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本篇文章给大家分享的是有关如何进行 Planning 模块源代码分析，丸趣 TV 小编觉得挺实用的，因此分享给大家学习，希望大家阅读完这篇文章后可以有所收获，话不多说，跟着丸趣 TV 小编一起来看看吧。
规划（Planning）模块位于命名空间：apollo::planning，其作用在于构建无人车从起点到终点的局部行驶路径，具体而言，就是给定导航地图、导航路径、当前定位点、车辆状态、周边目标的感知及预测信息，规划模块计算出可供控制模块执行的一条安全且舒适的行驶路径。
规划模块输出的路径是局部路径而非全局路径。举例，如无人车需从长沙智能驾驶研究院行驶至长沙高铁南站，首先需借助 Routing 模块输出全局导航路径，接下来才是规划模块基于全局导航路径进行一小段、一小段具体行驶路径的规划。
规划模块的作用是根据感知预测的结果，当前的车辆信息和路况规划出一条车辆能够行驶的轨迹，这个轨迹会交给控制模块，控制模块通过油门，刹车和方向盘使得车辆按照规划的轨迹运行。
前言
规划模块的轨迹是短期轨迹，即车辆短期内行驶的轨迹，长期轨迹是 Routing 模块规划出的导航轨迹，即起点到目的地的轨迹，规划模块会先生成导航轨迹，然后根据导航轨迹和路况的情况，沿着短期轨迹行驶，直到目的地。
规划模块内部结构及其与其他模块的交互示意如下图所示。
模块主入口
根据各功能模块的启动过程的分析，Planning 模块的主入口为：
int main(int argc, char** argv) {
2 google::SetUsageMessage( we use this program to load dag and run user apps.
3
4 // parse the argument
5 ModuleArgument module_args;
6 module_args.ParseArgument(argc, argv);
7
8 // initialize cyber
9 apollo::cyber::Init(argv[0]);
11 // start module
12 ModuleController controller(module_args);
13 if (!controller.Init()) {14 controller.Clear();
15 AERROR module start error.
16 return -1;
17 }
19 apollo::cyber::WaitForShutdown();
20 controller.Clear();
21 AINFO exit mainboard.
23 return 0;
24}Main 函数十分简单，首先是解析参数，初始化 Cyber 环境，接下来创建一个 ModuleController 类对象 controller，之后调用 controller.Init() 启动相关功能模块。进入 Cyber RT 的消息循环，等待 cyber::WaitForShutdown() 返回，清理资源并退出 Main 函数。ModuleController::Init() 函数内部调用了 ModuleController::LoadAll() 函数：
1bool ModuleController::LoadAll() { 2 const std::string work_root = common::WorkRoot();
3 const std::string current_path = common::GetCurrentPath();
4 const std::string dag_root_path = common::GetAbsolutePath(work_root, dag
5
6 for (auto dag_conf : args_.GetDAGConfList()) {
7 std::string module_path =
8 if (dag_conf == common::GetFileName(dag_conf)) {
9 // case dag conf argument var is a filename
10 module_path = common::GetAbsolutePath(dag_root_path, dag_conf);
11 } else if (dag_conf[0] == / ) {
12 // case dag conf argument var is an absolute path
13 module_path = dag_conf;
14 } else {
15 // case dag conf argument var is a relative path
16 module_path = common::GetAbsolutePath(current_path, dag_conf);
17 if (!common::PathExists(module_path)) {18 module_path = common::GetAbsolutePath(work_root, dag_conf);
19 }
20 }
21 AINFO Start initialize dag:
上述函数处理一个 dag_conf 配置文件循环，读取配置文件中的所有 dag_conf，并逐一调用 bool ModuleController::LoadModule(const std::string path) 函数加载功能模块。
对象的创建过程
进一步展开：
1#define CLASS_LOADER_REGISTER_CLASS_INTERNAL(Derived, Base, UniqueID) \
2 namespace { \
3 struct ProxyType##UniqueID { \
4 ProxyType##UniqueID() { \
5 apollo::cyber::class_loader::utility::RegisterClass( \
6 #Derived, #Base); \
7 } \
8 }; \
9 static ProxyType##UniqueID g_register_class_##UniqueID; \
10 }将 PlanningComponent 代入，最终得到：
1 namespace {
2 struct ProxyType__COUNTER__ {
3 ProxyType__COUNTER__() {
4 apollo::cyber::class_loader::utility::RegisterClass planningcomponent, apollo::cyber::componentbase (
5 PlanningComponent , apollo::cyber::ComponentBase
6 }
7 };
8 static ProxyType__COUNTER__ g_register_class___COUNTER__;
9 }
/planningcomponent, apollo::cyber::componentbase创建一个模板类 utility::ClassFactory derived, base= /derived, 对象 new_class_factrory_obj，为其添加类加载器，设置加载库的路径，将工厂类对象加入到 ClassClassFactoryMap 对象 factory_map 统一管理。通过该函数，Cyber 使用工厂方法模式完成产品类对象的创建：
动态创建过程
第一部分介绍模块主入口时，提及 bool ModuleController::LoadModule(const std::string path) 函数，正是该函数动态创建出了 apollo::planning::PlanningComponent 类对象。
函数内部调用分析如下：
1bool ModuleController::LoadModule(const std::string path) {
2 DagConfig dag_config;
3 if (!common::GetProtoFromFile(path, dag_config)) {4 AERROR Get proto failed, file: 上述函数从磁盘配置文件读取配置信息，并调用 bool ModuleController::LoadModule(const DagConfig dag_config) 函数加载功能模块：
1bool ModuleController::LoadModule(const DagConfig dag_config) { 2 const std::string work_root = common::WorkRoot();
3
4 for (auto module_config : dag_config.module_config()) {
5 std::string load_path;
6 // ...
