前言

在Apollo星火计划学习笔记——Apollo路径规划算法原理与实践与【Apollo学习笔记】——Planning模块讲到……Stage::Process的PlanOnReferenceLine函数会依次调用task_list中的TASK，本文将会继续以LaneFollow为例依次介绍其中的TASK部分究竟做了哪些工作。由于个人能力所限，文章可能有纰漏的地方，还请批评斧正。

在modules/planning/conf/scenario/lane_follow_config.pb.txt配置文件中，我们可以看到LaneFollow所需要执行的所有task。

stage_config: {stage_type: LANE_FOLLOW_DEFAULT_STAGEenabled: truetask_type: LANE_CHANGE_DECIDERtask_type: PATH_REUSE_DECIDERtask_type: PATH_LANE_BORROW_DECIDERtask_type: PATH_BOUNDS_DECIDERtask_type: PIECEWISE_JERK_PATH_OPTIMIZERtask_type: PATH_ASSESSMENT_DECIDERtask_type: PATH_DECIDERtask_type: RULE_BASED_STOP_DECIDERtask_type: SPEED_BOUNDS_PRIORI_DECIDERtask_type: SPEED_HEURISTIC_OPTIMIZERtask_type: SPEED_DECIDERtask_type: SPEED_BOUNDS_FINAL_DECIDERtask_type: PIECEWISE_JERK_SPEED_OPTIMIZER# task_type: PIECEWISE_JERK_NONLINEAR_SPEED_OPTIMIZERtask_type: RSS_DECIDER

本文将继续介绍LaneFollow的第7个TASK——PATH_DECIDER

PATH_DECIDER功能简介

根据选出的路径给出对障碍物的决策

若是绕行的路径，则产生绕行的决策；若前方有障碍物阻塞，则产生停止的决策。

PATH_DECIDER相关配置

modules/planning/conf/planning_config.pb.txt

default_task_config: {task_type: PATH_DECIDERpath_decider_config{static_obstacle_buffer: 0.3}
}

modules/planning/proto/task_config.proto

//
// PathDeciderConfigmessage PathDeciderConfig {// buffer for static obstacles (meter)optional double static_obstacle_buffer = 1 [default = 0.3];
}

PATH_DECIDER总体流程

输入:

Status PathDecider::Process(const ReferenceLineInfo *reference_line_info,const PathData &path_data,PathDecision *const path_decision) {

输出:
路径决策的信息都保存到了path_decision中。

路径决策代码流程及框架

在Process函数主要功能是调用了MakeObjectDecision函数。而在MakeObjectDecision函数中调用了MakeStaticObstacleDecision函数。

路径决策的主要功能都在MakeStaticObstacleDecision中。这部分代码还是比较清晰的。

Status PathDecider::Process(const ReferenceLineInfo *reference_line_info,const PathData &path_data,PathDecision *const path_decision) {// skip path_decider if reused pathif (FLAGS_enable_skip_path_tasks && reference_line_info->path_reusable()) {return Status::OK();}std::string blocking_obstacle_id;if (reference_line_info->GetBlockingObstacle() != nullptr) {blocking_obstacle_id = reference_line_info->GetBlockingObstacle()->Id();}// 调用MakeObjectDecision函数if (!MakeObjectDecision(path_data, blocking_obstacle_id, path_decision)) {const std::string msg = "Failed to make decision based on tunnel";AERROR << msg;return Status(ErrorCode::PLANNING_ERROR, msg);}return Status::OK();
}bool PathDecider::MakeObjectDecision(const PathData &path_data,const std::string &blocking_obstacle_id,PathDecision *const path_decision) {// path decider的主要功能在MakeStaticObstacleDecision中if (!MakeStaticObstacleDecision(path_data, blocking_obstacle_id,path_decision)) {AERROR << "Failed to make decisions for static obstacles";return false;}return true;
}

MakeStaticObstacleDecision

获取frenet坐标系下的坐标

  ... ...// 1.获取frenet坐标下的path路径const auto &frenet_path = path_data.frenet_frame_path();if (frenet_path.empty()) {AERROR << "Path is empty.";return false;}... ...

根据障碍物做决策

  ... ...// 2.遍历每个障碍物，做决策for (const auto *obstacle : path_decision->obstacles().Items()) {const std::string &obstacle_id = obstacle->Id();const std::string obstacle_type_name =PerceptionObstacle_Type_Name(obstacle->Perception().type());ADEBUG << "obstacle_id[<< " << obstacle_id << "] type["<< obstacle_type_name << "]";... ...

