<prompt> Hlalosa hore na koloi e se nang mokhanni e ka tseba joang hore na e eme neng ha e le letšoao.nan  <response>: Instruction in English: Explain the process of how a driverless car would know when to stop at a sign. . Response in English: Driverless cars, also known as autonomous vehicles, use a combination of sensors, cameras, machine learning algorithms, and advanced mapping software to perceive and understand their surroundings in real-time. This technology enables the car to know when to stop at a sign.The process starts with the cars sensors and cameras continuously scanning the environment for any relevant information, such as road signs, obstacles, pedestrians, and other vehicles. When the camera detects a stop sign, it sends the image data to the cars onboard computer.The onboard computer uses machine learning algorithms to interpret the image data and identify the stop sign. These algorithms are trained with vast amounts of data, enabling them to accurately recognize various road signs, including stop signs, even in different lighting and weather conditions.Once the stop sign is identified, the cars computer uses its advanced mapping software, which includes information about the location of all stop signs on the cars route, to confirm the presence of the stop sign. The car then calculates the distance to the stop sign and its current speed, and determines the appropriate time to start slowing down.The cars computer sends signals to the brakes, and the car begins to slow down and then comes to a complete stop at the appropriate location before the stop sign. It will then wait for its turn to proceed, using its sensors to detect when the road ahead is clear. Overall, the process of stopping at a sign is a combination of advanced technology and real-time decision making, allowing the driverless car to safely and accurately navigate the roads. . Response in Sesotho: Likoloi tse sa khanneng, tse tsejoang hape e le likoloi tse ikemetseng, li sebelisa motsoako oa li-sensor, likhamera, li-algorithms tsa ho ithuta ka mochini, le software e tsoetseng pele ea mapa ho bona le ho utloisisa tikoloho ea bona ka nako ea nnete. Theknoloji ena e thusa koloi ho tseba hore na e eme neng ha e le letšoao. Tsebetso ena e qala ka li-sensor tsa koloi le likhamera tse lulang li lekola tikoloho ho fumana lintlha leha e le life tse hlokahalang, joalo ka matšoao a tsela, litšitiso, batho ba tsamaeang ka maoto le likoloi tse ling. Ha khamera e bona letsoao la ho emisa, e romela data ea setšoantšo komporong ea koloi e ka sekepeng. Khomphutha ea onboard e sebelisa li-algorithms tsa ho ithuta ka mochini ho toloka data ea setšoantšo le ho tseba letsoao la ho emisa. Li-algorithms tsena li koetlisoa ka lintlha tse ngata, tse li nolofalletsang ho lemoha matšoao a fapaneng a litsela ka nepo, ho kenyeletsoa matšoao a ho emisa, esita le maemong a fapaneng a mabone le maemo a leholimo. Hang ha letsoao la ho emisa le tsebahala, komporo ea koloi e sebelisa software ea eona e tsoetseng pele ea mapa, e kenyelletsang tlhahisoleseling mabapi le sebaka sa matšoao ohle a ho emisa tseleng ea koloi, ho netefatsa boteng ba letšoao la ho emisa. Koloi e ntano lekanya sebaka sa sebaka sa letšoao la ho emisa le lebelo la hona joale, me e khetha nako e loketseng ea ho qala ho fokotsa lebelo. Khomphieutha ea koloi e romela matšoao ho mariki, me koloi e qala ho theoha butle ebe e ema ka ho feletseng sebakeng se loketseng pele ho letšoao la ho emisa. Joale e tla emela nako ea eona hore e tsoele pele, e sebelisa li-sensor tsa eona ho bona ha tsela e ka pele e hlakile. Ka kakaretso, mokhoa oa ho emisa letšoao ke motsoako oa theknoloji e tsoetseng pele le ho etsa liqeto ka nako ea sebele, ho lumella koloi e se nang mokhanni hore e tsamaee ka tsela e sireletsehileng le e nepahetseng litseleng. 