7 class_loader_manager_.LoadLibrary(load_path);
8 for (auto component : module_config.components()) { 9 const std::string class_name = component.class_name();
10 std::shared_ptr base =
11 class_loader_manager_.CreateClassObj(class_name);
12 if (base == nullptr) {
13 return false;
14 }
16 if (!base- Initialize(component.config())) {
17 return false;
18 }
19 component_list_.emplace_back(std::move(base));
20 }
22 // ...
23 }
24 return true;
25}
工厂类对象指针找到后，使用 classobj = factory- CreateObj(); 就顺理成章地将 PlanningComponent 类对象创建出来了。
具体规划算法分析
PublicRoadPlanner 规划算法
PublicRoadPlanner 算法从 Routing 模块输出的高精地图 Lane 序列获得全局导航路径。
基于场景、阶段和任务的理念进行规划，优点是能合理有效地应对每种场景，易于扩充，并且基于配置文件动态增减场景、阶段及使用的任务，灵活性强；缺点是可能会遗漏一些特殊场景，但可通过不断扩充新的场景加以解决。
该算法的主要执行流程如下：
可借助 GDB 调试命令对上述执行流程进行更为深入的理解，例如 TrafficLightProtectedStageApproach 阶段的 PathLaneBorrowDecider 任务的调用堆栈，从下往上看，对于任意一个任务的调用流程一目了然：
#0 apollo::planning::PathLaneBorrowDecider::Process (this=0x7f8c28294460, frame=0x7f8c38029f70,
2 reference_line_info=0x7f8c3802b140) at modules/planning/tasks/deciders/path_lane_borrow_decider/path_lane_borrow_decider.cc:39
3#1 0x00007f8c0468b7c8 in apollo::planning::Decider::Execute (this=0x7f8c28294460, frame=0x7f8c38029f70,
4 reference_line_info=0x7f8c3802b140) at modules/planning/tasks/deciders/decider.cc:31
5#2 0x00007f8c065c4a01 in apollo::planning::scenario::Stage::ExecuteTaskOnReferenceLine (this=0x7f8c28293eb0,
6 planning_start_point=..., frame=0x7f8c38029f70) at modules/planning/scenarios/stage.cc:96
7#3 0x00007f8c06e721da in apollo::planning::scenario::traffic_light::TrafficLightProtectedStageApproach::Process ( 8 this=0x7f8c28293eb0, planning_init_point=..., frame=0x7f8c38029f70) at
9 modules/planning/scenarios/traffic_light/protected/stage_approach.cc:48
10#4 0x00007f8c067f1732 in apollo::planning::scenario::Scenario::Process (11 this=0x7f8c2801bf20, planning_init_point=..., frame=0x7f8c38029f70)
12 at modules/planning/scenarios/scenario.cc:76
13#5 0x00007f8c186e153a in apollo::planning::PublicRoadPlanner::Plan (
14 this=0x23093de0, planning_start_point=..., frame=0x7f8c38029f70,
15 ptr_computed_trajectory=0x7f8b9a5fbed0) at modules/planning/planner/public_road/public_road_planner.cc:51
16#6 0x00007f8c19ee5937 in apollo::planning::OnLanePlanning::Plan (
17 this=0x237f3b0, current_time_stamp=1557133995.3679764, stitching_trajectory=std::vector of length 1,
18 capacity 1 = {...}, ptr_trajectory_pb=0x7f8b9a5fbed0) at modules/planning/on_lane_planning.cc:436
19#7 0x00007f8c19ee40fa in apollo::planning::OnLanePlanning::RunOnce (20 this=0x237f3b0, local_view=..., ptr_trajectory_pb=0x7f8b9a5fbed0) at modules/planning/on_lane_planning.cc:304
21#8 0x00007f8c1ab0d494 in apollo::planning::PlanningComponent::Proc (22 this=0x1d0f310, prediction_obstacles=std::shared_ptr (count 4, weak 0) 0x7f8b840164f8,
23 chassis=std::shared_ptr (count 4, weak 0) 0x7f8b84018a08,
24 localization_estimate=std::shared_ptr (count 4, weak 0) 0x7f8b8400d3b8) at modules/planning/planning_component.cc:134
25#9 0x00007f8c1abb46c4 in apollo::cyber::Component apollo::prediction::predictionobstacles, span=
26 apollo::canbus::Chassis, apollo::localization::LocalizationEstimate, apollo::cyber::NullType ::Process (this=0x1d0f310,
27 msg0=std::shared_ptr (count 4, weak 0) 0x7f8b840164f8, msg1=std::shared_ptr (count 4, weak 0) 0x7f8b84018a08,
