【Apollo学习笔记】——规划模块TASK之PATH_ASSESSMENT_DECIDER

文章目录

  • 前言
  • PATH_ASSESSMENT_DECIDER功能简介
  • PATH_ASSESSMENT_DECIDER相关信息
  • PATH_ASSESSMENT_DECIDER总体流程
    • 1. 去除无效路径
    • 2. 分析并加入重要信息给speed决策
      • SetPathInfo
        • SetPathPointType
    • 3. 排序选择最优的路径
    • 4. 更新必要的信息

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。

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_STAGE
  enabled: true
  task_type: LANE_CHANGE_DECIDER
  task_type: PATH_REUSE_DECIDER
  task_type: PATH_LANE_BORROW_DECIDER
  task_type: PATH_BOUNDS_DECIDER
  task_type: PIECEWISE_JERK_PATH_OPTIMIZER
  task_type: PATH_ASSESSMENT_DECIDER
  task_type: PATH_DECIDER
  task_type: RULE_BASED_STOP_DECIDER
  task_type: SPEED_BOUNDS_PRIORI_DECIDER
  task_type: SPEED_HEURISTIC_OPTIMIZER
  task_type: SPEED_DECIDER
  task_type: SPEED_BOUNDS_FINAL_DECIDER
  task_type: PIECEWISE_JERK_SPEED_OPTIMIZER
  # task_type: PIECEWISE_JERK_NONLINEAR_SPEED_OPTIMIZER
  task_type: RSS_DECIDER

本文将继续介绍LaneFollow的第6个TASK——PATH_ASSESSMENT_DECIDER

PATH_ASSESSMENT_DECIDER功能简介

路径评价,选出最优路径

【Apollo学习笔记】——规划模块TASK之PATH_ASSESSMENT_DECIDER_第1张图片
PATH_BOUNDS_DECIDER可以知道会产生以下几种类型的路径边界:

  • fallback
  • fallback+lanechange
  • fallback+pullover
  • fallback+regular

依据不同的边界会产生不同的路径,接着便需要筛选出一条最优的路径。依据以下规则,进行评价:

  • 路径是否和障碍物碰撞
  • 路径长度
  • 路径是否会停在对向车道
  • 路径离自车远近
  • 哪个路径更早回自车道

PATH_ASSESSMENT_DECIDER相关信息

  • 输入:Status PathAssessmentDecider::Process(Frame* const frame, ReferenceLineInfo* const reference_line_info)
    输入Frame,reference_line_info。
  • 输出:路径排序之后,选择第一个路径。结果保存在reference_line_info中

PATH_ASSESSMENT_DECIDER总体流程

【Apollo学习笔记】——规划模块TASK之PATH_ASSESSMENT_DECIDER_第2张图片

【Apollo学习笔记】——规划模块TASK之PATH_ASSESSMENT_DECIDER_第3张图片
首先来看看PathAssessmentDecider::Process流程部分:

Process部分主要完成路径重复使用判断、去除无效路径、分析路径并加入重要信息提供给速度决策部分、排序选择最优的路径以及最后的更新必要的信息。

1. 去除无效路径

  // 1. Remove invalid path.
  // 1. 删掉无效路径.
  std::vector<PathData> valid_path_data;
  for (const auto& curr_path_data : candidate_path_data) {
    // RecordDebugInfo(curr_path_data, curr_path_data.path_label(),
    //                 reference_line_info);
    if (curr_path_data.path_label().find("fallback") != std::string::npos) {
      // fallback的无效路径是偏离参考线以及道路的路径
      if (IsValidFallbackPath(*reference_line_info, curr_path_data)) {
        valid_path_data.push_back(curr_path_data);
      }
    } else {
      // regular的无效路径是偏离参考线、道路,碰撞,停在相邻的逆向车道的路径。
      if (IsValidRegularPath(*reference_line_info, curr_path_data)) {
        valid_path_data.push_back(curr_path_data);
      }
    }
  }
  const auto& end_time1 = std::chrono::system_clock::now();
  std::chrono::duration<double> diff = end_time1 - end_time0;
  ADEBUG << "Time for path validity checking: " << diff.count() * 1000
         << " msec.";

