多路行车距离

Question

我试图使用带有route()函数的ggmap包从由多对坐标组成的tibble获取驱动距离和时间。

数据：

locations <- tibble(start_loc = c("44.025135, -69.892204", "44.0175617, -70.0108097"), end_loc = "43.9195136, -69.9665309")

我想要结束的是附加了两个列的locations tibble，一个是总旅行时间，另一个是总距离。为此，我可能需要遍历locations中的每一行，通过route()函数传递每一对坐标。问题是来自route()的输出为路由中的每一步生成一行。

到目前为止我所拥有的是：

library(ggmap)
library(dplyr)

locations

# A tibble: 2 x 2
#  start_loc               end_loc                
# <chr>                   <chr>                  
#1 44.025135, -69.892204   43.9195136, -69.9665309
#2 44.0175617, -70.0108097 43.9195136, -69.9665309

for(i in 1:nrow(locations)) {
  route_output <- route(from = locations$start_loc[i], to = locations$end_loc[i], 
                        mode = c("driving"), output = c("simple"), units ="mi", structure = "legs")
}

route_output
# A tibble: 6 x 11
#      m    km  miles seconds minutes   hours start_lon start_lat end_lon end_lat route
#  <int> <dbl>  <dbl>   <int>   <dbl>   <dbl>     <dbl>     <dbl>   <dbl>   <dbl> <chr>
#1  2608 2.61  1.62       184   3.07  0.0511      -70.0      44.0   -70.0    44.0 A    
#2   524 0.524 0.326       32   0.533 0.00889     -70.0      44.0   -70.0    44.0 A    
#3  3106 3.11  1.93       232   3.87  0.0644      -70.0      44.0   -70.1    44.0 A    
#4  9516 9.52  5.91       528   8.8   0.147       -70.1      44.0   -70.0    43.9 A    
#5    88 0.088 0.0547       9   0.15  0.0025      -70.0      43.9   -70.0    43.9 A    
#6  1960 1.96  1.22       166   2.77  0.0461      -70.0      43.9   -70.0    43.9 A 

这显示的是仅针对最后一个start_loc end_loc对的路由的每一步。所以这不是我想要的循环，我也没有得到摘要信息。我甚至没有办法将route_output tibble重新定位到‘route_output’上。总之，我真的被堵住了。

关于该怎么做的建议？如果ggmap包对此没有好处，我还应该使用什么？

Answer 1

试一试如下：

library(ggmap)

locations <- data.frame(start_loc = c("44.025135, -69.892204", "44.0175617, -70.0108097"), end_loc = "43.9195136, -69.9665309")

trip_dist_time <- function(from, to, mode) {
    
    results <- ggmap::route(from, to, mode)
    
    data.frame(time_minutes = sum(results$minutes),
               distance_km = sum(results$km),
               mode = mode)
}

# Select a travel mode from "driving", "walking", "bicycling", "transit"
travel_mode <- "driving"

results <- mapply(trip_dist_time, locations$start_loc, locations$end_loc, travel_mode, SIMPLIFY = FALSE)
results <- Reduce(rbind, results)
results <- cbind(locations, results)
results

你会得到：

                start_loc                 end_loc time_minutes distance_km    mode
1   44.025135, -69.892204 43.9195136, -69.9665309        15.95      16.476 driving
2 44.0175617, -70.0108097 43.9195136, -69.9665309        19.40      17.802 driving