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    Journals >Infrared and Laser Engineering >Volume 49 >Issue 7 >Page 20190507 > Article
    • Infrared and Laser Engineering
    • Vol. 49, Issue 7, 20190507 (2020)
    Influences of weather conditions on vehicular infrared assistant driving performance
    Hongpei Wang, Guangqi Luan, Chao Tian, Jiaxiao Wang, Peng Yang, and Mingzhao Sun
    Author Affiliations
  • 中国华阴兵器试验中心，陕西 华阴 714200
    • show less
    DOI: 10.3788/IRLA20190507 Cite this Article
    Hongpei Wang, Guangqi Luan, Chao Tian, Jiaxiao Wang, Peng Yang, Mingzhao Sun. Influences of weather conditions on vehicular infrared assistant driving performance[J]. Infrared and Laser Engineering, 2020, 49(7): 20190507 Copy Citation Text show less

    Abstract

    Based on comprehensive analysis of vehicle infrared assisted driving safety braking process, infrared static detection model and dynamic detection model, the model of visual range for assistant driving safety was established. The relationship between maximum safe speed, road condition, infrared detection performance was analyzed. It is found that it is mainly related to sliding adhesion coefficient and detection distance. Through the correction calculation of infrared detection distance, the maximum safe speed at night was simulated. The results show that it is mainly affected by the temperature difference between target and background. Emphasis is laid on foggy and rainy weather for example analysis. The results show that foggy weather mainly affects the detection distance, especially when the visibility is less than 1 km, and the maximum safe speed need be controlled at 21-25 km/h when the visibility is 5 km. Rainy weather will affect the sliding adhesion coefficient and detection distance. The maximum safe speed control under infrared recognition is the main method for assistant driving. When rainfall intensity is 50 mm/h, the maximum safe speed need be controlled at 12-14 km/h.

    Keywords

    $S = {S_1} + {S_2} + {S_3}$(1)

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    $\begin{split} {S'} =\; & {S_1} + {S_2} + {S_3} + {S_4} + {S_5}=\\ & {V_0}{t_1} + {V_0}{t_2} + \frac{{{{\left( {{V_0}/3.6} \right)}^2}}}{{2{\varphi _s}g}} + {V_0}{t_4} + {V_0}{t_5} \end{split} $(2)

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    ${V_0}{t_1} + {V_0}{t_2} + \frac{{{{\left( {{V_0}/3.6} \right)}^2}}}{{2{\varphi _s}g}} + {V_0}{t_4} + {V_0}{t_5} + d \leqslant R$(3)

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    $\left\{ \begin{aligned} & \Delta {T_{\rm e}} \cdot {\tau _{\rm a}}(R) \geqslant MRTD(f) \\ & \frac{H}{{2{n_{\rm e}}R}} \geqslant \Delta \theta \end{aligned} \right.$(4)

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    ${p_2}(t) = {p_1}\left[ {1 - \exp \left( - \frac{t}{{{T_{\rm eye}}}}\right)} \right]$(5)

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    $\left\{ \begin{aligned} & \left\{ \begin{aligned} &\Delta {T_{\rm e}} \cdot {\tau _{\rm a}}(R) \geqslant MRTD(f) \\ & \frac{H}{{2{n_{\rm e}}R}} \geqslant \Delta \theta \end{aligned} \right. \\ & {p_2}(t) = {p_1}\left[ {1 - \exp ( - \frac{t}{{{T_{\rm eye}}}})} \right] \\ & {V_0}t + {V_0}{t_1} + {V_0}{t_2} + \frac{{{{\left( {{V_0}/3.6} \right)}^2}}}{{2{\varphi _{\rm s}}g}} + {V_0}{t_4} + {V_0}{t_5} + d \leqslant R \end{aligned} \right.$(6)

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    ${V_{\max }}(t + {t_1} + {t_2} + {t_4} + {t_5}) + \frac{{{{\left( {{V_{\max }}/3.6} \right)}^2}}}{{2{\varphi _{\rm s}}g}} + d = R$(7)

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    $MRTD\left( f \right) = \frac{{{{\text{π}} ^2} \cdot SN{R_{\rm DT}}}}{{4\sqrt {14} }}\left[ {\frac{{NETD \cdot f}}{{MT{F_{\rm S}}\left( f \right)}}} \right] \cdot {\left[ {\frac{{\alpha \beta }}{{{\tau _{\rm d}}{T_{\rm eye}}{f_{\rm P}}\Delta {f_{ n}}}}} \right]^{{1 / 2}}}$(8)

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    $\varepsilon = \left\{ {\begin{array}{*{20}{c}} {2{n_{\rm e}}{\varepsilon _0}}&{x{\text{方向}}}\\ {2{n_{\rm e}}/{\varepsilon _0}}&{y{\text{方向}}} \end{array}} \right.$(9)

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    ${p_1} = \int_{ - \infty }^{SNR - SN{R_{\rm DT}}} {\exp ( - {z^2}){\rm d}z} $(10)

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    $\begin{split} MRTD'\left( f \right) =\; & {k_1} \cdot {k_2} \cdot {k_3}\frac{{{\text{π} ^2} \cdot SN{R_{\rm DT}}}}{{4\sqrt {14} }}\cdot \\ & \left[ {\frac{{NETD \cdot f}}{{MT{F_{\rm S}}\left( f \right)}}} \right] \cdot {\left[ {\frac{{\alpha \beta }}{{{\tau _{\rm d}}{T_{\rm eye}}{f_{\rm P}}\Delta {f_{\rm n}}}}} \right]^{{1 / 2}}} \end{split} $(11)

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    $\left\{ \begin{aligned} & \left\{ \begin{aligned} & \Delta {T_{\rm e}} \cdot {\tau _{\rm a}}(R) \geqslant MRTD'(f) \\ & \frac{H}{{2{n_{\rm e}}R}} \geqslant \Delta \theta = \frac{1}{{2f}} \end{aligned} \right. \\ & {p_2}(t) = {p_1}\left[ {1 - \exp ( - \frac{t}{{{T_{\rm eye}}}})} \right] \\ & {V_{\max }}(t + {t_1} + {t_2} + {t_4} + {t_5}) + \frac{{{{\left( {{V_{\max }}/3.6} \right)}^2}}}{{2g{\varphi _{\rm s}}}} + d = R \end{aligned} \right.$(12)

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    $\tau (\lambda ) = {\varphi _e}(\lambda ,R)/{\varphi _e}(\lambda ,0) = \exp ( - R \cdot \mu (\lambda ))$(13)

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    Hongpei Wang, Guangqi Luan, Chao Tian, Jiaxiao Wang, Peng Yang, Mingzhao Sun. Influences of weather conditions on vehicular infrared assistant driving performance[J]. Infrared and Laser Engineering, 2020, 49(7): 20190507
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