其中fallback的无效路径是偏离参考线以及道路的路径。regular的无效路径是偏离参考线、道路,碰撞,停在相邻的逆向车道的路径。

2. 分析并加入重要信息给speed决策

  // 2. Analyze and add important info for speed decider to use
  // 2. 分析并加入重要信息给speed决策
  size_t cnt = 0;
  const Obstacle* blocking_obstacle_on_selflane = nullptr;
  for (size_t i = 0; i != valid_path_data.size(); ++i) {
    auto& curr_path_data = valid_path_data[i];
    if (curr_path_data.path_label().find("fallback") != std::string::npos) {
      // remove empty path_data.
      if (!curr_path_data.Empty()) {
        if (cnt != i) {
          valid_path_data[cnt] = curr_path_data;
        }
        ++cnt;
      }
      continue;
    }
    // 添加相关信息
    SetPathInfo(*reference_line_info, &curr_path_data);
    // Trim all the lane-borrowing paths so that it ends with an in-lane
    // position.
    // 修剪所有路径(只要不是pull-over),使其能够以in-lane结尾
    if (curr_path_data.path_label().find("pullover") == std::string::npos) {
      TrimTailingOutLanePoints(&curr_path_data);
    }

    // find blocking_obstacle_on_selflane, to be used for lane selection later
    // 找到self_lane上的阻塞障碍物, 为下一步选择车道做准备
    if (curr_path_data.path_label().find("self") != std::string::npos) {
      const auto blocking_obstacle_id = curr_path_data.blocking_obstacle_id();
      blocking_obstacle_on_selflane =
          reference_line_info->path_decision()->Find(blocking_obstacle_id);
    }

    // remove empty path_data.
    if (!curr_path_data.Empty()) {
      if (cnt != i) {
        valid_path_data[cnt] = curr_path_data;
      }
      ++cnt;
    }

    // RecordDebugInfo(curr_path_data, curr_path_data.path_label(),
    //                 reference_line_info);
    ADEBUG << "For " << curr_path_data.path_label() << ", "
           << "path length = " << curr_path_data.frenet_frame_path().size();
  }
  valid_path_data.resize(cnt);
  // If there is no valid path_data, exit.
  // 如果没有有效路径,退出
  if (valid_path_data.empty()) {
    const std::string msg = "Neither regular nor fallback path is valid.";
    AERROR << msg;
    return Status(ErrorCode::PLANNING_ERROR, msg);
  }
  ADEBUG << "There are " << valid_path_data.size() << " valid path data.";
  const auto& end_time2 = std::chrono::system_clock::now();
  diff = end_time2 - end_time1;
  ADEBUG << "Time for path info labeling: " << diff.count() * 1000 << " msec.";

SetPathInfo

void PathAssessmentDecider::SetPathInfo(
    const ReferenceLineInfo& reference_line_info, PathData* const path_data) {
  // Go through every path_point, and label its:
  //  - in-lane/out-of-lane info (side-pass or lane-change)
  //  - distance to the closest obstacle.
  std::vector<PathPointDecision> path_decision;

  // 0. Initialize the path info.
  InitPathPointDecision(*path_data, &path_decision);

  // 1. Label caution types, differently for side-pass or lane-change.
  if (reference_line_info.IsChangeLanePath()) {
    // If lane-change, then label the lane-changing part to
    // be out-on-forward lane.
    SetPathPointType(reference_line_info, *path_data, true, &path_decision);
  } else {
    // Otherwise, only do the label for borrow-lane generated paths.
    // 仅仅对借道进行标记
    if (path_data->path_label().find("fallback") == std::string::npos &&
        path_data->path_label().find("self") == std::string::npos) {
      SetPathPointType(reference_line_info, *path_data, false, &path_decision);
    }
  }

  // SetObstacleDistance(reference_line_info, *path_data, &path_decision);
  path_data->SetPathPointDecisionGuide(std::move(path_decision));
}

这一部分中函数SetPathInfo完成以下功能:初始化path info;根据是lane-change还是side-pass,设置路径点的类型;添加相关决策引导信息等信息。

SetPathPointType

在设置路径点的类型时涉及到SetPathPointType这一个函数。
流程如下图所示:

【Apollo学习笔记】——规划模块TASK之PATH_ASSESSMENT_DECIDER_第4张图片

void PathAssessmentDecider::SetPathPointType(
    const ReferenceLineInfo& reference_line_info, const PathData& path_data,
    const bool is_lane_change_path,
    std::vector<PathPointDecision>* const path_point_decision) {
  // Sanity checks.
  CHECK_NOTNULL(path_point_decision);

