文章目录

前言
PATH_BOUNDS_DECIDER功能简介
PATH_BOUNDS_DECIDER相关配置
PATH_BOUNDS_DECIDER总体流程
- InitPathBoundsDecider
- 1. fallback
- - GenerateFallbackPathBound
  - - InitPathBoundary
    - GetBoundaryFromLanesAndADC
    - - UpdatePathBoundaryWithBuffer
      - TrimPathBounds
- 2. pull over
- - GeneratePullOverPathBound
  - - GetBoundaryFromRoads
    - UpdatePullOverBoundaryByLaneBoundary
    - GetBoundaryFromStaticObstacles
    - SearchPullOverPosition
- 3. lane change
- - GenerateLaneChangePathBound
  - - GetBoundaryFromLaneChangeForbiddenZone
- 4. regular

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_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的第四个TASK——PATH_BOUNDS_DECIDER

PATH_BOUNDS_DECIDER功能简介

在这里插入图片描述利用前几个决策器，根据相应条件，产生相应的SL边界。这里说明以下Nudge障碍物的概念——主车旁边的障碍物未完全阻挡主车，主车可以通过绕行避过障碍物（注意图中的边界）。

PATH_BOUNDS_DECIDER相关配置

在modules/planning/conf/planning_config.pb.txt中有相关配置。

default_task_config: {
  task_type: PATH_BOUNDS_DECIDER
  path_bounds_decider_config {
    is_lane_borrowing: false
    is_pull_over: false
    is_extend_lane_bounds_to_include_adc: false
    pull_over_destination_to_adc_buffer: 25.0
    pull_over_destination_to_pathend_buffer: 4.0
    pull_over_road_edge_buffer: 0.15
    pull_over_approach_lon_distance_adjust_factor: 1.5
  }
}

modules/planning/proto/task_config.proto中也有相关参数

// PathBoundsDeciderConfig

message PathBoundsDeciderConfig {
  optional bool is_lane_borrowing = 1;
  optional bool is_pull_over = 2;
  // not search pull-over position if the destination is within this distance
  // from ADC
  optional double pull_over_destination_to_adc_buffer = 3 [default = 25.0];
  // not search pull-over position if the destination is within this distance to
  // path-end
  optional double pull_over_destination_to_pathend_buffer = 4 [default = 10.0];
  // disquality a pull-over position if the available path boundary's edge is
  // not within this distance from the road edge
  optional double pull_over_road_edge_buffer = 5 [default = 0.15];
  optional double pull_over_approach_lon_distance_adjust_factor = 6
      [default = 1.5];
  optional double adc_buffer_coeff = 7 [default = 1.0];
  optional bool is_extend_lane_bounds_to_include_adc = 8 [default = true];
}

数据结构

// modules/planning/tasks/deciders/path_bounds_decider/path_bounds_decider.cc
namespace {
// PathBoundPoint contains: (s, l_min, l_max).路径边界点
using PathBoundPoint = std::tuple<double, double, double>;
// PathBound contains a vector of PathBoundPoints.路径边界
using PathBound = std::vector<PathBoundPoint>;
// ObstacleEdge contains: (is_start_s, s, l_min, l_max, obstacle_id).障碍物的边
using ObstacleEdge = std::tuple<int, double, double, double, std::string>;
}  // namespace

参数设置

// modules/planning/tasks/deciders/path_bounds_decider/path_bounds_decider.h
// s方向的距离
constexpr double kPathBoundsDeciderHorizon = 100.0;
// s方向的间隔
constexpr double kPathBoundsDeciderResolution = 0.5;
// Lane宽度
constexpr double kDefaultLaneWidth = 5.0;
// Road的道路
constexpr double kDefaultRoadWidth = 20.0;
// TODO(all): Update extra tail point base on vehicle speed.
constexpr int kNumExtraTailBoundPoint = 20;
constexpr double kPulloverLonSearchCoeff = 1.5;
constexpr double kPulloverLatSearchCoeff = 1.25;