28 msg2=std::shared_ptr (count 4, weak 0) 0x7f8b8400d3b8) at ./cyber/component/component.h:291
29#10 0x00007f8c1aba2698 in apollo::cyber::Component apollo::prediction::predictionobstacles, span=
30 apollo::canbus::Chassis, apollo::localization::LocalizationEstimate, apollo::cyber::NullType ::Initialize(31 apollo::cyber::proto::ComponentConfig const)::{lambda(std::shared_ptr apollo::prediction::predictionobstacles const ,
32 std::shared_ptr const , std::shared_ptr apollo::localization::localizationestimate const )#2}::operator()
33 (std::shared_ptr apollo::prediction::predictionobstacles const , std::shared_ptr const ,
34 std::shared_ptr apollo::localization::localizationestimate const ) const (__closure=0x2059a430,
35 msg0=std::shared_ptr (count 4, weak 0) 0x7f8b840164f8, msg1=std::shared_ptr (count 4, weak 0) 0x7f8b84018a08,
36 msg2=std::shared_ptr (count 4, weak 0) 0x7f8b8400d3b8) at ./cyber/component/component.h:378
37#11 0x00007f8c1abb4ad2 in apollo::cyber::croutine::RoutineFactory apollo::cyber::croutine::CreateRoutineFactory
38 apollo::prediction::predictionobstacles, apollo::canbus::chassis, apollo::localization::localizationestimate,
39 apollo::cyber::Component apollo::prediction::predictionobstacles, apollo::canbus::chassis,
40 apollo::localization::LocalizationEstimate, apollo::cyber::NullType ::Initialize(41 apollo::cyber::proto::ComponentConfig const)::{lambda(std::shared_ptr apollo::prediction::predictionobstacles const ,
42 std::shared_ptr const , std::shared_ptr apollo::localization::localizationestimate const )#2}
43 (apollo::cyber::Component apollo::prediction::predictionobstacles, apollo::canbus::chassis,
44 apollo::localization::LocalizationEstimate, apollo::cyber::NullType ::Initialize(apollo::cyber::proto::ComponentConfig const)::
45 {lambda(std::shared_ptr apollo::prediction::predictionobstacles const , std::shared_ptr const ,
46 std::shared_ptr apollo::localization::localizationestimate const )#2} ,
47 std::shared_ptr apollo::cyber::data::datavisitor apollo::prediction::predictionobstacles,
48 apollo::canbus::Chassis, apollo::localization::LocalizationEstimate, apollo::cyber::NullType const )::
49 {lambda()#1}::operator()() const::{lambda()#1}::operator()() const (__closure=0x2059a420) at ./cyber/croutine/routine_factory.h:108
50#12 0x00007f8c1ac0466a in std::_Function_handler void (), apollo::cyber::croutine::routinefactory span=
51apollo::cyber::croutine::CreateRoutineFactory apollo::prediction::predictionobstacles, apollo::canbus::chassis, apollo::localization::localizationestimate,
52apollo::cyber::Component apollo::prediction::predictionobstacles, apollo::canbus::chassis, apollo::localization::localizationestimate,
53apollo::cyber::NullType ::Initialize(apollo::cyber::proto::ComponentConfig const)::{lambda(std::shared_ptr apollo::prediction::predictionobstacles const ,
54std::shared_ptr const , std::shared_ptr apollo::localization::localizationestimate const )#2}
55(apollo::cyber::Component apollo::prediction::predictionobstacles, apollo::canbus::chassis, apollo::localization::localizationestimate,
56apollo::cyber::NullType ::Initialize(apollo::cyber::proto::ComponentConfig const)::{lambda(std::shared_ptr apollo::prediction::predictionobstacles const ,
57std::shared_ptr const , std::shared_ptr apollo::localization::localizationestimate const )#2} ,
