Journal of Jilin University(Engineering and Technology Edition) ›› 2019, Vol. 49 ›› Issue (3): 720-726.doi: 10.13229/j.cnki.jdxbgxb20171143

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Finding shortest path considering traveler′s risk attitude

Qiang TU1(),Lin CHENG1(),Fen LIN2,Chao SUN1   

  1. 1. School of Transportation, Southeast University, Nanjing 210096, China
    2. Shanghai Municipal Engineering Design Institute Group Co. , Ltd. , Shanghai 200092, China
  • Received:2017-11-22 Online:2019-05-01 Published:2019-07-12
  • Contact: Lin CHENG E-mail:dqtu_1991@163.com;gist@seu.edu.cn

Abstract:

Due to the uncertainty in transportation system, the travel time of paths varies within a certain range. For stochastic transportation network, travelers have different risk attitudes which can be divided into three categories including risk?averse, risk?neutral and risk?seeking attitudes. The normal distribution was used to describe the randomness of travel time of links, and models of travel time budget, mean?extra travel time and mean?below travel time were considered to study travelers′ path selection behavior, in addition, travelers with multi?Point of Interests (POIs) were also considered. A label?correcting algorithm was proposed to solve this problem, setting α=0.75 and α=0.25 respectively. The results of shortest path selection of travelers with different risk attitudes were analyzed. The computational performance of the algorithm was tested in different scale of networks. The results show that the average operation time of the label?correcting algorithm is about 100 ms in the network with 10 000 nodes, which is about 42% slower than the classic algorithm of dijkstra in the deterministic network. Comparative analysis shows that the algorithm is fast and can meet the requirements of practical application.

Key words: engineering of communications and transportation system, path finding, risk attitude, travel time budget, multi?point of interests (POIs), label?correcting algorithm

CLC Number: 

  • U491.1

Fig.1

Sample network"

Table 1

Values of parameters in model"

模型λ(α)取值α取值
<0.5=0.5>0.5
TTBΦ-1(α)

风险

偏好

风险

中立

风险

规避

METT????exp-(Φ-1(α))222π(1-α)

风险

规避

风险

规避

风险

规避

MBTT-exp-(Φ-1(α))222πα

风险

偏好

风险

偏好

风险

偏好

Fig.2

Paths of POIs"

Fig.3

Sioux Falls network"

Table 2

Shortest paths for different models"

模型可靠度α最优路径均值方差出行时间
TTB0.751?3?4?5?6?8?13?14?241155.001020.001176.54
0.251?3?4?5?7?12?17?20?241145.002680.001110.08
METT0.751?3?4?5?6?8?13?14?241155.001020.001195.60
0.251?3?4?5?7?12?15?18?241145.002220.001164.96
MBTT0.751?3?10?21?22?23?241145.002680.001123.07
0.251?3?4?5?7?12?17?20?241155.003780.001076.85

Table 3

Effective paths"

编号路径信息均值方差
11?3?4?5?6?8?13?14?241155.001020.00
21?3?4?5?7?12?17?20?241145.002680.00
31?3?4?5?7?12?15?18?241145.002220.00
41?3?4?5?7?12?17?20?241155.003780.00

Fig.4

Curve of risk?averse traveler′s travel timeand reliability α"

Fig.5

Curves of risk?seeking traveler's travel time and reliability α"

Fig.6

Computational performance test of algorithm"

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