PATH_BOUNDS_DECIDER总体流程

总体流程依然先看Process部分
在这里插入图片描述
在Process方法中，分四种场景对路径边界进行计算，按照处理的顺序分别是：fallback，pull-over，lane-change，regular。其中regular场景根据是否借道又分为LEFT_BORROW, NO_BORROW, RIGHT_BORROW。

fallback场景的path bounds一定会生成，另外三种看情况，都是需要if判断。

InitPathBoundsDecider

InitPathBoundsDecider初始化planning_start_point、获取ADC S/L坐标信息、获取ADC当前所在的车道线宽度。

void PathBoundsDecider::InitPathBoundsDecider(
    const Frame& frame, const ReferenceLineInfo& reference_line_info) {
  const ReferenceLine& reference_line = reference_line_info.reference_line();
  common::TrajectoryPoint planning_start_point = frame.PlanningStartPoint();
  if (FLAGS_use_front_axe_center_in_path_planning) {
    planning_start_point =
        InferFrontAxeCenterFromRearAxeCenter(planning_start_point);
  }
  ADEBUG << "Plan at the starting point: x = "
         << planning_start_point.path_point().x()
         << ", y = " << planning_start_point.path_point().y()
         << ", and angle = " << planning_start_point.path_point().theta();

  // Initialize some private variables.
  // ADC s/l info.
  auto adc_sl_info = reference_line.ToFrenetFrame(planning_start_point);
  adc_frenet_s_ = adc_sl_info.first[0];
  adc_frenet_l_ = adc_sl_info.second[0];
  adc_frenet_sd_ = adc_sl_info.first[1];
  adc_frenet_ld_ = adc_sl_info.second[1] * adc_frenet_sd_;
  double offset_to_map = 0.0;
  reference_line.GetOffsetToMap(adc_frenet_s_, &offset_to_map);
  adc_l_to_lane_center_ = adc_frenet_l_ + offset_to_map;

  // ADC's lane width.
  double lane_left_width = 0.0;
  double lane_right_width = 0.0;
  if (!reference_line.GetLaneWidth(adc_frenet_s_, &lane_left_width,
                                   &lane_right_width)) {
    AWARN << "Failed to get lane width at planning start point.";
    adc_lane_width_ = kDefaultLaneWidth;
  } else {
    adc_lane_width_ = lane_left_width + lane_right_width;
  }
}

1. fallback

无论当前处于何种场景，都会调用GenerateFallbackPathBound() 来生成备用的path bound，在计算FallbackPathBound时不考虑障碍物边界，仅使用道路边界，并考虑借道信息来进行计算。
在这里插入图片描述
fallback部分主要包含两个函数，InitPathBoundary 和GetBoundaryFromLanesAndADC。fallback是备选的方案，只考虑adc信息和静态道路信息。

GenerateFallbackPathBound

Status PathBoundsDecider::GenerateFallbackPathBound(
    const ReferenceLineInfo& reference_line_info, PathBound* const path_bound) {
  // 1. Initialize the path boundaries to be an indefinitely large area.
  if (!InitPathBoundary(reference_line_info, path_bound)) {...
  // PathBoundsDebugString(*path_bound);

  // 2. Decide a rough boundary based on lane info and ADC's position
  std::string dummy_borrow_lane_type;
  if (!GetBoundaryFromLanesAndADC(reference_line_info,
                                  LaneBorrowInfo::NO_BORROW, 0.5, path_bound,
                                  &dummy_borrow_lane_type, true)) {...
  // PathBoundsDebugString(*path_bound);
  ADEBUG << "Completed generating fallback path boundaries.";
  return Status::OK();
}