  // Go through every path_point, and add in-lane/out-of-lane info.
  const auto& discrete_path = path_data.discretized_path();
  const auto& vehicle_config =
      common::VehicleConfigHelper::Instance()->GetConfig();
  const double ego_length = vehicle_config.vehicle_param().length();
  const double ego_width = vehicle_config.vehicle_param().width();
  const double ego_back_to_center =
      vehicle_config.vehicle_param().back_edge_to_center();
  // 车辆几何中心点与车辆后轴的偏移距离
  const double ego_center_shift_distance =
      ego_length / 2.0 - ego_back_to_center;

  bool is_prev_point_out_lane = false;
  for (size_t i = 0; i < discrete_path.size(); ++i) {
    // 以车辆后轴中心获取boundingbox
    const auto& rear_center_path_point = discrete_path[i];
    const double ego_theta = rear_center_path_point.theta();
    Box2d ego_box({rear_center_path_point.x(), rear_center_path_point.y()},
                  ego_theta, ego_length, ego_width);
    Vec2d shift_vec{ego_center_shift_distance * std::cos(ego_theta),
                    ego_center_shift_distance * std::sin(ego_theta)};
    // 将boundingbox从车辆后轴中心变换到几何中心(apollo在这里采用的是AABB的boundingbox,其中有些细节等之后再细看)
    ego_box.Shift(shift_vec);
    // 得到SL坐标系下的boundary
    SLBoundary ego_sl_boundary;
    if (!reference_line_info.reference_line().GetSLBoundary(ego_box,
                                                            &ego_sl_boundary)) {
      ADEBUG << "Unable to get SL-boundary of ego-vehicle.";
      continue;
    }
    double lane_left_width = 0.0;
    double lane_right_width = 0.0;
    double middle_s =
        (ego_sl_boundary.start_s() + ego_sl_boundary.end_s()) / 2.0;
    if (reference_line_info.reference_line().GetLaneWidth(
            middle_s, &lane_left_width, &lane_right_width)) {
      // Rough sl boundary estimate using single point lane width
      double back_to_inlane_extra_buffer = 0.2;
      double in_and_out_lane_hysteresis_buffer =
          is_prev_point_out_lane ? back_to_inlane_extra_buffer : 0.0;

      // Check for lane-change and lane-borrow differently:
      if (is_lane_change_path) {
        // For lane-change path, only transitioning part is labeled as
        // out-of-lane.
        if (ego_sl_boundary.start_l() > lane_left_width ||
            ego_sl_boundary.end_l() < -lane_right_width) {
          // This means that ADC hasn't started lane-change yet.
          // 再次重申,变道时是以要变道的目标车道作为参考线
          std::get<1>((*path_point_decision)[i]) =
              PathData::PathPointType::IN_LANE;
        } else if (ego_sl_boundary.start_l() >
                       -lane_right_width + back_to_inlane_extra_buffer &&
                   ego_sl_boundary.end_l() <
                       lane_left_width - back_to_inlane_extra_buffer) {
          // This means that ADC has safely completed lane-change with margin.
          std::get<1>((*path_point_decision)[i]) =
              PathData::PathPointType::IN_LANE;
        } else {
          // ADC is right across two lanes.
          std::get<1>((*path_point_decision)[i]) =
              PathData::PathPointType::OUT_ON_FORWARD_LANE;
        }
      } else {
        // For lane-borrow path, as long as ADC is not on the lane of
        // reference-line, it is out on other lanes. It might even be
        // on reverse lane!
        if (ego_sl_boundary.end_l() >
                lane_left_width + in_and_out_lane_hysteresis_buffer ||
            ego_sl_boundary.start_l() <
                -lane_right_width - in_and_out_lane_hysteresis_buffer) {
          if (path_data.path_label().find("reverse") != std::string::npos) {
            std::get<1>((*path_point_decision)[i]) =
                PathData::PathPointType::OUT_ON_REVERSE_LANE;
          } else if (path_data.path_label().find("forward") !=
                     std::string::npos) {
            std::get<1>((*path_point_decision)[i]) =
                PathData::PathPointType::OUT_ON_FORWARD_LANE;
          } else {
            std::get<1>((*path_point_decision)[i]) =
                PathData::PathPointType::UNKNOWN;
          }
          if (!is_prev_point_out_lane) {
            if (ego_sl_boundary.end_l() >
                    lane_left_width + back_to_inlane_extra_buffer ||
                ego_sl_boundary.start_l() <
                    -lane_right_width - back_to_inlane_extra_buffer) {
              is_prev_point_out_lane = true;
            }
          }
        } else {
          // The path point is within the reference_line's lane.
          std::get<1>((*path_point_decision)[i]) =
              PathData::PathPointType::IN_LANE;
          if (is_prev_point_out_lane) {
            is_prev_point_out_lane = false;
          }
        }
      }
    } else {
      AERROR << "reference line not ready when setting path point guide";
      return;
    }
  }
}

