Feature requrest: Estimate and record trip travel times

[EwoutH]

It would be a very useful feature for me to be able to estimate and record travel times of trips in UXsim.

• Estimate the expected travel time based on the current state of the network.
• Record the final travel time a trip took.

The first one can be used to make decisions on (for agents making a mode choice for example), the second can be usefull as metric / KPI.

[toruseo]

They are available :)

Record the final travel time a trip took.

This is already implemented. Vehicle.travel_time records its trip travel time. Or, you can output all vehicles' detailed travel logs by World.analyzer.vehicles_to_pandas() and analyze anything as you want.

Estimate the expected travel time based on the current state of the network.

For this, so-called "instantaneous travel time" may be useful. Link.instant_travel_time(t) returns one for that link on time t. In fact, vehicles in UXsim basically uses this information for their routing.

[EwoutH]

Vehicle.travel_time records its trip travel time.

I missed that, thanks!

so-called "instantaneous travel time" may be useful.

Do you think it would be useful to have a function that returns that total value for the shortest route from some node A to some node B? For example, if I'm an agent deciding to go by car or by bike from A to B, I might want to check what the current travel time is from A to B by car to base my decision on.

[toruseo]

That is not difficult. You can create a graph whose link cost is Link.instant_travel_time(t) and then perform shortest path search.

RouteChoice.route_search_all() is doing very similar thing, so it can be a basis for that. Maybe adding the following function to RouteChoice can work. I havent tested it at all, so please check carefully.

    def route_search_all_on_time(s, t, infty=np.inf):
        """
        Compute the current shortest path based on instantanious travel time on time t.
        Experimental, not tested.

        Parameters
        ----------
        t : float
            Time in seconds.
        infty : float
            value representing infinity.
            
        Returns
        -------
        np.array
            The distance matrix. dist[i,j] is the shortest distance from node i to node j.
        """
        adj_mat_time = np.zeros([len(s.W.NODES), len(s.W.NODES)])
        for link in s.W.LINKS:
            i = link.start_node.id
            j = link.end_node.id
            if s.W.ADJ_MAT[i,j]:
                adj_mat_time[i,j] = link.instant_travel_time(t) + link.route_choice_penalty #TODO: link.route_choice_penalty may be time-dependent
                if link.capacity_in == 0: #流入禁止の場合は通行不可
                    adj_mat_time[i,j] = np.inf
            else:
                adj_mat_time[i,j] = np.inf

        dist, pred = floyd_warshall(adj_mat_time, return_predecessors=True)

        return dist