InitPathBoundary

InitPathBoundary从adc当前位置开始，以0.5m为间隔取点，直到终点，将 [左, 右] 边界设置为double的 [lowerst, max]。

bool PathBoundsDecider::InitPathBoundary(
  ...
  // Starting from ADC's current position, increment until the horizon, and
  // set lateral bounds to be infinite at every spot.
  // 从adc当前位置开始，以0.5m为间隔取点，直到终点，将 [左, 右] 边界设置为double的 [lowerst, max]
  for (double curr_s = adc_frenet_s_;
       curr_s < std::fmin(adc_frenet_s_ +
                              std::fmax(kPathBoundsDeciderHorizon,
                                        reference_line_info.GetCruiseSpeed() *
                                            FLAGS_trajectory_time_length),
                          reference_line.Length());
       curr_s += kPathBoundsDeciderResolution) {
    path_bound->emplace_back(curr_s, std::numeric_limits<double>::lowest(),
                             std::numeric_limits<double>::max());
  }
...}

GetBoundaryFromLanesAndADC

GetBoundaryFromLanesAndADC首先获取当前车道的宽度；再根据是否发生借道的决策，获取相邻车道的宽度（包括对向车道以及同向相邻车道）；再根据ADC的位置和速度计算边界；最后更新边界。

// TODO(jiacheng): this function is to be retired soon.
bool PathBoundsDecider::GetBoundaryFromLanesAndADC(
  ...
  for (size_t i = 0; i < path_bound->size(); ++i) {
    double curr_s = std::get<0>((*path_bound)[i]);
    // 1. Get the current lane width at current point.获取当前点车道的宽度
    if (!reference_line.GetLaneWidth(curr_s, &curr_lane_left_width,
                                     &curr_lane_right_width)) {
      AWARN << "Failed to get lane width at s = " << curr_s;
      curr_lane_left_width = past_lane_left_width;
      curr_lane_right_width = past_lane_right_width;
    } else {...}

    // 2. Get the neighbor lane widths at the current point.获取当前点相邻车道的宽度
    double curr_neighbor_lane_width = 0.0;
    if (CheckLaneBoundaryType(reference_line_info, curr_s, lane_borrow_info)) {
      hdmap::Id neighbor_lane_id;
      if (lane_borrow_info == LaneBorrowInfo::LEFT_BORROW) {
        // 借左车道
        ...
      } else if (lane_borrow_info == LaneBorrowInfo::RIGHT_BORROW) {
        // 借右车道
        ...
      }
    }

    // 3. 根据道路宽度，adc的位置和速度计算合适的边界。
    static constexpr double kMaxLateralAccelerations = 1.5;
    double offset_to_map = 0.0;
    reference_line.GetOffsetToMap(curr_s, &offset_to_map);

    double ADC_speed_buffer = (adc_frenet_ld_ > 0 ? 1.0 : -1.0) *
                              adc_frenet_ld_ * adc_frenet_ld_ /
                              kMaxLateralAccelerations / 2.0;
    // 向左车道借到，左边界会变成左侧车道左边界
    double curr_left_bound_lane =
        curr_lane_left_width + (lane_borrow_info == LaneBorrowInfo::LEFT_BORROW
                                    ? curr_neighbor_lane_width
                                    : 0.0);
    // 和上面类似
    double curr_right_bound_lane =
        -curr_lane_right_width -
        (lane_borrow_info == LaneBorrowInfo::RIGHT_BORROW
             ? curr_neighbor_lane_width
             : 0.0);

    double curr_left_bound = 0.0;  // 左边界
    double curr_right_bound = 0.0;  // 右边界
    // 计算左边界和右边界
    if (config_.path_bounds_decider_config()
            .is_extend_lane_bounds_to_include_adc() ||
        is_fallback_lanechange) {
      // extend path bounds to include ADC in fallback or change lane path
      // bounds.
      double curr_left_bound_adc =
          std::fmax(adc_l_to_lane_center_,
                    adc_l_to_lane_center_ + ADC_speed_buffer) +
          GetBufferBetweenADCCenterAndEdge() + ADC_buffer;
      curr_left_bound =
          std::fmax(curr_left_bound_lane, curr_left_bound_adc) - offset_to_map;

      double curr_right_bound_adc =
          std::fmin(adc_l_to_lane_center_,
                    adc_l_to_lane_center_ + ADC_speed_buffer) -
          GetBufferBetweenADCCenterAndEdge() - ADC_buffer;
      curr_right_bound =
          std::fmin(curr_right_bound_lane, curr_right_bound_adc) -
          offset_to_map;
    } else {
      curr_left_bound = curr_left_bound_lane - offset_to_map;
      curr_right_bound = curr_right_bound_lane - offset_to_map;
    }