PS:关于ego_box.Shift(shift_vec);这一步是如何实现的,可以关注这篇博客:Apollo EM中path_assesment_task相关细节的讨论

3. 排序选择最优的路径

  ... ...
  // 3. Pick the optimal path.
  // 3. 选择最优路径,两两比较路径。排序是根据 ComparePathData 函数的返回值进行的。
  std::sort(valid_path_data.begin(), valid_path_data.end(),
            std::bind(ComparePathData, std::placeholders::_1,
                      std::placeholders::_2, blocking_obstacle_on_selflane));

  ADEBUG << "Using '" << valid_path_data.front().path_label()
         << "' path out of " << valid_path_data.size() << " path(s)";
  if (valid_path_data.front().path_label().find("fallback") !=
      std::string::npos) {
    FLAGS_static_obstacle_nudge_l_buffer = 0.8;
  }
  *(reference_line_info->mutable_path_data()) = valid_path_data.front();
  reference_line_info->SetBlockingObstacle(
      valid_path_data.front().blocking_obstacle_id());
  const auto& end_time3 = std::chrono::system_clock::now();
  diff = end_time3 - end_time2;
  ADEBUG << "Time for optimal path selection: " << diff.count() * 1000
         << " msec.";
  ... ...

主要排序规则在ComparePathData函数中。

bool ComparePathData(const PathData& lhs, const PathData& rhs,
                     const Obstacle* blocking_obstacle) {
  ADEBUG << "Comparing " << lhs.path_label() << " and " << rhs.path_label();
  // Empty path_data is never the larger one.
  // 空的路径永远排在后面
  if (lhs.Empty()) {
    ADEBUG << "LHS is empty.";
    return false;
  }
  if (rhs.Empty()) {
    ADEBUG << "RHS is empty.";
    return true;
  }
  // Regular path goes before fallback path.regular > fallback
  // 如果lhs是regular路径而rhs是fallback路径,那么lhs会被认为更好,返回true。
  bool lhs_is_regular = lhs.path_label().find("regular") != std::string::npos;
  bool rhs_is_regular = rhs.path_label().find("regular") != std::string::npos;
  if (lhs_is_regular != rhs_is_regular) {
    return lhs_is_regular;
  }
  // Select longer path.
  // If roughly same length, then select self-lane path.
  bool lhs_on_selflane = lhs.path_label().find("self") != std::string::npos;
  bool rhs_on_selflane = rhs.path_label().find("self") != std::string::npos;
  static constexpr double kSelfPathLengthComparisonTolerance = 15.0;
  static constexpr double kNeighborPathLengthComparisonTolerance = 25.0;
  double lhs_path_length = lhs.frenet_frame_path().back().s();
  double rhs_path_length = rhs.frenet_frame_path().back().s();
  // 至少其中有一条是self_lane
  if (lhs_on_selflane || rhs_on_selflane) {
    // 如果两条路径的长度相差超过了kSelfPathLengthComparisonTolerance(在这里是15.0),那么较长的路径将被认为更好。
    if (std::fabs(lhs_path_length - rhs_path_length) >
        kSelfPathLengthComparisonTolerance) {
      return lhs_path_length > rhs_path_length;
    } else {
      // 如果两条路径的长度相差在这个容差范围内,并且其中一条路径在"self"车道上,那么"self"车道上的路径将被认为更好。
      return lhs_on_selflane;
    }
  } else {
    // 没有一条是self_lane
    if (std::fabs(lhs_path_length - rhs_path_length) >
        kNeighborPathLengthComparisonTolerance) {
      return lhs_path_length > rhs_path_length;
    }
  }
  // If roughly same length, and must borrow neighbor lane,
  // then prefer to borrow forward lane rather than reverse lane.
  int lhs_on_reverse =
