美赛2017C学习笔记

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Problem Chosen

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industry, an evaluation should be made to find out the influence on traffic when more and more non-

self-driving-vehicles(NSDV) are replaced by SDVs while few studies were done on the interactions

between SDVs and NSDVs and the cooperations among SDVs themselves.

parison of different kinds of traffic flow models in the past few decades. In order to take the re-

lationships of SDVs and NSDVs into consideration, we improve the traditional CA model which

emphasizes on status and rules of changes, by redesigning these two factors. Before building a CA

model, discretization should be done first. By learning the average length, speed, acceleration of

running vehicles on highway and the reaction time of human beings, the size of a cell and the time

information with other SDVs and the joint decision making. Specifically, we create a new conception

’SDV-Train’ to simulate the cooperations among SDVs.

we try to find out when and how should a vehicle change a lane. Two main parameters are involved

in this model: Lane-Changing Motivation (LCM) and Lane-Changing Secuirty (LCS). LCM depends

on whether changing a lane can increase the speed and LCS shows the whether it is safe when lane-

changing. Only when both LCM and LCS are satisfied, may a vehicle change its lane. Details of

these two parameters vary between SDVs and NSDVs considering the huge difference between an

automatic control system and a human driver. A two-step turning method is specially made for this

model in correspondence with the real world.

comparing the real data and the data we gain from simulations. We find that the lack of traffic

capacity in this area is huge. Although adding SDVs to the street can reduce this lack, it is not a cure.

We believe a comprehensive method should be applied in this area including setting a SDV Lane

and broadening highways in some particularly narrow parts.

Keywords: Traffic Flow Model; Self-Driving Vehicle; Cellular Automata

Contents

1 Introduction 1

4 Details of the Model 4

6 Appliance of the Model 17

7 Sensitivity Analysis 18

8 Conclusions 19

9 Strengths and weaknesses 19

10 A Letter 20

1 Introduction

people’s need and traffic delays can be seen everywhere during peak hours. However, at this time

building more roads or adding lanes in this area is extremely difficult and expensive. In order to

increase the capacity of highways without increasing the number of lanes or roads, allowing self-

driving vehicles(SDVs) to run on the road should be taken into consideration. A model is needed to

evaluate SDVs’ influence on the traffic flow.

driving vehicles (NSDVs), number of lanes and traffic volume.

data.

interactions between SDVs and NSDVs, unpredictability of human-beings and other factors.

rules to simulate the traffic flow on a multilane highway. This is the Multilane Traffic Model. After

simplifying the behaviors of real vehicles’ changing lanes, we make rules on when and how a cell

move across lanes. Both the motivation and the safety concern are considered. Furthermore, we

make special rules to simulate human behaviors and cooperations among SDVs including the form

of a chain of SDVs called the SDV-Train.

analyzing the data, we find several interesting features of the mixed traffic flow. The correlations

among the average speed, the traffic flow and the percentage of SDVs are strong. These three pa-

increases and even triples but we believe the traffic situation in this area is still not abundant. More

methods including broaden a few parts of the current highway and setting a SDV Lane should be

taken into consideration.

2 Simplifications and Assumptions of the Problem

1. Straight Road

A highway in this model should be straight or its degree of curvature can be ignored [1]. A

vehicle’s speed and other conditions does not change because of the shape of the road.

2. The number of lanes should remain constant for a long period.

3. The highway is in good condition and the traffic flow is not affected by the rough road.

4. No pedestrian, animal or any form of obstacle can be found on the highway so the traffic flow

• Only one SDV Lane can be set in our model considering the width of the highway is

limited.

• The SDV Lane will be placed on the edge of the road to prevent a separation of lanes for

NSDVs.

7. The width of each lane is 12 feet.

8. The speed limit of all highways is 60mph.

1. In this model, only average length, speed, acceleration and other features of vehicles are used.

Although there is a great diversity among different vehicles, this difference can be ignored and

the result of the model would not be greatly affected.