    // 4. 更新边界.
    if (!UpdatePathBoundaryWithBuffer(i, curr_left_bound, curr_right_bound,
                                      path_bound, is_left_lane_boundary,
                                      is_right_lane_boundary)) {
      path_blocked_idx = static_cast<int>(i);
    }
... }

PS:
涉及到的几个参数：
（1）ADC_speed_buffer，我的理解是车辆以最大横向加速度将横向速度降为0所经过的距离。 $lat=\frac {{V_{lat}}^2} {2a}$

    double ADC_speed_buffer = (adc_frenet_ld_ > 0 ? 1.0 : -1.0) *
                              adc_frenet_ld_ * adc_frenet_ld_ /
                              kMaxLateralAccelerations / 2.0;

(2) curr_left_bound_lane、curr_right_bound_lane基于车道线的左右边界，如果产生变道，则加上相邻车道的宽度。

    double curr_left_bound_lane =
        curr_lane_left_width + (lane_borrow_info == LaneBorrowInfo::LEFT_BORROW
                                    ? curr_neighbor_lane_width
                                    : 0.0);

    double curr_right_bound_lane =
        -curr_lane_right_width -
        (lane_borrow_info == LaneBorrowInfo::RIGHT_BORROW
             ? curr_neighbor_lane_width
             : 0.0);

（3）curr_left_bound_adc基于自车产生的边界。根据ADC_speed_buffer，ADC_buffer（0.5，可以认为是横向安全区间）,半车宽，adc_l_to_lane_center_（自车相对于车道中心的偏移量）计算。

      double curr_left_bound_adc =
          std::fmax(adc_l_to_lane_center_,
                    adc_l_to_lane_center_ + ADC_speed_buffer) +
          GetBufferBetweenADCCenterAndEdge() + ADC_buffer;

计算示意图大致如下：
在这里插入图片描述
（4）offset_to_map：相对地图的偏移量。

UpdatePathBoundaryWithBuffer

UpdatePathBoundaryWithBuffer首先计算缓冲边界（实际意义就是将左右边界各收缩半个车宽），若(l_min > l_max)，即右边界大于左边界，则发生block，不更新。

bool PathBoundsDecider::UpdatePathBoundaryWithBuffer(
    size_t idx, double left_bound, double right_bound,
    PathBound* const path_boundaries, bool is_left_lane_bound,
    bool is_right_lane_bound) {
  // substract vehicle width when bound does not come from the lane boundary
  // 计算缓冲边界，默认是1.0
  const double default_adc_buffer_coeff = 1.0;
  double left_adc_buffer_coeff =
      (is_left_lane_bound
           ? config_.path_bounds_decider_config().adc_buffer_coeff()
           : default_adc_buffer_coeff);
  double right_adc_buffer_coeff =
      (is_right_lane_bound
           ? config_.path_bounds_decider_config().adc_buffer_coeff()
           : default_adc_buffer_coeff);

  // Update the right bound (l_min):
  double new_l_min =
      std::fmax(std::get<1>((*path_boundaries)[idx]),
                right_bound + right_adc_buffer_coeff *
                                  GetBufferBetweenADCCenterAndEdge());
  // Update the left bound (l_max):
  double new_l_max = std::fmin(
      std::get<2>((*path_boundaries)[idx]),
      left_bound - left_adc_buffer_coeff * GetBufferBetweenADCCenterAndEdge());

  // Check if ADC is blocked.
  // If blocked, don't update anything, return false.
  if (new_l_min > new_l_max) {
    ADEBUG << "Path is blocked at idx = " << idx;
    return false;
  }
  // Otherwise, update path_boundaries and center_line; then return true.
  std::get<1>((*path_boundaries)[idx]) = new_l_min;
  std::get<2>((*path_boundaries)[idx]) = new_l_max;
  return true;
}