      ContainsOutOnReverseLane(lhs.path_point_decision_guide());
  int rhs_on_reverse =
      ContainsOutOnReverseLane(rhs.path_point_decision_guide());
  // TODO(jiacheng): make this a flag.
  // 如果需要借用逆向车道的次数差超过了6次,那么次数较少的路径将被认为更好(相当于选择逆向距离短的)。
  if (std::abs(lhs_on_reverse - rhs_on_reverse) > 6) {
    return lhs_on_reverse < rhs_on_reverse;
  }
  // For two lane-borrow directions, based on ADC's position,
  // select the more convenient one.
  if ((lhs.path_label().find("left") != std::string::npos &&
       rhs.path_label().find("right") != std::string::npos) ||
      (lhs.path_label().find("right") != std::string::npos &&
       rhs.path_label().find("left") != std::string::npos)) {
    if (blocking_obstacle) {
      // select left/right path based on blocking_obstacle's position
      // 有障碍物,选择合适的方向,左或右借道
      const double obstacle_l =
          (blocking_obstacle->PerceptionSLBoundary().start_l() +
           blocking_obstacle->PerceptionSLBoundary().end_l()) /
          2;
      ADEBUG << "obstacle[" << blocking_obstacle->Id() << "] l[" << obstacle_l
             << "]";
      // 如果阻挡障碍物的横向位置大于0(在障碍物的右侧),那么含有"right"的路径将被认为更好;否则,含有"left"的路径将被认为更好。
      return (obstacle_l > 0.0
                  ? (lhs.path_label().find("right") != std::string::npos)
                  : (lhs.path_label().find("left") != std::string::npos));
    } else {
      // select left/right path based on ADC's position
      // 无障碍物,根据adc的位置选择借道方向
      double adc_l = lhs.frenet_frame_path().front().l();
      if (adc_l < -1.0) {
        return lhs.path_label().find("right") != std::string::npos;
      } else if (adc_l > 1.0) {
        return lhs.path_label().find("left") != std::string::npos;
      }
    }
  }
  // If same length, both neighbor lane are forward,
  // then select the one that returns to in-lane earlier.
  // 路径长度相同,相邻车道都是前向的,选择较早返回自车道的路径
  static constexpr double kBackToSelfLaneComparisonTolerance = 20.0;
  int lhs_back_idx = GetBackToInLaneIndex(lhs.path_point_decision_guide());
  int rhs_back_idx = GetBackToInLaneIndex(rhs.path_point_decision_guide());
  double lhs_back_s = lhs.frenet_frame_path()[lhs_back_idx].s();
  double rhs_back_s = rhs.frenet_frame_path()[rhs_back_idx].s();
  if (std::fabs(lhs_back_s - rhs_back_s) > kBackToSelfLaneComparisonTolerance) {
    return lhs_back_idx < rhs_back_idx;
  }
  // If same length, both forward, back to inlane at same time,
  // select the left one to side-pass.
  // 如果路径长度相同,前向借道,返回自车道时间相同,选择从左侧借道的路径
  bool lhs_on_leftlane = lhs.path_label().find("left") != std::string::npos;
  bool rhs_on_leftlane = rhs.path_label().find("left") != std::string::npos;
  if (lhs_on_leftlane != rhs_on_leftlane) {
    ADEBUG << "Select " << (lhs_on_leftlane ? "left" : "right") << " lane over "
           << (!lhs_on_leftlane ? "left" : "right") << " lane.";
    return lhs_on_leftlane;
  }
  // Otherwise, they are the same path, lhs is not < rhs.
  // 最后如果两条路径相同,则 lhs is not < rhl
  return false;
}

路径排序规则如下:(道路评估的优劣通过排序获得)

1.空的路径永远排在后面
2.regular > fallback
3.如果self-lane有一个存在,选择那个。如果都存在,选择较长的.如果长度接近,选择self-lane如果self-lane都不存在,选择较长的路径
4.如果路径长度接近,且都要借道:

