198 lines
7.6 KiB
C++
198 lines
7.6 KiB
C++
#include "engine/plugins/plugin_base.hpp"
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#include "engine/plugins/match.hpp"
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#include "engine/map_matching/bayes_classifier.hpp"
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#include "engine/api/match_parameters.hpp"
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#include "engine/api/match_api.hpp"
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#include "util/coordinate_calculation.hpp"
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#include "util/integer_range.hpp"
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#include "util/json_logger.hpp"
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#include "util/json_util.hpp"
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#include "util/string_util.hpp"
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#include <cstdlib>
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#include <algorithm>
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#include <memory>
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#include <string>
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#include <vector>
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namespace osrm
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{
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namespace engine
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{
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namespace plugins
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{
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// Filters PhantomNodes to obtain a set of viable candiates
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void filterCandidates(const std::vector<util::Coordinate> &coordinates,
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MatchPlugin::CandidateLists &candidates_lists)
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{
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for (const auto current_coordinate : util::irange<std::size_t>(0, coordinates.size()))
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{
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bool allow_uturn = false;
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if (coordinates.size() - 1 > current_coordinate && 0 < current_coordinate)
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{
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double turn_angle = util::coordinate_calculation::computeAngle(
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coordinates[current_coordinate - 1], coordinates[current_coordinate],
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coordinates[current_coordinate + 1]);
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// sharp turns indicate a possible uturn
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if (turn_angle <= 90.0 || turn_angle >= 270.0)
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{
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allow_uturn = true;
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}
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}
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auto &candidates = candidates_lists[current_coordinate];
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if (candidates.empty())
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{
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continue;
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}
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// sort by forward id, then by reverse id and then by distance
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std::sort(
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candidates.begin(), candidates.end(),
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[](const PhantomNodeWithDistance &lhs, const PhantomNodeWithDistance &rhs)
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{
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return lhs.phantom_node.forward_segment_id.id < rhs.phantom_node.forward_segment_id.id ||
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(lhs.phantom_node.forward_segment_id.id == rhs.phantom_node.forward_segment_id.id &&
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(lhs.phantom_node.reverse_segment_id.id < rhs.phantom_node.reverse_segment_id.id ||
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(lhs.phantom_node.reverse_segment_id.id == rhs.phantom_node.reverse_segment_id.id &&
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lhs.distance < rhs.distance)));
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});
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auto new_end = std::unique(
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candidates.begin(), candidates.end(),
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[](const PhantomNodeWithDistance &lhs, const PhantomNodeWithDistance &rhs)
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{
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return lhs.phantom_node.forward_segment_id.id == rhs.phantom_node.forward_segment_id.id &&
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lhs.phantom_node.reverse_segment_id.id == rhs.phantom_node.reverse_segment_id.id;
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});
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candidates.resize(new_end - candidates.begin());
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if (!allow_uturn)
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{
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const auto compact_size = candidates.size();
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for (const auto i : util::irange<std::size_t>(0, compact_size))
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{
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// Split edge if it is bidirectional and append reverse direction to end of list
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if (candidates[i].phantom_node.forward_segment_id.enabled &&
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candidates[i].phantom_node.reverse_segment_id.enabled)
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{
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PhantomNode reverse_node(candidates[i].phantom_node);
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reverse_node.forward_segment_id.enabled = false;
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candidates.push_back(
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PhantomNodeWithDistance{reverse_node, candidates[i].distance});
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candidates[i].phantom_node.reverse_segment_id.enabled = false;
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}
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}
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}
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// sort by distance to make pruning effective
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std::sort(candidates.begin(), candidates.end(),
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[](const PhantomNodeWithDistance &lhs, const PhantomNodeWithDistance &rhs)
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{
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return lhs.distance < rhs.distance;
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});
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}
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}
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Status MatchPlugin::HandleRequest(const api::MatchParameters ¶meters,
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util::json::Object &json_result)
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{
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BOOST_ASSERT(parameters.IsValid());
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// enforce maximum number of locations for performance reasons
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if (max_locations_map_matching > 0 &&
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static_cast<int>(parameters.coordinates.size()) > max_locations_map_matching)
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{
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return Error("TooBig", "Too many trace coordinates", json_result);
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}
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if (!CheckAllCoordinates(parameters.coordinates))
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{
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return Error("InvalidValue", "Invalid coordinate value.", json_result);
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}
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// assuming radius is the standard deviation of a normal distribution
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// that models GPS noise (in this model), x3 should give us the correct
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// search radius with > 99% confidence
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std::vector<double> search_radiuses;
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if (parameters.radiuses.empty())
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{
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search_radiuses.resize(parameters.coordinates.size(),
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DEFAULT_GPS_PRECISION * RADIUS_MULTIPLIER);
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}
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else
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{
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search_radiuses.resize(parameters.coordinates.size());
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std::transform(parameters.radiuses.begin(), parameters.radiuses.end(),
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search_radiuses.begin(), [](const boost::optional<double> &maybe_radius)
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{
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if (maybe_radius)
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{
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return *maybe_radius * RADIUS_MULTIPLIER;
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}
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else
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{
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return DEFAULT_GPS_PRECISION * RADIUS_MULTIPLIER;
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}
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});
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}
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auto candidates_lists = GetPhantomNodesInRange(parameters, search_radiuses);
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filterCandidates(parameters.coordinates, candidates_lists);
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if (std::all_of(candidates_lists.begin(), candidates_lists.end(),
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[](const std::vector<PhantomNodeWithDistance> &candidates)
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{
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return candidates.empty();
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}))
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{
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return Error("NoSegment",
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std::string("Could not find a matching segment for any coordinate."),
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json_result);
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}
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// call the actual map matching
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SubMatchingList sub_matchings = map_matching(candidates_lists, parameters.coordinates,
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parameters.timestamps, parameters.radiuses);
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if (sub_matchings.size() == 0)
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{
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return Error("NoMatch", "Could not match the trace.", json_result);
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}
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std::vector<InternalRouteResult> sub_routes(sub_matchings.size());
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for (auto index : util::irange(0UL, sub_matchings.size()))
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{
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BOOST_ASSERT(sub_matchings[index].nodes.size() > 1);
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// FIXME we only run this to obtain the geometry
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// The clean way would be to get this directly from the map matching plugin
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PhantomNodes current_phantom_node_pair;
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for (unsigned i = 0; i < sub_matchings[index].nodes.size() - 1; ++i)
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{
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current_phantom_node_pair.source_phantom = sub_matchings[index].nodes[i];
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current_phantom_node_pair.target_phantom = sub_matchings[index].nodes[i + 1];
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BOOST_ASSERT(current_phantom_node_pair.source_phantom.IsValid());
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BOOST_ASSERT(current_phantom_node_pair.target_phantom.IsValid());
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sub_routes[index].segment_end_coordinates.emplace_back(current_phantom_node_pair);
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}
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shortest_path(sub_routes[index].segment_end_coordinates, {}, sub_routes[index]);
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BOOST_ASSERT(sub_routes[index].shortest_path_length != INVALID_EDGE_WEIGHT);
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}
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api::MatchAPI match_api{BasePlugin::facade, parameters};
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match_api.MakeResponse(sub_matchings, sub_routes, json_result);
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return Status::Ok;
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}
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}
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}
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}
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