TrimPathBounds

TrimPathBounds截断block之后的边界点。

2. pull over

在这里插入图片描述

GeneratePullOverPathBound

核心逻辑在GeneratePullOverPathBound中。
InitPathBoundary在fallback部分已经讨论过了，接着来看GetBoundaryFromRoads。

GetBoundaryFromRoads

GetBoundaryFromRoads主要完成：获取道路边界；更新道路边界；裁剪block之后的边界点。

GetBoundaryFromRoads根据道路信息确定一个大致的边界。返回的边界是相对于车道中心（而不是reference_line）的，尽管在大多数情况下reference_line与车道中心的偏差可以忽略不计。

UpdatePullOverBoundaryByLaneBoundary

之后调用UpdatePullOverBoundaryByLaneBoundary更新pull over的边界。pull over有两种状态：PULL_OVER和EMERGENCY_PULL_OVER。
对于PULL_OVER，选取车道左边界作为边界。对于EMERGENCY_PULL_OVER，选取左/右车道边界作为边界，因为可能会在对向车道停车。

GetBoundaryFromStaticObstacles

根据静态障碍物对边界进行调整。它将确保边界不包含任何静态障碍，这样之后优化时生成的路径就不会与任何静态障碍碰撞。

在这里插入图片描述

SearchPullOverPosition

它的目的是搜索停车点，为了能够容纳车的尺寸，因为要先搜索可以停车的区域，然后在该区域内取一点作为停车点。搜索区域时，要先确定一个端点，然后向前或向后考察另一个端点，以及考察两端点之间的区域是否符合要求。

搜索pull over位置的过程：

根据pull_over_status.pull_over_type()判断是前向搜索（pull
over开头第一个点），还是后向搜索（pull over末尾后一个点）
两层循环，外层控制搜索的索引idx，内层控制进一步的索引（前向idx+1，后向idx-1）。
根据内外两层循环的索引，判断搜索到的空间是否满足宽度和长度要求，判断是否可以pull over

bool PathBoundsDecider::SearchPullOverPosition(
    const Frame& frame, const ReferenceLineInfo& reference_line_info,
    const std::vector<std::tuple<double, double, double>>& path_bound,
    std::tuple<double, double, double, int>* const pull_over_configuration) {
  const auto& pull_over_status =
      injector_->planning_context()->planning_status().pull_over();

  // 搜索方向，默认前向搜索
  bool search_backward = false;  // search FORWARD by default

  double pull_over_s = 0.0;
  if (pull_over_status.pull_over_type() ==
      PullOverStatus::EMERGENCY_PULL_OVER) {...}

  int idx = 0;
  if (search_backward) {
    // 后向搜索，定位pull over末尾的一个点.
    idx = static_cast<int>(path_bound.size()) - 1;
    while (idx >= 0 && std::get<0>(path_bound[idx]) > pull_over_s) {
      --idx;
    }
  } else {
    // 前向搜索，定位emergency pull over开头后的第一个点.
    while (idx < static_cast<int>(path_bound.size()) &&
           std::get<0>(path_bound[idx]) < pull_over_s) {
      ++idx;
    }
  }
  
  // 为pull over搜索到一个可行的位置，主要是确定该区域的宽度和长度
  const double pull_over_space_length =
      kPulloverLonSearchCoeff *
          VehicleConfigHelper::GetConfig().vehicle_param().length() -
      FLAGS_obstacle_lon_start_buffer - FLAGS_obstacle_lon_end_buffer;
  const double pull_over_space_width =
      (kPulloverLatSearchCoeff - 1.0) *
      VehicleConfigHelper::GetConfig().vehicle_param().width();
  const double adc_half_width =
      VehicleConfigHelper::GetConfig().vehicle_param().width() / 2.0;

