x,1), the optimal edge for the node is in N%(x,4), and the iteration it was marked in is recorded in N%(x,3). (We count an iteration as any loop in which a candidate node is marked, which in this simple example will occur on every run through the open set.) N%(x,0) also looks like a distance, but it doesn't correlate to a highway distance. To construct the itinerary at the end, it starts with San Bernardino and then repeatedly walks the selected edge to the next node until it reaches Needles. It's painfully obvious that compared to our models Roadsearch is considering a much smaller number of nodes (18, 34, 169, 251, 262, 311, 375, 442 and 443), counting the five in the optimal solution, and it duly converges on the optimal routing in just four iterations compared to twelve in our best case. I did look at its read pattern and found that N%(x,0) and N%(x,1) lit up a lot. These values are clearly important to computing whatever heuristic it's using, so I pulled out a few from across North America. I stared at it for awhile until it dawned on me what the numbers are. Do you see what I saw? Here, let me plot these locations on a Mercator projection for you (using the United States' territorial boundaries): coordinates. The first column increases going north, and the second column increases going west. Indeed, in the very paper written by Hart et al., they suggest that the straight-line distance from the current node to the goal would make a dandy heuristic and now we can compute it! The thing we have to watch for here is that the scales of the mileage and the coordinates are not identical, and if we use a simple distance calculation we'll end up clobbering the cumulative mileage with it — which would not only make it non-admissible as a heuristic, but also give us the wrong answer. To avoid that, we'll compute a fudge factor to yield miles from "map units" and keep the heuristic function at the same scale. Let's take San Diego, California to Bangor, Maine as a reference standard, for which computing the geodesic distance using WGS 84 yields 2,696.83 miles from city centre to city centre as the crow flies. If we compute the straight-line distance between them using the coordinates above, we get 8703.63 "map units," which is a ratio of 3.23:1. To wit: We now have implemented an h(x) that for a given node x returns its straight-line distance from the target node. Let's try it out. Remembering that Roadsearch works it backwards, we converge on the same solution examining the same nodes in the same number of iterations (four). Further proof is if we dump the program's array writes for the opposite direction: This routing proceeds in six iterations, just as we do, and once again the nodes we end up considering in our new A-star model are also the same. It also explains N%(x,0) — this is the straight-line distance and thus our heuristic, calculated (it's backwards) as the distance to the "start." For example, Palm Springs is indeed roughly 135 miles from Needles as the crow flies, again depending on your exact termini, whereas the western US 95/Interstate 40 junction is only about 11 miles. It should also be obvious that this "fudge" divisor has a direct effect on the efficiency of the routine. While we're purportedly using it as a means to scale down the heuristic, doing so is actually just a backhanded way of deciding how strongly we want the heuristic weighted. However, we can't really appreciate its magnitude in a problem space this small, so now we'll throw it a big one: drive from San Diego (376) to Bangor (17). (I did myself drive from Bangor to San Diego in 2006, but via Georgia to visit relatives.) This route requires a lot more computation and will also generate multiple useless cycles in which no node is sufficiently profitable, so I added code to our heuristic A-star router to explicitly count iterations only when a candidate node is marked: With our computed initial fudge factor of 3.23, we get this (again, worked backwards): And now for the real thing. quick. Both our simulation and the real program agree on the optimal route, as demonstrated by the cumulative mileage. N%(x,3). Interestingly, we do not: our simulation converged on the optimal route in 328 iterations, but the Commodore got it in 307. However, if we tune our simulation's fudge factor to 3.03, we also get it in 307. Is there an optimal fudge divisor? We know the optimal route, so we'll run a whole bunch of simulations over the entire interval, rejecting ones that get the wrong answer and noting the iterations that were required for the right ones. In fact, we can do this generally for any routing by using the longhand Dijkstra method to get the correct answer and then run a whole bunch of tweaked A-stars compared with its routing after that. In our simulation, stepping the fudge divisor over the interval from 0 inclusive to 4 by 0.001 increments, I ran six long haul drives in total, San Diego (376) to Bangor (17) and back, Bellingham, WA (24) to Miami, FL (291) and back, and then San Francisco, CA (377) to Washington, DC (465) and back. I then plotted them all out as curves. h(x)=0 heuristic from above, which is always accurate and the least goal directed (and consequently requires the most iterations). First off, there is no single fudge divisor that always yields the most optimal route for all of our test cases. Notice how much of the graph yields absolutely wrong answers (so nothing is plotted), and even in the interval between around 2.2 and 2.8 or so not all of the curves are valid. They all become valid around 3, which I enlarged in the inset on the left, and each one's iteration count slowly rises after that with the zero heuristic as more or less the upper asymptote. Except for the purple curve, however, 3 is not generally their lower bound. Second, there is no single fudge divisor that always corresponds to the program's iteration count, which is 311 (17 to 376), 307 (376 to 17), 183 (291 to 24), 264 (24 to 291), 261 (377 to 465) and 220 (465 to 377). With the value of 3.03 from above, however, our simulation generally