diff --git a/.marksman.toml b/.marksman.toml new file mode 100644 index 0000000..e69de29 diff --git a/2-intelligent-transportation-system.md b/2-intelligent-transportation-system.md new file mode 100644 index 0000000..9bb1e64 --- /dev/null +++ b/2-intelligent-transportation-system.md @@ -0,0 +1,182 @@ +# Intelligent Transportation Systems + +## Introduction to ITS: A key component in smart cities + +### Variants: + + - Surface ITS + - Air transport + - Maritime + +### Methods and (information and communication) technologies (or bullshit buzzwords) + +- Fancy words used to achieve ITS, they are interconnected to each other +- Also called features (? TODO verify in tutorial) +- Smart sensing and computing + - Using mobile data + - Wearables sensing + - Vehicle based sensing +- Smart performance + - Automation + - Real-time information + - Dynamic optimization +- Smart Travel behavior + - Efficiency + - Reliability + - Safety +- Smart Infrastructure + - Active travel + - Shared travel + - Data driven +- Smart city planning and policy making + - Integrated development & Spatial planning + - Transportation & Traffic strategy + - Environment and public safety +- Multi modal systems (????) + +### Examples in Smart City Planning and Policy Making + +- Smart intersections: reduce traffic jam, allow ambulance to pass with priority +- Vehicle sharing +- Active travel aka. walking: environment friendly +- Public transport: Optimizes wait, and increases reliability + +## Reasons + +### Climate + +- Current situation: Climate changes leads to more extreme weather: + - Temperature + - Greenhouse gas emission + - Air pollution +- ITS Vehicle features helps protecting the environment (Didn't elaborate): + - Speed vs. Pollutant: finding optimum speed for least $CO_2$ + - BEV (Battery-based Electric Vehicles) vs. ICEV (Internal Combustion Engine + Vehicles): + - The emission of $CO_2$ during the life-cycle: manufacture, usage, + maintenance + - Optimizing the occupancy of public transport: the occupancy level (how + many people it holds) vs. The energy used + - $$Railways \gt Aircraft \gt Buses \gt LightVehicles$$ + +### Safety + +- Current situation: Car accidents + - Driver failed to look properly + - Driver careless, reckless or in a hurry + - Failed to judge other's speed +- ITS features can help to avoid accidents caused by drivers (Didn't elaborate) + +### Efficiency + +- Current situation: People spend a lot of time waiting for traffic jams +- ITS feature can help reduce traffic congestion (Didn't elaborate) + +### Experience / Cost + +- ITS feature can help to improve public transport experience and cost. + +## Implementation + +### Implementing ITS with information and communication technology + +#### Information needed + +- Vehicle data +- System data: infrastructure status, traffic, parking spaces +- Intelligence: insights provided by data centers or cloud servers, by mining + data from the aforementioned sources or other sources + +#### Communication needed + +- Wireless +- Mobile network +- Road Side Unit (RSU): ICT(Information and Communication Technologies) gateway + deployed by the side of the road to facilitate wireless communication with + cars. + +### Vehicle to everything: V2X + +- Four types of communications + - V2V: Vehicle to vehicle + - V2I: Vehicle to infrastructure + - V2N: Vehicle to network + - V2P: Vehicle to pedestrian +- Usage: + - Use RSU to connect to network + - Use V2I to monitor traffic + - Use V2V for safety and ADAS + - Use V2N to provide over the top cloud services + +### Data sources + +#### Smart Infrastructure: Road sensors + +- Disruptive vs Non-disruptive: + - ![sensors](./assets/2-sensors.png) + +#### Smart Vehicles: Vehicle mounted sensors + +- Radar: long range +- Camera: efficient cost and FOV +- Lidar: depth, mid range +- Ultrasonic: Low cost, short range + +#### Vulnerable Road Users (VRU): Sensors carried by VRUS + +- Road safety in cities +- Technologies: + - No tech: gesture + - Wireless tech: P2X cycle bag + - Visual tech: LED on cloth + - Control tech + +### Perception + +#### Vehicle-Road-Cloud Integration System (VRCIS) + +- Integrates with cloud: + - Local: On board, millisecond level + - Cloud: + - Edge cloud, 100 ms + - Region cloud, seconds + - Central cloud, sub-minute +- More processing the higher you go + +#### Collaborative perception + +- This is spatial only +- Based on VRCIS, has a physical layer vs. cyber layer + - Physical layer(vehicle side, road side, VRU side) provides data / + insights, and send it to + - Cyber layer(edge, region, central cloud), which generates perceptual + fusion, then send it back to + - Physical layer, to give collaborative perception +- Single Node: Perception Fusion Method + - Single view + - Multi view: many more sensors on a single node +- Multi Node: collaborative view, vehicle side and road side donate data that's + coupled together, so a cloud can have better analysis + +#### Cross domain perception: not only spatial (shape), for example also traffic flow + +##### Macroscopic traffic flow: use image, spatial and time + +##### Microscopic: use many image + +## Summary: Smart mobility (Seems important) + +- Definition: Existing Transportation systems augment with ICT. +- Intelligent vs. Smart: + - Intelligent when it offer insights and human act on these; + - Smart when it acts independently on insights in near-real time. +- Reason: + - For safer, more efficient, more environment friendly, better experience, + more inclusive, and more. +- Implementation: + - Deploy sensors in vehicles, roads, VRUs + - Allow them to communicate + - Allow them to exchange information with other infrastructure (e.g., mobile + network) + - Allow them to analyse/interpret data + - Allow them to communicate to generate collaborative knowledge diff --git a/assets/2-sensors.png b/assets/2-sensors.png new file mode 100644 index 0000000..9a83db6 Binary files /dev/null and b/assets/2-sensors.png differ