  // 2. Find a window that is close to road-edge.
  /*
    这里用了内外两层循环进行搜索，外层循环控制搜索的开始的端点idx。
    内层控制另一个端点。根据找到的两个端点，判断区域是否可以pull over
  */
  bool has_a_feasible_window = false;
  while ((search_backward && idx >= 0 &&
          std::get<0>(path_bound[idx]) - std::get<0>(path_bound.front()) >
              pull_over_space_length) ||
         (!search_backward && idx < static_cast<int>(path_bound.size()) &&
          std::get<0>(path_bound.back()) - std::get<0>(path_bound[idx]) >
              pull_over_space_length)) {

    while ((search_backward && j >= 0 &&
            std::get<0>(path_bound[idx]) - std::get<0>(path_bound[j]) <
                pull_over_space_length) ||
           (!search_backward && j < static_cast<int>(path_bound.size()) &&
            std::get<0>(path_bound[j]) - std::get<0>(path_bound[idx]) <
                pull_over_space_length)) {...}
    
    // 找到可行区域，获取停车区域的位置和姿态
    if (is_feasible_window) {
    ...
    break;}
    ...}  // 外层while
...
}

3. lane change

在这里插入图片描述
核心逻辑在GenerateLaneChangePathBound函数中，与前面的场景计算流程大同小异。主要核心部分在GetBoundaryFromLaneChangeForbiddenZone部分。

GenerateLaneChangePathBound

Status PathBoundsDecider::GenerateLaneChangePathBound(
    const ReferenceLineInfo& reference_line_info,
    std::vector<std::tuple<double, double, double>>* const path_bound) {
  // 1.初始化，和前面的步骤类似
  if (!InitPathBoundary(reference_line_info, path_bound)) {...}


  // 2. 根据道路和adc的信息获取一个大致的路径边界
  std::string dummy_borrow_lane_type;
  if (!GetBoundaryFromLanesAndADC(reference_line_info,
                                  LaneBorrowInfo::NO_BORROW, 0.1, path_bound,
                                  &dummy_borrow_lane_type, true)) {...}
 

  // 3. Remove the S-length of target lane out of the path-bound.
  GetBoundaryFromLaneChangeForbiddenZone(reference_line_info, path_bound);


  // 根据静态障碍物调整边界.
  if (!GetBoundaryFromStaticObstacles(reference_line_info.path_decision(),
                                      path_bound, &blocking_obstacle_id)) {...}
  ...
}

GetBoundaryFromLaneChangeForbiddenZone

GetBoundaryFromLaneChangeForbiddenZone函数运行流程如下：

如果当前位置可以变道，则直接变道
如果有一个lane-change的起点，则直接使用它
逐个检查变道前的点的边界，改变边界的值（如果已经过了变道点，则返回）

void PathBoundsDecider::GetBoundaryFromLaneChangeForbiddenZone(
    const ReferenceLineInfo& reference_line_info, PathBound* const path_bound) {
  // Sanity checks.
  CHECK_NOTNULL(path_bound);
  const ReferenceLine& reference_line = reference_line_info.reference_line();

  // If there is a pre-determined lane-change starting position, then use it;
  // otherwise, decide one.
  auto* lane_change_status = injector_->planning_context()
                                 ->mutable_planning_status()
                                 ->mutable_change_lane();
  // 1.当前位置直接变道。
  if (lane_change_status->is_clear_to_change_lane()) {
    ADEBUG << "Current position is clear to change lane. No need prep s.";
    lane_change_status->set_exist_lane_change_start_position(false);
    return;
  }
  double lane_change_start_s = 0.0;
  // 2.如果已经有一个lane-change的起点，就直接使用它，否则再找一个
  if (lane_change_status->exist_lane_change_start_position()) {
    common::SLPoint point_sl;
    reference_line.XYToSL(lane_change_status->lane_change_start_position(),
                          &point_sl);
    lane_change_start_s = point_sl.s();
  } else {
    // TODO(jiacheng): train ML model to learn this.
    // 设置为adc前方一段距离为变道起始点
    lane_change_start_s = FLAGS_lane_change_prepare_length + adc_frenet_s_;
    