does better than the real thing, which is both gratifying for the purposes of pathfinding and frustrating for the purposes of modeling. B%(x,3)). That assures it will always have an insuperably high cost, yet be unlikely to overflow if it's involved in any calculations, and thus it will never be pulled from the open set for evaluation. The in-memory database is always reloaded from disk after the route is disposed of. As our final stop in this article nearly as long as some of the drives we've analysed, we'll do my first 2005 long haul expedition along US Highway 395. This is a useful way to show how to add your own roads and what the program does with that, since not all of its segments are in the database. M, which will then cause the program to ignore any extraneous ones. Style points are added if you clear the records in the RELative files and turn them into nulls, though this isn't required. For the 1985 release, set M to 20 34 38 37 20 0D 20 37 37 35 20 0D 20 32 31 35 20 0D 20 39 39 39 39 20 0D, which is (in PETSCII) 487 cities, 775 road segments, 215 road names and serial number 9999 or as you like. (Note this will not change the serial number in the editor, but with this patch you're only using the main program in any case.) However, if you try to use a disk modified this way to add routes or cities, it will correctly recognize the new ones as new but erroneously find their old links in the arrays. That will not only get you unexpected residual road links to any new cities, but the links' presence can also confuse the program to such an extent it will end up in an infinite loop. In this case you'll need to delete these hanging links by patching MATS to null out the entries in B%() and N%() referring to city numbers greater than 487 and road numbers greater than 215 (remember that there are three arrays in that file and that multi-dimensional arrays run out each dimension before going to the next, meaning you can't just truncate it and stuff nulls on the end). This is simple to understand in concept but a little tedious to do, so I have left this as an exercise for the reader. Should I come up with a clean MATS myself, I will put it up somewhere if there is interest; for now we'll do our work on a well-loved copy which means that the city numbers you see here may not necessarily be the ones you get if you're following along at home. From there it proceeded north to the Columbia River gorge and intersected US 730 further west, then went east with it as before to US 12. This intermediate state is shown on this 1976 Donnelley atlas page, with the relevant portion highlighted. It was not until around 1986-7 when Interstate 82 was completed that US 395 was moved to I-82 instead as its present-day routing, leaving only a tiny residual overlap with US 730 east of Umatilla, Oregon. The problem is that none of these locations have waypoints we can easily connect to. M or MATS to disk until this point so that if the process gets aborted in the middle, the database remains internally consistent except for some harmless unreferenced RELative file records that can be overwritten later. N%() as its heuristic, but we were never asked for anything like latitude or longitude. How, then, can it get this information for the new cities we just created? At this point I dumped the RELative files and the new MATS to find out, and it so happens that the new city gets the same coordinates as the one it was connected to: both Wallula Junction and Walla Walla get coordinates 8062 and 20802, which are Walla Walla's coordinates. As we are connecting a couple new cities together along US 12, they also get the same coordinates, up to Yakima which retains its own. If we extended from both sides into the middle it would probably have made the database slightly more accurate at the cost of some inconvenient dancing around. This would be a good idea if you needed to reconstruct or chop up a particularly long segment, for example. I had also made an earlier call-forward that cities added from the editor sometimes don't have columns 4 or 5 set to zero. I can see this for the entries the previous owner entered, but all of mine ended up zero, so I'm not sure under what conditions that occurred. It doesn't seem to matter to the program in any case. .d64 disk images for this program all show new routes had been added suggests they got non-trivial usage by their owners, which really speaks to the strengths of the program and what it could accomplish. While it's hardly a sexy interface, it's functional and straightforward, and clearly a significant amount of time was spent getting the map data in and tuning up the routing algorithm so that it could perform decently on an entry-level home computer. Unfortunately, I suspect it didn't sell a lot of copies, because there are few advertisements for Columbia Software in any magazine of the time and no evidence that the Commodore version sold any better than the Apple II release did. That's a shame because I think its technical achievements merited a better market reception then, and it certainly deserves historical recognition today. We take things like Google Maps almost for granted, but a program that could drive a highway map on your 1985 Apple or Commodore would truly have been fascinating. As for me, I look forward to another long haul road trip in the future, maybe US 95 or US 101, or possibly reacquainting myself with US 6 which I drove in 2006 from Bishop to Cape Cod, Massachusetts. Regardless of where we end up going, though, this time we won't be taking the SX-64 with us — my wife has insisted on getting her seat back.

An affordable, AI-assisted, wearable robotic arm? That’s not science fiction – it’s RedSnapper, an open-source prosthesis built by PAC Tech, a team of high school students from Istituto Maria Immacolata in Gorgonzola, Italy. Powered entirely by Arduino boards, their project won the national “Robot Arm Makers” title at the 2025 RomeCup – and we think […] The post Meet the teens behind RedSnapper: a smart Arduino-powered prosthetic arm appeared first on Arduino Blog.