58std::shared_ptr apollo::cyber::data::datavisitor apollo::prediction::predictionobstacles, apollo::canbus::chassis, apollo::localization::localizationestimate,
59apollo::cyber::NullType const )::{lambda()#1}::operator()() const::{lambda()#1} ::_M_invoke(std::_Any_data const) (__functor=...) at
60/usr/include/c++/4.8/functional:2071
61#13 0x00007f8c5f5b86e8 in std::function::operator()() const (this=0x205f1160) at /usr/include/c++/4.8/functional:2471
62#14 0x00007f8c57560cbc in apollo::cyber::croutine::CRoutine::Run (this=0x205f1148) at ./cyber/croutine/croutine.h:143
63#15 0x00007f8c5755ff55 in apollo::cyber::croutine::(anonymous namespace)::CRoutineEntry (arg=0x205f1148) at cyber/croutine/croutine.cc:43
/apollo::cyber::data::datavisitor apollo::prediction::predictionobstacles, apollo::canbus::chassis, apollo::localization::localizationestimate,
/apollo::localization::localizationestimate /apollo::prediction::predictionobstacles /apollo::prediction::predictionobstacles, apollo::canbus::chassis, apollo::localization::localizationestimate,
/apollo::localization::localizationestimate /apollo::prediction::predictionobstacles /apollo::prediction::predictionobstacles, apollo::canbus::chassis, apollo::localization::localizationestimate,
/apollo::prediction::predictionobstacles, apollo::canbus::chassis, apollo::localization::localizationestimate,
/void (), apollo::cyber::croutine::routinefactory /apollo::cyber::data::datavisitor apollo::prediction::predictionobstacles,
/apollo::localization::localizationestimate /apollo::prediction::predictionobstacles /apollo::prediction::predictionobstacles, apollo::canbus::chassis,
/apollo::localization::localizationestimate /apollo::prediction::predictionobstacles /apollo::prediction::predictionobstacles, apollo::canbus::chassis,
/apollo::prediction::predictionobstacles, apollo::canbus::chassis, apollo::localization::localizationestimate,
/apollo::localization::localizationestimate /apollo::prediction::predictionobstacles /apollo::localization::localizationestimate /apollo::prediction::predictionobstacles /apollo::prediction::predictionobstacles, /apollo::prediction::predictionobstacles, 所有规划算法共用的流程略去不表，与 PublicRoadPlanner 规划算法相关的有两处，一处是 PublicRoadPlanner::Init，另一处是 PublicRoadPlanner::Plan。
下面来看场景更新函数 ScenarioManager::Update 的代码：
1void ScenarioManager::Update(const common::TrajectoryPoint ego_point,
2 const Frame frame) {3 CHECK(!frame.reference_line_info().empty());
4 Observe(frame);
5 ScenarioDispatch(ego_point, frame);
6}该函数包含两个子函数：ScenarioManager::Observe 和 ScenarioManager::ScenarioDispatch，其中前者用于更新 first_encountered_overlap_map_，代码如下所示：
1void ScenarioManager::Observe(const Frame frame) {
2 // init first_encountered_overlap_map_
3 first_encountered_overlap_map_.clear();
4 const auto reference_line_info = frame.reference_line_info().front();
5 const auto first_encountered_overlaps =
6 reference_line_info.FirstEncounteredOverlaps();
7 for (const auto overlap : first_encountered_overlaps) {
8 if (overlap.first == ReferenceLineInfo::PNC_JUNCTION ||
9 overlap.first == ReferenceLineInfo::SIGNAL ||
10 overlap.first == ReferenceLineInfo::STOP_SIGN ||
11 overlap.first == ReferenceLineInfo::YIELD_SIGN) {12 first_encountered_overlap_map_[overlap.first] = overlap.second;
13 }
14 }
15}以上就是如何进行 Planning 模块源代码分析，丸趣 TV 小编相信有部分知识点可能是我们日常工作会见到或用到的。希望你能通过这篇文章学到更多知识。更多详情敬请关注丸趣 TV 行业资讯频道。
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