如果障碍物不是静态或virtual，则跳过

    // 2.1 如果障碍物不是静态的或者是virtual的，就跳过if (!obstacle->IsStatic() || obstacle->IsVirtual()) {    // （stop fence，各种fence）continue;}

如果障碍物有了ignore/stop决策，则跳过

    // 2.2 如果障碍物已经有 ignore/stop 决策，就跳过if (obstacle->HasLongitudinalDecision() &&obstacle->LongitudinalDecision().has_ignore() &&obstacle->HasLateralDecision() &&obstacle->LateralDecision().has_ignore()) {continue;}if (obstacle->HasLongitudinalDecision() &&obstacle->LongitudinalDecision().has_stop()) {// STOP decisioncontinue;}

如果障碍物挡住了路径，加stop决策

    // 2.3 如果障碍物挡住了路径，加stop决策if (obstacle->Id() == blocking_obstacle_id &&!injector_->planning_context()->planning_status().path_decider().is_in_path_lane_borrow_scenario()) {// Add stop decisionADEBUG << "Blocking obstacle = " << blocking_obstacle_id;ObjectDecisionType object_decision;*object_decision.mutable_stop() = GenerateObjectStopDecision(*obstacle);path_decision->AddLongitudinalDecision("PathDecider/blocking_obstacle",obstacle->Id(), object_decision);continue;}

如果是clear-zone，跳过

    // 2.4 如果是clear-zone，跳过if (obstacle->reference_line_st_boundary().boundary_type() ==STBoundary::BoundaryType::KEEP_CLEAR) {continue;}

如果障碍物不在路径上，跳过

    // 2.5 如果障碍物不在路径上，跳过ObjectDecisionType object_decision;object_decision.mutable_ignore();const auto &sl_boundary = obstacle->PerceptionSLBoundary();if (sl_boundary.end_s() < frenet_path.front().s() ||sl_boundary.start_s() > frenet_path.back().s()) {path_decision->AddLongitudinalDecision("PathDecider/not-in-s",obstacle->Id(), object_decision);path_decision->AddLateralDecision("PathDecider/not-in-s", obstacle->Id(),object_decision);continue;}

nudge判断

• 如果距离静态障碍物距离太远，则忽略。
• 如果静态障碍物距离车道中心太近，则停止。
• 如果横向方向很近，则避开。

    // 2.6 nudge判断，如果距离静态障碍物距离太远，则忽略。//               如果静态障碍物距离车道中心太近，则停止。//               如果横向方向很近，则避开。if (curr_l - lateral_radius > sl_boundary.end_l() ||curr_l + lateral_radius < sl_boundary.start_l()) {// 1. IGNORE if laterally too far away.path_decision->AddLateralDecision("PathDecider/not-in-l", obstacle->Id(),object_decision);} else if (sl_boundary.end_l() >= curr_l - min_nudge_l &&sl_boundary.start_l() <= curr_l + min_nudge_l) {// 2. STOP if laterally too overlapping.*object_decision.mutable_stop() = GenerateObjectStopDecision(*obstacle);if (path_decision->MergeWithMainStop(object_decision.stop(), obstacle->Id(),reference_line_info_->reference_line(),reference_line_info_->AdcSlBoundary())) {path_decision->AddLongitudinalDecision("PathDecider/nearest-stop",obstacle->Id(), object_decision);} else {ObjectDecisionType object_decision;object_decision.mutable_ignore();path_decision->AddLongitudinalDecision("PathDecider/not-nearest-stop",obstacle->Id(), object_decision);}} else {// 3. NUDGE if laterally very close.if (sl_boundary.end_l() < curr_l - min_nudge_l) {  // &&// sl_boundary.end_l() > curr_l - min_nudge_l - 0.3) {// LEFT_NUDGEObjectNudge *object_nudge_ptr = object_decision.mutable_nudge();object_nudge_ptr->set_type(ObjectNudge::LEFT_NUDGE);object_nudge_ptr->set_distance_l(config_.path_decider_config().static_obstacle_buffer());path_decision->AddLateralDecision("PathDecider/left-nudge",obstacle->Id(), object_decision);} else if (sl_boundary.start_l() > curr_l + min_nudge_l) {  // &&// sl_boundary.start_l() < curr_l + min_nudge_l + 0.3) {// RIGHT_NUDGEObjectNudge *object_nudge_ptr = object_decision.mutable_nudge();object_nudge_ptr->set_type(ObjectNudge::RIGHT_NUDGE);object_nudge_ptr->set_distance_l(-config_.path_decider_config().static_obstacle_buffer());path_decision->AddLateralDecision("PathDecider/right-nudge",obstacle->Id(), object_decision);}}