  • (1) 都要借逆向车道,选择距离短的
  • (2) 针对具有两个借道方向的情况:
    • 有障碍物,选择合适的方向,左或右借道
    • 无障碍物,根据adc的位置选择借道方向
  • (3) 路径长度相同,相邻车道都是前向的,选择较早返回自车道的路径
  • (4) 如果路径长度相同,前向借道,返回自车道时间相同,选择从左侧借道的路径

5.最后如果两条路径相同,则 lhs is not < rhl

排序之后:选择最优路径,即第一个路径

4. 更新必要的信息

  // 4. Update necessary info for lane-borrow decider's future uses.
  // Update front static obstacle's info.
  auto* mutable_path_decider_status = injector_->planning_context()
                                          ->mutable_planning_status()
                                          ->mutable_path_decider();
  if (reference_line_info->GetBlockingObstacle() != nullptr) {
    int front_static_obstacle_cycle_counter =
        mutable_path_decider_status->front_static_obstacle_cycle_counter();
    mutable_path_decider_status->set_front_static_obstacle_cycle_counter(
        std::max(front_static_obstacle_cycle_counter, 0));
    mutable_path_decider_status->set_front_static_obstacle_cycle_counter(
        std::min(front_static_obstacle_cycle_counter + 1, 10));
    mutable_path_decider_status->set_front_static_obstacle_id(
        reference_line_info->GetBlockingObstacle()->Id());
  } else {
    int front_static_obstacle_cycle_counter =
        mutable_path_decider_status->front_static_obstacle_cycle_counter();
    mutable_path_decider_status->set_front_static_obstacle_cycle_counter(
        std::min(front_static_obstacle_cycle_counter, 0));
    mutable_path_decider_status->set_front_static_obstacle_cycle_counter(
        std::max(front_static_obstacle_cycle_counter - 1, -10));
  }

  // Update self-lane usage info.
  if (reference_line_info->path_data().path_label().find("self") !=
      std::string::npos) {
    // && std::get<1>(reference_line_info->path_data()
    //                 .path_point_decision_guide()
    //                 .front()) == PathData::PathPointType::IN_LANE)
    int able_to_use_self_lane_counter =
        mutable_path_decider_status->able_to_use_self_lane_counter();

    if (able_to_use_self_lane_counter < 0) {
      able_to_use_self_lane_counter = 0;
    }
    mutable_path_decider_status->set_able_to_use_self_lane_counter(
        std::min(able_to_use_self_lane_counter + 1, 10));
  } else {
    mutable_path_decider_status->set_able_to_use_self_lane_counter(0);
  }

  // Update side-pass direction.
  if (mutable_path_decider_status->is_in_path_lane_borrow_scenario()) {
    bool left_borrow = false;
    bool right_borrow = false;
    const auto& path_decider_status =
        injector_->planning_context()->planning_status().path_decider();
    for (const auto& lane_borrow_direction :
         path_decider_status.decided_side_pass_direction()) {
      if (lane_borrow_direction == PathDeciderStatus::LEFT_BORROW &&
          reference_line_info->path_data().path_label().find("left") !=
              std::string::npos) {
        left_borrow = true;
      }
      if (lane_borrow_direction == PathDeciderStatus::RIGHT_BORROW &&
          reference_line_info->path_data().path_label().find("right") !=
              std::string::npos) {
        right_borrow = true;
      }
    }

    mutable_path_decider_status->clear_decided_side_pass_direction();
    if (right_borrow) {
      mutable_path_decider_status->add_decided_side_pass_direction(
          PathDeciderStatus::RIGHT_BORROW);
    }
    if (left_borrow) {
      mutable_path_decider_status->add_decided_side_pass_direction(
          PathDeciderStatus::LEFT_BORROW);
    }
  }
  const auto& end_time4 = std::chrono::system_clock::now();
  diff = end_time4 - end_time3;
  ADEBUG << "Time for FSM state updating: " << diff.count() * 1000 << " msec.";

  // Plot the path in simulator for debug purpose.
  RecordDebugInfo(reference_line_info->path_data(), "Planning PathData",
                  reference_line_info);
  return Status::OK();

更新必要信息:

1.更新adc前方静态障碍物的信息
2.更新自车道使用信息
3.更新旁车道的方向根据:PathDeciderStatusRIGHT_BORROWLEFT_BORROW判断是从左侧借道,还是从右侧借道

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