    // Update the decided lane_change_start_s into planning-context.
    // 更新变道起始点的信息
    common::SLPoint lane_change_start_sl;
    lane_change_start_sl.set_s(lane_change_start_s);
    lane_change_start_sl.set_l(0.0);
    common::math::Vec2d lane_change_start_xy;
    reference_line.SLToXY(lane_change_start_sl, &lane_change_start_xy);
    lane_change_status->set_exist_lane_change_start_position(true);
    lane_change_status->mutable_lane_change_start_position()->set_x(
        lane_change_start_xy.x());
    lane_change_status->mutable_lane_change_start_position()->set_y(
        lane_change_start_xy.y());
  }

  // Remove the target lane out of the path-boundary, up to the decided S.
  if (lane_change_start_s < adc_frenet_s_) {
    // If already passed the decided S, then return.
    // lane_change_status->set_exist_lane_change_start_position(false);
    return;
  }
  // 逐个检查变道前的点的边界，改变边界的值
  for (size_t i = 0; i < path_bound->size(); ++i) {
    double curr_s = std::get<0>((*path_bound)[i]);
    if (curr_s > lane_change_start_s) {
      break;
    }
    double curr_lane_left_width = 0.0;
    double curr_lane_right_width = 0.0;
    double offset_to_map = 0.0;
    reference_line.GetOffsetToMap(curr_s, &offset_to_map);
    if (reference_line.GetLaneWidth(curr_s, &curr_lane_left_width,
                                    &curr_lane_right_width)) {
      double offset_to_lane_center = 0.0;
      reference_line.GetOffsetToMap(curr_s, &offset_to_lane_center);
      curr_lane_left_width += offset_to_lane_center;
      curr_lane_right_width -= offset_to_lane_center;
    }
    curr_lane_left_width -= offset_to_map;
    curr_lane_right_width += offset_to_map;

    std::get<1>((*path_bound)[i]) =
        adc_frenet_l_ > curr_lane_left_width   //右变道已跨过车道线，设定右界限
            ? curr_lane_left_width + GetBufferBetweenADCCenterAndEdge()
            : std::get<1>((*path_bound)[i]);
    std::get<1>((*path_bound)[i]) =
        std::fmin(std::get<1>((*path_bound)[i]), adc_frenet_l_ - 0.1);
    std::get<2>((*path_bound)[i]) =
        adc_frenet_l_ < -curr_lane_right_width
            ? -curr_lane_right_width - GetBufferBetweenADCCenterAndEdge()
            : std::get<2>((*path_bound)[i]);  //左变道已跨过车道线，设定左界限
    std::get<2>((*path_bound)[i]) =
        std::fmax(std::get<2>((*path_bound)[i]), adc_frenet_l_ + 0.1);
  }
}

PS：变道时是以相邻车道的参考线作为参考线。以向右变道为例，变道前（指跨过车道线线前adc_frenet_l_ > curr_lane_left_width），使用原先的path bound，不给右侧留空间；变道之后，再进行更新。

4. regular

在这里插入图片描述
代码流程如下：

Status PathBoundsDecider::GenerateRegularPathBound(
    const ReferenceLineInfo& reference_line_info,
    const LaneBorrowInfo& lane_borrow_info, PathBound* const path_bound,
    std::string* const blocking_obstacle_id,
    std::string* const borrow_lane_type) {
  // 1.初始化边界.
  if (!InitPathBoundary(reference_line_info, path_bound)) {...}


  // 2.根据adc位置和lane信息确定大致的边界
  if (!GetBoundaryFromLanesAndADC(reference_line_info, lane_borrow_info, 0.1,
                                  path_bound, borrow_lane_type)) {...}
  // PathBoundsDebugString(*path_bound);

  // 3.根据障碍物调整道路边界
  if (!GetBoundaryFromStaticObstacles(reference_line_info.path_decision(),
                                      path_bound, blocking_obstacle_id)) {...}
  ...
}

流程和上面的几个基本类似，借道有三种类型

  enum class LaneBorrowInfo {
    LEFT_BORROW,
    NO_BORROW,
    RIGHT_BORROW,
  };

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