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Add parameters for map matching

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This commit is contained in:
Patrick Niklaus
2015-03-02 23:12:44 +01:00
parent d89b171f49
commit e5830b0116
5 changed files with 94 additions and 77 deletions
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routing_algorithms/map_matching.hpp
+44 -61
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@@ -75,67 +75,42 @@ template <class DataFacadeT> class MapMatching final
SearchEngineData &engine_working_data;
// FIXME this value should be a table based on samples/meter (or samples/min)
constexpr static const double beta = 10.0;
constexpr static const double sigma_z = 4.07;
constexpr static const double log_sigma_z = std::log(sigma_z);
constexpr static const double default_beta = 10.0;
constexpr static const double default_sigma_z = 4.07;
constexpr static const double log_2_pi = std::log(2 * M_PI);
constexpr static double emission_probability(const double distance)
// closures to precompute log -> only simple floating point operations
struct EmissionLogProbability
{
return (1. / (std::sqrt(2. * M_PI) * sigma_z)) *
std::exp(-0.5 * std::pow((distance / sigma_z), 2.));
}
double sigma_z;
double log_sigma_z;
constexpr static double transition_probability(const float d_t, const float beta)
EmissionLogProbability(const double sigma_z)
: sigma_z(sigma_z)
, log_sigma_z(std::log(sigma_z))
{
}
double operator()(const double distance) const
{
return -0.5 * (log_2_pi + (distance / sigma_z) * (distance / sigma_z)) - log_sigma_z;
}
};
struct TransitionLogProbability
{
return (1. / beta) * std::exp(-d_t / beta);
}
double beta;
double log_beta;
TransitionLogProbability(const double beta)
: beta(beta)
, log_beta(std::log(beta))
{
}
constexpr static double log_emission_probability(const double distance)
{
return -0.5 * (log_2_pi + (distance / sigma_z) * (distance / sigma_z)) - log_sigma_z;
}
constexpr static double log_transition_probability(const float d_t, const float beta)
{
return -std::log(beta) - d_t / beta;
}
// TODO: needs to be estimated from the input locations
// FIXME These values seem wrong. Higher beta for more samples/minute? Should be inverse
// proportional.
// samples/min and beta
// 1 0.49037673
// 2 0.82918373
// 3 1.24364564
// 4 1.67079581
// 5 2.00719298
// 6 2.42513007
// 7 2.81248831
// 8 3.15745473
// 9 3.52645392
// 10 4.09511775
// 11 4.67319795
// 21 12.55107715
// 12 5.41088180
// 13 6.47666590
// 14 6.29010734
// 15 7.80752112
// 16 8.09074504
// 17 8.08550528
// 18 9.09405065
// 19 11.09090603
// 20 11.87752824
// 21 12.55107715
// 22 15.82820829
// 23 17.69496773
// 24 18.07655652
// 25 19.63438911
// 26 25.40832185
// 27 23.76001877
// 28 28.43289797
// 29 32.21683062
// 30 34.56991141
double operator()(const double d_t) const
{
return -log_beta - d_t / beta;
}
};
double get_network_distance(const PhantomNode &source_phantom,
const PhantomNode &target_phantom) const
@@ -231,9 +206,10 @@ template <class DataFacadeT> class MapMatching final
std::vector<bool> breakage;
const Matching::CandidateLists &candidates_list;
const EmissionLogProbability& emission_log_probability;
HiddenMarkovModel(const Matching::CandidateLists &candidates_list)
: breakage(candidates_list.size()), candidates_list(candidates_list)
HiddenMarkovModel(const Matching::CandidateLists &candidates_list, const EmissionLogProbability& emission_log_probability)
: breakage(candidates_list.size()), candidates_list(candidates_list), emission_log_probability(emission_log_probability)
{
for (const auto &l : candidates_list)
{
@@ -271,7 +247,7 @@ template <class DataFacadeT> class MapMatching final
for (auto s = 0u; s < viterbi[initial_timestamp].size(); ++s)
{
viterbi[initial_timestamp][s] =
log_emission_probability(candidates_list[initial_timestamp][s].second);
emission_log_probability(candidates_list[initial_timestamp][s].second);
parents[initial_timestamp][s] = std::make_pair(initial_timestamp, s);
pruned[initial_timestamp][s] =
viterbi[initial_timestamp][s] < Matching::MINIMAL_LOG_PROB;
@@ -297,6 +273,7 @@ template <class DataFacadeT> class MapMatching final
}
};
// Provides the debug interface for introspection tools
struct DebugInfo
{
DebugInfo(const osrm::json::Logger* logger)
@@ -419,11 +396,17 @@ template <class DataFacadeT> class MapMatching final
void operator()(const Matching::CandidateLists &candidates_list,
const std::vector<FixedPointCoordinate> &trace_coordinates,
const std::vector<unsigned> &trace_timestamps,
const double matching_beta,
const double gps_precision,
Matching::SubMatchingList &sub_matchings) const
{
BOOST_ASSERT(candidates_list.size() > 0);
HiddenMarkovModel model(candidates_list);
// TODO replace default values with table lookup based on sampling frequency
EmissionLogProbability emission_log_probability(gps_precision > 0 ? gps_precision : default_sigma_z);
TransitionLogProbability transition_log_probability(matching_beta > 0 ? matching_beta : default_beta);
HiddenMarkovModel model(candidates_list, emission_log_probability);
unsigned initial_timestamp = model.initialize(0);
if (initial_timestamp == Matching::INVALID_STATE)
@@ -464,7 +447,7 @@ template <class DataFacadeT> class MapMatching final
{
// how likely is candidate s_prime at time t to be emitted?
const double emission_pr =
log_emission_probability(candidates_list[t][s_prime].second);
emission_log_probability(candidates_list[t][s_prime].second);
double new_value = prev_viterbi[s] + emission_pr;
if (current_viterbi[s_prime] > new_value)
continue;
@@ -483,7 +466,7 @@ template <class DataFacadeT> class MapMatching final
if (d_t > 500)
continue;
const double transition_pr = log_transition_probability(d_t, beta);
const double transition_pr = transition_log_probability(d_t);
new_value += transition_pr;
debug.add_transition_info(prev_unbroken_timestamp, t, s, s_prime,