PATH_DECIDER相关子函数

GenerateObjectStopDecision主要用以生成停止决策。

ObjectStop PathDecider::GenerateObjectStopDecision(const Obstacle &obstacle) const {ObjectStop object_stop;// Calculate stop distance with the obstacle using the ADC's minimum turning radiusdouble stop_distance = obstacle.MinRadiusStopDistance(VehicleConfigHelper::GetConfig().vehicle_param());object_stop.set_reason_code(StopReasonCode::STOP_REASON_OBSTACLE);object_stop.set_distance_s(-stop_distance);// 停止时的参考位置const double stop_ref_s =obstacle.PerceptionSLBoundary().start_s() - stop_distance;const auto stop_ref_point =reference_line_info_->reference_line().GetReferencePoint(stop_ref_s);object_stop.mutable_stop_point()->set_x(stop_ref_point.x());object_stop.mutable_stop_point()->set_y(stop_ref_point.y());object_stop.set_stop_heading(stop_ref_point.heading());return object_stop;
}

对于停止距离的计算，会调用MinRadiusStopDistance函数,
modules/planning/common/obstacle.cc

double Obstacle::MinRadiusStopDistance(const common::VehicleParam& vehicle_param) const {if (min_radius_stop_distance_ > 0) {return min_radius_stop_distance_;}// 定义一个停止距离的缓冲区0.5mstatic constexpr double stop_distance_buffer = 0.5;// 获取最小安全转弯半径const double min_turn_radius = VehicleConfigHelper::MinSafeTurnRadius();// 计算横向距离double lateral_diff =vehicle_param.width() / 2.0 + std::max(std::fabs(sl_boundary_.start_l()),std::fabs(sl_boundary_.end_l()));const double kEpison = 1e-5;lateral_diff = std::min(lateral_diff, min_turn_radius - kEpison);// 勾股定理求得停止距离double stop_distance =std::sqrt(std::fabs(min_turn_radius * min_turn_radius -(min_turn_radius - lateral_diff) *(min_turn_radius - lateral_diff))) +stop_distance_buffer;// 减掉车辆前端到后轴中心的距离stop_distance -= vehicle_param.front_edge_to_center();// 限幅stop_distance = std::min(stop_distance, FLAGS_max_stop_distance_obstacle); // 10.0stop_distance = std::max(stop_distance, FLAGS_min_stop_distance_obstacle); // 6.0return stop_distance;
}

计算示意图如下：

modules/common/configs/vehicle_config_helper.cc

double VehicleConfigHelper::MinSafeTurnRadius() {const auto &param = vehicle_config_.vehicle_param();double lat_edge_to_center =std::max(param.left_edge_to_center(), param.right_edge_to_center());double lon_edge_to_center =std::max(param.front_edge_to_center(), param.back_edge_to_center());return std::sqrt((lat_edge_to_center + param.min_turn_radius()) *(lat_edge_to_center + param.min_turn_radius()) +lon_edge_to_center * lon_edge_to_center);
}

MinSafeTurnRadius这段函数是获取当车辆以最大转向角转弯时的最大安全转弯半径。具体计算参考下图：

$A,B,C,D$分别是车辆的四个角，$XO$是车辆的最小转弯半径VehicleParam.min_turn_radius()，$X$与$AD$之间的距离是左边缘到中心的距离left_edge_to_center，$X$与$AB$之间的距离是前边缘到中心的距离front_edge_to_center。最大安全转弯半径则是$AO$，定义中心到横向边缘最长的距离为$l_{lat}$，到纵向边缘最长的距离为$l_{lon}$，$AO$计算公式如下：
$$AO=\sqrt{(XO+l_{lat}{)}^2+{l_{lon}}^2}$$
个人感觉这么做是为了获得足够的安全冗余量。

参考

[1] 路径决策